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 0 40078 2835065 2702433 2026-09-29T16:07:59Z ~2026-52467-89 3111839 /* */ 2835065 wikitext text/x-wiki Linear operators can be thought of as infinite dimensional matrices. Hence we can use well known results from matrix theory when dealing with linear operators. However, wdsesessese have to be careful. A finite dimensional matrix has an inverse if none of its eigenvalues are zero. For an infinite dimensional matrix, even though all the eigenvectors may be nonzero, we might have a sequence of eigenvalues that tend to zero. There are several other subtleties that we will discuss in the course of this series of lectures. Let us start off with the basics, i.e., linear vector spaces. ==Linear Vector Spaces (''S'')== Let <math>\mathcal{S}</math> be a linear vector space. ===Addition and scalar multiplication=== Let us first define addition and scalar multiplication in this space. The addition operation acts completely in <math>\mathcal{S}</math> while the scalar multiplication operation may involve multiplication either by a real (in <math>\mathbb{R}</math>) or by a complex number (in <math>\mathbb{C}</math>). These operations must have the following closure properties: #If <math>\mathbf{x}, \mathbf{y} \in \mathcal{S}</math> then <math>\mathbf{x} + \mathbf{y} \in \mathcal{S}</math>. #If <math>\alpha \in \mathbb{R}</math> (or <math>\mathbb{C}</math>) and <math>\mathbf{x} \in \mathcal{S}</math> then <math>\alpha~\mathbf{x} \in \mathcal{S}</math>. And the following laws must hold for addition #<math>\mathbf{x} + \mathbf{y}</math> = <math>\mathbf{y} + \mathbf{x} \qquad</math> Commutative law. #<math>\mathbf{x} + (\mathbf{y} + \mathbf{z})</math> = <math>(\mathbf{x} + \mathbf{y}) + \mathbf{z} \qquad</math> Associative law. #<math>\exists \mathbf{0} \in \mathcal{S}</math> such that <math>\mathbf{0} + \mathbf{x} = \mathbf{x} \quad \forall \mathbf{x} \in \mathcal{S} \qquad </math> Additive identity. #<math>\forall \mathbf{x} \in \mathcal{S} \quad \exists -\mathbf{x} \in \mathcal{S}</math> such that <math>-\mathbf{x} + \mathbf{x} = \mathbf{0} \qquad </math> Additive inverse. For scalar multiplication we have the properties #<math>\alpha~(\beta~\mathbf{x}) = (\alpha~\beta)~\mathbf{x}</math>. #<math>(\alpha + \beta)~\mathbf{x} = \alpha~\mathbf{x} + \beta~\mathbf{x}</math>. #<math>\alpha~(\mathbf{x}+\mathbf{y}) = \alpha~\mathbf{x} + \alpha~\mathbf{y}</math>. #<math>\mathbf{1}~\mathbf{x} = \mathbf{x}</math>. #<math>\mathbf{0}~\mathbf{x} = \mathbf{0}</math>. ====Example 1: ''n'' tuples==== The <math>n</math> tuples <math>(x_1, x_2, \dots, x_n)</math> with :<math> \begin{align} (x_1, x_2, \dots, x_n) + (y_1, y_2, \dots, y_n) & = (x_1 + y_1, x_2 + y_2, \dots, x_n + y_n) \\ \alpha~(x_1, x_2, \dots, x_n) & = (\alpha~x_1, \alpha~x_2, \dots, \alpha~x_n) \end{align} </math> form a linear vector space. ====Example 2: Matrices==== Another example of a linear vector space is the set of <math>2 \times 2</math> matrices with addition as usual and scalar multiplication, or more generally <math>n\times m</math> matrices. :<math> \alpha\begin{bmatrix} x_{11} & x_{12} \\ x_{21} & x_{22} \end{bmatrix} = \begin{bmatrix} \alpha~x_{11} & \alpha~x_{12} \\ \alpha~x_{21} & \alpha~x_{22} \end{bmatrix} </math> ====Example 3: Polynomials==== The space of <math>n</math>-th order polynomials forms a linear vector space. :<math> p_n = \sum_{j=1}^n \alpha_j~x^j </math> ====Example 4: Continuous functions==== The space of continuous functions, say in <math>[0, 1]</math>, also forms a linear vector space with addition and scalar multiplication defined as usual. ===Linear Dependence=== A set of vectors <math>\mathbf{x}_1, \mathbf{x}_2, \dots, \mathbf{x}_n \in \mathcal{S}</math> are said to be linearly dependent if <math>\exists~ \alpha_1, \alpha_2, \dots, \alpha_n</math> not all zero such that :<math> \alpha~\mathbf{x}_1 + \alpha~\mathbf{x}_2 + \dots + \alpha~\mathbf{x}_n = \mathbf{0} </math> If such a set of constants <math>\alpha_1, \alpha_2, \dots, \alpha_n</math> does not exist then the vectors are said to be linearly independent. ====Example==== Consider the matrices :<math> \boldsymbol{M}_1 = \begin{bmatrix} 1 & 0 \\ 0 & 2 \end{bmatrix}, \boldsymbol{M}_2 = \begin{bmatrix} 1 & 0 \\ 0 & 0 \end{bmatrix}, \boldsymbol{M}_3 = \begin{bmatrix} 0 & 0 \\ 0 & -1 \end{bmatrix} </math> These are linearly dependent since <math>\boldsymbol{M}_1 - \boldsymbol{M}_2 + 2~\boldsymbol{M}_3 = \mathbf{0}</math>. ===Span=== The span of a set of vectors <math>(\boldsymbol{T})</math> is the set of all vectors that are linear combinations of the vectors <math>\mathbf{x}_i</math>. Thus :<math> \text{span}(\boldsymbol{T}) = \{\boldsymbol{T}_1, \boldsymbol{T}_2, \dots, \boldsymbol{T}_n\} </math> where :<math> \boldsymbol{T}_i = \alpha_1~\mathbf{x}_1 + \alpha_2~\mathbf{x}_2 + \dots + \alpha_n~\mathbf{x}_n </math> as <math>\alpha_1, \alpha_2, \dots, \alpha_n</math> vary. ====Spanning set==== If the span = <math>\mathcal{S}</math> then <math>\boldsymbol{T}</math> is said to be a spanning set. ===Basis=== If <math>\boldsymbol{T}</math> is a spanning set and its elements are linearly independent then we call it a basis for <math>\mathcal{S}</math>. A vector in <math>\mathcal{S}</math> has a unique representation as a linear combination of the basis elements. This is because adding two vectors is the same as adding the coefficients of the basis elements, and if any vector had two distinct representations, the basis would no longer be linearly independent, as <math display="block">\vec{v} = a_1 \vec e_1 + a_2 \vec e_2 + \dots = b_1 \vec e_1 + b_2 \vec{e}_2 + \dots</math>implies that<math display="block">\vec v - \vec v = (a_1-b_1)\vec e_1 + (a_2-b_2)\vec e_2 + \dots = \vec 0</math>which is only permissible (by linear independence) if the <math display="inline">a_i - b_i</math> are all zero. ====Dimension==== The dimension of a space <math>\mathcal{S}</math> is the number of elements in the basis. This is independent of actual elements that form the basis and is a property of <math>\mathcal{S}</math>. ====Example 1: Vectors in ''R²''==== Any two non-collinear vectors <math>\mathbb{R}^2</math> is a basis for <math>\mathbb{R}^2</math> because any other vector in <math>\mathbb{R}^2</math> can be expressed as a linear combination of the two vectors. ====Example 2: Matrices==== A basis for the linear space of <math>2 \times 2</math> matrices is :<math> \begin{bmatrix} 1 & 0 \\ 0 & 0 \end{bmatrix}, \begin{bmatrix} 1 & 1 \\ 0 & 0 \end{bmatrix}, \begin{bmatrix} 1 & 1 \\ 0 & 1 \end{bmatrix}, \begin{bmatrix} 1 & 3 \\ 1 & 1 \end{bmatrix} </math> Note that there is a lot of nonuniqueness in the choice of bases. One important skill that you should develop is to choose the right basis to solve a particular problem. ====Example 3: Polynomials==== The set <math>\{1, x, x^2, \dots, x^n\}</math> is a basis for polynomials of degree <math>n</math>. ====Example 4: The natural basis==== A natural basis is the set <math>\{ \mathbf{e}_1, \mathbf{e}_2, \dots, \mathbf{e}_n\}</math> where the <math>j</math>th entry of <math>\mathbf{e}_k</math> is :<math> \delta_{jk} = \begin{cases} 1 & \mbox{for} ~j = k \\ 0 & \mbox{for}~ j \ne k \end{cases} </math> The quantity <math>\delta_{jk}</math> is also called the Kronecker delta. ===Inner Product Spaces=== To give more structure to the idea of a vector space we need concepts such as magnitude and angle. The inner product provides that structure. The inner product generalizes the concept of an angle and is defined as a function :<math> \langle\bullet,~\bullet\rangle : \mathcal{S}\times\mathcal{S} \rightarrow \mathbb{R} \quad (\text{or}~\mathbb{C}~\text{for a complex vector space}) </math> with the properties #<math>\langle\mathbf{x},~\mathbf{y}\rangle = \overline{\langle\mathbf{y},~\mathbf{x}\rangle} \qquad</math> overbar indicates complex conjugation. #<math>\langle\alpha~\mathbf{x},~\mathbf{y}\rangle = \alpha~\langle\mathbf{x},~\mathbf{y}\rangle \quad</math> Linear with respect to scalar multiplication. #<math>\langle\mathbf{x}+\mathbf{y},~\mathbf{z}\rangle = \langle\mathbf{x},~\mathbf{z}\rangle + \langle\mathbf{y},~\mathbf{z}\rangle \quad</math> Linearity with respect to addition. #<math>\langle\mathbf{x},~\mathbf{x}\rangle > \mathbf{0}</math> if <math>\mathbf{x} \ne 0</math> and <math>\langle\mathbf{x},~\mathbf{x}\rangle = \mathbf{0}</math> if and only if <math>\mathbf{x} = \mathbf{0}</math>. A vector space with an inner product is called an inner product space. ====Example 1:==== :<math> \langle\mathbf{x},~\beta~\mathbf{y}\rangle = \overline{\langle\beta~\mathbf{y},~\mathbf{x}\rangle} = \overline{\beta}~\overline{\langle\mathbf{y},~\mathbf{x}\rangle} = \overline{\beta}\langle\mathbf{x},~\mathbf{y}\rangle </math> ====Example 2: Discrete vectors==== In <math>\mathbb{R}^n</math> with <math>\mathbf{x} = \{x_1, x_2, \dots, x_n \}</math> and <math>\mathbf{y} = \{y_1, y_2, \dots, y_n \}</math> the Eulidean norm is given by :<math> \langle\mathbf{x},~\mathbf{y}\rangle = \sum_n x_n~y_n </math> With <math>\mathbf{x}, \mathbf{y} \in \mathbb{C}^n</math> the standard norm is :<math> \langle\mathbf{x},~\mathbf{y}\rangle = \sum_k x_k~\overline{y_k} </math> ====Example 3: Continuous functions==== For two complex valued continuous functions <math>f(x)</math> and <math>g(x)</math> in <math>[0, 1]</math> we could approximately represent them by their function values at '' equally spaced points.'' Approximate <math>f(x)</math> and <math>g(x)</math> by :<math> \begin{align} F & = \{f(x_1), f(x_2), \dots, f(x_n)\} \qquad \text{with} ~x_k = \cfrac{k}{n}\\ G & = \{g(x_1), g(x_2), \dots, g(x_n)\} \qquad \text{with} ~x_k = \cfrac{k}{n} \end{align} </math> With that approximation, a natural norm is :<math> \langle F,~G\rangle = \cfrac{1}{n}~\sum_{k=1}^n f(x_k)~\overline{g(x_k)} </math> Taking the limit as <math>n \rightarrow \infty</math> (show this) :<math> \langle f,~g\rangle = \int_0^1 f(x)~\overline{g(x)}~dx </math> If we took '' non-equally spaced'' yet smoothly distributed points we would get :<math> \langle f,~g\rangle = \int_0^1 f(x)~\overline{g(x)}~w(x)~dx </math> where <math>w(x) > 0</math> is a smooth weighting function (show this). There are many other inner products possible. For functions that are not only continuous but also differentiable, a useful norm is :<math> \langle f,~g\rangle = \int_0^1 \left[f(x)~\overline{g(x)} + f^{'}(x)~\overline{g^{'}(x)}\right]~dx </math> We will continue further explorations into linear vector spaces in the next lecture. [[Category:Functional analysis]] {{lecture}} 9muju7crnzsirap4h6fschh728wguc4 0 51671 2835045 1134396 2026-09-29T13:35:53Z ~2026-52341-66 3111834 โหมด AI ทั้งหมด รูปภาพ วิดีโอ วิดีโอสั้น เว็บ เที่ยวบิน การเงิน ข่าวสาร Maps หนังสือ ช็อปปิ้ง วัตถุในรูปคือ แก่นไม้หรือตอไม้เก่า ที่มีเนื้อไม้สีเข้มและมีร่องรอยการผุกร่อนตามธรรมชาติ ซึ่งมักจะถูกนำมาใช้เป็นเครื่องรางของขลังตามความเชื่อเรื่อง เมตตามหาเสน่ห์ (เช่น แก่นไม้รักดำ, ไม้รักซ้อนตายพราย หรือแก่นไม้พญางิ้วดำ) หรืออาจเป็นขอนไม้ธรรมชาติสำหรับนำไปตกแต่งตู้ปลา สวนถาด และงานศิลปะต่าง ๆ หากต้องการทราบข้อมูลเพิ่มเติม สามารถระบุรายละเอียดที่อยากรู้ได้เลยครับ เช่น: ต้องการให้ช่วย ตรวจสอบลักษณะเฉพาะ 2835045 wikitext text/x-wiki FLOSS stands for [[w:FLOSS|Free/Libre and Open Source Software]]. There is a [[w:List_of_open_source_software_packages|list on Wikipedia]]. Here we are interested in FLOSS for academics, scientists, researchers and educators. Our [[School:Computer science|School of Computer Science]] has extensive coverage of FLOSS operating systems and programming. == Resources(Sickle)T135170 == วัตถุในรูปคือ <mark>แก่นไม้หรือตอไม้เก่า ที่มีเนื้อไม้สีเข้มและมีร่องรอยการผุกร่อนตามธรรมชาติ ซึ่งมักจะถูกนำมาใช้เป็นเครื่องรางของขลังตามความเชื่อเรื่อง เมตตามหาเสน่ห์</mark> (เช่น แก่นไม้รักดำ, ไม้รักซ้อนตายพราย หรือแก่นไม้พญางิ้วดำ) หรืออาจเป็นขอนไม้ธรรมชาติสำหรับนำไปตกแต่งตู้ปลา สวนถาด และงานศิลปะต่าง ๆ หากต้องการทราบข้อมูลเพิ่มเติม สามารถระบุรายละเอียดที่อยากรู้ได้เลยครับ เช่น: * ต้องการให้ช่วย '''ตรวจสอบลักษณะเฉพาะ''' ของไม้ชนิดนี้เพิ่มเติม? * ต้องการทราบ '''ประวัติความเชื่อหรือพุทธคุณ''' ของไม้รักเก่าในทางเครื่องราง? * เป็น '''ชิ้นส่วนพระกรุ''' หรือเครื่องรางจากเกจิอาจารย์ท่านใดเป็นพิเศษหรือไม่? {{wp}} * [[/Challenges for Developers/]] * [[/FLOSS4Geography/]] * [[/FLOSS4Science/]] * [[/FLOSS and education/]] * [[/FLOSS for Education/]] * [[/FLOSS for Educators/]] * [[/FLOSS for Scientists and Researchers/]] * [[/FLOSS for Social Entrepreneurs and Students of Social Entrepreneurship/]] * [[/FLOSS in Science Research Agenda/]] * [[/Manuals/]] * [[Linux]] & [[BSD]] [[Category:FLOSS]] 7jia55pyeb779tq1w4kkay5oxmjba5t 2835048 2835045 2026-09-29T13:42:13Z NDG 3006541 Reverted edits by [[Special:Contribs/~2026-52341-66|~2026-52341-66]] ([[User talk:~2026-52341-66|talk]]) to last version by Dave Braunschweig: Wrong language 1134396 wikitext text/x-wiki FLOSS stands for [[w:FLOSS|Free/Libre and Open Source Software]]. There is a [[w:List_of_open_source_software_packages|list on Wikipedia]]. Here we are interested in FLOSS for academics, scientists, researchers and educators. Our [[School:Computer science|School of Computer Science]] has extensive coverage of FLOSS operating systems and programming. == Resources == {{wp}} * [[/Challenges for Developers/]] * [[/FLOSS4Geography/]] * [[/FLOSS4Science/]] * [[/FLOSS and education/]] * [[/FLOSS for Education/]] * [[/FLOSS for Educators/]] * [[/FLOSS for Scientists and Researchers/]] * [[/FLOSS for Social Entrepreneurs and Students of Social Entrepreneurship/]] * [[/FLOSS in Science Research Agenda/]] * [[/Manuals/]] * [[Linux]] & [[BSD]] [[Category:FLOSS]] l9dy19rmegjlkqwxoahialqf8r8m4ml 0 55801 2835066 2815483 2026-09-29T18:10:43Z ~2026-52467-41 3111846 i made sure noone will ruin it 2835066 wikitext text/x-wiki {{Educational Media Awareness Campaign/Nav}}Please do not mess this page up i put a lot of dedication to it and if it gets messed up ill crash out__NOTOC__ {{Robelbox | theme = 14 | title = Greetings Fellow Humans, | width = 100% | icon = Nuvola gaim.svg | iconwidth = 48px }} <div style="{{Robelbox/pad}}"> == Goals == The goal of the [[Educational Media Awareness Campaign]] is twofold: # To help educators effectively use the internet to find suitable media for learning resources. # To assist educators in integrating media correctly and legally, ensuring reusability and proper permission handling. This campaign is primarily targeted at the primary and secondary education sectors, but it is also beneficial for tertiary, informal, and other educational fields. == Background == One of the biggest challenges faced by creators of digital educational resources is the ''illegal use of images and graphic content''. Publishers—both digital and print—regularly receive submissions that must be rejected due to copyright violations. Image copyright infringement is especially common in schools. This situation is paradoxical. In recent years, the availability of well-documented, reusable, and redistributable media has increased significantly: * [[c:|Wikimedia Commons]] provides millions of legally reusable, well-categorized images. * [[w:Flickr|Flickr]] also offers a vast collection of reusable images, though less structured. In addition, although somewhat controversial, [[w:Artificial intelligence|artificial intelligence]] is increasingly effective in helping to develop free to use educational media. With such resources available, there is no need for illegal use of images. The [[Educational Media Awareness Campaign]] aims to solve this issue by: * Showcasing galleries of reusable images * Providing case studies on finding appropriate media * Listing trusted media repositories * Offering tutorials on licensing and documentation A key focus is introducing educators to the effective educational use of Wikimedia Commons. == A Multi-site Effort == The [[Educational Media Awareness Campaign]] is a subproject of Wikiversity Outreach. It collaborates with various educational and media platforms to expand its impact. == Galleries and Pictures of the Day == The campaign includes: * 100+ featured images * Coverage across 12 major school subjects * Carefully written captions with source links * Access to thousands of related images These images serve as entry points for educators. Additionally: * Images are organized into dynamic pages * They can be used as "Picture of the Day" on wikis * Separate rotating sections exist for each subject == Investigation and Analysis of Digital Educational Resources == With technological advancement, digital educational resources have become increasingly diverse. A survey of 82 undergraduate students revealed: * Students prefer digital resources for self-directed learning * Search engines are the most commonly used access method * Traditional computers are still the preferred device To maximize effectiveness, educational providers should: * Understand user behavior * Align resources with user needs * Optimize accessibility and usability == See also == * [[meta:Education]] </div> {{robelbox/close}} [[Category:EMAC]] cyu1gjoenujf43hc0rmg94u02cdcjj2 2835072 2835066 2026-09-29T20:15:52Z Codename Noreste 2969951 Reverted edit by [[Special:Contributions/~2026-52467-41|~2026-52467-41]] ([[User_talk:~2026-52467-41|talk]]) to last version by [[User:ShakespeareFan00|ShakespeareFan00]] using [[Wikiversity:Rollback|rollback]] 2815483 wikitext text/x-wiki {{Educational Media Awareness Campaign/Nav}} __NOTOC__ {{Robelbox | theme = 14 | title = Greetings Fellow Humans, | width = 100% | icon = Nuvola gaim.svg | iconwidth = 48px }} <div style="{{Robelbox/pad}}"> == Goals == The goal of the [[Educational Media Awareness Campaign]] is twofold: # To help educators effectively use the internet to find suitable media for learning resources. # To assist educators in integrating media correctly and legally, ensuring reusability and proper permission handling. This campaign is primarily targeted at the primary and secondary education sectors, but it is also beneficial for tertiary, informal, and other educational fields. == Background == One of the biggest challenges faced by creators of digital educational resources is the ''illegal use of images and graphic content''. Publishers—both digital and print—regularly receive submissions that must be rejected due to copyright violations. Image copyright infringement is especially common in schools. This situation is paradoxical. In recent years, the availability of well-documented, reusable, and redistributable media has increased significantly: * [[c:|Wikimedia Commons]] provides millions of legally reusable, well-categorized images. * [[w:Flickr|Flickr]] also offers a vast collection of reusable images, though less structured. In addition, although somewhat controversial, [[w:Artificial intelligence|artificial intelligence]] is increasingly effective in helping to develop free to use educational media. With such resources available, there is no need for illegal use of images. The [[Educational Media Awareness Campaign]] aims to solve this issue by: * Showcasing galleries of reusable images * Providing case studies on finding appropriate media * Listing trusted media repositories * Offering tutorials on licensing and documentation A key focus is introducing educators to the effective educational use of Wikimedia Commons. == A Multi-site Effort == The [[Educational Media Awareness Campaign]] is a subproject of Wikiversity Outreach. It collaborates with various educational and media platforms to expand its impact. == Galleries and Pictures of the Day == The campaign includes: * 100+ featured images * Coverage across 12 major school subjects * Carefully written captions with source links * Access to thousands of related images These images serve as entry points for educators. Additionally: * Images are organized into dynamic pages * They can be used as "Picture of the Day" on wikis * Separate rotating sections exist for each subject == Investigation and Analysis of Digital Educational Resources == With technological advancement, digital educational resources have become increasingly diverse. A survey of 82 undergraduate students revealed: * Students prefer digital resources for self-directed learning * Search engines are the most commonly used access method * Traditional computers are still the preferred device To maximize effectiveness, educational providers should: * Understand user behavior * Align resources with user needs * Optimize accessibility and usability == See also == * [[meta:Education]] </div> {{robelbox/close}} [[Category:EMAC]] niz0bpsflroru1bex8a029wsvudqbz2 5 62711 2835046 2833282 2026-09-29T13:39:00Z ~2026-52341-66 3111834 /* 8b/10b */ new section 2835046 wikitext text/x-wiki Added a frame and a caption to the screenshot for better usability, as I noticed that it was not obviously an image when the article is browsed quickly. I got confused at first, until I read the text above it. Couldn't get the image width to work for some reason, needs to be fixed. ==remark: explain that it's global right at begin== was logged out and got presented: "Why create a Wikiversity account? Not logged in. Please log in to view or edit items on your watchlist." I was wondering why restrict this account to WV only? when there is right there told it is a global account, it could be more activating. Anyways, later... ----[[User:Erkan_Yilmaz|Erkan Yilmaz]] <small>uses the [[Wikiversity:Chat]] + [[Identi.ca]]</small> 01:31, 9 May 2011 (UTC) 大FAS == Wikiversity == Wikiversity is a Wikimedia Foundation project that supports learning communities, their learning materials, and resulting activities. It differs from Wikipedia in that it offers tutorials and other materials for the fostering of learning, rather than an encyclopedia; like Wikipedia, it is available in many languages. [[User:Butterfly Florist|Butterfly Florist]] ([[User talk:Butterfly Florist|discuss]] • [[Special:Contributions/Butterfly Florist|contribs]]) 06:26, 20 September 2022 (UTC) It offers tutorials [[User:Butterfly Florist|Butterfly Florist]] ([[User talk:Butterfly Florist|discuss]] • [[Special:Contributions/Butterfly Florist|contribs]]) 07:47, 27 September 2022 (UTC) == The importance of having a wikiversity account == Nothing [[User:Butterfly Florist|Butterfly Florist]] ([[User talk:Butterfly Florist|discuss]] • [[Special:Contributions/Butterfly Florist|contribs]]) 06:47, 27 September 2022 (UTC) == 8b/10b == cohnection Closed-sQL [[Special:Contributions/~2026-52341-66|~2026-52341-66]] ([[User talk:~2026-52341-66|talk]]) 13:39, 29 September 2026 (UTC) 6z4poz3c0hkrzymkc5nes1rzn0mozsn 2835047 2835046 2026-09-29T13:41:39Z NDG 3006541 Reverted edits by [[Special:Contribs/~2026-52341-66|~2026-52341-66]] ([[User talk:~2026-52341-66|talk]]) to last version by PieWriter: test edits, please use the sandbox 2688613 wikitext text/x-wiki Added a frame and a caption to the screenshot for better usability, as I noticed that it was not obviously an image when the article is browsed quickly. I got confused at first, until I read the text above it. Couldn't get the image width to work for some reason, needs to be fixed. ==remark: explain that it's global right at begin== was logged out and got presented: "Why create a Wikiversity account? Not logged in. Please log in to view or edit items on your watchlist." I was wondering why restrict this account to WV only? when there is right there told it is a global account, it could be more activating. Anyways, later... ----[[User:Erkan_Yilmaz|Erkan Yilmaz]] <small>uses the [[Wikiversity:Chat]] + [[Identi.ca]]</small> 01:31, 9 May 2011 (UTC) 大FAS == Wikiversity == Wikiversity is a Wikimedia Foundation project that supports learning communities, their learning materials, and resulting activities. It differs from Wikipedia in that it offers tutorials and other materials for the fostering of learning, rather than an encyclopedia; like Wikipedia, it is available in many languages. [[User:Butterfly Florist|Butterfly Florist]] ([[User talk:Butterfly Florist|discuss]] • [[Special:Contributions/Butterfly Florist|contribs]]) 06:26, 20 September 2022 (UTC) It offers tutorials [[User:Butterfly Florist|Butterfly Florist]] ([[User talk:Butterfly Florist|discuss]] • [[Special:Contributions/Butterfly Florist|contribs]]) 07:47, 27 September 2022 (UTC) == The importance of having a wikiversity account == Nothing [[User:Butterfly Florist|Butterfly Florist]] ([[User talk:Butterfly Florist|discuss]] • [[Special:Contributions/Butterfly Florist|contribs]]) 06:47, 27 September 2022 (UTC) 7uiuyaaluiur117wwf5xwovq1b0tmxs 0 96387 2835115 2833707 2026-09-30T04:32:16Z Jtneill 10242 /* Social contribution (10%) */ 2835115 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): *** Include the title, subtitle, headings, text, tables, figures, references, see also, and external links; don't include 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/1NUNjMCM5xOVsHj1LJuRnK8BgEdXPn4TbRf-Q6PH3oXg/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]] l9rlr47h70szljc3cazi844777sss9y 0 98607 2835081 2834798 2026-09-30T00:00:54Z Jtneill 10242 /* Multimedia */ Update video link 2835081 wikitext text/x-wiki {{Motivation and emotion/Lectures|Lecture 8: Aspects of emotion|eighth}} {{Motivation and emotion/Lectures/Complete}} <!-- {{Motivation and emotion/Lectures/In development}} --> <!-- {{Motivation and emotion/Lectures/Complete}} --> ==Overview== [[File:Two people with brain cogs turning.png|right|250px|thumb|<div style='text-align: center;'>What causes emotion?<br>Biology?<br>Cognition?<br>Sociality?</div>]] This lecture: * discusses biological, cognitive, and social psychological aspects of [[emotion]] * considers the potential of [[w:affective computing|affective computing]] Take-home messages: * Biology and cognition work together to generate emotion * Facial expressions can influence emotional state * Other people are the source of most of our emotions * Emotions are contagious * Computers are increasingly able to detect, imitate, and respond to human emotion ==Outline== * Biological * Cognitive * Social * Affective computing ==Biological aspects of emotion== [[File:Bipolar Dyptych 1 365.jpg|thumb|right|200px|'''Figure 1'''. What is the role of the body in causing emotion?]] [[File:Expression of the Emotions Figure 1.png|thumb|right|200px|'''Figure 2'''. The human face has over 80 muscles; ~half of which are involved in expressing ~3,000 different expressions of emotion]] * What is the role of the body in emotion (see Figure 1)? ** Does bodily reaction follow emotion? ** Or does bodily reaction lead to emotion? * [[w:James–Lange theory|James–Lange theory of emotion]]: ** Sequence *** Stimulus → Bodily reaction → Emotion e.g., *** Sudden cold shower → Increased heart rate → Surprise? Fear? ** Emotion is a way of making sense of bodily changes ** Criticisms *** Boldy reactions are part of a general response that does not vary much between emotions *** Emotional experiences occur more quickly than physiological reactions ** Contemporary perspective *** Distinct physiological differences are evident for some emotions, but only a few have distinct [[w:Autonomic nervous system|autonomic nervous system]] patterns *** Emotions recruit bodily reactions to facilitate adaptative behaviours such as fighting, fleeing, and nurturing * Brain activations for specific emotions ** Distinct neural circuits underlie the core emotions of joy, fear, rage, and anxiety ([[w:Gray's biopsychological theory of personality|Gray]]) *** Behavioural approach system *** Fight or flight system *** Behavioural inhibition system ** Neuroscience studies of brain activity during emotional experiences map core emotions to distinct patterns of neural activity * [[w:Facial feedback hypothesis|Facial feedback hypothesis]] ** The facial feedback hypothesis (FFH) proposes that emotional experience arises from interpretation of one's facial expression *** Strong view: FF causes emotion *** Weak view: FF modifies emotion *** Critics: FF effect is small ** Facial expression of core emotions is cross-culturally universal (see Figure 2) *** Some emotions (e.g., joy) are easier to recognise than others (e.g., fear) *** Some cultures (e.g., Western) are better at recognising emotion (e.g., because they focus on the mouth) than other cultures (e.g., Eastern because they focus on the eyes) ==Cognitive aspects of emotion== * Biology alone doesn't explain all aspects of emotion, particularly complex emotions such as hope, pride, envy, and gratitude * Appraisal ** Appraisals, rather than events per se, elicit emotion ** Appraisals evaluates significance of events *** Primary: "Is this event significant to me and my well-being?"; if yes, "Is the event good (beneficial) or bad (harmful)?" *** Secondary: "Can I cope with this situation?" → emotion (e.g., liking/disliking) → approach vs. withdrawal ** Complex appraisal models account for approx. 2/3rds of emotional variability by mapping perceived types of benefit/harm/threat to specific emotions * Emotion knowledge ** Ability to differentiate different types and intensities of emotion ** Part of [[w:Emotional intelligence|emotional intelligence]] ** Can be taught and developed * Attribution ** Different explanations for why life events occur leads to different emotional experiences *** Primary: Good or bad? *** Secondary: Cause? ** Example: *** Primary: Good event *** Secondary: Internal cause *** Emotion: Pride ==Social aspects of emotion== [[File:Just love cropped cropped.jpg|thumb|right|200px|'''Figure 3'''. Emotions are socially intense experiences, bringing us together and driving us apart]] * Emotions are socially intense experiences (see Figure 3) ** Through emotional expression, we signal our needs to others ** Social experiences are the most frequent source of day-to-day emotion; these experiences: *** bring us together (e.g., joy and gratitude) and *** push us apart (e.g., anger, contempt, and schadenfreude) ** [[w:Emotional contagion|Emotional contagion]]: People tend to converge on similar emotions due to: *** [[w:Mirror neuron|Mirror neuron]]s fire in response to observing others' emotion *** People tend to mimic others' emotional expressions * Social sharing of emotion provides conversational context for people to re-experience and recount their emotional experiences ** Social-affective sharing: Listening, comforting, empathy, support → provides temporary relief ** Cognitive sharing: Reframing, meaning-making, reprioritising → stimulates cognitive work for emotional healing and recovery * Common view of emotions as short-lived is challenged by social research about emotion because emotional experiences tend to be retold and relived through social sharing, contributing to emotional continuity over days, weeks, and even years ==Affective computing== [[File:Sophia (robot).jpg|thumb|200px|'''Figure 4'''. Electronic devices such as robots are increasingly able to detect and respond to human emotion.]] * [[w:Affective computing|Affective computing]] is an interdisciplinary field which studies how [[w:Artificial intelligence|artificial intelligence]] can recognise and respond to human emotion * If emotions show ANS specificity, then sensors built into electronic devices can monitor human and adjust accordingly (e.g., empathically) (see Figure 4) ==Readings== * Chapter 12: Aspects of emotion ([[Motivation and emotion/Readings/Textbooks/Reeve/2024|Reeve, 2024]]) ==Multimedia== * [https://youtu.be/-PFqzYoKkCc?si=fG7dii--OsI85wL6&t=12 Emotions revealed] (KQED QUEST, 2008, YouTube) (11:05 mins): Explains Paul Ekman's work on codifying the intricate ways in which emotions are revealed through facial expressions * [https://www.youtube.com/embed/TdsFGqhoAEo?si=slTlN00GwXbELkDM&amp;start=18&end=160 Why we can't not smile] (Epic Science, 2014, YouTube) (2:22 mins): Explores unconscious emotional mimicry in relation to smiling * [https://www.youtube.com/watch?v=JMLsHI8aV0g How China is using artificial intelligence in classrooms] (The Wall Street Journal, 2020, YouTube) (5:43 mins): Shows real-world application of emotion AI being used to monitor students, illustrating potentials and risks of affective computing ==Slides== * [https://docs.google.com/presentation/d/1b6mSQQGASDgImEPjDt9DyU4Tm2NtT1GO1k0UdWLSSeE/edit?usp=sharing Aspects of emotion] (Google Slides) <!-- * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) * Handouts ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|Download 6 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|100px]] ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|Download 3 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|100px]] * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) --> ==See also== * [[/Images/]] ; Lectures * [[{{#titleparts:{{PAGENAME}}|2}}/Nature of emotion|Nature of emotion]] (Previous lecture) * [[{{#titleparts:{{PAGENAME}}|2}}/Individual emotions|Individual emotions]] (Next lecture) ;Tutorial * [[{{#titleparts:{{PAGENAME}}|1}}/Tutorials/Measuring emotion|Measuring emotion]] (Tutorial) ;Wikiversity * [[:Category:Motivation and emotion/Book/Affective computing|Affective computing]] (Book chapter category) * [[Motivation and emotion/Book/2014/Appraisal and emotion|Appraisal and emotion]] (Book chapter, 2014) <!-- [[Motivation and emotion/Book/2024/Attribution theory and emotion|Attribution theory and emotion]] (Book chapter 2024) --> * [[Motivation and emotion/Book/2014/Facial Action Coding System|Facial Action Coding System]] (Book chapter, 2014) * [[Motivation and emotion/Book/2023/Smiling and emotion|Smiling and emotion]] (Book chapter, 2023) ;Wikipedia Topics * [[w:Affective computing|Affective computing]] * [[w:Appraisal theory|Appraisal]] * [[w:Attribution (psychology)|Attribution]] * [[w:Gray's biopsychological theory of personality|Gray's biopsychological theory of personality]] * [[w:James–Lange theory|James–Lange theory]] * [[w:Sophia (robot)|Sophia (robot)]] People * [[w:Magda B. Arnold|Magda B. Arnold]] * [[w:Paul Ekman|Paul Ekman]] * [[w:Jeffrey Alan Gray|Jeffrey Gray]] * [[w:Carroll Izard|Carroll Izard]] ==Recording== * [Lecture 8] (2026) * [https://au-lti.bbcollab.com/recording/91c30feb657c4f0db225b3babaefd962 Lecture 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/9c2e9707be814a9d87cc9131d0782390 Lecture 8 recording] (2024) * [https://au-lti.bbcollab.com/recording/4c3533d7c9294b2da8dc4aaa8aac0b93 Lecture 8 recording] (2023) * [https://au-lti.bbcollab.com/recording/def61ff43cfb4f0084e26aac0bc0b52f Lecture 8 recording] (2022) * [https://au-lti.bbcollab.com/recording/7a2b4dd5a81246c096581c3461eae997 Lecture 8 recording] (2021) * [https://au-lti.bbcollab.com/recording/9173da24929249c0905c62f676287d83 Lecture 8 recording] (2020) * [https://echo360.org.au/media/00c6015a-2dd9-48c5-9d78-1f1891908d30/public Lecture 8 recording] (2019) * [https://echo360.org.au/media/17d036bf-4c49-45a9-9dd7-6d9364a51263/public Lecture 8 recording] (2016) --> ==References== {{Hanging indent|1= Gray, J. A. (1987). ''The psychology of fear and stress'' (2nd ed.). Cambridge University Press. <!-- Izard, C. E. (2010). The many meanings/aspects of emotion: Definitions, functions, activation, and regulation. ''Emotion Review'', ''2''(4), 363–370. https://doi.org/10.1177/1754073910374661 --> }} ==External links== * [https://www.paulekman.com Paul Ekman Group] (paulekman.com) * [https://www.bps.org.uk/research-digest/precise-meaning-emotion-words-different-around-world The precise meaning of emotion words is different around the world] (bps.org.uk) * [https://www.youtube.com/watch?v=2Qb_XnEUcY8 The scary truth behind AI's emotional power] (AI for Humans, 2025; YouTube 11:42 mins) ;Multimedia * [https://www.youtube.com/watch?v=ui2_mZWyYK8 Can humanoid robots like Ameca develop emotions?] (Genz Ai Revolution, 2025, YouTube) (3:13 mins)<!-- : Explores whether robots genuinely feel emotions or merely simulate them through sensors and advanced programming. Raises ethical questions about human–robot interaction, emotional mimicry, and the implications of machines acting as companions, caretakers, or friends. --> * [https://youtu.be/WY0j1cZtnp0 In your face] (Mind Field Ep 7, YouTube, 24:33 mins) * [https://www.youtube.com/watch?v=Sq36J9pNaEo Meet Sophia, World's first AI humanoid robot] (Tony Robbins, 2020, YouTube; 9:55 mins): Interview with an AI robot about life, the universe, and everything * [https://www.youtube.com/watch?v=wjW-v0IPT_M Robots that show emotion] (David Hanson, TED talk, 7:29 mins) * [https://www.youtube.com/watch?v=U9cGdRNMdQQ The hidden power of smiling] (Ron Gutman, TED talk; 7:26 mins) * [https://www.youtube.com/watch?v=Uq6XgrYBugo Why we have an emotional connection to robots] (Kate Darling, 2018, TED talk; 11:51 mins) {{Motivation and emotion/Lectures/Navigation}} [[Category:Motivation and emotion/Lectures/Aspects of emotion]] i6pjo2y64j0qs0zy45fp2poto5eql6s 2835082 2835081 2026-09-30T00:04:40Z Jtneill 10242 /* Multimedia */ Fix link 2835082 wikitext text/x-wiki {{Motivation and emotion/Lectures|Lecture 8: Aspects of emotion|eighth}} {{Motivation and emotion/Lectures/Complete}} <!-- {{Motivation and emotion/Lectures/In development}} --> <!-- {{Motivation and emotion/Lectures/Complete}} --> ==Overview== [[File:Two people with brain cogs turning.png|right|250px|thumb|<div style='text-align: center;'>What causes emotion?<br>Biology?<br>Cognition?<br>Sociality?</div>]] This lecture: * discusses biological, cognitive, and social psychological aspects of [[emotion]] * considers the potential of [[w:affective computing|affective computing]] Take-home messages: * Biology and cognition work together to generate emotion * Facial expressions can influence emotional state * Other people are the source of most of our emotions * Emotions are contagious * Computers are increasingly able to detect, imitate, and respond to human emotion ==Outline== * Biological * Cognitive * Social * Affective computing ==Biological aspects of emotion== [[File:Bipolar Dyptych 1 365.jpg|thumb|right|200px|'''Figure 1'''. What is the role of the body in causing emotion?]] [[File:Expression of the Emotions Figure 1.png|thumb|right|200px|'''Figure 2'''. The human face has over 80 muscles; ~half of which are involved in expressing ~3,000 different expressions of emotion]] * What is the role of the body in emotion (see Figure 1)? ** Does bodily reaction follow emotion? ** Or does bodily reaction lead to emotion? * [[w:James–Lange theory|James–Lange theory of emotion]]: ** Sequence *** Stimulus → Bodily reaction → Emotion e.g., *** Sudden cold shower → Increased heart rate → Surprise? Fear? ** Emotion is a way of making sense of bodily changes ** Criticisms *** Boldy reactions are part of a general response that does not vary much between emotions *** Emotional experiences occur more quickly than physiological reactions ** Contemporary perspective *** Distinct physiological differences are evident for some emotions, but only a few have distinct [[w:Autonomic nervous system|autonomic nervous system]] patterns *** Emotions recruit bodily reactions to facilitate adaptative behaviours such as fighting, fleeing, and nurturing * Brain activations for specific emotions ** Distinct neural circuits underlie the core emotions of joy, fear, rage, and anxiety ([[w:Gray's biopsychological theory of personality|Gray]]) *** Behavioural approach system *** Fight or flight system *** Behavioural inhibition system ** Neuroscience studies of brain activity during emotional experiences map core emotions to distinct patterns of neural activity * [[w:Facial feedback hypothesis|Facial feedback hypothesis]] ** The facial feedback hypothesis (FFH) proposes that emotional experience arises from interpretation of one's facial expression *** Strong view: FF causes emotion *** Weak view: FF modifies emotion *** Critics: FF effect is small ** Facial expression of core emotions is cross-culturally universal (see Figure 2) *** Some emotions (e.g., joy) are easier to recognise than others (e.g., fear) *** Some cultures (e.g., Western) are better at recognising emotion (e.g., because they focus on the mouth) than other cultures (e.g., Eastern because they focus on the eyes) ==Cognitive aspects of emotion== * Biology alone doesn't explain all aspects of emotion, particularly complex emotions such as hope, pride, envy, and gratitude * Appraisal ** Appraisals, rather than events per se, elicit emotion ** Appraisals evaluates significance of events *** Primary: "Is this event significant to me and my well-being?"; if yes, "Is the event good (beneficial) or bad (harmful)?" *** Secondary: "Can I cope with this situation?" → emotion (e.g., liking/disliking) → approach vs. withdrawal ** Complex appraisal models account for approx. 2/3rds of emotional variability by mapping perceived types of benefit/harm/threat to specific emotions * Emotion knowledge ** Ability to differentiate different types and intensities of emotion ** Part of [[w:Emotional intelligence|emotional intelligence]] ** Can be taught and developed * Attribution ** Different explanations for why life events occur leads to different emotional experiences *** Primary: Good or bad? *** Secondary: Cause? ** Example: *** Primary: Good event *** Secondary: Internal cause *** Emotion: Pride ==Social aspects of emotion== [[File:Just love cropped cropped.jpg|thumb|right|200px|'''Figure 3'''. Emotions are socially intense experiences, bringing us together and driving us apart]] * Emotions are socially intense experiences (see Figure 3) ** Through emotional expression, we signal our needs to others ** Social experiences are the most frequent source of day-to-day emotion; these experiences: *** bring us together (e.g., joy and gratitude) and *** push us apart (e.g., anger, contempt, and schadenfreude) ** [[w:Emotional contagion|Emotional contagion]]: People tend to converge on similar emotions due to: *** [[w:Mirror neuron|Mirror neuron]]s fire in response to observing others' emotion *** People tend to mimic others' emotional expressions * Social sharing of emotion provides conversational context for people to re-experience and recount their emotional experiences ** Social-affective sharing: Listening, comforting, empathy, support → provides temporary relief ** Cognitive sharing: Reframing, meaning-making, reprioritising → stimulates cognitive work for emotional healing and recovery * Common view of emotions as short-lived is challenged by social research about emotion because emotional experiences tend to be retold and relived through social sharing, contributing to emotional continuity over days, weeks, and even years ==Affective computing== [[File:Sophia (robot).jpg|thumb|200px|'''Figure 4'''. Electronic devices such as robots are increasingly able to detect and respond to human emotion.]] * [[w:Affective computing|Affective computing]] is an interdisciplinary field which studies how [[w:Artificial intelligence|artificial intelligence]] can recognise and respond to human emotion * If emotions show ANS specificity, then sensors built into electronic devices can monitor human and adjust accordingly (e.g., empathically) (see Figure 4) ==Readings== * Chapter 12: Aspects of emotion ([[Motivation and emotion/Readings/Textbooks/Reeve/2024|Reeve, 2024]]) ==Multimedia== * [https://youtu.be/-PFqzYoKkCc?si=fG7dii--OsI85wL6&t=12 Emotions revealed] (KQED QUEST, 2008, YouTube) (11:05 mins): Explains Paul Ekman's work on codifying the intricate ways in which emotions are revealed through facial expressions * [https://youtu.be/TdsFGqhoAEo?si=wEqf3LvrpQpqQ_q8&t=18 Why we can't not smile] (Epic Science, 2014, YouTube) (2:29 mins): Explores unconscious emotional mimicry in relation to smiling * [https://www.youtube.com/watch?v=JMLsHI8aV0g How China is using artificial intelligence in classrooms] (The Wall Street Journal, 2020, YouTube) (5:43 mins): Shows real-world application of emotion AI being used to monitor students, illustrating potentials and risks of affective computing ==Slides== * [https://docs.google.com/presentation/d/1b6mSQQGASDgImEPjDt9DyU4Tm2NtT1GO1k0UdWLSSeE/edit?usp=sharing Aspects of emotion] (Google Slides) <!-- * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) * Handouts ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|Download 6 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|100px]] ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|Download 3 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|100px]] * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) --> ==See also== * [[/Images/]] ; Lectures * [[{{#titleparts:{{PAGENAME}}|2}}/Nature of emotion|Nature of emotion]] (Previous lecture) * [[{{#titleparts:{{PAGENAME}}|2}}/Individual emotions|Individual emotions]] (Next lecture) ;Tutorial * [[{{#titleparts:{{PAGENAME}}|1}}/Tutorials/Measuring emotion|Measuring emotion]] (Tutorial) ;Wikiversity * [[:Category:Motivation and emotion/Book/Affective computing|Affective computing]] (Book chapter category) * [[Motivation and emotion/Book/2014/Appraisal and emotion|Appraisal and emotion]] (Book chapter, 2014) <!-- [[Motivation and emotion/Book/2024/Attribution theory and emotion|Attribution theory and emotion]] (Book chapter 2024) --> * [[Motivation and emotion/Book/2014/Facial Action Coding System|Facial Action Coding System]] (Book chapter, 2014) * [[Motivation and emotion/Book/2023/Smiling and emotion|Smiling and emotion]] (Book chapter, 2023) ;Wikipedia Topics * [[w:Affective computing|Affective computing]] * [[w:Appraisal theory|Appraisal]] * [[w:Attribution (psychology)|Attribution]] * [[w:Gray's biopsychological theory of personality|Gray's biopsychological theory of personality]] * [[w:James–Lange theory|James–Lange theory]] * [[w:Sophia (robot)|Sophia (robot)]] People * [[w:Magda B. Arnold|Magda B. Arnold]] * [[w:Paul Ekman|Paul Ekman]] * [[w:Jeffrey Alan Gray|Jeffrey Gray]] * [[w:Carroll Izard|Carroll Izard]] ==Recording== * [Lecture 8] (2026) * [https://au-lti.bbcollab.com/recording/91c30feb657c4f0db225b3babaefd962 Lecture 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/9c2e9707be814a9d87cc9131d0782390 Lecture 8 recording] (2024) * [https://au-lti.bbcollab.com/recording/4c3533d7c9294b2da8dc4aaa8aac0b93 Lecture 8 recording] (2023) * [https://au-lti.bbcollab.com/recording/def61ff43cfb4f0084e26aac0bc0b52f Lecture 8 recording] (2022) * [https://au-lti.bbcollab.com/recording/7a2b4dd5a81246c096581c3461eae997 Lecture 8 recording] (2021) * [https://au-lti.bbcollab.com/recording/9173da24929249c0905c62f676287d83 Lecture 8 recording] (2020) * [https://echo360.org.au/media/00c6015a-2dd9-48c5-9d78-1f1891908d30/public Lecture 8 recording] (2019) * [https://echo360.org.au/media/17d036bf-4c49-45a9-9dd7-6d9364a51263/public Lecture 8 recording] (2016) --> ==References== {{Hanging indent|1= Gray, J. A. (1987). ''The psychology of fear and stress'' (2nd ed.). Cambridge University Press. <!-- Izard, C. E. (2010). The many meanings/aspects of emotion: Definitions, functions, activation, and regulation. ''Emotion Review'', ''2''(4), 363–370. https://doi.org/10.1177/1754073910374661 --> }} ==External links== * [https://www.paulekman.com Paul Ekman Group] (paulekman.com) * [https://www.bps.org.uk/research-digest/precise-meaning-emotion-words-different-around-world The precise meaning of emotion words is different around the world] (bps.org.uk) * [https://www.youtube.com/watch?v=2Qb_XnEUcY8 The scary truth behind AI's emotional power] (AI for Humans, 2025; YouTube 11:42 mins) ;Multimedia * [https://www.youtube.com/watch?v=ui2_mZWyYK8 Can humanoid robots like Ameca develop emotions?] (Genz Ai Revolution, 2025, YouTube) (3:13 mins)<!-- : Explores whether robots genuinely feel emotions or merely simulate them through sensors and advanced programming. Raises ethical questions about human–robot interaction, emotional mimicry, and the implications of machines acting as companions, caretakers, or friends. --> * [https://youtu.be/WY0j1cZtnp0 In your face] (Mind Field Ep 7, YouTube, 24:33 mins) * [https://www.youtube.com/watch?v=Sq36J9pNaEo Meet Sophia, World's first AI humanoid robot] (Tony Robbins, 2020, YouTube; 9:55 mins): Interview with an AI robot about life, the universe, and everything * [https://www.youtube.com/watch?v=wjW-v0IPT_M Robots that show emotion] (David Hanson, TED talk, 7:29 mins) * [https://www.youtube.com/watch?v=U9cGdRNMdQQ The hidden power of smiling] (Ron Gutman, TED talk; 7:26 mins) * [https://www.youtube.com/watch?v=Uq6XgrYBugo Why we have an emotional connection to robots] (Kate Darling, 2018, TED talk; 11:51 mins) {{Motivation and emotion/Lectures/Navigation}} [[Category:Motivation and emotion/Lectures/Aspects of emotion]] kp8flzl6ynghu1ol0m7pphjgqs9zotx 2835090 2835082 2026-09-30T02:12:36Z Jtneill 10242 /* External links */ * https://www.darwinproject.ac.uk/commentary/human-nature/expression-emotions The expression of emotions] (Darwin Project, University of Cambridge) 2835090 wikitext text/x-wiki {{Motivation and emotion/Lectures|Lecture 8: Aspects of emotion|eighth}} {{Motivation and emotion/Lectures/Complete}} <!-- {{Motivation and emotion/Lectures/In development}} --> <!-- {{Motivation and emotion/Lectures/Complete}} --> ==Overview== [[File:Two people with brain cogs turning.png|right|250px|thumb|<div style='text-align: center;'>What causes emotion?<br>Biology?<br>Cognition?<br>Sociality?</div>]] This lecture: * discusses biological, cognitive, and social psychological aspects of [[emotion]] * considers the potential of [[w:affective computing|affective computing]] Take-home messages: * Biology and cognition work together to generate emotion * Facial expressions can influence emotional state * Other people are the source of most of our emotions * Emotions are contagious * Computers are increasingly able to detect, imitate, and respond to human emotion ==Outline== * Biological * Cognitive * Social * Affective computing ==Biological aspects of emotion== [[File:Bipolar Dyptych 1 365.jpg|thumb|right|200px|'''Figure 1'''. What is the role of the body in causing emotion?]] [[File:Expression of the Emotions Figure 1.png|thumb|right|200px|'''Figure 2'''. The human face has over 80 muscles; ~half of which are involved in expressing ~3,000 different expressions of emotion]] * What is the role of the body in emotion (see Figure 1)? ** Does bodily reaction follow emotion? ** Or does bodily reaction lead to emotion? * [[w:James–Lange theory|James–Lange theory of emotion]]: ** Sequence *** Stimulus → Bodily reaction → Emotion e.g., *** Sudden cold shower → Increased heart rate → Surprise? Fear? ** Emotion is a way of making sense of bodily changes ** Criticisms *** Boldy reactions are part of a general response that does not vary much between emotions *** Emotional experiences occur more quickly than physiological reactions ** Contemporary perspective *** Distinct physiological differences are evident for some emotions, but only a few have distinct [[w:Autonomic nervous system|autonomic nervous system]] patterns *** Emotions recruit bodily reactions to facilitate adaptative behaviours such as fighting, fleeing, and nurturing * Brain activations for specific emotions ** Distinct neural circuits underlie the core emotions of joy, fear, rage, and anxiety ([[w:Gray's biopsychological theory of personality|Gray]]) *** Behavioural approach system *** Fight or flight system *** Behavioural inhibition system ** Neuroscience studies of brain activity during emotional experiences map core emotions to distinct patterns of neural activity * [[w:Facial feedback hypothesis|Facial feedback hypothesis]] ** The facial feedback hypothesis (FFH) proposes that emotional experience arises from interpretation of one's facial expression *** Strong view: FF causes emotion *** Weak view: FF modifies emotion *** Critics: FF effect is small ** Facial expression of core emotions is cross-culturally universal (see Figure 2) *** Some emotions (e.g., joy) are easier to recognise than others (e.g., fear) *** Some cultures (e.g., Western) are better at recognising emotion (e.g., because they focus on the mouth) than other cultures (e.g., Eastern because they focus on the eyes) ==Cognitive aspects of emotion== * Biology alone doesn't explain all aspects of emotion, particularly complex emotions such as hope, pride, envy, and gratitude * Appraisal ** Appraisals, rather than events per se, elicit emotion ** Appraisals evaluates significance of events *** Primary: "Is this event significant to me and my well-being?"; if yes, "Is the event good (beneficial) or bad (harmful)?" *** Secondary: "Can I cope with this situation?" → emotion (e.g., liking/disliking) → approach vs. withdrawal ** Complex appraisal models account for approx. 2/3rds of emotional variability by mapping perceived types of benefit/harm/threat to specific emotions * Emotion knowledge ** Ability to differentiate different types and intensities of emotion ** Part of [[w:Emotional intelligence|emotional intelligence]] ** Can be taught and developed * Attribution ** Different explanations for why life events occur leads to different emotional experiences *** Primary: Good or bad? *** Secondary: Cause? ** Example: *** Primary: Good event *** Secondary: Internal cause *** Emotion: Pride ==Social aspects of emotion== [[File:Just love cropped cropped.jpg|thumb|right|200px|'''Figure 3'''. Emotions are socially intense experiences, bringing us together and driving us apart]] * Emotions are socially intense experiences (see Figure 3) ** Through emotional expression, we signal our needs to others ** Social experiences are the most frequent source of day-to-day emotion; these experiences: *** bring us together (e.g., joy and gratitude) and *** push us apart (e.g., anger, contempt, and schadenfreude) ** [[w:Emotional contagion|Emotional contagion]]: People tend to converge on similar emotions due to: *** [[w:Mirror neuron|Mirror neuron]]s fire in response to observing others' emotion *** People tend to mimic others' emotional expressions * Social sharing of emotion provides conversational context for people to re-experience and recount their emotional experiences ** Social-affective sharing: Listening, comforting, empathy, support → provides temporary relief ** Cognitive sharing: Reframing, meaning-making, reprioritising → stimulates cognitive work for emotional healing and recovery * Common view of emotions as short-lived is challenged by social research about emotion because emotional experiences tend to be retold and relived through social sharing, contributing to emotional continuity over days, weeks, and even years ==Affective computing== [[File:Sophia (robot).jpg|thumb|200px|'''Figure 4'''. Electronic devices such as robots are increasingly able to detect and respond to human emotion.]] * [[w:Affective computing|Affective computing]] is an interdisciplinary field which studies how [[w:Artificial intelligence|artificial intelligence]] can recognise and respond to human emotion * If emotions show ANS specificity, then sensors built into electronic devices can monitor human and adjust accordingly (e.g., empathically) (see Figure 4) ==Readings== * Chapter 12: Aspects of emotion ([[Motivation and emotion/Readings/Textbooks/Reeve/2024|Reeve, 2024]]) ==Multimedia== * [https://youtu.be/-PFqzYoKkCc?si=fG7dii--OsI85wL6&t=12 Emotions revealed] (KQED QUEST, 2008, YouTube) (11:05 mins): Explains Paul Ekman's work on codifying the intricate ways in which emotions are revealed through facial expressions * [https://youtu.be/TdsFGqhoAEo?si=wEqf3LvrpQpqQ_q8&t=18 Why we can't not smile] (Epic Science, 2014, YouTube) (2:29 mins): Explores unconscious emotional mimicry in relation to smiling * [https://www.youtube.com/watch?v=JMLsHI8aV0g How China is using artificial intelligence in classrooms] (The Wall Street Journal, 2020, YouTube) (5:43 mins): Shows real-world application of emotion AI being used to monitor students, illustrating potentials and risks of affective computing ==Slides== * [https://docs.google.com/presentation/d/1b6mSQQGASDgImEPjDt9DyU4Tm2NtT1GO1k0UdWLSSeE/edit?usp=sharing Aspects of emotion] (Google Slides) <!-- * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) * Handouts ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|Download 6 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|100px]] ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|Download 3 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|100px]] * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) --> ==See also== * [[/Images/]] ; Lectures * [[{{#titleparts:{{PAGENAME}}|2}}/Nature of emotion|Nature of emotion]] (Previous lecture) * [[{{#titleparts:{{PAGENAME}}|2}}/Individual emotions|Individual emotions]] (Next lecture) ;Tutorial * [[{{#titleparts:{{PAGENAME}}|1}}/Tutorials/Measuring emotion|Measuring emotion]] (Tutorial) ;Wikiversity * [[:Category:Motivation and emotion/Book/Affective computing|Affective computing]] (Book chapter category) * [[Motivation and emotion/Book/2014/Appraisal and emotion|Appraisal and emotion]] (Book chapter, 2014) <!-- [[Motivation and emotion/Book/2024/Attribution theory and emotion|Attribution theory and emotion]] (Book chapter 2024) --> * [[Motivation and emotion/Book/2014/Facial Action Coding System|Facial Action Coding System]] (Book chapter, 2014) * [[Motivation and emotion/Book/2023/Smiling and emotion|Smiling and emotion]] (Book chapter, 2023) ;Wikipedia Topics * [[w:Affective computing|Affective computing]] * [[w:Appraisal theory|Appraisal]] * [[w:Attribution (psychology)|Attribution]] * [[w:Gray's biopsychological theory of personality|Gray's biopsychological theory of personality]] * [[w:James–Lange theory|James–Lange theory]] * [[w:Sophia (robot)|Sophia (robot)]] People * [[w:Magda B. Arnold|Magda B. Arnold]] * [[w:Paul Ekman|Paul Ekman]] * [[w:Jeffrey Alan Gray|Jeffrey Gray]] * [[w:Carroll Izard|Carroll Izard]] ==Recording== * [Lecture 8] (2026) * [https://au-lti.bbcollab.com/recording/91c30feb657c4f0db225b3babaefd962 Lecture 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/9c2e9707be814a9d87cc9131d0782390 Lecture 8 recording] (2024) * [https://au-lti.bbcollab.com/recording/4c3533d7c9294b2da8dc4aaa8aac0b93 Lecture 8 recording] (2023) * [https://au-lti.bbcollab.com/recording/def61ff43cfb4f0084e26aac0bc0b52f Lecture 8 recording] (2022) * [https://au-lti.bbcollab.com/recording/7a2b4dd5a81246c096581c3461eae997 Lecture 8 recording] (2021) * [https://au-lti.bbcollab.com/recording/9173da24929249c0905c62f676287d83 Lecture 8 recording] (2020) * [https://echo360.org.au/media/00c6015a-2dd9-48c5-9d78-1f1891908d30/public Lecture 8 recording] (2019) * [https://echo360.org.au/media/17d036bf-4c49-45a9-9dd7-6d9364a51263/public Lecture 8 recording] (2016) --> ==References== {{Hanging indent|1= Gray, J. A. (1987). ''The psychology of fear and stress'' (2nd ed.). Cambridge University Press. <!-- Izard, C. E. (2010). The many meanings/aspects of emotion: Definitions, functions, activation, and regulation. ''Emotion Review'', ''2''(4), 363–370. https://doi.org/10.1177/1754073910374661 --> }} ==External links== * [https://www.paulekman.com Paul Ekman Group] (paulekman.com) * [https://www.bps.org.uk/research-digest/precise-meaning-emotion-words-different-around-world The precise meaning of emotion words is different around the world] (bps.org.uk) * https://www.darwinproject.ac.uk/commentary/human-nature/expression-emotions The expression of emotions] (Darwin Project, University of Cambridge) * [https://www.youtube.com/watch?v=2Qb_XnEUcY8 The scary truth behind AI's emotional power] (AI for Humans, 2025; YouTube 11:42 mins) ;Multimedia * [https://www.youtube.com/watch?v=ui2_mZWyYK8 Can humanoid robots like Ameca develop emotions?] (Genz Ai Revolution, 2025, YouTube) (3:13 mins)<!-- : Explores whether robots genuinely feel emotions or merely simulate them through sensors and advanced programming. Raises ethical questions about human–robot interaction, emotional mimicry, and the implications of machines acting as companions, caretakers, or friends. --> * [https://youtu.be/WY0j1cZtnp0 In your face] (Mind Field Ep 7, YouTube, 24:33 mins) * [https://www.youtube.com/watch?v=Sq36J9pNaEo Meet Sophia, World's first AI humanoid robot] (Tony Robbins, 2020, YouTube; 9:55 mins): Interview with an AI robot about life, the universe, and everything * [https://www.youtube.com/watch?v=wjW-v0IPT_M Robots that show emotion] (David Hanson, TED talk, 7:29 mins) * [https://www.youtube.com/watch?v=U9cGdRNMdQQ The hidden power of smiling] (Ron Gutman, TED talk; 7:26 mins) * [https://www.youtube.com/watch?v=Uq6XgrYBugo Why we have an emotional connection to robots] (Kate Darling, 2018, TED talk; 11:51 mins) {{Motivation and emotion/Lectures/Navigation}} [[Category:Motivation and emotion/Lectures/Aspects of emotion]] 71ch31rmilf9e4rhxhdkotpmk5yuj94 2835092 2835090 2026-09-30T02:17:52Z Jtneill 10242 /* External links */ 2835092 wikitext text/x-wiki {{Motivation and emotion/Lectures|Lecture 8: Aspects of emotion|eighth}} {{Motivation and emotion/Lectures/Complete}} <!-- {{Motivation and emotion/Lectures/In development}} --> <!-- {{Motivation and emotion/Lectures/Complete}} --> ==Overview== [[File:Two people with brain cogs turning.png|right|250px|thumb|<div style='text-align: center;'>What causes emotion?<br>Biology?<br>Cognition?<br>Sociality?</div>]] This lecture: * discusses biological, cognitive, and social psychological aspects of [[emotion]] * considers the potential of [[w:affective computing|affective computing]] Take-home messages: * Biology and cognition work together to generate emotion * Facial expressions can influence emotional state * Other people are the source of most of our emotions * Emotions are contagious * Computers are increasingly able to detect, imitate, and respond to human emotion ==Outline== * Biological * Cognitive * Social * Affective computing ==Biological aspects of emotion== [[File:Bipolar Dyptych 1 365.jpg|thumb|right|200px|'''Figure 1'''. What is the role of the body in causing emotion?]] [[File:Expression of the Emotions Figure 1.png|thumb|right|200px|'''Figure 2'''. The human face has over 80 muscles; ~half of which are involved in expressing ~3,000 different expressions of emotion]] * What is the role of the body in emotion (see Figure 1)? ** Does bodily reaction follow emotion? ** Or does bodily reaction lead to emotion? * [[w:James–Lange theory|James–Lange theory of emotion]]: ** Sequence *** Stimulus → Bodily reaction → Emotion e.g., *** Sudden cold shower → Increased heart rate → Surprise? Fear? ** Emotion is a way of making sense of bodily changes ** Criticisms *** Boldy reactions are part of a general response that does not vary much between emotions *** Emotional experiences occur more quickly than physiological reactions ** Contemporary perspective *** Distinct physiological differences are evident for some emotions, but only a few have distinct [[w:Autonomic nervous system|autonomic nervous system]] patterns *** Emotions recruit bodily reactions to facilitate adaptative behaviours such as fighting, fleeing, and nurturing * Brain activations for specific emotions ** Distinct neural circuits underlie the core emotions of joy, fear, rage, and anxiety ([[w:Gray's biopsychological theory of personality|Gray]]) *** Behavioural approach system *** Fight or flight system *** Behavioural inhibition system ** Neuroscience studies of brain activity during emotional experiences map core emotions to distinct patterns of neural activity * [[w:Facial feedback hypothesis|Facial feedback hypothesis]] ** The facial feedback hypothesis (FFH) proposes that emotional experience arises from interpretation of one's facial expression *** Strong view: FF causes emotion *** Weak view: FF modifies emotion *** Critics: FF effect is small ** Facial expression of core emotions is cross-culturally universal (see Figure 2) *** Some emotions (e.g., joy) are easier to recognise than others (e.g., fear) *** Some cultures (e.g., Western) are better at recognising emotion (e.g., because they focus on the mouth) than other cultures (e.g., Eastern because they focus on the eyes) ==Cognitive aspects of emotion== * Biology alone doesn't explain all aspects of emotion, particularly complex emotions such as hope, pride, envy, and gratitude * Appraisal ** Appraisals, rather than events per se, elicit emotion ** Appraisals evaluates significance of events *** Primary: "Is this event significant to me and my well-being?"; if yes, "Is the event good (beneficial) or bad (harmful)?" *** Secondary: "Can I cope with this situation?" → emotion (e.g., liking/disliking) → approach vs. withdrawal ** Complex appraisal models account for approx. 2/3rds of emotional variability by mapping perceived types of benefit/harm/threat to specific emotions * Emotion knowledge ** Ability to differentiate different types and intensities of emotion ** Part of [[w:Emotional intelligence|emotional intelligence]] ** Can be taught and developed * Attribution ** Different explanations for why life events occur leads to different emotional experiences *** Primary: Good or bad? *** Secondary: Cause? ** Example: *** Primary: Good event *** Secondary: Internal cause *** Emotion: Pride ==Social aspects of emotion== [[File:Just love cropped cropped.jpg|thumb|right|200px|'''Figure 3'''. Emotions are socially intense experiences, bringing us together and driving us apart]] * Emotions are socially intense experiences (see Figure 3) ** Through emotional expression, we signal our needs to others ** Social experiences are the most frequent source of day-to-day emotion; these experiences: *** bring us together (e.g., joy and gratitude) and *** push us apart (e.g., anger, contempt, and schadenfreude) ** [[w:Emotional contagion|Emotional contagion]]: People tend to converge on similar emotions due to: *** [[w:Mirror neuron|Mirror neuron]]s fire in response to observing others' emotion *** People tend to mimic others' emotional expressions * Social sharing of emotion provides conversational context for people to re-experience and recount their emotional experiences ** Social-affective sharing: Listening, comforting, empathy, support → provides temporary relief ** Cognitive sharing: Reframing, meaning-making, reprioritising → stimulates cognitive work for emotional healing and recovery * Common view of emotions as short-lived is challenged by social research about emotion because emotional experiences tend to be retold and relived through social sharing, contributing to emotional continuity over days, weeks, and even years ==Affective computing== [[File:Sophia (robot).jpg|thumb|200px|'''Figure 4'''. Electronic devices such as robots are increasingly able to detect and respond to human emotion.]] * [[w:Affective computing|Affective computing]] is an interdisciplinary field which studies how [[w:Artificial intelligence|artificial intelligence]] can recognise and respond to human emotion * If emotions show ANS specificity, then sensors built into electronic devices can monitor human and adjust accordingly (e.g., empathically) (see Figure 4) ==Readings== * Chapter 12: Aspects of emotion ([[Motivation and emotion/Readings/Textbooks/Reeve/2024|Reeve, 2024]]) ==Multimedia== * [https://youtu.be/-PFqzYoKkCc?si=fG7dii--OsI85wL6&t=12 Emotions revealed] (KQED QUEST, 2008, YouTube) (11:05 mins): Explains Paul Ekman's work on codifying the intricate ways in which emotions are revealed through facial expressions * [https://youtu.be/TdsFGqhoAEo?si=wEqf3LvrpQpqQ_q8&t=18 Why we can't not smile] (Epic Science, 2014, YouTube) (2:29 mins): Explores unconscious emotional mimicry in relation to smiling * [https://www.youtube.com/watch?v=JMLsHI8aV0g How China is using artificial intelligence in classrooms] (The Wall Street Journal, 2020, YouTube) (5:43 mins): Shows real-world application of emotion AI being used to monitor students, illustrating potentials and risks of affective computing ==Slides== * [https://docs.google.com/presentation/d/1b6mSQQGASDgImEPjDt9DyU4Tm2NtT1GO1k0UdWLSSeE/edit?usp=sharing Aspects of emotion] (Google Slides) <!-- * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) * Handouts ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|Download 6 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|100px]] ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|Download 3 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|100px]] * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) --> ==See also== * [[/Images/]] ; Lectures * [[{{#titleparts:{{PAGENAME}}|2}}/Nature of emotion|Nature of emotion]] (Previous lecture) * [[{{#titleparts:{{PAGENAME}}|2}}/Individual emotions|Individual emotions]] (Next lecture) ;Tutorial * [[{{#titleparts:{{PAGENAME}}|1}}/Tutorials/Measuring emotion|Measuring emotion]] (Tutorial) ;Wikiversity * [[:Category:Motivation and emotion/Book/Affective computing|Affective computing]] (Book chapter category) * [[Motivation and emotion/Book/2014/Appraisal and emotion|Appraisal and emotion]] (Book chapter, 2014) <!-- [[Motivation and emotion/Book/2024/Attribution theory and emotion|Attribution theory and emotion]] (Book chapter 2024) --> * [[Motivation and emotion/Book/2014/Facial Action Coding System|Facial Action Coding System]] (Book chapter, 2014) * [[Motivation and emotion/Book/2023/Smiling and emotion|Smiling and emotion]] (Book chapter, 2023) ;Wikipedia Topics * [[w:Affective computing|Affective computing]] * [[w:Appraisal theory|Appraisal]] * [[w:Attribution (psychology)|Attribution]] * [[w:Gray's biopsychological theory of personality|Gray's biopsychological theory of personality]] * [[w:James–Lange theory|James–Lange theory]] * [[w:Sophia (robot)|Sophia (robot)]] People * [[w:Magda B. Arnold|Magda B. Arnold]] * [[w:Paul Ekman|Paul Ekman]] * [[w:Jeffrey Alan Gray|Jeffrey Gray]] * [[w:Carroll Izard|Carroll Izard]] ==Recording== * [Lecture 8] (2026) * [https://au-lti.bbcollab.com/recording/91c30feb657c4f0db225b3babaefd962 Lecture 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/9c2e9707be814a9d87cc9131d0782390 Lecture 8 recording] (2024) * [https://au-lti.bbcollab.com/recording/4c3533d7c9294b2da8dc4aaa8aac0b93 Lecture 8 recording] (2023) * [https://au-lti.bbcollab.com/recording/def61ff43cfb4f0084e26aac0bc0b52f Lecture 8 recording] (2022) * [https://au-lti.bbcollab.com/recording/7a2b4dd5a81246c096581c3461eae997 Lecture 8 recording] (2021) * [https://au-lti.bbcollab.com/recording/9173da24929249c0905c62f676287d83 Lecture 8 recording] (2020) * [https://echo360.org.au/media/00c6015a-2dd9-48c5-9d78-1f1891908d30/public Lecture 8 recording] (2019) * [https://echo360.org.au/media/17d036bf-4c49-45a9-9dd7-6d9364a51263/public Lecture 8 recording] (2016) --> ==References== {{Hanging indent|1= Gray, J. A. (1987). ''The psychology of fear and stress'' (2nd ed.). Cambridge University Press. <!-- Izard, C. E. (2010). The many meanings/aspects of emotion: Definitions, functions, activation, and regulation. ''Emotion Review'', ''2''(4), 363–370. https://doi.org/10.1177/1754073910374661 --> }} ==External links== * [https://www.paulekman.com Paul Ekman Group] (paulekman.com) * [https://www.bps.org.uk/research-digest/precise-meaning-emotion-words-different-around-world The precise meaning of emotion words is different around the world] (bps.org.uk) * [https://www.darwinproject.ac.uk/commentary/human-nature/expression-emotions The expression of emotions] (Darwin Project, University of Cambridge) * [https://www.youtube.com/watch?v=2Qb_XnEUcY8 The scary truth behind AI's emotional power] (AI for Humans, 2025; YouTube 11:42 mins) ;Multimedia * [https://www.youtube.com/watch?v=ui2_mZWyYK8 Can humanoid robots like Ameca develop emotions?] (Genz Ai Revolution, 2025, YouTube) (3:13 mins)<!-- : Explores whether robots genuinely feel emotions or merely simulate them through sensors and advanced programming. Raises ethical questions about human–robot interaction, emotional mimicry, and the implications of machines acting as companions, caretakers, or friends. --> * [https://youtu.be/WY0j1cZtnp0 In your face] (Mind Field Ep 7, YouTube, 24:33 mins) * [https://www.youtube.com/watch?v=Sq36J9pNaEo Meet Sophia, World's first AI humanoid robot] (Tony Robbins, 2020, YouTube; 9:55 mins): Interview with an AI robot about life, the universe, and everything * [https://www.youtube.com/watch?v=wjW-v0IPT_M Robots that show emotion] (David Hanson, TED talk, 7:29 mins) * [https://www.youtube.com/watch?v=U9cGdRNMdQQ The hidden power of smiling] (Ron Gutman, TED talk; 7:26 mins) * [https://www.youtube.com/watch?v=Uq6XgrYBugo Why we have an emotional connection to robots] (Kate Darling, 2018, TED talk; 11:51 mins) {{Motivation and emotion/Lectures/Navigation}} [[Category:Motivation and emotion/Lectures/Aspects of emotion]] 76g3yf9klcuiyl9e5l1ihysywc4wmrg 2835098 2835092 2026-09-30T03:04:13Z Jtneill 10242 /* Recording */ 2835098 wikitext text/x-wiki {{Motivation and emotion/Lectures|Lecture 8: Aspects of emotion|eighth}} {{Motivation and emotion/Lectures/Complete}} <!-- {{Motivation and emotion/Lectures/In development}} --> <!-- {{Motivation and emotion/Lectures/Complete}} --> ==Overview== [[File:Two people with brain cogs turning.png|right|250px|thumb|<div style='text-align: center;'>What causes emotion?<br>Biology?<br>Cognition?<br>Sociality?</div>]] This lecture: * discusses biological, cognitive, and social psychological aspects of [[emotion]] * considers the potential of [[w:affective computing|affective computing]] Take-home messages: * Biology and cognition work together to generate emotion * Facial expressions can influence emotional state * Other people are the source of most of our emotions * Emotions are contagious * Computers are increasingly able to detect, imitate, and respond to human emotion ==Outline== * Biological * Cognitive * Social * Affective computing ==Biological aspects of emotion== [[File:Bipolar Dyptych 1 365.jpg|thumb|right|200px|'''Figure 1'''. What is the role of the body in causing emotion?]] [[File:Expression of the Emotions Figure 1.png|thumb|right|200px|'''Figure 2'''. The human face has over 80 muscles; ~half of which are involved in expressing ~3,000 different expressions of emotion]] * What is the role of the body in emotion (see Figure 1)? ** Does bodily reaction follow emotion? ** Or does bodily reaction lead to emotion? * [[w:James–Lange theory|James–Lange theory of emotion]]: ** Sequence *** Stimulus → Bodily reaction → Emotion e.g., *** Sudden cold shower → Increased heart rate → Surprise? Fear? ** Emotion is a way of making sense of bodily changes ** Criticisms *** Boldy reactions are part of a general response that does not vary much between emotions *** Emotional experiences occur more quickly than physiological reactions ** Contemporary perspective *** Distinct physiological differences are evident for some emotions, but only a few have distinct [[w:Autonomic nervous system|autonomic nervous system]] patterns *** Emotions recruit bodily reactions to facilitate adaptative behaviours such as fighting, fleeing, and nurturing * Brain activations for specific emotions ** Distinct neural circuits underlie the core emotions of joy, fear, rage, and anxiety ([[w:Gray's biopsychological theory of personality|Gray]]) *** Behavioural approach system *** Fight or flight system *** Behavioural inhibition system ** Neuroscience studies of brain activity during emotional experiences map core emotions to distinct patterns of neural activity * [[w:Facial feedback hypothesis|Facial feedback hypothesis]] ** The facial feedback hypothesis (FFH) proposes that emotional experience arises from interpretation of one's facial expression *** Strong view: FF causes emotion *** Weak view: FF modifies emotion *** Critics: FF effect is small ** Facial expression of core emotions is cross-culturally universal (see Figure 2) *** Some emotions (e.g., joy) are easier to recognise than others (e.g., fear) *** Some cultures (e.g., Western) are better at recognising emotion (e.g., because they focus on the mouth) than other cultures (e.g., Eastern because they focus on the eyes) ==Cognitive aspects of emotion== * Biology alone doesn't explain all aspects of emotion, particularly complex emotions such as hope, pride, envy, and gratitude * Appraisal ** Appraisals, rather than events per se, elicit emotion ** Appraisals evaluates significance of events *** Primary: "Is this event significant to me and my well-being?"; if yes, "Is the event good (beneficial) or bad (harmful)?" *** Secondary: "Can I cope with this situation?" → emotion (e.g., liking/disliking) → approach vs. withdrawal ** Complex appraisal models account for approx. 2/3rds of emotional variability by mapping perceived types of benefit/harm/threat to specific emotions * Emotion knowledge ** Ability to differentiate different types and intensities of emotion ** Part of [[w:Emotional intelligence|emotional intelligence]] ** Can be taught and developed * Attribution ** Different explanations for why life events occur leads to different emotional experiences *** Primary: Good or bad? *** Secondary: Cause? ** Example: *** Primary: Good event *** Secondary: Internal cause *** Emotion: Pride ==Social aspects of emotion== [[File:Just love cropped cropped.jpg|thumb|right|200px|'''Figure 3'''. Emotions are socially intense experiences, bringing us together and driving us apart]] * Emotions are socially intense experiences (see Figure 3) ** Through emotional expression, we signal our needs to others ** Social experiences are the most frequent source of day-to-day emotion; these experiences: *** bring us together (e.g., joy and gratitude) and *** push us apart (e.g., anger, contempt, and schadenfreude) ** [[w:Emotional contagion|Emotional contagion]]: People tend to converge on similar emotions due to: *** [[w:Mirror neuron|Mirror neuron]]s fire in response to observing others' emotion *** People tend to mimic others' emotional expressions * Social sharing of emotion provides conversational context for people to re-experience and recount their emotional experiences ** Social-affective sharing: Listening, comforting, empathy, support → provides temporary relief ** Cognitive sharing: Reframing, meaning-making, reprioritising → stimulates cognitive work for emotional healing and recovery * Common view of emotions as short-lived is challenged by social research about emotion because emotional experiences tend to be retold and relived through social sharing, contributing to emotional continuity over days, weeks, and even years ==Affective computing== [[File:Sophia (robot).jpg|thumb|200px|'''Figure 4'''. Electronic devices such as robots are increasingly able to detect and respond to human emotion.]] * [[w:Affective computing|Affective computing]] is an interdisciplinary field which studies how [[w:Artificial intelligence|artificial intelligence]] can recognise and respond to human emotion * If emotions show ANS specificity, then sensors built into electronic devices can monitor human and adjust accordingly (e.g., empathically) (see Figure 4) ==Readings== * Chapter 12: Aspects of emotion ([[Motivation and emotion/Readings/Textbooks/Reeve/2024|Reeve, 2024]]) ==Multimedia== * [https://youtu.be/-PFqzYoKkCc?si=fG7dii--OsI85wL6&t=12 Emotions revealed] (KQED QUEST, 2008, YouTube) (11:05 mins): Explains Paul Ekman's work on codifying the intricate ways in which emotions are revealed through facial expressions * [https://youtu.be/TdsFGqhoAEo?si=wEqf3LvrpQpqQ_q8&t=18 Why we can't not smile] (Epic Science, 2014, YouTube) (2:29 mins): Explores unconscious emotional mimicry in relation to smiling * [https://www.youtube.com/watch?v=JMLsHI8aV0g How China is using artificial intelligence in classrooms] (The Wall Street Journal, 2020, YouTube) (5:43 mins): Shows real-world application of emotion AI being used to monitor students, illustrating potentials and risks of affective computing ==Slides== * [https://docs.google.com/presentation/d/1b6mSQQGASDgImEPjDt9DyU4Tm2NtT1GO1k0UdWLSSeE/edit?usp=sharing Aspects of emotion] (Google Slides) <!-- * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) * Handouts ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|Download 6 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|100px]] ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|Download 3 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|100px]] * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) --> ==See also== * [[/Images/]] ; Lectures * [[{{#titleparts:{{PAGENAME}}|2}}/Nature of emotion|Nature of emotion]] (Previous lecture) * [[{{#titleparts:{{PAGENAME}}|2}}/Individual emotions|Individual emotions]] (Next lecture) ;Tutorial * [[{{#titleparts:{{PAGENAME}}|1}}/Tutorials/Measuring emotion|Measuring emotion]] (Tutorial) ;Wikiversity * [[:Category:Motivation and emotion/Book/Affective computing|Affective computing]] (Book chapter category) * [[Motivation and emotion/Book/2014/Appraisal and emotion|Appraisal and emotion]] (Book chapter, 2014) <!-- [[Motivation and emotion/Book/2024/Attribution theory and emotion|Attribution theory and emotion]] (Book chapter 2024) --> * [[Motivation and emotion/Book/2014/Facial Action Coding System|Facial Action Coding System]] (Book chapter, 2014) * [[Motivation and emotion/Book/2023/Smiling and emotion|Smiling and emotion]] (Book chapter, 2023) ;Wikipedia Topics * [[w:Affective computing|Affective computing]] * [[w:Appraisal theory|Appraisal]] * [[w:Attribution (psychology)|Attribution]] * [[w:Gray's biopsychological theory of personality|Gray's biopsychological theory of personality]] * [[w:James–Lange theory|James–Lange theory]] * [[w:Sophia (robot)|Sophia (robot)]] People * [[w:Magda B. Arnold|Magda B. Arnold]] * [[w:Paul Ekman|Paul Ekman]] * [[w:Jeffrey Alan Gray|Jeffrey Gray]] * [[w:Carroll Izard|Carroll Izard]] ==Recording== * [https://au-lti.bbcollab.com/recording/b5b2ddd8506749aabd7c81149fecaa7e Lecture 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/91c30feb657c4f0db225b3babaefd962 Lecture 8] (2025) * [https://au-lti.bbcollab.com/recording/9c2e9707be814a9d87cc9131d0782390 Lecture 8 recording] (2024) * [https://au-lti.bbcollab.com/recording/4c3533d7c9294b2da8dc4aaa8aac0b93 Lecture 8 recording] (2023) * [https://au-lti.bbcollab.com/recording/def61ff43cfb4f0084e26aac0bc0b52f Lecture 8 recording] (2022) * [https://au-lti.bbcollab.com/recording/7a2b4dd5a81246c096581c3461eae997 Lecture 8 recording] (2021) * [https://au-lti.bbcollab.com/recording/9173da24929249c0905c62f676287d83 Lecture 8 recording] (2020) * [https://echo360.org.au/media/00c6015a-2dd9-48c5-9d78-1f1891908d30/public Lecture 8 recording] (2019) * [https://echo360.org.au/media/17d036bf-4c49-45a9-9dd7-6d9364a51263/public Lecture 8 recording] (2016) --> ==References== {{Hanging indent|1= Gray, J. A. (1987). ''The psychology of fear and stress'' (2nd ed.). Cambridge University Press. <!-- Izard, C. E. (2010). The many meanings/aspects of emotion: Definitions, functions, activation, and regulation. ''Emotion Review'', ''2''(4), 363–370. https://doi.org/10.1177/1754073910374661 --> }} ==External links== * [https://www.paulekman.com Paul Ekman Group] (paulekman.com) * [https://www.bps.org.uk/research-digest/precise-meaning-emotion-words-different-around-world The precise meaning of emotion words is different around the world] (bps.org.uk) * [https://www.darwinproject.ac.uk/commentary/human-nature/expression-emotions The expression of emotions] (Darwin Project, University of Cambridge) * [https://www.youtube.com/watch?v=2Qb_XnEUcY8 The scary truth behind AI's emotional power] (AI for Humans, 2025; YouTube 11:42 mins) ;Multimedia * [https://www.youtube.com/watch?v=ui2_mZWyYK8 Can humanoid robots like Ameca develop emotions?] (Genz Ai Revolution, 2025, YouTube) (3:13 mins)<!-- : Explores whether robots genuinely feel emotions or merely simulate them through sensors and advanced programming. Raises ethical questions about human–robot interaction, emotional mimicry, and the implications of machines acting as companions, caretakers, or friends. --> * [https://youtu.be/WY0j1cZtnp0 In your face] (Mind Field Ep 7, YouTube, 24:33 mins) * [https://www.youtube.com/watch?v=Sq36J9pNaEo Meet Sophia, World's first AI humanoid robot] (Tony Robbins, 2020, YouTube; 9:55 mins): Interview with an AI robot about life, the universe, and everything * [https://www.youtube.com/watch?v=wjW-v0IPT_M Robots that show emotion] (David Hanson, TED talk, 7:29 mins) * [https://www.youtube.com/watch?v=U9cGdRNMdQQ The hidden power of smiling] (Ron Gutman, TED talk; 7:26 mins) * [https://www.youtube.com/watch?v=Uq6XgrYBugo Why we have an emotional connection to robots] (Kate Darling, 2018, TED talk; 11:51 mins) {{Motivation and emotion/Lectures/Navigation}} [[Category:Motivation and emotion/Lectures/Aspects of emotion]] 21eo66oidjzil0zl3ppealm2owks2l6 2835130 2835098 2026-09-30T07:05:47Z Jtneill 10242 /* Biological aspects of emotion */ + citations 2835130 wikitext text/x-wiki {{Motivation and emotion/Lectures|Lecture 8: Aspects of emotion|eighth}} {{Motivation and emotion/Lectures/Complete}} <!-- {{Motivation and emotion/Lectures/In development}} --> <!-- {{Motivation and emotion/Lectures/Complete}} --> ==Overview== [[File:Two people with brain cogs turning.png|right|250px|thumb|<div style='text-align: center;'>What causes emotion?<br>Biology?<br>Cognition?<br>Sociality?</div>]] This lecture: * discusses biological, cognitive, and social psychological aspects of [[emotion]] * considers the potential of [[w:affective computing|affective computing]] Take-home messages: * Biology and cognition work together to generate emotion * Facial expressions can influence emotional state * Other people are the source of most of our emotions * Emotions are contagious * Computers are increasingly able to detect, imitate, and respond to human emotion ==Outline== * Biological * Cognitive * Social * Affective computing ==Biological aspects of emotion== [[File:Bipolar Dyptych 1 365.jpg|thumb|right|200px|'''Figure 1'''. What is the role of the body in causing emotion?]] [[File:Expression of the Emotions Figure 1.png|thumb|right|200px|'''Figure 2'''. The human face has over 80 muscles; ~half of which are involved in expressing ~3,000 different expressions of emotion]] * What is the role of the body in emotion (see Figure 1)? ** Does bodily reaction follow emotion? ** Or does bodily reaction lead to emotion? * [[w:James–Lange theory|James–Lange theory of emotion]]: ** Sequence *** Stimulus → Bodily reaction → Emotion e.g., *** Sudden cold shower → Increased heart rate → Surprise? Fear? ** Emotion is a way of making sense of bodily changes ** Criticisms *** Boldy reactions are part of a general response that does not vary much between emotions *** Emotional experiences occur more quickly than physiological reactions ** Contemporary perspective *** Distinct physiological differences are evident for some emotions, but only a few have distinct [[w:Autonomic nervous system|autonomic nervous system]] patterns *** Emotions recruit bodily reactions to facilitate adaptative behaviours such as fighting, fleeing, and nurturing * Brain activations for specific emotions ** Distinct neural circuits underlie the core emotions of joy, fear, rage, and anxiety ([[w:Gray's biopsychological theory of personality|Gray]]) *** Behavioural approach system *** Fight or flight system *** Behavioural inhibition system ** Neuroscience studies of brain activity during emotional experiences map core emotions to distinct patterns of neural activity * [[w:Facial feedback hypothesis|Facial feedback hypothesis]] ** The facial feedback hypothesis (FFH) proposes that emotional experience arises from interpretation of one's facial expression *** Strong view: FF causes emotion *** Weak view: FF modifies emotion *** Evidence: FF effect is small (Coles et al., 2019, 2022) ** Facial expression of core emotions is cross-culturally universal (see Figure 2) *** Some emotions (e.g., joy) are easier to recognise than others (e.g., fear) *** Some cultures (e.g., Western) are better at recognising emotion (e.g., because they focus on the mouth) than other cultures (e.g., Eastern because they focus on the eyes) ==Cognitive aspects of emotion== * Biology alone doesn't explain all aspects of emotion, particularly complex emotions such as hope, pride, envy, and gratitude * Appraisal ** Appraisals, rather than events per se, elicit emotion ** Appraisals evaluates significance of events *** Primary: "Is this event significant to me and my well-being?"; if yes, "Is the event good (beneficial) or bad (harmful)?" *** Secondary: "Can I cope with this situation?" → emotion (e.g., liking/disliking) → approach vs. withdrawal ** Complex appraisal models account for approx. 2/3rds of emotional variability by mapping perceived types of benefit/harm/threat to specific emotions * Emotion knowledge ** Ability to differentiate different types and intensities of emotion ** Part of [[w:Emotional intelligence|emotional intelligence]] ** Can be taught and developed * Attribution ** Different explanations for why life events occur leads to different emotional experiences *** Primary: Good or bad? *** Secondary: Cause? ** Example: *** Primary: Good event *** Secondary: Internal cause *** Emotion: Pride ==Social aspects of emotion== [[File:Just love cropped cropped.jpg|thumb|right|200px|'''Figure 3'''. Emotions are socially intense experiences, bringing us together and driving us apart]] * Emotions are socially intense experiences (see Figure 3) ** Through emotional expression, we signal our needs to others ** Social experiences are the most frequent source of day-to-day emotion; these experiences: *** bring us together (e.g., joy and gratitude) and *** push us apart (e.g., anger, contempt, and schadenfreude) ** [[w:Emotional contagion|Emotional contagion]]: People tend to converge on similar emotions due to: *** [[w:Mirror neuron|Mirror neuron]]s fire in response to observing others' emotion *** People tend to mimic others' emotional expressions * Social sharing of emotion provides conversational context for people to re-experience and recount their emotional experiences ** Social-affective sharing: Listening, comforting, empathy, support → provides temporary relief ** Cognitive sharing: Reframing, meaning-making, reprioritising → stimulates cognitive work for emotional healing and recovery * Common view of emotions as short-lived is challenged by social research about emotion because emotional experiences tend to be retold and relived through social sharing, contributing to emotional continuity over days, weeks, and even years ==Affective computing== [[File:Sophia (robot).jpg|thumb|200px|'''Figure 4'''. Electronic devices such as robots are increasingly able to detect and respond to human emotion.]] * [[w:Affective computing|Affective computing]] is an interdisciplinary field which studies how [[w:Artificial intelligence|artificial intelligence]] can recognise and respond to human emotion * If emotions show ANS specificity, then sensors built into electronic devices can monitor human and adjust accordingly (e.g., empathically) (see Figure 4) ==Readings== * Chapter 12: Aspects of emotion ([[Motivation and emotion/Readings/Textbooks/Reeve/2024|Reeve, 2024]]) ==Multimedia== * [https://youtu.be/-PFqzYoKkCc?si=fG7dii--OsI85wL6&t=12 Emotions revealed] (KQED QUEST, 2008, YouTube) (11:05 mins): Explains Paul Ekman's work on codifying the intricate ways in which emotions are revealed through facial expressions * [https://youtu.be/TdsFGqhoAEo?si=wEqf3LvrpQpqQ_q8&t=18 Why we can't not smile] (Epic Science, 2014, YouTube) (2:29 mins): Explores unconscious emotional mimicry in relation to smiling * [https://www.youtube.com/watch?v=JMLsHI8aV0g How China is using artificial intelligence in classrooms] (The Wall Street Journal, 2020, YouTube) (5:43 mins): Shows real-world application of emotion AI being used to monitor students, illustrating potentials and risks of affective computing ==Slides== * [https://docs.google.com/presentation/d/1b6mSQQGASDgImEPjDt9DyU4Tm2NtT1GO1k0UdWLSSeE/edit?usp=sharing Aspects of emotion] (Google Slides) <!-- * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) * Handouts ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|Download 6 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|100px]] ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|Download 3 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|100px]] * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) --> ==See also== * [[/Images/]] ; Lectures * [[{{#titleparts:{{PAGENAME}}|2}}/Nature of emotion|Nature of emotion]] (Previous lecture) * [[{{#titleparts:{{PAGENAME}}|2}}/Individual emotions|Individual emotions]] (Next lecture) ;Tutorial * [[{{#titleparts:{{PAGENAME}}|1}}/Tutorials/Measuring emotion|Measuring emotion]] (Tutorial) ;Wikiversity * [[:Category:Motivation and emotion/Book/Affective computing|Affective computing]] (Book chapter category) * [[Motivation and emotion/Book/2014/Appraisal and emotion|Appraisal and emotion]] (Book chapter, 2014) <!-- [[Motivation and emotion/Book/2024/Attribution theory and emotion|Attribution theory and emotion]] (Book chapter 2024) --> * [[Motivation and emotion/Book/2014/Facial Action Coding System|Facial Action Coding System]] (Book chapter, 2014) * [[Motivation and emotion/Book/2023/Smiling and emotion|Smiling and emotion]] (Book chapter, 2023) ;Wikipedia Topics * [[w:Affective computing|Affective computing]] * [[w:Appraisal theory|Appraisal]] * [[w:Attribution (psychology)|Attribution]] * [[w:Gray's biopsychological theory of personality|Gray's biopsychological theory of personality]] * [[w:James–Lange theory|James–Lange theory]] * [[w:Sophia (robot)|Sophia (robot)]] People * [[w:Magda B. Arnold|Magda B. Arnold]] * [[w:Paul Ekman|Paul Ekman]] * [[w:Jeffrey Alan Gray|Jeffrey Gray]] * [[w:Carroll Izard|Carroll Izard]] ==Recording== * [https://au-lti.bbcollab.com/recording/b5b2ddd8506749aabd7c81149fecaa7e Lecture 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/91c30feb657c4f0db225b3babaefd962 Lecture 8] (2025) * [https://au-lti.bbcollab.com/recording/9c2e9707be814a9d87cc9131d0782390 Lecture 8 recording] (2024) * [https://au-lti.bbcollab.com/recording/4c3533d7c9294b2da8dc4aaa8aac0b93 Lecture 8 recording] (2023) * [https://au-lti.bbcollab.com/recording/def61ff43cfb4f0084e26aac0bc0b52f Lecture 8 recording] (2022) * [https://au-lti.bbcollab.com/recording/7a2b4dd5a81246c096581c3461eae997 Lecture 8 recording] (2021) * [https://au-lti.bbcollab.com/recording/9173da24929249c0905c62f676287d83 Lecture 8 recording] (2020) * [https://echo360.org.au/media/00c6015a-2dd9-48c5-9d78-1f1891908d30/public Lecture 8 recording] (2019) * [https://echo360.org.au/media/17d036bf-4c49-45a9-9dd7-6d9364a51263/public Lecture 8 recording] (2016) --> ==References== {{Hanging indent|1= Gray, J. A. (1987). ''The psychology of fear and stress'' (2nd ed.). Cambridge University Press. <!-- Izard, C. E. (2010). The many meanings/aspects of emotion: Definitions, functions, activation, and regulation. ''Emotion Review'', ''2''(4), 363–370. https://doi.org/10.1177/1754073910374661 --> }} ==External links== * [https://www.paulekman.com Paul Ekman Group] (paulekman.com) * [https://www.bps.org.uk/research-digest/precise-meaning-emotion-words-different-around-world The precise meaning of emotion words is different around the world] (bps.org.uk) * [https://www.darwinproject.ac.uk/commentary/human-nature/expression-emotions The expression of emotions] (Darwin Project, University of Cambridge) * [https://www.youtube.com/watch?v=2Qb_XnEUcY8 The scary truth behind AI's emotional power] (AI for Humans, 2025; YouTube 11:42 mins) ;Multimedia * [https://www.youtube.com/watch?v=ui2_mZWyYK8 Can humanoid robots like Ameca develop emotions?] (Genz Ai Revolution, 2025, YouTube) (3:13 mins)<!-- : Explores whether robots genuinely feel emotions or merely simulate them through sensors and advanced programming. Raises ethical questions about human–robot interaction, emotional mimicry, and the implications of machines acting as companions, caretakers, or friends. --> * [https://youtu.be/WY0j1cZtnp0 In your face] (Mind Field Ep 7, YouTube, 24:33 mins) * [https://www.youtube.com/watch?v=Sq36J9pNaEo Meet Sophia, World's first AI humanoid robot] (Tony Robbins, 2020, YouTube; 9:55 mins): Interview with an AI robot about life, the universe, and everything * [https://www.youtube.com/watch?v=wjW-v0IPT_M Robots that show emotion] (David Hanson, TED talk, 7:29 mins) * [https://www.youtube.com/watch?v=U9cGdRNMdQQ The hidden power of smiling] (Ron Gutman, TED talk; 7:26 mins) * [https://www.youtube.com/watch?v=Uq6XgrYBugo Why we have an emotional connection to robots] (Kate Darling, 2018, TED talk; 11:51 mins) {{Motivation and emotion/Lectures/Navigation}} [[Category:Motivation and emotion/Lectures/Aspects of emotion]] t94hdd87qcmv6repjldvyf58bh9s18z 2835131 2835130 2026-09-30T07:07:00Z Jtneill 10242 /* References */ + Coles References 2835131 wikitext text/x-wiki {{Motivation and emotion/Lectures|Lecture 8: Aspects of emotion|eighth}} {{Motivation and emotion/Lectures/Complete}} <!-- {{Motivation and emotion/Lectures/In development}} --> <!-- {{Motivation and emotion/Lectures/Complete}} --> ==Overview== [[File:Two people with brain cogs turning.png|right|250px|thumb|<div style='text-align: center;'>What causes emotion?<br>Biology?<br>Cognition?<br>Sociality?</div>]] This lecture: * discusses biological, cognitive, and social psychological aspects of [[emotion]] * considers the potential of [[w:affective computing|affective computing]] Take-home messages: * Biology and cognition work together to generate emotion * Facial expressions can influence emotional state * Other people are the source of most of our emotions * Emotions are contagious * Computers are increasingly able to detect, imitate, and respond to human emotion ==Outline== * Biological * Cognitive * Social * Affective computing ==Biological aspects of emotion== [[File:Bipolar Dyptych 1 365.jpg|thumb|right|200px|'''Figure 1'''. What is the role of the body in causing emotion?]] [[File:Expression of the Emotions Figure 1.png|thumb|right|200px|'''Figure 2'''. The human face has over 80 muscles; ~half of which are involved in expressing ~3,000 different expressions of emotion]] * What is the role of the body in emotion (see Figure 1)? ** Does bodily reaction follow emotion? ** Or does bodily reaction lead to emotion? * [[w:James–Lange theory|James–Lange theory of emotion]]: ** Sequence *** Stimulus → Bodily reaction → Emotion e.g., *** Sudden cold shower → Increased heart rate → Surprise? Fear? ** Emotion is a way of making sense of bodily changes ** Criticisms *** Boldy reactions are part of a general response that does not vary much between emotions *** Emotional experiences occur more quickly than physiological reactions ** Contemporary perspective *** Distinct physiological differences are evident for some emotions, but only a few have distinct [[w:Autonomic nervous system|autonomic nervous system]] patterns *** Emotions recruit bodily reactions to facilitate adaptative behaviours such as fighting, fleeing, and nurturing * Brain activations for specific emotions ** Distinct neural circuits underlie the core emotions of joy, fear, rage, and anxiety ([[w:Gray's biopsychological theory of personality|Gray]]) *** Behavioural approach system *** Fight or flight system *** Behavioural inhibition system ** Neuroscience studies of brain activity during emotional experiences map core emotions to distinct patterns of neural activity * [[w:Facial feedback hypothesis|Facial feedback hypothesis]] ** The facial feedback hypothesis (FFH) proposes that emotional experience arises from interpretation of one's facial expression *** Strong view: FF causes emotion *** Weak view: FF modifies emotion *** Evidence: FF effect is small (Coles et al., 2019, 2022) ** Facial expression of core emotions is cross-culturally universal (see Figure 2) *** Some emotions (e.g., joy) are easier to recognise than others (e.g., fear) *** Some cultures (e.g., Western) are better at recognising emotion (e.g., because they focus on the mouth) than other cultures (e.g., Eastern because they focus on the eyes) ==Cognitive aspects of emotion== * Biology alone doesn't explain all aspects of emotion, particularly complex emotions such as hope, pride, envy, and gratitude * Appraisal ** Appraisals, rather than events per se, elicit emotion ** Appraisals evaluates significance of events *** Primary: "Is this event significant to me and my well-being?"; if yes, "Is the event good (beneficial) or bad (harmful)?" *** Secondary: "Can I cope with this situation?" → emotion (e.g., liking/disliking) → approach vs. withdrawal ** Complex appraisal models account for approx. 2/3rds of emotional variability by mapping perceived types of benefit/harm/threat to specific emotions * Emotion knowledge ** Ability to differentiate different types and intensities of emotion ** Part of [[w:Emotional intelligence|emotional intelligence]] ** Can be taught and developed * Attribution ** Different explanations for why life events occur leads to different emotional experiences *** Primary: Good or bad? *** Secondary: Cause? ** Example: *** Primary: Good event *** Secondary: Internal cause *** Emotion: Pride ==Social aspects of emotion== [[File:Just love cropped cropped.jpg|thumb|right|200px|'''Figure 3'''. Emotions are socially intense experiences, bringing us together and driving us apart]] * Emotions are socially intense experiences (see Figure 3) ** Through emotional expression, we signal our needs to others ** Social experiences are the most frequent source of day-to-day emotion; these experiences: *** bring us together (e.g., joy and gratitude) and *** push us apart (e.g., anger, contempt, and schadenfreude) ** [[w:Emotional contagion|Emotional contagion]]: People tend to converge on similar emotions due to: *** [[w:Mirror neuron|Mirror neuron]]s fire in response to observing others' emotion *** People tend to mimic others' emotional expressions * Social sharing of emotion provides conversational context for people to re-experience and recount their emotional experiences ** Social-affective sharing: Listening, comforting, empathy, support → provides temporary relief ** Cognitive sharing: Reframing, meaning-making, reprioritising → stimulates cognitive work for emotional healing and recovery * Common view of emotions as short-lived is challenged by social research about emotion because emotional experiences tend to be retold and relived through social sharing, contributing to emotional continuity over days, weeks, and even years ==Affective computing== [[File:Sophia (robot).jpg|thumb|200px|'''Figure 4'''. Electronic devices such as robots are increasingly able to detect and respond to human emotion.]] * [[w:Affective computing|Affective computing]] is an interdisciplinary field which studies how [[w:Artificial intelligence|artificial intelligence]] can recognise and respond to human emotion * If emotions show ANS specificity, then sensors built into electronic devices can monitor human and adjust accordingly (e.g., empathically) (see Figure 4) ==Readings== * Chapter 12: Aspects of emotion ([[Motivation and emotion/Readings/Textbooks/Reeve/2024|Reeve, 2024]]) ==Multimedia== * [https://youtu.be/-PFqzYoKkCc?si=fG7dii--OsI85wL6&t=12 Emotions revealed] (KQED QUEST, 2008, YouTube) (11:05 mins): Explains Paul Ekman's work on codifying the intricate ways in which emotions are revealed through facial expressions * [https://youtu.be/TdsFGqhoAEo?si=wEqf3LvrpQpqQ_q8&t=18 Why we can't not smile] (Epic Science, 2014, YouTube) (2:29 mins): Explores unconscious emotional mimicry in relation to smiling * [https://www.youtube.com/watch?v=JMLsHI8aV0g How China is using artificial intelligence in classrooms] (The Wall Street Journal, 2020, YouTube) (5:43 mins): Shows real-world application of emotion AI being used to monitor students, illustrating potentials and risks of affective computing ==Slides== * [https://docs.google.com/presentation/d/1b6mSQQGASDgImEPjDt9DyU4Tm2NtT1GO1k0UdWLSSeE/edit?usp=sharing Aspects of emotion] (Google Slides) <!-- * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) * Handouts ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|Download 6 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 6slidesperpage.pdf|100px]] ** [[Media:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|Download 3 slides to a page]]: [[File:Motivation and Emotion - Lecture 08 - Aspects of emotion 3slidesperpage.pdf|100px]] * [http://www.slideshare.net/jtneill/aspects-of-emotion Lecture slides] (Slideshare) --> ==See also== * [[/Images/]] ; Lectures * [[{{#titleparts:{{PAGENAME}}|2}}/Nature of emotion|Nature of emotion]] (Previous lecture) * [[{{#titleparts:{{PAGENAME}}|2}}/Individual emotions|Individual emotions]] (Next lecture) ;Tutorial * [[{{#titleparts:{{PAGENAME}}|1}}/Tutorials/Measuring emotion|Measuring emotion]] (Tutorial) ;Wikiversity * [[:Category:Motivation and emotion/Book/Affective computing|Affective computing]] (Book chapter category) * [[Motivation and emotion/Book/2014/Appraisal and emotion|Appraisal and emotion]] (Book chapter, 2014) <!-- [[Motivation and emotion/Book/2024/Attribution theory and emotion|Attribution theory and emotion]] (Book chapter 2024) --> * [[Motivation and emotion/Book/2014/Facial Action Coding System|Facial Action Coding System]] (Book chapter, 2014) * [[Motivation and emotion/Book/2023/Smiling and emotion|Smiling and emotion]] (Book chapter, 2023) ;Wikipedia Topics * [[w:Affective computing|Affective computing]] * [[w:Appraisal theory|Appraisal]] * [[w:Attribution (psychology)|Attribution]] * [[w:Gray's biopsychological theory of personality|Gray's biopsychological theory of personality]] * [[w:James–Lange theory|James–Lange theory]] * [[w:Sophia (robot)|Sophia (robot)]] People * [[w:Magda B. Arnold|Magda B. Arnold]] * [[w:Paul Ekman|Paul Ekman]] * [[w:Jeffrey Alan Gray|Jeffrey Gray]] * [[w:Carroll Izard|Carroll Izard]] ==Recording== * [https://au-lti.bbcollab.com/recording/b5b2ddd8506749aabd7c81149fecaa7e Lecture 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/91c30feb657c4f0db225b3babaefd962 Lecture 8] (2025) * [https://au-lti.bbcollab.com/recording/9c2e9707be814a9d87cc9131d0782390 Lecture 8 recording] (2024) * [https://au-lti.bbcollab.com/recording/4c3533d7c9294b2da8dc4aaa8aac0b93 Lecture 8 recording] (2023) * [https://au-lti.bbcollab.com/recording/def61ff43cfb4f0084e26aac0bc0b52f Lecture 8 recording] (2022) * [https://au-lti.bbcollab.com/recording/7a2b4dd5a81246c096581c3461eae997 Lecture 8 recording] (2021) * [https://au-lti.bbcollab.com/recording/9173da24929249c0905c62f676287d83 Lecture 8 recording] (2020) * [https://echo360.org.au/media/00c6015a-2dd9-48c5-9d78-1f1891908d30/public Lecture 8 recording] (2019) * [https://echo360.org.au/media/17d036bf-4c49-45a9-9dd7-6d9364a51263/public Lecture 8 recording] (2016) --> ==References== {{Hanging indent|1= Coles, N. A., Larsen, J. T., & Lench, H. C. (2019). A meta-analysis of the facial feedback literature: Effects of facial feedback on emotional experience are small and variable. ''Psychological Bulletin'', ''145''(6), 610–651. https://doi.org/10.1037/bul0000194 Coles, N. A., March, D. S., Marmolejo-Ramos, F., Larsen, J. T., Arinze, N. C., Ndukaihe, I. L. G., Willis, M. L., Foroni, F., Reggev, N., Mokady, A., Forscher, P. S., Hunter, J. F., Kaminski, G., Yüvrük, E., Kapucu, A., Nagy, T., Hajdu, N., Tejada, J., Freitag, R. M. K., … Liuzza, M. T. (2022). A multi-lab test of the facial feedback hypothesis by the Many Smiles Collaboration. ''Nature Human Behaviour'', ''6''(12), 1731–1742. https://doi.org/10.1038/s41562-022-01458-9 Gray, J. A. (1987). ''The psychology of fear and stress'' (2nd ed.). Cambridge University Press. <!-- Izard, C. E. (2010). The many meanings/aspects of emotion: Definitions, functions, activation, and regulation. ''Emotion Review'', ''2''(4), 363–370. https://doi.org/10.1177/1754073910374661 --> }} ==External links== * [https://www.paulekman.com Paul Ekman Group] (paulekman.com) * [https://www.bps.org.uk/research-digest/precise-meaning-emotion-words-different-around-world The precise meaning of emotion words is different around the world] (bps.org.uk) * [https://www.darwinproject.ac.uk/commentary/human-nature/expression-emotions The expression of emotions] (Darwin Project, University of Cambridge) * [https://www.youtube.com/watch?v=2Qb_XnEUcY8 The scary truth behind AI's emotional power] (AI for Humans, 2025; YouTube 11:42 mins) ;Multimedia * [https://www.youtube.com/watch?v=ui2_mZWyYK8 Can humanoid robots like Ameca develop emotions?] (Genz Ai Revolution, 2025, YouTube) (3:13 mins)<!-- : Explores whether robots genuinely feel emotions or merely simulate them through sensors and advanced programming. Raises ethical questions about human–robot interaction, emotional mimicry, and the implications of machines acting as companions, caretakers, or friends. --> * [https://youtu.be/WY0j1cZtnp0 In your face] (Mind Field Ep 7, YouTube, 24:33 mins) * [https://www.youtube.com/watch?v=Sq36J9pNaEo Meet Sophia, World's first AI humanoid robot] (Tony Robbins, 2020, YouTube; 9:55 mins): Interview with an AI robot about life, the universe, and everything * [https://www.youtube.com/watch?v=wjW-v0IPT_M Robots that show emotion] (David Hanson, TED talk, 7:29 mins) * [https://www.youtube.com/watch?v=U9cGdRNMdQQ The hidden power of smiling] (Ron Gutman, TED talk; 7:26 mins) * [https://www.youtube.com/watch?v=Uq6XgrYBugo Why we have an emotional connection to robots] (Kate Darling, 2018, TED talk; 11:51 mins) {{Motivation and emotion/Lectures/Navigation}} [[Category:Motivation and emotion/Lectures/Aspects of emotion]] qd7jdqtp7ophb9z6qlofdtg5vx21swg 0 124883 2835123 2805029 2026-09-30T05:11:25Z ~2026-52682-35 3111865 /* Properties */ 2835123 wikitext text/x-wiki ==Transition Metals== ===Defining a transition element=== A transition metal is a d-block element that can form at least one stable ion with an incomplete d sub-shell. D-block elements are so-called because their sub-shell with the highest energy level is a d sub-shell. In A2-level chemistry, you only need to know of the first row of the d-block, elements Scandium(Sc) - Zinc(Zn). Of these ten metals, all but Scandium(Sc) and Zinc(Zn) are transition elements. ===Electronic configuration=== The electronic configuration for Scandium(Sc) is: 1s²2s²2p⁶3s²3p⁶4s²3d¹. As you move across the first row of the d-block, electrons are added onto the 3d sub-shells, up to Zinc(Zn): 1s²2s²2p⁶3s²3p⁶4s²3d¹⁰. The 4s sub-shells are generally written before the 3d sub-shells.This is because 4s sub-shells have a lower energy level than 3d sub-shells and a therefore filled before 3d sub-shells. <br> There are two exceptions to this in the top row of the d-block, Copper(Cu) and Chromium(Cr). The electronic configuration for Copper(Cu) is 1s²2s²2p⁶3s²3p⁶'''4s¹3d⁵''', and for Chromium(Cr) it is 1s²2s²2p⁶3s²3p⁶'''4s¹3d¹⁰'''. These elements act like this as it is more energetically favored for the electrons to half-fill all of the orbitals, or fill all the d-orbitals leaving the s-orbital half-filled. <br> When forming ions, electrons are taken from the 4s sub-shell before the 3d sub-shell. <br>e.g. <br>Nickel(Ni): 1s²2s²2p⁶3s²3p⁶4s²3d⁸ <br>Nickel(II)(Ni²⁺): 1s²2s²2p⁶3s²3p⁶3d⁸ <br>Nickel(III)(Ni³⁺): 1s²2s²2p⁶3s²3p⁶3d⁷ ===Properties=== All of the transition metals have the properties of metals. This includes: high melting and boiling points, high density, shiny surface, forms giant metallic lattices and conducts electricity. As well as these there are properties that only apply to transition metals. <br>These are: *Variable oxidation states *Form coloured compounds *Catalytic properties *From complex ions <br> The transition elements you need to know (Ti to Cu) can all form two or more ions with oxidation numbers +2 and above. <br> When light passes though a solution, some of the wavelengths are absorbed. The colour you see is a result of wavelengths that were ''not'' absorbed by the ions. e.g. A Cu²⁺ solution absorbed light at red/orange wavelengths, therefore we see it as blue. Generally, if a compound does not contain a transition metal ion (one with incompletely filled d-orbitals) it will be colourless. ===Catalytic Uses=== Transition metals are good catalysts. There are two main ways in which they are used. *They can provide a surface for a reactant to adsorb onto. The reactant can then be desorbed to take part in the reaction. *They can change their oxidation state and then bond with the reactants to give a lower activation energy. <br> There are some well known uses of transition metals as catalyst that you should know. *Iron (Fe) - used in the Haber process in the production of ammonia (NH₃) *Vanadium Oxide (V₂O₅) - used in the contact process in the formation of sulphur trioxide(SO₃) for the production of sulpuric acid(H₂SO₄) *Nickel (Ni) - used for hydrogenation of alkenes, breaking the double bond to form alkanes *Manganese Oxide (MnO₂) - in the decomposition of hydrogen peroxide(H₂O₂) which is a simple way to produce oxygen gas(O₂) ==Complex Ions== A complex ion contains a central transition metal ion surrounded by (usually 4 or 6) ligands. A ligand is a molecule or ion which can donate a lone pair of electrons to form a coordinate bond with a central ion in a complex ion. A complex ion is given a '''coordination number''' which indicates the number of coordinate bonds to the central ion. 6 and 4 are common coordination numbers. <br> Some common ligands include: *Water(H₂O) *Ammonia(NH₃) *Chloride(Cl^-) *Hydroxide(OH^-) *Thiocyanate(SCN^-) *Cyanide(CN^-) <br> An example of a complex ion would be [Cu((H₂O)₆]²⁺. We can work out the charge and oxidation number by looking at the overall charge and charge of the ligands. In this example the overall charge is 2+ and the six ligands are neutral. From that we can see that the central Cu ion must have a charge of 2+ and therefore an oxidation number of +2. <br> [FeCl₄]^2- contains four chloride(Cl^-) ligands that add up to a total charge of 4-. Using the same technique, we can work out that the central Fe ion has a charge of 2+. [FeCl₄]^2- only has four ligands because of the size of the chloride(Cl^-) ions. They are too big to fit six into the complex ion. ==Redox Titrations== == (end) == <br>Back to [[Chemistry (A-Level)]] [[Category:Chemistry]] 95kpd5d0h17urn4hpxk2e0n9frp9yv5 0 139384 2835049 2834536 2026-09-29T13:45:04Z Young1lim 21186 /* Adder */ 2835049 wikitext text/x-wiki == Adder == * Binary Adder Architecture Exploration ( [[Media:Adder.20131113.pdf|pdf]] ) {| class="wikitable" |- ! Adder type !! Overview !! Analysis !! VHDL Level Design !! CMOS Level Design |- | '''1. Ripple Carry Adder''' || [[Media:VLSI.Arith.1A.RCA.20250522.pdf|A]]|| || [[Media:Adder.rca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.1D.RCA.CMOS.20211108.pdf|pdf]] |- | '''2. Carry Lookahead Adder''' || [[Media:VLSI.Arith.2A.CLA.20260722.pdf|A]], [[Media:VLSI.Arith.2B.CLA.20260928.pdf|B]], [[Media:VLSI.Arith.2C.CLA.20260928.pdf|C]], [[Media:VLSI.Arith.2D.CLA.20260720.pdf|D]] || || [[Media:Adder.cla.20140313.pdf|pdf]]|| |- | '''3. Carry Save Adder''' || [[Media:VLSI.Arith.1.A.CSave.20151209.pdf|A]]|| || || |- || '''4. Carry Select Adder''' || [[Media:VLSI.Arith.1.A.CSelA.20191002.pdf|A]]|| || || |- || '''5. Carry Skip Adder''' || [[Media:VLSI.Arith.5A.CSkip.20250405.pdf|A]]|| || || [[Media:VLSI.Arith.5D.CSkip.CMOS.20211108.pdf|pdf]] |- || '''6. Carry Chain Adder''' || [[Media:VLSI.Arith.6A.CCA.20211109.pdf|A]]|| || [[Media:VLSI.Arith.6C.CCA.VHDL.20211109.pdf|pdf]], [[Media:Adder.cca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.6D.CCA.CMOS.20211109.pdf|pdf]] |- || '''7. Kogge-Stone Adder''' || [[Media:VLSI.Arith.1.A.KSA.20140315.pdf|A]]|| || [[Media:Adder.ksa.20140409.pdf|pdf]]|| |- || '''8. Prefix Adder''' || [[Media:VLSI.Arith.1.A.PFA.20140314.pdf|A]]|| || || |- || '''9.1 Variable Block Adder''' || [[Media:VLSI.Arith.1A.VBA.20221110.pdf|A]], [[Media:VLSI.Arith.1B.VBA.20230911.pdf|B]], [[Media:VLSI.Arith.1C.VBA.20240622.pdf|C]], [[Media:VLSI.Arith.1C.VBA.20250218.pdf|D]]|| || || |- || '''9.2 Multi-Level Variable Block Adder''' || [[Media:VLSI.Arith.1.A.VBA-Multi.20221031.pdf|A]]|| || || |} </br> === Adder Architectures Suitable for FPGA === * FPGA Carry-Chain Adder ([[Media:VLSI.Arith.1.A.FPGA-CCA.20210421.pdf|pdf]]) * FPGA Carry Select Adder ([[Media:VLSI.Arith.1.B.FPGA-CarrySelect.20210522.pdf|pdf]]) * FPGA Variable Block Adder ([[Media:VLSI.Arith.1.C.FPGA-VariableBlock.20220125.pdf|pdf]]) * FPGA Carry Lookahead Adder ([[Media:VLSI.Arith.1.D.FPGA-CLookahead.20210304.pdf|pdf]]) * Carry-Skip Adder </br> == Barrel Shifter == * Barrel Shifter Architecture Exploration ([[Media:Bshift.20131105.pdf|bshfit.vhdl]], [[Media:Bshift.makefile.20131109.pdf|bshfit.makefile]]) </br> '''Mux Based Barrel Shifter''' * Analysis ([[Media:Arith.BShfiter.20151207.pdf|pdf]]) * Implementation </br> == Multiplier == === Array Multipliers === * Analysis ([[Media:VLSI.Arith.1.A.Mult.20151209.pdf|pdf]]) </br> === Tree Mulltipliers === * Lattice Multiplication ([[Media:VLSI.Arith.LatticeMult.20170204.pdf|pdf]]) * Wallace Tree ([[Media:VLSI.Arith.WallaceTree.20170204.pdf|pdf]]) * Dadda Tree ([[Media:VLSI.Arith.DaddaTree.20170701.pdf|pdf]]) </br> === Booth Multipliers === * [[Media:RNS4.BoothEncode.20161005.pdf|Booth Encoding Note]] * Booth Multiplier Note ([[Media:BoothMult.20160929.pdf|H1.pdf]]) </br> == Divider == * Binary Divider ([[Media:VLSI.Arith.1.A.Divider.20131217.pdf|pdf]])</br> </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Digital Circuit Design]] [[Category:FPGA]] 1i81liik1wbezywwxkh21ujeu0ja98l 2835052 2835049 2026-09-29T13:47:05Z Young1lim 21186 /* Adder */ 2835052 wikitext text/x-wiki == Adder == * Binary Adder Architecture Exploration ( [[Media:Adder.20131113.pdf|pdf]] ) {| class="wikitable" |- ! Adder type !! Overview !! Analysis !! VHDL Level Design !! CMOS Level Design |- | '''1. Ripple Carry Adder''' || [[Media:VLSI.Arith.1A.RCA.20250522.pdf|A]]|| || [[Media:Adder.rca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.1D.RCA.CMOS.20211108.pdf|pdf]] |- | '''2. Carry Lookahead Adder''' || [[Media:VLSI.Arith.2A.CLA.20260722.pdf|A]], [[Media:VLSI.Arith.2B.CLA.20260928-1.pdf|B]], [[Media:VLSI.Arith.2C.CLA.20260928.pdf|C]], [[Media:VLSI.Arith.2D.CLA.20260720.pdf|D]] || || [[Media:Adder.cla.20140313.pdf|pdf]]|| |- | '''3. Carry Save Adder''' || [[Media:VLSI.Arith.1.A.CSave.20151209.pdf|A]]|| || || |- || '''4. Carry Select Adder''' || [[Media:VLSI.Arith.1.A.CSelA.20191002.pdf|A]]|| || || |- || '''5. Carry Skip Adder''' || [[Media:VLSI.Arith.5A.CSkip.20250405.pdf|A]]|| || || [[Media:VLSI.Arith.5D.CSkip.CMOS.20211108.pdf|pdf]] |- || '''6. Carry Chain Adder''' || [[Media:VLSI.Arith.6A.CCA.20211109.pdf|A]]|| || [[Media:VLSI.Arith.6C.CCA.VHDL.20211109.pdf|pdf]], [[Media:Adder.cca.20140313.pdf|pdf]] || [[Media:VLSI.Arith.6D.CCA.CMOS.20211109.pdf|pdf]] |- || '''7. Kogge-Stone Adder''' || [[Media:VLSI.Arith.1.A.KSA.20140315.pdf|A]]|| || [[Media:Adder.ksa.20140409.pdf|pdf]]|| |- || '''8. Prefix Adder''' || [[Media:VLSI.Arith.1.A.PFA.20140314.pdf|A]]|| || || |- || '''9.1 Variable Block Adder''' || [[Media:VLSI.Arith.1A.VBA.20221110.pdf|A]], [[Media:VLSI.Arith.1B.VBA.20230911.pdf|B]], [[Media:VLSI.Arith.1C.VBA.20240622.pdf|C]], [[Media:VLSI.Arith.1C.VBA.20250218.pdf|D]]|| || || |- || '''9.2 Multi-Level Variable Block Adder''' || [[Media:VLSI.Arith.1.A.VBA-Multi.20221031.pdf|A]]|| || || |} </br> === Adder Architectures Suitable for FPGA === * FPGA Carry-Chain Adder ([[Media:VLSI.Arith.1.A.FPGA-CCA.20210421.pdf|pdf]]) * FPGA Carry Select Adder ([[Media:VLSI.Arith.1.B.FPGA-CarrySelect.20210522.pdf|pdf]]) * FPGA Variable Block Adder ([[Media:VLSI.Arith.1.C.FPGA-VariableBlock.20220125.pdf|pdf]]) * FPGA Carry Lookahead Adder ([[Media:VLSI.Arith.1.D.FPGA-CLookahead.20210304.pdf|pdf]]) * Carry-Skip Adder </br> == Barrel Shifter == * Barrel Shifter Architecture Exploration ([[Media:Bshift.20131105.pdf|bshfit.vhdl]], [[Media:Bshift.makefile.20131109.pdf|bshfit.makefile]]) </br> '''Mux Based Barrel Shifter''' * Analysis ([[Media:Arith.BShfiter.20151207.pdf|pdf]]) * Implementation </br> == Multiplier == === Array Multipliers === * Analysis ([[Media:VLSI.Arith.1.A.Mult.20151209.pdf|pdf]]) </br> === Tree Mulltipliers === * Lattice Multiplication ([[Media:VLSI.Arith.LatticeMult.20170204.pdf|pdf]]) * Wallace Tree ([[Media:VLSI.Arith.WallaceTree.20170204.pdf|pdf]]) * Dadda Tree ([[Media:VLSI.Arith.DaddaTree.20170701.pdf|pdf]]) </br> === Booth Multipliers === * [[Media:RNS4.BoothEncode.20161005.pdf|Booth Encoding Note]] * Booth Multiplier Note ([[Media:BoothMult.20160929.pdf|H1.pdf]]) </br> == Divider == * Binary Divider ([[Media:VLSI.Arith.1.A.Divider.20131217.pdf|pdf]])</br> </br> </br> go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Digital Circuit Design]] [[Category:FPGA]] e9bg2veb0iuqodnm36kkzf78wd9qz0f 0 171005 2835055 2834154 2026-09-29T13:48:59Z Young1lim 21186 /* Geometric Series Examples */ 2835055 wikitext text/x-wiki Many of the functions that arise naturally in mathematics and real world applications can be extended to and regarded as complex functions, meaning the input, as well as the output, can be complex numbers <math>x+iy</math>, where <math>i=\sqrt{-1}</math>, in such a way that it is a more natural object to study. '''Complex analysis''', which used to be known as '''function theory''' or '''theory of functions of a single complex variable''', is a sub-field of analysis that studies such functions (more specifically, '''holomorphic''' functions) on the complex plane, or part (domain) or extension (Riemann surface) thereof. It notably has great importance in number theory, e.g. the [[Riemann zeta function]] (for the distribution of primes) and other <math>L</math>-functions, modular forms, elliptic functions, etc. <blockquote>The shortest path between two truths in the real domain passes through the complex domain. — [[wikipedia:Jacques_Hadamard|Jacques Hadamard]]</blockquote>In a certain sense, the essence of complex functions is captured by the principle of [[analytic continuation]].{{mathematics}} ==''' Complex Functions '''== * Complex Functions ([[Media:CAnal.1.A.CFunction.20140222.Basic.pdf|1.A.pdf]], [[Media:CAnal.1.B.CFunction.20140111.Octave.pdf|1.B.pdf]], [[Media:CAnal.1.C.CFunction.20140111.Extend.pdf|1.C.pdf]]) * Complex Exponential and Logarithm ([[Media:CAnal.5.A.CLog.20131017.pdf|5.A.pdf]], [[Media:CAnal.5.A.Octave.pdf|5.B.pdf]]) * Complex Trigonometric and Hyperbolic ([[Media:CAnal.7.A.CTrigHyper..pdf|7.A.pdf]], [[Media:CAnal.7.A.Octave..pdf|7.B.pdf]]) '''Complex Function Note''' : 1. Exp and Log Function Note ([[Media:ComplexExp.29160721.pdf|H1.pdf]]) : 2. Trig and TrigH Function Note ([[Media:CAnal.Trig-H.29160901.pdf|H1.pdf]]) : 3. Inverse Trig and TrigH Functions Note ([[Media:CAnal.Hyper.29160829.pdf|H1.pdf]]) ==''' Complex Integrals '''== * Complex Integrals ([[Media:CAnal.2.A.CIntegral.20140224.Basic.pdf|2.A.pdf]], [[Media:CAnal.2.B.CIntegral.20140117.Octave.pdf|2.B.pdf]], [[Media:CAnal.2.C.CIntegral.20140117.Extend.pdf|2.C.pdf]]) ==''' Complex Series '''== * Complex Series ([[Media:CPX.Series.20150226.2.Basic.pdf|3.A.pdf]], [[Media:CAnal.3.B.CSeries.20140121.Octave.pdf|3.B.pdf]], [[Media:CAnal.3.C.CSeries.20140303.Extend.pdf|3.C.pdf]]) ==''' Residue Integrals '''== * Residue Integrals ([[Media:CAnal.4.A.Residue.20140227.Basic.pdf|4.A.pdf]], [[Media:CAnal.4.B.pdf|4.B.pdf]], [[Media:CAnal.4.C.Residue.20140423.Extend.pdf|4.C.pdf]]) ==='''Residue Integrals Note'''=== * Laurent Series with the Residue Theorem Note ([[Media:Laurent.1.Residue.20170713.pdf|H1.pdf]]) * Laurent Series with Applications Note ([[Media:Laurent.2.Applications.20170327.pdf|H1.pdf]]) * Laurent Series and the z-Transform Note ([[Media:Laurent.3.z-Trans.20170831.pdf|H1.pdf]]) * Laurent Series as a Geometric Series Note ([[Media:Laurent.4.GSeries.20170802.pdf|H1.pdf]]) === Laurent Series and the z-Transform Example Note === * Overview ([[Media:Laurent.4.z-Example.20170926.pdf|H1.pdf]]) ====Geometric Series Examples==== * Causality ([[Media:Laurent.5.Causality.1.A.20191026n.pdf|A.pdf]], [[Media:Laurent.5.Causality.1.B.20191026.pdf|B.pdf]]) * Time Shift ([[Media:Laurent.5.TimeShift.2.A.20191028.pdf|A.pdf]], [[Media:Laurent.5.TimeShift.2.B.20191029.pdf|B.pdf]]) * Reciprocity ([[Media:Laurent.5.Reciprocity.3A.20191030.pdf|A.pdf]], [[Media:Laurent.5.Reciprocity.3B.20191031.pdf|B.pdf]]) * Combinations ([[Media:Laurent.5.Combination.4A.20200702.pdf|A.pdf]], [[Media:Laurent.5.Combination.4B.20201002.pdf|B.pdf]]) * Properties ([[Media:Laurent.5.Property.5A.20220105.pdf|A.pdf]], [[Media:Laurent.5.Property.5B.20220126.pdf|B.pdf]]) * Permutations ([[Media:Laurent.6.Permutation.6A.20230711.pdf|A.pdf]], [[Media:Laurent.5.Permutation.6B.20251225.pdf|B.pdf]], [[Media:Laurent.5.Permutation.6C.20260928.pdf|C.pdf]], [[Media:Laurent.5.Permutation.6C.20240528.pdf|D.pdf]]) * Applications ([[Media:Laurent.5.Application.6B.20220723.pdf|A.pdf]]) * Double Pole Case :- Examples ([[Media:Laurent.5.DPoleEx.7A.20220722.pdf|A.pdf]], [[Media:Laurent.5.DPoleEx.7B.20220720.pdf|B.pdf]]) :- Properties ([[Media:Laurent.5.DPoleProp.5A.20190226.pdf|A.pdf]], [[Media:Laurent.5.DPoleProp.5B.20190228.pdf|B.pdf]]) ====The Case Examples==== * Example Overview : ([[Media:Laurent.4.Example.0.A.20171208.pdf|0A.pdf]], [[Media:Laurent.6.CaseExample.0.B.20180205.pdf|0B.pdf]]) * Example Case 1 : ([[Media:Laurent.4.Example.1.A.20171107.pdf|1A.pdf]], [[Media:Laurent.4.Example.1.B.20171227.pdf|1B.pdf]]) * Example Case 2 : ([[Media:Laurent.4.Example.2.A.20171107.pdf|2A.pdf]], [[Media:Laurent.4.Example.2.B.20171227.pdf|2B.pdf]]) * Example Case 3 : ([[Media:Laurent.4.Example.3.A.20171017.pdf|3A.pdf]], [[Media:Laurent.4.Example.3.B.20171226.pdf|3B.pdf]]) * Example Case 4 : ([[Media:Laurent.4.Example.4.A.20171017.pdf|4A.pdf]], [[Media:Laurent.4.Example.4.B.20171228.pdf|4B.pdf]]) * Example Summary : ([[Media:Laurent.4.Example.5.A.20171212.pdf|5A.pdf]], [[Media:Laurent.4.Example.5.B.20171230.pdf|5B.pdf]]) ==''' Conformal Mapping '''== * Conformal Mapping ([[Media:CAnal.6.A.Conformal.20131224.pdf|6.A.pdf]], [[Media:CAnal.6.A.Octave..pdf|6.B.pdf]]) go to [ [[Electrical_%26_Computer_Engineering_Studies]] ] [[Category:Complex analysis]] pymz75wmcwr1bx5z71cmioxgeeec4wr 1 206506 2835038 2834949 2026-09-29T13:09:25Z Nv0011 3111788 /* Associate editor application of Neil Vedwan */ 2835038 wikitext text/x-wiki <noinclude> {{WikiJournal editorial application top |archive box = {{Archive box|[[/Archive 2016]]<br>[[/Archive 2017]]<br>[[/Archive 2018]]<br>[[/Archive 2019]]<br>[[/Archive 2020]]<br>[[/Archive 2022]]<br>[[/Archive 2023]] }} }} </noinclude> ==Associate editor application of OGUNJIMI OLUWOLE TEMIDAYO== {{WikiJournal editor application submitted | position =Associate editor | name =OGUNJIMI OLUWOLE TEMIDAYO | qualifications =M.Sc. Geography and Planning | link =Linkedin.com/in/oluwole-ogunjimi | areas_of_expertise =Enivironmental Management and Data Analysis | professional_experience =An administrator with over five years of working experience in both healthcare and education sectors. I have a Master’s degree from the University of Lagos and a Bachelor's degree from the University of Ibadan, I have developed significant research skills, especially in analyzing the impacts of human activities on water quality and understanding the socio-economic effects of environmental changes. With hands-on experience in geospatial mapping, data analytics, and programming (Python), he combines his passion for environmental conservation with a commitment to translating research findings into actionable insights. | publishing_experience =Environmental and Socio-Economic Impact of Artisanal Mining in Oke Ogun Region, 2016. https://drive.google.com/file/d/1l9WTh-ZhUpKbRN_TP28oP-mvlaiWGf0S/view?usp=drive_link Impact of Human Activities on Water Quality of Kudeti River, Ibadan, Oyo State, Nigeria, 2016. https://drive.google.com/file/d/1N00Eo1RitC5dKoX38G1H8r7MJsKdD3Aw/view?usp=drive_link Impact of Rural Transportation on The Distribution of Agricultural Produce in Obafemi Owode Local Government Area, Ogun State, Nigeria, 2023. https://drive.google.com/file/d/1YMYpcdC1JqnxQO-fq5eM3eitbHpQH-HB/view?usp=drive_link | open_experience =I am an active Wikipedia editor with over 300 edits. Significant editing history on English Wikipedia under username "Kamoranesi90". | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 12:35, 18 October 2024 (UTC) }} * {{re|Kamoranesi90}} Please adjust your security settings for the 3 Google Drive links. I am unable to view them. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 13:32, 25 October 2024 (UTC) *:Thank you @[[User:OhanaUnited|OhanaUnited]]. I have adjusted the security settings. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 14:49, 25 October 2024 (UTC) *::Thank you. Do you have any publication examples which are peer-reviewed? For example, these could be journal articles or book chapters. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 25 October 2024 (UTC) *:::No, I don't but I am working on publishing my research works. Thank you [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 09:19, 26 October 2024 (UTC) *::::I am open to '''support''' your associate editor application with mentorship from board members to support your growth in gaining experience around the publishing area. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:52, 14 November 2024 (UTC) *:::::Wow. That's great. I am open to learning from your wealth of knowledge and experience. I appreciate your kind gesture. *:::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 18:59, 14 November 2024 (UTC) *::::::Please wait for other editorial board members to review and comment on your application. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 21:44, 18 November 2024 (UTC) *:::::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 02:59, 22 November 2024 (UTC) *If [[User:OhanaUnited]] is happy to mentor, I think you would be a valuable addition to the team, so I would be willing to support. Associate editor positions don't need to be as experienced as board members, just willing to learn and able to work well with others, especially if someone is able to take the lead if calleging scenarios arise (e.g. confilcting peer reviews). [[User:Evolution and evolvability|T.Shafee(Evo&#65120;Evo)]]^{[[User talk:Evolution and evolvability|talk]]} 02:48, 9 January 2025 (UTC) *'''Support application''' Though I lack experience in such matters, I have recently learned enough to recognize this to be an easy decision. Regarding mentoring, I think I could use some mentoring myself. Whenever appropriate, please CC me on mentor-mentee communications. In particular, I am having trouble dealing with the large number of referee invites required to recruit volunteers. [[User:Guy vandegrift|Guy vandegrift]] ([[User talk:Guy vandegrift|discuss]] • [[Special:Contributions/Guy vandegrift|contribs]]) 18:50, 11 January 2025 (UTC) {{re|Kamoranesi90}} My apologies for the delay in getting back to you. '''Result: Accepted into the editorial board as associate editor.''' : [[WikiJournal User Group/Editorial guidelines#Adding editorial board members|Next steps]] (add <code>DONE</code> or <code><nowiki>{{Done}}</nowiki></code> after someone has performed the task): # [[{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member|Send a welcome message and confirm their preferred email address]] (usually in their provided website link, else via [[Special:EmailUser]]) {{clickable button 2|Onboarding email template|url=https://en.wikiversity.org/wiki/{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member}} # Copy their information over to [[{{ROOTPAGENAME}}/Editorial board|editorial board page]] using the {{tlx|WikiJournal editor summary}} template # Add their name and start data to the [d:{{WJQboard|default=Q75674277}} relevant editorial board] on wikidata # Direct-add them to the {{WJX}}board mailing list ([https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!managemembers/{{WJX}}board/add via this link]) which will grant them access to the private page only visible to board members # Welcome them at the {{#if:|wjm|WJM}}board mailing list so that they are informed # Finally, move the application to [[Talk:{{ROOTPAGENAME}}/Editors/Archive_{{CURRENTYEAR}}|this year's archive page]] [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 2 April 2025 (UTC) {{ping|Kamoranesi90}}, can you confirm if you're still interested in joining? I have emailed you through the wiki's email function a while back but did not receive a response from you. I also noticed that [https://guc.toolforge.org/?by=date&user=Kamoranesi90 you haven't edited in any WMF projects since November 2024] so I don't know if you still monitor your account for notifications. If I don't hear from you by the end of this month, I will archive this application without prejudice (i.e. you are more than welcome to continue the process to join as an associate editor when you replied back to this message). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 03:43, 2 January 2026 (UTC) ==Editorial board application of Max Loomes== {{WikiJournal editor application submitted | position =Editorial board | name =Max Loomes | qualifications =Bachelor of psychology (Hons I)(USYD), Master of Clinical Psychology (UTS), PhD Candidate (UTS) | link =https://profiles.uts.edu.au/student_Max.W.Loomes | areas_of_expertise =Mental health, psychiatry, public health | professional_experience =Research (9 years, ~4 institutions, various areas both qualitative and quantitative, field work [ecology/education psychology], preclinical trials, project managing, clinical practice (trauma, schizophrenia), teaching (~1 year at 2 institutions for psychology undergraduate and post-graduate, some masters). | publishing_experience =Published ~12 articles/chapters, reviewed for three different journals | open_experience =Have updated various wikipedia pages and big believer in open access and dismantling the highly capitalistic structures that govern journal publishing | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) }} :<nowiki>Great to see this application! I support it; have known Max for several years and he is passionate about many of the values behind WikiJournal ~~~</nowiki> [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:46, 4 February 2026 (UTC) --[[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) :* '''Support'''. Applicant has experience in research, publishing and open access (both Wikipedia and journal). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 00:23, 27 May 2025 (UTC) ==Editorial board application of Alex O. Holcombe== {{WikiJournal editor application submitted | position =Editorial board | name =Alex O. Holcombe | qualifications =PhD in psychology | link =https://profiles.sydney.edu.au/alex.holcombe | areas_of_expertise =Psychology, neuroscience | professional_experience =Full-time academic position for 20 years | publishing_experience =Advisory board or editorial board member of journals and initiatives including PLOS ONE, Collabra:Psychology, Replication Research, Meta-ROR, Meta-psychology... | open_experience =Have been an Associate Editor of WikiJournalOfScience for the last couple years, handled three articles to publication, and have attended most, I think, of the monthly meetings in the last two years | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:56, 4 February 2026 (UTC) }} : I '''strongly support''' promoting Alex to be a full editorial board member. He has the handling editor for a number of submissions, e.g. [[WikiJournal of Science/Hypericum sechmenii|1]], [[WikiJournal of Science/The Himalayan fossil hoax|2]] and [[WikiJournal of Science/Popular Pet Reptile, the Leopard Gecko (Eublepharis macularius), Spontaneously Uses Running Wheel– Is It Locomotion Play?|3]]). He also gave insightful comments towards the operations of the WikiJournal of Science editorial board and the broader WikiJournal publishing umbrella. We need the expertise like Alex to further strengthen the board's expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:03, 5 February 2026 (UTC) ==Associate editor application of Neil Vedwan==--[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:09, 29 September 2026 (UTC) {{WikiJournal editor application submitted | position =Associate editor | name =Neil Vedwan | qualifications = | link = | areas_of_expertise =Type theory, Formal Methods, Computational Complexity, Computability, Category Theory, Set Theory | professional_experience = Independent Researcher (in collaboration with faculty @ Montclair State University) | publishing_experience =Reviewer at zbMath Open, In the process of getting 2 papers published | open_experience =Contributor to CSLib (a library of Lean 4), Wikipedia contributor | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[Special:Contributions/~2026-52029-76|~2026-52029-76]] ([[User talk:~2026-52029-76|talk]]) 03:53, 28 September 2026 (UTC) }} :It looks like you're not logged in. Please log in and attach your signature to this application. Furthermore, I am unable to find a research by this name in Montclair State University's website with your area of expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 06:52, 28 September 2026 (UTC) 1dnrcugnwr372q4ljr4u8oughej3hxt 2835039 2835038 2026-09-29T13:17:21Z Nv0011 3111788 Undid revision [[Special:Diff/2835038|2835038]] by [[Special:Contributions/Nv0011|Nv0011]] ([[User talk:Nv0011|talk]]) 2835039 wikitext text/x-wiki <noinclude> {{WikiJournal editorial application top |archive box = {{Archive box|[[/Archive 2016]]<br>[[/Archive 2017]]<br>[[/Archive 2018]]<br>[[/Archive 2019]]<br>[[/Archive 2020]]<br>[[/Archive 2022]]<br>[[/Archive 2023]] }} }} </noinclude> ==Associate editor application of OGUNJIMI OLUWOLE TEMIDAYO== {{WikiJournal editor application submitted | position =Associate editor | name =OGUNJIMI OLUWOLE TEMIDAYO | qualifications =M.Sc. Geography and Planning | link =Linkedin.com/in/oluwole-ogunjimi | areas_of_expertise =Enivironmental Management and Data Analysis | professional_experience =An administrator with over five years of working experience in both healthcare and education sectors. I have a Master’s degree from the University of Lagos and a Bachelor's degree from the University of Ibadan, I have developed significant research skills, especially in analyzing the impacts of human activities on water quality and understanding the socio-economic effects of environmental changes. With hands-on experience in geospatial mapping, data analytics, and programming (Python), he combines his passion for environmental conservation with a commitment to translating research findings into actionable insights. | publishing_experience =Environmental and Socio-Economic Impact of Artisanal Mining in Oke Ogun Region, 2016. https://drive.google.com/file/d/1l9WTh-ZhUpKbRN_TP28oP-mvlaiWGf0S/view?usp=drive_link Impact of Human Activities on Water Quality of Kudeti River, Ibadan, Oyo State, Nigeria, 2016. https://drive.google.com/file/d/1N00Eo1RitC5dKoX38G1H8r7MJsKdD3Aw/view?usp=drive_link Impact of Rural Transportation on The Distribution of Agricultural Produce in Obafemi Owode Local Government Area, Ogun State, Nigeria, 2023. https://drive.google.com/file/d/1YMYpcdC1JqnxQO-fq5eM3eitbHpQH-HB/view?usp=drive_link | open_experience =I am an active Wikipedia editor with over 300 edits. Significant editing history on English Wikipedia under username "Kamoranesi90". | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 12:35, 18 October 2024 (UTC) }} * {{re|Kamoranesi90}} Please adjust your security settings for the 3 Google Drive links. I am unable to view them. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 13:32, 25 October 2024 (UTC) *:Thank you @[[User:OhanaUnited|OhanaUnited]]. I have adjusted the security settings. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 14:49, 25 October 2024 (UTC) *::Thank you. Do you have any publication examples which are peer-reviewed? For example, these could be journal articles or book chapters. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 25 October 2024 (UTC) *:::No, I don't but I am working on publishing my research works. Thank you [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 09:19, 26 October 2024 (UTC) *::::I am open to '''support''' your associate editor application with mentorship from board members to support your growth in gaining experience around the publishing area. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:52, 14 November 2024 (UTC) *:::::Wow. That's great. I am open to learning from your wealth of knowledge and experience. I appreciate your kind gesture. *:::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 18:59, 14 November 2024 (UTC) *::::::Please wait for other editorial board members to review and comment on your application. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 21:44, 18 November 2024 (UTC) *:::::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 02:59, 22 November 2024 (UTC) *If [[User:OhanaUnited]] is happy to mentor, I think you would be a valuable addition to the team, so I would be willing to support. Associate editor positions don't need to be as experienced as board members, just willing to learn and able to work well with others, especially if someone is able to take the lead if calleging scenarios arise (e.g. confilcting peer reviews). [[User:Evolution and evolvability|T.Shafee(Evo&#65120;Evo)]]^{[[User talk:Evolution and evolvability|talk]]} 02:48, 9 January 2025 (UTC) *'''Support application''' Though I lack experience in such matters, I have recently learned enough to recognize this to be an easy decision. Regarding mentoring, I think I could use some mentoring myself. Whenever appropriate, please CC me on mentor-mentee communications. In particular, I am having trouble dealing with the large number of referee invites required to recruit volunteers. [[User:Guy vandegrift|Guy vandegrift]] ([[User talk:Guy vandegrift|discuss]] • [[Special:Contributions/Guy vandegrift|contribs]]) 18:50, 11 January 2025 (UTC) {{re|Kamoranesi90}} My apologies for the delay in getting back to you. '''Result: Accepted into the editorial board as associate editor.''' : [[WikiJournal User Group/Editorial guidelines#Adding editorial board members|Next steps]] (add <code>DONE</code> or <code><nowiki>{{Done}}</nowiki></code> after someone has performed the task): # [[{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member|Send a welcome message and confirm their preferred email address]] (usually in their provided website link, else via [[Special:EmailUser]]) {{clickable button 2|Onboarding email template|url=https://en.wikiversity.org/wiki/{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member}} # Copy their information over to [[{{ROOTPAGENAME}}/Editorial board|editorial board page]] using the {{tlx|WikiJournal editor summary}} template # Add their name and start data to the [d:{{WJQboard|default=Q75674277}} relevant editorial board] on wikidata # Direct-add them to the {{WJX}}board mailing list ([https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!managemembers/{{WJX}}board/add via this link]) which will grant them access to the private page only visible to board members # Welcome them at the {{#if:|wjm|WJM}}board mailing list so that they are informed # Finally, move the application to [[Talk:{{ROOTPAGENAME}}/Editors/Archive_{{CURRENTYEAR}}|this year's archive page]] [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 2 April 2025 (UTC) {{ping|Kamoranesi90}}, can you confirm if you're still interested in joining? I have emailed you through the wiki's email function a while back but did not receive a response from you. I also noticed that [https://guc.toolforge.org/?by=date&user=Kamoranesi90 you haven't edited in any WMF projects since November 2024] so I don't know if you still monitor your account for notifications. If I don't hear from you by the end of this month, I will archive this application without prejudice (i.e. you are more than welcome to continue the process to join as an associate editor when you replied back to this message). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 03:43, 2 January 2026 (UTC) ==Editorial board application of Max Loomes== {{WikiJournal editor application submitted | position =Editorial board | name =Max Loomes | qualifications =Bachelor of psychology (Hons I)(USYD), Master of Clinical Psychology (UTS), PhD Candidate (UTS) | link =https://profiles.uts.edu.au/student_Max.W.Loomes | areas_of_expertise =Mental health, psychiatry, public health | professional_experience =Research (9 years, ~4 institutions, various areas both qualitative and quantitative, field work [ecology/education psychology], preclinical trials, project managing, clinical practice (trauma, schizophrenia), teaching (~1 year at 2 institutions for psychology undergraduate and post-graduate, some masters). | publishing_experience =Published ~12 articles/chapters, reviewed for three different journals | open_experience =Have updated various wikipedia pages and big believer in open access and dismantling the highly capitalistic structures that govern journal publishing | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) }} :<nowiki>Great to see this application! I support it; have known Max for several years and he is passionate about many of the values behind WikiJournal ~~~</nowiki> [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:46, 4 February 2026 (UTC) --[[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) :* '''Support'''. Applicant has experience in research, publishing and open access (both Wikipedia and journal). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 00:23, 27 May 2025 (UTC) ==Editorial board application of Alex O. Holcombe== {{WikiJournal editor application submitted | position =Editorial board | name =Alex O. Holcombe | qualifications =PhD in psychology | link =https://profiles.sydney.edu.au/alex.holcombe | areas_of_expertise =Psychology, neuroscience | professional_experience =Full-time academic position for 20 years | publishing_experience =Advisory board or editorial board member of journals and initiatives including PLOS ONE, Collabra:Psychology, Replication Research, Meta-ROR, Meta-psychology... | open_experience =Have been an Associate Editor of WikiJournalOfScience for the last couple years, handled three articles to publication, and have attended most, I think, of the monthly meetings in the last two years | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:56, 4 February 2026 (UTC) }} : I '''strongly support''' promoting Alex to be a full editorial board member. He has the handling editor for a number of submissions, e.g. [[WikiJournal of Science/Hypericum sechmenii|1]], [[WikiJournal of Science/The Himalayan fossil hoax|2]] and [[WikiJournal of Science/Popular Pet Reptile, the Leopard Gecko (Eublepharis macularius), Spontaneously Uses Running Wheel– Is It Locomotion Play?|3]]). He also gave insightful comments towards the operations of the WikiJournal of Science editorial board and the broader WikiJournal publishing umbrella. We need the expertise like Alex to further strengthen the board's expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:03, 5 February 2026 (UTC) ==Associate editor application of Neil Vedwan== {{WikiJournal editor application submitted | position =Associate editor | name =Neil Vedwan | qualifications = | link = | areas_of_expertise =Type theory, Formal Methods, Computational Complexity, Computability, Category Theory, Set Theory | professional_experience = Independent Researcher (in collaboration with faculty @ Montclair State University) | publishing_experience =Reviewer at zbMath Open, In the process of getting 2 papers published | open_experience =Contributor to CSLib (a library of Lean 4), Wikipedia contributor | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[Special:Contributions/~2026-52029-76|~2026-52029-76]] ([[User talk:~2026-52029-76|talk]]) 03:53, 28 September 2026 (UTC) }} :It looks like you're not logged in. Please log in and attach your signature to this application. Furthermore, I am unable to find a research by this name in Montclair State University's website with your area of expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 06:52, 28 September 2026 (UTC) e8wb0mdqvn5hxlqjenleo2wv2dtwed6 2835040 2835039 2026-09-29T13:19:45Z Nv0011 3111788 /* Associate editor application of Neil Vedwan */ 2835040 wikitext text/x-wiki <noinclude> {{WikiJournal editorial application top |archive box = {{Archive box|[[/Archive 2016]]<br>[[/Archive 2017]]<br>[[/Archive 2018]]<br>[[/Archive 2019]]<br>[[/Archive 2020]]<br>[[/Archive 2022]]<br>[[/Archive 2023]] }} }} </noinclude> ==Associate editor application of OGUNJIMI OLUWOLE TEMIDAYO== {{WikiJournal editor application submitted | position =Associate editor | name =OGUNJIMI OLUWOLE TEMIDAYO | qualifications =M.Sc. Geography and Planning | link =Linkedin.com/in/oluwole-ogunjimi | areas_of_expertise =Enivironmental Management and Data Analysis | professional_experience =An administrator with over five years of working experience in both healthcare and education sectors. I have a Master’s degree from the University of Lagos and a Bachelor's degree from the University of Ibadan, I have developed significant research skills, especially in analyzing the impacts of human activities on water quality and understanding the socio-economic effects of environmental changes. With hands-on experience in geospatial mapping, data analytics, and programming (Python), he combines his passion for environmental conservation with a commitment to translating research findings into actionable insights. | publishing_experience =Environmental and Socio-Economic Impact of Artisanal Mining in Oke Ogun Region, 2016. https://drive.google.com/file/d/1l9WTh-ZhUpKbRN_TP28oP-mvlaiWGf0S/view?usp=drive_link Impact of Human Activities on Water Quality of Kudeti River, Ibadan, Oyo State, Nigeria, 2016. https://drive.google.com/file/d/1N00Eo1RitC5dKoX38G1H8r7MJsKdD3Aw/view?usp=drive_link Impact of Rural Transportation on The Distribution of Agricultural Produce in Obafemi Owode Local Government Area, Ogun State, Nigeria, 2023. https://drive.google.com/file/d/1YMYpcdC1JqnxQO-fq5eM3eitbHpQH-HB/view?usp=drive_link | open_experience =I am an active Wikipedia editor with over 300 edits. Significant editing history on English Wikipedia under username "Kamoranesi90". | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 12:35, 18 October 2024 (UTC) }} * {{re|Kamoranesi90}} Please adjust your security settings for the 3 Google Drive links. I am unable to view them. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 13:32, 25 October 2024 (UTC) *:Thank you @[[User:OhanaUnited|OhanaUnited]]. I have adjusted the security settings. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 14:49, 25 October 2024 (UTC) *::Thank you. Do you have any publication examples which are peer-reviewed? For example, these could be journal articles or book chapters. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 25 October 2024 (UTC) *:::No, I don't but I am working on publishing my research works. Thank you [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 09:19, 26 October 2024 (UTC) *::::I am open to '''support''' your associate editor application with mentorship from board members to support your growth in gaining experience around the publishing area. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:52, 14 November 2024 (UTC) *:::::Wow. That's great. I am open to learning from your wealth of knowledge and experience. I appreciate your kind gesture. *:::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 18:59, 14 November 2024 (UTC) *::::::Please wait for other editorial board members to review and comment on your application. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 21:44, 18 November 2024 (UTC) *:::::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 02:59, 22 November 2024 (UTC) *If [[User:OhanaUnited]] is happy to mentor, I think you would be a valuable addition to the team, so I would be willing to support. Associate editor positions don't need to be as experienced as board members, just willing to learn and able to work well with others, especially if someone is able to take the lead if calleging scenarios arise (e.g. confilcting peer reviews). [[User:Evolution and evolvability|T.Shafee(Evo&#65120;Evo)]]^{[[User talk:Evolution and evolvability|talk]]} 02:48, 9 January 2025 (UTC) *'''Support application''' Though I lack experience in such matters, I have recently learned enough to recognize this to be an easy decision. Regarding mentoring, I think I could use some mentoring myself. Whenever appropriate, please CC me on mentor-mentee communications. In particular, I am having trouble dealing with the large number of referee invites required to recruit volunteers. [[User:Guy vandegrift|Guy vandegrift]] ([[User talk:Guy vandegrift|discuss]] • [[Special:Contributions/Guy vandegrift|contribs]]) 18:50, 11 January 2025 (UTC) {{re|Kamoranesi90}} My apologies for the delay in getting back to you. '''Result: Accepted into the editorial board as associate editor.''' : [[WikiJournal User Group/Editorial guidelines#Adding editorial board members|Next steps]] (add <code>DONE</code> or <code><nowiki>{{Done}}</nowiki></code> after someone has performed the task): # [[{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member|Send a welcome message and confirm their preferred email address]] (usually in their provided website link, else via [[Special:EmailUser]]) {{clickable button 2|Onboarding email template|url=https://en.wikiversity.org/wiki/{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member}} # Copy their information over to [[{{ROOTPAGENAME}}/Editorial board|editorial board page]] using the {{tlx|WikiJournal editor summary}} template # Add their name and start data to the [d:{{WJQboard|default=Q75674277}} relevant editorial board] on wikidata # Direct-add them to the {{WJX}}board mailing list ([https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!managemembers/{{WJX}}board/add via this link]) which will grant them access to the private page only visible to board members # Welcome them at the {{#if:|wjm|WJM}}board mailing list so that they are informed # Finally, move the application to [[Talk:{{ROOTPAGENAME}}/Editors/Archive_{{CURRENTYEAR}}|this year's archive page]] [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 2 April 2025 (UTC) {{ping|Kamoranesi90}}, can you confirm if you're still interested in joining? I have emailed you through the wiki's email function a while back but did not receive a response from you. I also noticed that [https://guc.toolforge.org/?by=date&user=Kamoranesi90 you haven't edited in any WMF projects since November 2024] so I don't know if you still monitor your account for notifications. If I don't hear from you by the end of this month, I will archive this application without prejudice (i.e. you are more than welcome to continue the process to join as an associate editor when you replied back to this message). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 03:43, 2 January 2026 (UTC) ==Editorial board application of Max Loomes== {{WikiJournal editor application submitted | position =Editorial board | name =Max Loomes | qualifications =Bachelor of psychology (Hons I)(USYD), Master of Clinical Psychology (UTS), PhD Candidate (UTS) | link =https://profiles.uts.edu.au/student_Max.W.Loomes | areas_of_expertise =Mental health, psychiatry, public health | professional_experience =Research (9 years, ~4 institutions, various areas both qualitative and quantitative, field work [ecology/education psychology], preclinical trials, project managing, clinical practice (trauma, schizophrenia), teaching (~1 year at 2 institutions for psychology undergraduate and post-graduate, some masters). | publishing_experience =Published ~12 articles/chapters, reviewed for three different journals | open_experience =Have updated various wikipedia pages and big believer in open access and dismantling the highly capitalistic structures that govern journal publishing | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) }} :<nowiki>Great to see this application! I support it; have known Max for several years and he is passionate about many of the values behind WikiJournal ~~~</nowiki> [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:46, 4 February 2026 (UTC) --[[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) :* '''Support'''. Applicant has experience in research, publishing and open access (both Wikipedia and journal). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 00:23, 27 May 2025 (UTC) ==Editorial board application of Alex O. Holcombe== {{WikiJournal editor application submitted | position =Editorial board | name =Alex O. Holcombe | qualifications =PhD in psychology | link =https://profiles.sydney.edu.au/alex.holcombe | areas_of_expertise =Psychology, neuroscience | professional_experience =Full-time academic position for 20 years | publishing_experience =Advisory board or editorial board member of journals and initiatives including PLOS ONE, Collabra:Psychology, Replication Research, Meta-ROR, Meta-psychology... | open_experience =Have been an Associate Editor of WikiJournalOfScience for the last couple years, handled three articles to publication, and have attended most, I think, of the monthly meetings in the last two years | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:56, 4 February 2026 (UTC) }} : I '''strongly support''' promoting Alex to be a full editorial board member. He has the handling editor for a number of submissions, e.g. [[WikiJournal of Science/Hypericum sechmenii|1]], [[WikiJournal of Science/The Himalayan fossil hoax|2]] and [[WikiJournal of Science/Popular Pet Reptile, the Leopard Gecko (Eublepharis macularius), Spontaneously Uses Running Wheel– Is It Locomotion Play?|3]]). He also gave insightful comments towards the operations of the WikiJournal of Science editorial board and the broader WikiJournal publishing umbrella. We need the expertise like Alex to further strengthen the board's expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:03, 5 February 2026 (UTC) ==Associate editor application of Neil Vedwan== {{WikiJournal editor application submitted | position =Associate editor | name =Neil Vedwan | qualifications = | link = | areas_of_expertise =Type theory, Formal Methods, Computational Complexity, Computability, Category Theory, Set Theory | professional_experience = Independent Researcher (in collaboration with faculty @ Montclair State University) | publishing_experience =Reviewer at zbMath Open (mathematical reviewing database), In the process of getting 2 papers published | open_experience =Contributor to CSLib (a library of Lean 4), Wikipedia contributor | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:19, 29 September 2026 (UTC) [[Special:Contributions/~2026-52029-76|~2026-52029-76]] ([[User talk:~2026-52029-76|talk]]) 03:53, 28 September 2026 (UTC) }} :It looks like you're not logged in. Please log in and attach your signature to this application. Furthermore, I am unable to find a research by this name in Montclair State University's website with your area of expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 06:52, 28 September 2026 (UTC) s4c5w1by1zmzyoiul0wpaw0gdgk6wx3 2835044 2835040 2026-09-29T13:34:11Z Nv0011 3111788 /* Associate editor application of Neil Vedwan */ Reply 2835044 wikitext text/x-wiki <noinclude> {{WikiJournal editorial application top |archive box = {{Archive box|[[/Archive 2016]]<br>[[/Archive 2017]]<br>[[/Archive 2018]]<br>[[/Archive 2019]]<br>[[/Archive 2020]]<br>[[/Archive 2022]]<br>[[/Archive 2023]] }} }} </noinclude> ==Associate editor application of OGUNJIMI OLUWOLE TEMIDAYO== {{WikiJournal editor application submitted | position =Associate editor | name =OGUNJIMI OLUWOLE TEMIDAYO | qualifications =M.Sc. Geography and Planning | link =Linkedin.com/in/oluwole-ogunjimi | areas_of_expertise =Enivironmental Management and Data Analysis | professional_experience =An administrator with over five years of working experience in both healthcare and education sectors. I have a Master’s degree from the University of Lagos and a Bachelor's degree from the University of Ibadan, I have developed significant research skills, especially in analyzing the impacts of human activities on water quality and understanding the socio-economic effects of environmental changes. With hands-on experience in geospatial mapping, data analytics, and programming (Python), he combines his passion for environmental conservation with a commitment to translating research findings into actionable insights. | publishing_experience =Environmental and Socio-Economic Impact of Artisanal Mining in Oke Ogun Region, 2016. https://drive.google.com/file/d/1l9WTh-ZhUpKbRN_TP28oP-mvlaiWGf0S/view?usp=drive_link Impact of Human Activities on Water Quality of Kudeti River, Ibadan, Oyo State, Nigeria, 2016. https://drive.google.com/file/d/1N00Eo1RitC5dKoX38G1H8r7MJsKdD3Aw/view?usp=drive_link Impact of Rural Transportation on The Distribution of Agricultural Produce in Obafemi Owode Local Government Area, Ogun State, Nigeria, 2023. https://drive.google.com/file/d/1YMYpcdC1JqnxQO-fq5eM3eitbHpQH-HB/view?usp=drive_link | open_experience =I am an active Wikipedia editor with over 300 edits. Significant editing history on English Wikipedia under username "Kamoranesi90". | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 12:35, 18 October 2024 (UTC) }} * {{re|Kamoranesi90}} Please adjust your security settings for the 3 Google Drive links. I am unable to view them. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 13:32, 25 October 2024 (UTC) *:Thank you @[[User:OhanaUnited|OhanaUnited]]. I have adjusted the security settings. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 14:49, 25 October 2024 (UTC) *::Thank you. Do you have any publication examples which are peer-reviewed? For example, these could be journal articles or book chapters. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 25 October 2024 (UTC) *:::No, I don't but I am working on publishing my research works. Thank you [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 09:19, 26 October 2024 (UTC) *::::I am open to '''support''' your associate editor application with mentorship from board members to support your growth in gaining experience around the publishing area. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:52, 14 November 2024 (UTC) *:::::Wow. That's great. I am open to learning from your wealth of knowledge and experience. I appreciate your kind gesture. *:::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 18:59, 14 November 2024 (UTC) *::::::Please wait for other editorial board members to review and comment on your application. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 21:44, 18 November 2024 (UTC) *:::::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 02:59, 22 November 2024 (UTC) *If [[User:OhanaUnited]] is happy to mentor, I think you would be a valuable addition to the team, so I would be willing to support. Associate editor positions don't need to be as experienced as board members, just willing to learn and able to work well with others, especially if someone is able to take the lead if calleging scenarios arise (e.g. confilcting peer reviews). [[User:Evolution and evolvability|T.Shafee(Evo&#65120;Evo)]]^{[[User talk:Evolution and evolvability|talk]]} 02:48, 9 January 2025 (UTC) *'''Support application''' Though I lack experience in such matters, I have recently learned enough to recognize this to be an easy decision. Regarding mentoring, I think I could use some mentoring myself. Whenever appropriate, please CC me on mentor-mentee communications. In particular, I am having trouble dealing with the large number of referee invites required to recruit volunteers. [[User:Guy vandegrift|Guy vandegrift]] ([[User talk:Guy vandegrift|discuss]] • [[Special:Contributions/Guy vandegrift|contribs]]) 18:50, 11 January 2025 (UTC) {{re|Kamoranesi90}} My apologies for the delay in getting back to you. '''Result: Accepted into the editorial board as associate editor.''' : [[WikiJournal User Group/Editorial guidelines#Adding editorial board members|Next steps]] (add <code>DONE</code> or <code><nowiki>{{Done}}</nowiki></code> after someone has performed the task): # [[{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member|Send a welcome message and confirm their preferred email address]] (usually in their provided website link, else via [[Special:EmailUser]]) {{clickable button 2|Onboarding email template|url=https://en.wikiversity.org/wiki/{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member}} # Copy their information over to [[{{ROOTPAGENAME}}/Editorial board|editorial board page]] using the {{tlx|WikiJournal editor summary}} template # Add their name and start data to the [d:{{WJQboard|default=Q75674277}} relevant editorial board] on wikidata # Direct-add them to the {{WJX}}board mailing list ([https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!managemembers/{{WJX}}board/add via this link]) which will grant them access to the private page only visible to board members # Welcome them at the {{#if:|wjm|WJM}}board mailing list so that they are informed # Finally, move the application to [[Talk:{{ROOTPAGENAME}}/Editors/Archive_{{CURRENTYEAR}}|this year's archive page]] [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 2 April 2025 (UTC) {{ping|Kamoranesi90}}, can you confirm if you're still interested in joining? I have emailed you through the wiki's email function a while back but did not receive a response from you. I also noticed that [https://guc.toolforge.org/?by=date&user=Kamoranesi90 you haven't edited in any WMF projects since November 2024] so I don't know if you still monitor your account for notifications. If I don't hear from you by the end of this month, I will archive this application without prejudice (i.e. you are more than welcome to continue the process to join as an associate editor when you replied back to this message). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 03:43, 2 January 2026 (UTC) ==Editorial board application of Max Loomes== {{WikiJournal editor application submitted | position =Editorial board | name =Max Loomes | qualifications =Bachelor of psychology (Hons I)(USYD), Master of Clinical Psychology (UTS), PhD Candidate (UTS) | link =https://profiles.uts.edu.au/student_Max.W.Loomes | areas_of_expertise =Mental health, psychiatry, public health | professional_experience =Research (9 years, ~4 institutions, various areas both qualitative and quantitative, field work [ecology/education psychology], preclinical trials, project managing, clinical practice (trauma, schizophrenia), teaching (~1 year at 2 institutions for psychology undergraduate and post-graduate, some masters). | publishing_experience =Published ~12 articles/chapters, reviewed for three different journals | open_experience =Have updated various wikipedia pages and big believer in open access and dismantling the highly capitalistic structures that govern journal publishing | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) }} :<nowiki>Great to see this application! I support it; have known Max for several years and he is passionate about many of the values behind WikiJournal ~~~</nowiki> [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:46, 4 February 2026 (UTC) --[[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) :* '''Support'''. Applicant has experience in research, publishing and open access (both Wikipedia and journal). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 00:23, 27 May 2025 (UTC) ==Editorial board application of Alex O. Holcombe== {{WikiJournal editor application submitted | position =Editorial board | name =Alex O. Holcombe | qualifications =PhD in psychology | link =https://profiles.sydney.edu.au/alex.holcombe | areas_of_expertise =Psychology, neuroscience | professional_experience =Full-time academic position for 20 years | publishing_experience =Advisory board or editorial board member of journals and initiatives including PLOS ONE, Collabra:Psychology, Replication Research, Meta-ROR, Meta-psychology... | open_experience =Have been an Associate Editor of WikiJournalOfScience for the last couple years, handled three articles to publication, and have attended most, I think, of the monthly meetings in the last two years | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:56, 4 February 2026 (UTC) }} : I '''strongly support''' promoting Alex to be a full editorial board member. He has the handling editor for a number of submissions, e.g. [[WikiJournal of Science/Hypericum sechmenii|1]], [[WikiJournal of Science/The Himalayan fossil hoax|2]] and [[WikiJournal of Science/Popular Pet Reptile, the Leopard Gecko (Eublepharis macularius), Spontaneously Uses Running Wheel– Is It Locomotion Play?|3]]). He also gave insightful comments towards the operations of the WikiJournal of Science editorial board and the broader WikiJournal publishing umbrella. We need the expertise like Alex to further strengthen the board's expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:03, 5 February 2026 (UTC) ==Associate editor application of Neil Vedwan== {{WikiJournal editor application submitted | position =Associate editor | name =Neil Vedwan | qualifications = | link = | areas_of_expertise =Type theory, Formal Methods, Computational Complexity, Computability, Category Theory, Set Theory | professional_experience = Independent Researcher (in collaboration with faculty @ Montclair State University) | publishing_experience =Reviewer at zbMath Open (mathematical reviewing database), In the process of getting 2 papers published | open_experience =Contributor to CSLib (a library of Lean 4), Wikipedia contributor | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:19, 29 September 2026 (UTC) [[Special:Contributions/~2026-52029-76|~2026-52029-76]] ([[User talk:~2026-52029-76|talk]]) 03:53, 28 September 2026 (UTC) }} :It looks like you're not logged in. Please log in and attach your signature to this application. Furthermore, I am unable to find a research by this name in Montclair State University's website with your area of expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 06:52, 28 September 2026 (UTC) ::Apologies for the confusion, I accidentally submitted while logged out. ::To clarify my affiliation: I'm an independent researcher collaborating on research with faculty at Montclair State, which is why I'm not listed in the staff directory. My active work includes reviewing papers for zbMATH Open & contributing to CSLib. If you need to verify anything else, please let me know. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:34, 29 September 2026 (UTC) kvno37aebl1nrfxe852swo92xtu83a4 2835068 2835044 2026-09-29T19:23:32Z ~2026-52479-71 3111850 /* Associate editor application of Neil Vedwan */ 2835068 wikitext text/x-wiki <noinclude> {{WikiJournal editorial application top |archive box = {{Archive box|[[/Archive 2016]]<br>[[/Archive 2017]]<br>[[/Archive 2018]]<br>[[/Archive 2019]]<br>[[/Archive 2020]]<br>[[/Archive 2022]]<br>[[/Archive 2023]] }} }} </noinclude> ==Associate editor application of OGUNJIMI OLUWOLE TEMIDAYO== {{WikiJournal editor application submitted | position =Associate editor | name =OGUNJIMI OLUWOLE TEMIDAYO | qualifications =M.Sc. Geography and Planning | link =Linkedin.com/in/oluwole-ogunjimi | areas_of_expertise =Enivironmental Management and Data Analysis | professional_experience =An administrator with over five years of working experience in both healthcare and education sectors. I have a Master’s degree from the University of Lagos and a Bachelor's degree from the University of Ibadan, I have developed significant research skills, especially in analyzing the impacts of human activities on water quality and understanding the socio-economic effects of environmental changes. With hands-on experience in geospatial mapping, data analytics, and programming (Python), he combines his passion for environmental conservation with a commitment to translating research findings into actionable insights. | publishing_experience =Environmental and Socio-Economic Impact of Artisanal Mining in Oke Ogun Region, 2016. https://drive.google.com/file/d/1l9WTh-ZhUpKbRN_TP28oP-mvlaiWGf0S/view?usp=drive_link Impact of Human Activities on Water Quality of Kudeti River, Ibadan, Oyo State, Nigeria, 2016. https://drive.google.com/file/d/1N00Eo1RitC5dKoX38G1H8r7MJsKdD3Aw/view?usp=drive_link Impact of Rural Transportation on The Distribution of Agricultural Produce in Obafemi Owode Local Government Area, Ogun State, Nigeria, 2023. https://drive.google.com/file/d/1YMYpcdC1JqnxQO-fq5eM3eitbHpQH-HB/view?usp=drive_link | open_experience =I am an active Wikipedia editor with over 300 edits. Significant editing history on English Wikipedia under username "Kamoranesi90". | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 12:35, 18 October 2024 (UTC) }} * {{re|Kamoranesi90}} Please adjust your security settings for the 3 Google Drive links. I am unable to view them. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 13:32, 25 October 2024 (UTC) *:Thank you @[[User:OhanaUnited|OhanaUnited]]. I have adjusted the security settings. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 14:49, 25 October 2024 (UTC) *::Thank you. Do you have any publication examples which are peer-reviewed? For example, these could be journal articles or book chapters. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 25 October 2024 (UTC) *:::No, I don't but I am working on publishing my research works. Thank you [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 09:19, 26 October 2024 (UTC) *::::I am open to '''support''' your associate editor application with mentorship from board members to support your growth in gaining experience around the publishing area. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:52, 14 November 2024 (UTC) *:::::Wow. That's great. I am open to learning from your wealth of knowledge and experience. I appreciate your kind gesture. *:::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 18:59, 14 November 2024 (UTC) *::::::Please wait for other editorial board members to review and comment on your application. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 21:44, 18 November 2024 (UTC) *:::::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 02:59, 22 November 2024 (UTC) *If [[User:OhanaUnited]] is happy to mentor, I think you would be a valuable addition to the team, so I would be willing to support. Associate editor positions don't need to be as experienced as board members, just willing to learn and able to work well with others, especially if someone is able to take the lead if calleging scenarios arise (e.g. confilcting peer reviews). [[User:Evolution and evolvability|T.Shafee(Evo&#65120;Evo)]]^{[[User talk:Evolution and evolvability|talk]]} 02:48, 9 January 2025 (UTC) *'''Support application''' Though I lack experience in such matters, I have recently learned enough to recognize this to be an easy decision. Regarding mentoring, I think I could use some mentoring myself. Whenever appropriate, please CC me on mentor-mentee communications. In particular, I am having trouble dealing with the large number of referee invites required to recruit volunteers. [[User:Guy vandegrift|Guy vandegrift]] ([[User talk:Guy vandegrift|discuss]] • [[Special:Contributions/Guy vandegrift|contribs]]) 18:50, 11 January 2025 (UTC) {{re|Kamoranesi90}} My apologies for the delay in getting back to you. '''Result: Accepted into the editorial board as associate editor.''' : [[WikiJournal User Group/Editorial guidelines#Adding editorial board members|Next steps]] (add <code>DONE</code> or <code><nowiki>{{Done}}</nowiki></code> after someone has performed the task): # [[{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member|Send a welcome message and confirm their preferred email address]] (usually in their provided website link, else via [[Special:EmailUser]]) {{clickable button 2|Onboarding email template|url=https://en.wikiversity.org/wiki/{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member}} # Copy their information over to [[{{ROOTPAGENAME}}/Editorial board|editorial board page]] using the {{tlx|WikiJournal editor summary}} template # Add their name and start data to the [d:{{WJQboard|default=Q75674277}} relevant editorial board] on wikidata # Direct-add them to the {{WJX}}board mailing list ([https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!managemembers/{{WJX}}board/add via this link]) which will grant them access to the private page only visible to board members # Welcome them at the {{#if:|wjm|WJM}}board mailing list so that they are informed # Finally, move the application to [[Talk:{{ROOTPAGENAME}}/Editors/Archive_{{CURRENTYEAR}}|this year's archive page]] [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 2 April 2025 (UTC) {{ping|Kamoranesi90}}, can you confirm if you're still interested in joining? I have emailed you through the wiki's email function a while back but did not receive a response from you. I also noticed that [https://guc.toolforge.org/?by=date&user=Kamoranesi90 you haven't edited in any WMF projects since November 2024] so I don't know if you still monitor your account for notifications. If I don't hear from you by the end of this month, I will archive this application without prejudice (i.e. you are more than welcome to continue the process to join as an associate editor when you replied back to this message). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 03:43, 2 January 2026 (UTC) ==Editorial board application of Max Loomes== {{WikiJournal editor application submitted | position =Editorial board | name =Max Loomes | qualifications =Bachelor of psychology (Hons I)(USYD), Master of Clinical Psychology (UTS), PhD Candidate (UTS) | link =https://profiles.uts.edu.au/student_Max.W.Loomes | areas_of_expertise =Mental health, psychiatry, public health | professional_experience =Research (9 years, ~4 institutions, various areas both qualitative and quantitative, field work [ecology/education psychology], preclinical trials, project managing, clinical practice (trauma, schizophrenia), teaching (~1 year at 2 institutions for psychology undergraduate and post-graduate, some masters). | publishing_experience =Published ~12 articles/chapters, reviewed for three different journals | open_experience =Have updated various wikipedia pages and big believer in open access and dismantling the highly capitalistic structures that govern journal publishing | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) }} :<nowiki>Great to see this application! I support it; have known Max for several years and he is passionate about many of the values behind WikiJournal ~~~</nowiki> [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:46, 4 February 2026 (UTC) --[[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) :* '''Support'''. Applicant has experience in research, publishing and open access (both Wikipedia and journal). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 00:23, 27 May 2025 (UTC) ==Editorial board application of Alex O. Holcombe== {{WikiJournal editor application submitted | position =Editorial board | name =Alex O. Holcombe | qualifications =PhD in psychology | link =https://profiles.sydney.edu.au/alex.holcombe | areas_of_expertise =Psychology, neuroscience | professional_experience =Full-time academic position for 20 years | publishing_experience =Advisory board or editorial board member of journals and initiatives including PLOS ONE, Collabra:Psychology, Replication Research, Meta-ROR, Meta-psychology... | open_experience =Have been an Associate Editor of WikiJournalOfScience for the last couple years, handled three articles to publication, and have attended most, I think, of the monthly meetings in the last two years | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:56, 4 February 2026 (UTC) }} : I '''strongly support''' promoting Alex to be a full editorial board member. He has the handling editor for a number of submissions, e.g. [[WikiJournal of Science/Hypericum sechmenii|1]], [[WikiJournal of Science/The Himalayan fossil hoax|2]] and [[WikiJournal of Science/Popular Pet Reptile, the Leopard Gecko (Eublepharis macularius), Spontaneously Uses Running Wheel– Is It Locomotion Play?|3]]). He also gave insightful comments towards the operations of the WikiJournal of Science editorial board and the broader WikiJournal publishing umbrella. We need the expertise like Alex to further strengthen the board's expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:03, 5 February 2026 (UTC) ==Associate editor application of Neil Vedwan== {{WikiJournal editor application submitted | position =Associate editor | name =Neil Vedwan | qualifications = | link = | areas_of_expertise =Type theory, Formal Methods, Computational Complexity, Computability, Theoretical Computer Science, Category Theory, Set Theory | professional_experience = Independent Researcher (in collaboration with faculty @ Montclair State University) | publishing_experience =Reviewer at zbMath Open (mathematical reviewing database), In the process of getting 2 papers published | open_experience =Contributor to CSLib (a library of Lean 4), Wikipedia contributor | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:19, 29 September 2026 (UTC) [[Special:Contributions/~2026-52029-76|~2026-52029-76]] ([[User talk:~2026-52029-76|talk]]) 03:53, 28 September 2026 (UTC) }} :It looks like you're not logged in. Please log in and attach your signature to this application. Furthermore, I am unable to find a research by this name in Montclair State University's website with your area of expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 06:52, 28 September 2026 (UTC) ::Apologies for the confusion, I accidentally submitted while logged out. ::To clarify my affiliation: I'm an independent researcher collaborating on research with faculty at Montclair State, which is why I'm not listed in the staff directory. My active work includes reviewing papers for zbMATH Open & contributing to CSLib. If you need to verify anything else, please let me know. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:34, 29 September 2026 (UTC) l8z7dv0grjhynp6jkavyf2tv12ktpzg 2835069 2835068 2026-09-29T19:25:54Z Nv0011 3111788 /* Associate editor application of Neil Vedwan */ 2835069 wikitext text/x-wiki <noinclude> {{WikiJournal editorial application top |archive box = {{Archive box|[[/Archive 2016]]<br>[[/Archive 2017]]<br>[[/Archive 2018]]<br>[[/Archive 2019]]<br>[[/Archive 2020]]<br>[[/Archive 2022]]<br>[[/Archive 2023]] }} }} </noinclude> ==Associate editor application of OGUNJIMI OLUWOLE TEMIDAYO== {{WikiJournal editor application submitted | position =Associate editor | name =OGUNJIMI OLUWOLE TEMIDAYO | qualifications =M.Sc. Geography and Planning | link =Linkedin.com/in/oluwole-ogunjimi | areas_of_expertise =Enivironmental Management and Data Analysis | professional_experience =An administrator with over five years of working experience in both healthcare and education sectors. I have a Master’s degree from the University of Lagos and a Bachelor's degree from the University of Ibadan, I have developed significant research skills, especially in analyzing the impacts of human activities on water quality and understanding the socio-economic effects of environmental changes. With hands-on experience in geospatial mapping, data analytics, and programming (Python), he combines his passion for environmental conservation with a commitment to translating research findings into actionable insights. | publishing_experience =Environmental and Socio-Economic Impact of Artisanal Mining in Oke Ogun Region, 2016. https://drive.google.com/file/d/1l9WTh-ZhUpKbRN_TP28oP-mvlaiWGf0S/view?usp=drive_link Impact of Human Activities on Water Quality of Kudeti River, Ibadan, Oyo State, Nigeria, 2016. https://drive.google.com/file/d/1N00Eo1RitC5dKoX38G1H8r7MJsKdD3Aw/view?usp=drive_link Impact of Rural Transportation on The Distribution of Agricultural Produce in Obafemi Owode Local Government Area, Ogun State, Nigeria, 2023. https://drive.google.com/file/d/1YMYpcdC1JqnxQO-fq5eM3eitbHpQH-HB/view?usp=drive_link | open_experience =I am an active Wikipedia editor with over 300 edits. Significant editing history on English Wikipedia under username "Kamoranesi90". | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 12:35, 18 October 2024 (UTC) }} * {{re|Kamoranesi90}} Please adjust your security settings for the 3 Google Drive links. I am unable to view them. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 13:32, 25 October 2024 (UTC) *:Thank you @[[User:OhanaUnited|OhanaUnited]]. I have adjusted the security settings. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 14:49, 25 October 2024 (UTC) *::Thank you. Do you have any publication examples which are peer-reviewed? For example, these could be journal articles or book chapters. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 25 October 2024 (UTC) *:::No, I don't but I am working on publishing my research works. Thank you [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 09:19, 26 October 2024 (UTC) *::::I am open to '''support''' your associate editor application with mentorship from board members to support your growth in gaining experience around the publishing area. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:52, 14 November 2024 (UTC) *:::::Wow. That's great. I am open to learning from your wealth of knowledge and experience. I appreciate your kind gesture. *:::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 18:59, 14 November 2024 (UTC) *::::::Please wait for other editorial board members to review and comment on your application. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 21:44, 18 November 2024 (UTC) *:::::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 02:59, 22 November 2024 (UTC) *If [[User:OhanaUnited]] is happy to mentor, I think you would be a valuable addition to the team, so I would be willing to support. Associate editor positions don't need to be as experienced as board members, just willing to learn and able to work well with others, especially if someone is able to take the lead if calleging scenarios arise (e.g. confilcting peer reviews). [[User:Evolution and evolvability|T.Shafee(Evo&#65120;Evo)]]^{[[User talk:Evolution and evolvability|talk]]} 02:48, 9 January 2025 (UTC) *'''Support application''' Though I lack experience in such matters, I have recently learned enough to recognize this to be an easy decision. Regarding mentoring, I think I could use some mentoring myself. Whenever appropriate, please CC me on mentor-mentee communications. In particular, I am having trouble dealing with the large number of referee invites required to recruit volunteers. [[User:Guy vandegrift|Guy vandegrift]] ([[User talk:Guy vandegrift|discuss]] • [[Special:Contributions/Guy vandegrift|contribs]]) 18:50, 11 January 2025 (UTC) {{re|Kamoranesi90}} My apologies for the delay in getting back to you. '''Result: Accepted into the editorial board as associate editor.''' : [[WikiJournal User Group/Editorial guidelines#Adding editorial board members|Next steps]] (add <code>DONE</code> or <code><nowiki>{{Done}}</nowiki></code> after someone has performed the task): # [[{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member|Send a welcome message and confirm their preferred email address]] (usually in their provided website link, else via [[Special:EmailUser]]) {{clickable button 2|Onboarding email template|url=https://en.wikiversity.org/wiki/{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member}} # Copy their information over to [[{{ROOTPAGENAME}}/Editorial board|editorial board page]] using the {{tlx|WikiJournal editor summary}} template # Add their name and start data to the [d:{{WJQboard|default=Q75674277}} relevant editorial board] on wikidata # Direct-add them to the {{WJX}}board mailing list ([https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!managemembers/{{WJX}}board/add via this link]) which will grant them access to the private page only visible to board members # Welcome them at the {{#if:|wjm|WJM}}board mailing list so that they are informed # Finally, move the application to [[Talk:{{ROOTPAGENAME}}/Editors/Archive_{{CURRENTYEAR}}|this year's archive page]] [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 2 April 2025 (UTC) {{ping|Kamoranesi90}}, can you confirm if you're still interested in joining? I have emailed you through the wiki's email function a while back but did not receive a response from you. I also noticed that [https://guc.toolforge.org/?by=date&user=Kamoranesi90 you haven't edited in any WMF projects since November 2024] so I don't know if you still monitor your account for notifications. If I don't hear from you by the end of this month, I will archive this application without prejudice (i.e. you are more than welcome to continue the process to join as an associate editor when you replied back to this message). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 03:43, 2 January 2026 (UTC) ==Editorial board application of Max Loomes== {{WikiJournal editor application submitted | position =Editorial board | name =Max Loomes | qualifications =Bachelor of psychology (Hons I)(USYD), Master of Clinical Psychology (UTS), PhD Candidate (UTS) | link =https://profiles.uts.edu.au/student_Max.W.Loomes | areas_of_expertise =Mental health, psychiatry, public health | professional_experience =Research (9 years, ~4 institutions, various areas both qualitative and quantitative, field work [ecology/education psychology], preclinical trials, project managing, clinical practice (trauma, schizophrenia), teaching (~1 year at 2 institutions for psychology undergraduate and post-graduate, some masters). | publishing_experience =Published ~12 articles/chapters, reviewed for three different journals | open_experience =Have updated various wikipedia pages and big believer in open access and dismantling the highly capitalistic structures that govern journal publishing | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) }} :<nowiki>Great to see this application! I support it; have known Max for several years and he is passionate about many of the values behind WikiJournal ~~~</nowiki> [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:46, 4 February 2026 (UTC) --[[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) :* '''Support'''. Applicant has experience in research, publishing and open access (both Wikipedia and journal). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 00:23, 27 May 2025 (UTC) ==Editorial board application of Alex O. Holcombe== {{WikiJournal editor application submitted | position =Editorial board | name =Alex O. Holcombe | qualifications =PhD in psychology | link =https://profiles.sydney.edu.au/alex.holcombe | areas_of_expertise =Psychology, neuroscience | professional_experience =Full-time academic position for 20 years | publishing_experience =Advisory board or editorial board member of journals and initiatives including PLOS ONE, Collabra:Psychology, Replication Research, Meta-ROR, Meta-psychology... | open_experience =Have been an Associate Editor of WikiJournalOfScience for the last couple years, handled three articles to publication, and have attended most, I think, of the monthly meetings in the last two years | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:56, 4 February 2026 (UTC) }} : I '''strongly support''' promoting Alex to be a full editorial board member. He has the handling editor for a number of submissions, e.g. [[WikiJournal of Science/Hypericum sechmenii|1]], [[WikiJournal of Science/The Himalayan fossil hoax|2]] and [[WikiJournal of Science/Popular Pet Reptile, the Leopard Gecko (Eublepharis macularius), Spontaneously Uses Running Wheel– Is It Locomotion Play?|3]]). He also gave insightful comments towards the operations of the WikiJournal of Science editorial board and the broader WikiJournal publishing umbrella. We need the expertise like Alex to further strengthen the board's expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:03, 5 February 2026 (UTC) ==Associate editor application of Neil Vedwan== {{WikiJournal editor application submitted | position =Associate editor | name =Neil Vedwan | qualifications = | link = | areas_of_expertise =Type theory, Formal Methods, Computational Complexity, Computability, Theoretical Computer Science, Category Theory, Set Theory | professional_experience = Independent Researcher (in collaboration with faculty @ Montclair State University) | publishing_experience =Reviewer at zbMath Open (mathematical reviewing database), In the process of getting 2 papers published | open_experience =Contributor to CSLib (a library of Lean 4), OEIS Associate Editor (mathematical database/encyclopedia) | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:19, 29 September 2026 (UTC) [[Special:Contributions/~2026-52029-76|~2026-52029-76]] ([[User talk:~2026-52029-76|talk]]) 03:53, 28 September 2026 (UTC) }} :It looks like you're not logged in. Please log in and attach your signature to this application. Furthermore, I am unable to find a research by this name in Montclair State University's website with your area of expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 06:52, 28 September 2026 (UTC) ::Apologies for the confusion, I accidentally submitted while logged out. ::To clarify my affiliation: I'm an independent researcher collaborating on research with faculty at Montclair State, which is why I'm not listed in the staff directory. My active work includes reviewing papers for zbMATH Open & contributing to CSLib. If you need to verify anything else, please let me know. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:34, 29 September 2026 (UTC) qstk7nazl6ycfp2deix8j5kr7j1tbgy 2835070 2835069 2026-09-29T19:27:09Z Nv0011 3111788 /* Associate editor application of Neil Vedwan */ 2835070 wikitext text/x-wiki <noinclude> {{WikiJournal editorial application top |archive box = {{Archive box|[[/Archive 2016]]<br>[[/Archive 2017]]<br>[[/Archive 2018]]<br>[[/Archive 2019]]<br>[[/Archive 2020]]<br>[[/Archive 2022]]<br>[[/Archive 2023]] }} }} </noinclude> ==Associate editor application of OGUNJIMI OLUWOLE TEMIDAYO== {{WikiJournal editor application submitted | position =Associate editor | name =OGUNJIMI OLUWOLE TEMIDAYO | qualifications =M.Sc. Geography and Planning | link =Linkedin.com/in/oluwole-ogunjimi | areas_of_expertise =Enivironmental Management and Data Analysis | professional_experience =An administrator with over five years of working experience in both healthcare and education sectors. I have a Master’s degree from the University of Lagos and a Bachelor's degree from the University of Ibadan, I have developed significant research skills, especially in analyzing the impacts of human activities on water quality and understanding the socio-economic effects of environmental changes. With hands-on experience in geospatial mapping, data analytics, and programming (Python), he combines his passion for environmental conservation with a commitment to translating research findings into actionable insights. | publishing_experience =Environmental and Socio-Economic Impact of Artisanal Mining in Oke Ogun Region, 2016. https://drive.google.com/file/d/1l9WTh-ZhUpKbRN_TP28oP-mvlaiWGf0S/view?usp=drive_link Impact of Human Activities on Water Quality of Kudeti River, Ibadan, Oyo State, Nigeria, 2016. https://drive.google.com/file/d/1N00Eo1RitC5dKoX38G1H8r7MJsKdD3Aw/view?usp=drive_link Impact of Rural Transportation on The Distribution of Agricultural Produce in Obafemi Owode Local Government Area, Ogun State, Nigeria, 2023. https://drive.google.com/file/d/1YMYpcdC1JqnxQO-fq5eM3eitbHpQH-HB/view?usp=drive_link | open_experience =I am an active Wikipedia editor with over 300 edits. Significant editing history on English Wikipedia under username "Kamoranesi90". | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 12:35, 18 October 2024 (UTC) }} * {{re|Kamoranesi90}} Please adjust your security settings for the 3 Google Drive links. I am unable to view them. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 13:32, 25 October 2024 (UTC) *:Thank you @[[User:OhanaUnited|OhanaUnited]]. I have adjusted the security settings. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 14:49, 25 October 2024 (UTC) *::Thank you. Do you have any publication examples which are peer-reviewed? For example, these could be journal articles or book chapters. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 25 October 2024 (UTC) *:::No, I don't but I am working on publishing my research works. Thank you [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 09:19, 26 October 2024 (UTC) *::::I am open to '''support''' your associate editor application with mentorship from board members to support your growth in gaining experience around the publishing area. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:52, 14 November 2024 (UTC) *:::::Wow. That's great. I am open to learning from your wealth of knowledge and experience. I appreciate your kind gesture. *:::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 18:59, 14 November 2024 (UTC) *::::::Please wait for other editorial board members to review and comment on your application. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 21:44, 18 November 2024 (UTC) *:::::::Thank you. [[User:Kamoranesi90|Kamoranesi90]] ([[User talk:Kamoranesi90|discuss]] • [[Special:Contributions/Kamoranesi90|contribs]]) 02:59, 22 November 2024 (UTC) *If [[User:OhanaUnited]] is happy to mentor, I think you would be a valuable addition to the team, so I would be willing to support. Associate editor positions don't need to be as experienced as board members, just willing to learn and able to work well with others, especially if someone is able to take the lead if calleging scenarios arise (e.g. confilcting peer reviews). [[User:Evolution and evolvability|T.Shafee(Evo&#65120;Evo)]]^{[[User talk:Evolution and evolvability|talk]]} 02:48, 9 January 2025 (UTC) *'''Support application''' Though I lack experience in such matters, I have recently learned enough to recognize this to be an easy decision. Regarding mentoring, I think I could use some mentoring myself. Whenever appropriate, please CC me on mentor-mentee communications. In particular, I am having trouble dealing with the large number of referee invites required to recruit volunteers. [[User:Guy vandegrift|Guy vandegrift]] ([[User talk:Guy vandegrift|discuss]] • [[Special:Contributions/Guy vandegrift|contribs]]) 18:50, 11 January 2025 (UTC) {{re|Kamoranesi90}} My apologies for the delay in getting back to you. '''Result: Accepted into the editorial board as associate editor.''' : [[WikiJournal User Group/Editorial guidelines#Adding editorial board members|Next steps]] (add <code>DONE</code> or <code><nowiki>{{Done}}</nowiki></code> after someone has performed the task): # [[{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member|Send a welcome message and confirm their preferred email address]] (usually in their provided website link, else via [[Special:EmailUser]]) {{clickable button 2|Onboarding email template|url=https://en.wikiversity.org/wiki/{{ROOTPAGENAMEE}}/Editorial_guidelines/Message_templates#Onboarding_a_new_board_member}} # Copy their information over to [[{{ROOTPAGENAME}}/Editorial board|editorial board page]] using the {{tlx|WikiJournal editor summary}} template # Add their name and start data to the [d:{{WJQboard|default=Q75674277}} relevant editorial board] on wikidata # Direct-add them to the {{WJX}}board mailing list ([https://groups.google.com/forum/?utm_medium=email&utm_source=footer#!managemembers/{{WJX}}board/add via this link]) which will grant them access to the private page only visible to board members # Welcome them at the {{#if:|wjm|WJM}}board mailing list so that they are informed # Finally, move the application to [[Talk:{{ROOTPAGENAME}}/Editors/Archive_{{CURRENTYEAR}}|this year's archive page]] [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 20:12, 2 April 2025 (UTC) {{ping|Kamoranesi90}}, can you confirm if you're still interested in joining? I have emailed you through the wiki's email function a while back but did not receive a response from you. I also noticed that [https://guc.toolforge.org/?by=date&user=Kamoranesi90 you haven't edited in any WMF projects since November 2024] so I don't know if you still monitor your account for notifications. If I don't hear from you by the end of this month, I will archive this application without prejudice (i.e. you are more than welcome to continue the process to join as an associate editor when you replied back to this message). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 03:43, 2 January 2026 (UTC) ==Editorial board application of Max Loomes== {{WikiJournal editor application submitted | position =Editorial board | name =Max Loomes | qualifications =Bachelor of psychology (Hons I)(USYD), Master of Clinical Psychology (UTS), PhD Candidate (UTS) | link =https://profiles.uts.edu.au/student_Max.W.Loomes | areas_of_expertise =Mental health, psychiatry, public health | professional_experience =Research (9 years, ~4 institutions, various areas both qualitative and quantitative, field work [ecology/education psychology], preclinical trials, project managing, clinical practice (trauma, schizophrenia), teaching (~1 year at 2 institutions for psychology undergraduate and post-graduate, some masters). | publishing_experience =Published ~12 articles/chapters, reviewed for three different journals | open_experience =Have updated various wikipedia pages and big believer in open access and dismantling the highly capitalistic structures that govern journal publishing | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) }} :<nowiki>Great to see this application! I support it; have known Max for several years and he is passionate about many of the values behind WikiJournal ~~~</nowiki> [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:46, 4 February 2026 (UTC) --[[User:Maxwloomes|Maxwloomes]] ([[User talk:Maxwloomes|discuss]] • [[Special:Contributions/Maxwloomes|contribs]]) 06:34, 13 May 2025 (UTC) :* '''Support'''. Applicant has experience in research, publishing and open access (both Wikipedia and journal). [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 00:23, 27 May 2025 (UTC) ==Editorial board application of Alex O. Holcombe== {{WikiJournal editor application submitted | position =Editorial board | name =Alex O. Holcombe | qualifications =PhD in psychology | link =https://profiles.sydney.edu.au/alex.holcombe | areas_of_expertise =Psychology, neuroscience | professional_experience =Full-time academic position for 20 years | publishing_experience =Advisory board or editorial board member of journals and initiatives including PLOS ONE, Collabra:Psychology, Replication Research, Meta-ROR, Meta-psychology... | open_experience =Have been an Associate Editor of WikiJournalOfScience for the last couple years, handled three articles to publication, and have attended most, I think, of the monthly meetings in the last two years | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. [[User:Aoholcombe|Aoholcombe]] ([[User talk:Aoholcombe|discuss]] • [[Special:Contributions/Aoholcombe|contribs]]) 20:56, 4 February 2026 (UTC) }} : I '''strongly support''' promoting Alex to be a full editorial board member. He has the handling editor for a number of submissions, e.g. [[WikiJournal of Science/Hypericum sechmenii|1]], [[WikiJournal of Science/The Himalayan fossil hoax|2]] and [[WikiJournal of Science/Popular Pet Reptile, the Leopard Gecko (Eublepharis macularius), Spontaneously Uses Running Wheel– Is It Locomotion Play?|3]]). He also gave insightful comments towards the operations of the WikiJournal of Science editorial board and the broader WikiJournal publishing umbrella. We need the expertise like Alex to further strengthen the board's expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 18:03, 5 February 2026 (UTC) ==Associate editor application of Neil Vedwan== {{WikiJournal editor application submitted | position =Associate editor | name =Neil Vedwan | qualifications = | link = | areas_of_expertise =Type theory, Formal Methods, Computational Complexity, Computability, Theoretical Computer Science, Category Theory, Set Theory | professional_experience = Independent Researcher (in collaboration with faculty @ Montclair State University) | publishing_experience =Reviewer at zbMath Open (mathematical reviewing database), In the process of getting 2 papers published | open_experience =Contributor to CSLib (a library of Lean 4), OEIS Contributor (mathematical database/encyclopedia) | policy_confirm =I confirm that I will act in accordance with the policies of the WikiJournal of Science. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:19, 29 September 2026 (UTC) [[Special:Contributions/~2026-52029-76|~2026-52029-76]] ([[User talk:~2026-52029-76|talk]]) 03:53, 28 September 2026 (UTC) }} :It looks like you're not logged in. Please log in and attach your signature to this application. Furthermore, I am unable to find a research by this name in Montclair State University's website with your area of expertise. [[User:OhanaUnited|<b><span style="color: #0000FF;">OhanaUnited</span></b>]][[User talk:OhanaUnited|<b><span style="color: green;">^{Talk page}</span></b>]] 06:52, 28 September 2026 (UTC) ::Apologies for the confusion, I accidentally submitted while logged out. ::To clarify my affiliation: I'm an independent researcher collaborating on research with faculty at Montclair State, which is why I'm not listed in the staff directory. My active work includes reviewing papers for zbMATH Open & contributing to CSLib. If you need to verify anything else, please let me know. --[[User:Nv0011|Nv0011]] ([[User talk:Nv0011|discuss]] • [[Special:Contributions/Nv0011|contribs]]) 13:34, 29 September 2026 (UTC) 6eyqzt0wqco7bau18jn63kgccorcuaf 2 219126 2835145 2834987 2026-09-30T09:29:27Z ThaniosAkro 2805358 /* Check all conditions */ 2835145 wikitext text/x-wiki ==Table== {| class="wikitable" |- | From <math>(3):</math> || <math>p^3</math>|| || <math>+Ap</math> || <math>+B</math>|| <math>= 0</math> || <math>\dots (5)</math> |- | From <math>(4):</math> || || <math>Cp^2</math>|| <math></math> || <math>+D</math>|| <math>= 0</math> || <math>\dots (6)</math> |- | <math>(5)*D</math> || <math>Dp^3</math>|| || <math>+DAp</math> || <math>+DB</math>|| <math>= 0</math> || <math>\dots (7)</math> |- | <math>(6)*B</math> || || <math>BCp^2</math>|| <math></math> || <math>+BD</math>|| <math>= 0</math> || <math>\dots (8)</math> |- | <math>(7)-(8)</math> || <math>Dp^3</math>||<math>-BCp^2</math> || <math>+DAp</math> || <math></math>|| <math>= 0</math> || <math>\dots (9)</math> |- | Simplify <math>(9)</math> || <math></math>||<math>Dp^2</math> || <math>-BCp</math> || <math>+DA</math>|| <math>= 0</math> || <math>\dots (10)</math> |- | <math>(6)*A</math> || || <math>ACp^2</math>|| <math></math> || <math>+AD</math>|| <math>= 0</math> || <math>\dots (11)</math> |- | <math>(10)-(11)</math> || <math></math>||<math>Dp^2-ACp^2</math> || <math>-BCp</math> || <math></math>|| <math>= 0</math> || <math>\dots (12)</math> |- | Simplify <math>(12)</math> || <math></math>|| || <math>Dp-ACp</math> || <math>-BC</math> || <math>= 0</math> || <math>\dots (13)</math> |} ====First result==== <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ====Calculate R==== <syntaxhighlight> </syntaxhighlight> Produce matrix corrected: <syntaxhighlight lang=python> print ('\nCreating new matrix with corrections:') matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> Circuit parameters: <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> Calculate 1664 values of R: <syntaxhighlight lang=python> Values_of_R = [] number_of_columns = 65 for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = (1) i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) values_of_e = [ i*r for i,r in zip ( values_of_i, values_of_R ) ] ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of tests =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR), 1e-14) s1 = 'sum' ; print(s1,'=',eval(s1)) </syntaxhighlight> <syntaxhighlight> Number of tests = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> R = 723.928575988442547699732563335265663515838075102937503680598 </syntaxhighlight> <math>\text{R}</math> is printed with precision of 60. ==Making the Decimal object== The following function verifies that we are working with Decimal objects. <syntaxhighlight lang=python> import sys import decimal getcontext = decimal.getcontext dD = D = Decimal = decimal.Decimal DT = decimal.DecimalTuple dgt = decimal.getcontext() dgt.prec = 50 def print_error (error, x=None, thisName=None) : """ Prints error derived from sys.exc_info(). """ list1 = error.split(',') v1 = ','.join(list1[1:-1]) if thisName : print (thisName) if x != None : print (' Input =', (str(x))[:60]) print (' ', list1[0]) print (' ', v1) print (' ', list1[-1]) def makeDecimal (x, flag = 0) : ''' output = makeDecimal (x [, flag]) x is a single object convertible to Decimal object. returns Decimal object or returns None on error. ''' thisName = 'makeDecimal (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, dD) : return x if isinstance(x, int) : return dD(x) if isinstance(x, float) : return dD(str(x)) if isinstance(x, str) : try : error = '' output = dD(x) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if isinstance(x, (list,tuple,DT)) : try : error = '' v1,v2,v3 = x if isinstance(v2, (tuple,list)) : output = dD(x) else : output = dD( ( v1, list(v2), v3 ) ) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if flag : print (' Input not recognized.') return None </syntaxhighlight> ===checkComplex(x)=== This function verifies that the object is a valid complex tuple. <syntaxhighlight lang=python> def checkComplex(x, flag = 0) : """ status = checkComplex(x [, flag]) x must be : (v1,v2,'rectangular') or (v1,v2,'polar') v1,v2 must be type Decimal. """ thisName = 'checkComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) try: error = '' v1,v2,str1 = x isinstance (v1,dD) or ({}['v1 must be type Decimal.']) isinstance (v2,dD) or ({}['v2 must be type Decimal.']) (isinstance (str1,str) and str1) or ({}['str1 must be valid string.']) str1 = str1.lower() if str1 == 'rectangular'[:len(str1)] : pass elif str1 == 'polar'[:len(str1)] : pass else : ({}['str1 must be "rectangular" or "polar".']) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return False return True </syntaxhighlight> ===str_to_complex (input_string)=== <syntaxhighlight lang=python> import re # The re pattern for numbers to be found in string of type complex. # In string like ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' # extracts '1234567890987654323456E-6' and '+987654321234567890987e+2J'. # eval allows ' 12_3456_7890_9876_5432_3456E-6 + 987654321234567890987e+2J '. # Conversion to Decimal allows: '__987_65432123____4567890_987___'. # eval does not allow ' 0123 ' but allows ' 2e04 '. # Conversion to Decimal allows: ' 0123 ' digits = '[_0123456789]' integer = '[_0123456789]{1,}' # Matches 1 23 345 4567 56789 exponent = '[Ee][\+\-]{{0,1}}{}'.format(integer) # Matches e8 e+8 e-8 or E8 E+8 E-8 Exponent = '({}){{0,1}}'.format(exponent) # exponent 0 or 1 times. float1 = '({})\.{{0,1}}'.format(integer) # Matches 123 2345. float2 = '{}{{0,}}\.{}'.format(digits, integer) # Matches 123.345 .345 float_ = '(({})|({}))'.format(float2,float1) rvalue = '{}({})'.format(float_,Exponent) rvalue_signed = '[\+\-]{{0,1}}{}'.format(rvalue) ivalue_signed = '{}[Jj]'.format(rvalue_signed) def str_to_complex (input_string) : """ a,b = str_to_complex (input_string) input_string could be ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' input_string could be ' ' ' ( 12345678909876543234561234567890987.654323456E-6 + 987654321234567890987987654321.23764567890987e+2J ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + # Note the '_' 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or '4', '-4', '(4)', '(-4)', '-(4)', '-(-4)' or '( +3j)', '+(-3J)', '-(3j)', '-(-3J)' or '( 4+3j)', '+(-3 + 4J)','-( 4+3j)', '-(-3 + 4J)', This function retains precision of a,b """ try : status = 0 isinstance(input_string,str) or ({}['input_string not type str.']) str1 = input_string.strip() cx1 = eval(str1) isinstance(cx1,(int,float,complex)) or ({}['cx1 not desired type.']) except : status = 1 if status : return # This code removes white lines and comments, if any, at end of each line. new_line = ''' '''[-1:] lines = [ line for Line in str1.split(new_line) for line in [ Line.rstrip() ] if line ] lines = [ v for line in lines for parts in [ line.split('#') ] for v in [ parts[0]] ] str1 = ''.join(lines) str1 = ''.join(str1.split()) if isinstance (cx1, (int,float)) : resultr = re.search(rvalue_signed, str1) resultr or ({}['rvalue not found.']) dD1 = dD(resultr[0]) v1 = eval(str(dD1)) if v1 == cx1 : return dD1,dD(0) if v1 == -cx1 : return -dD1,dD(0) ({}['dD1 not recognized.']) # cx1 must be complex. It must contain imaginary value. resulti = re.search(ivalue_signed, str1) resulti or ({}['ivalue not found.']) str2j = resulti[0] ; str2 = str2j[:-1] dD2 = dD(str2) str1 = ''.join(str1.split(str2j)) # cx1 may contain real value. resultr = re.search(rvalue_signed, str1) if resultr : dD1 = dD(resultr[0]) else : dD1 = dD(0) cx2 = complex(dD1,dD2) if cx2.real == cx1.real : pass elif cx2.real == -cx1.real : dD1 = dD1.copy_negate() else : ({}['dD1 Not Recognized.']) if cx2.imag == cx1.imag : pass elif cx2.imag == -cx1.imag : dD2 = dD2.copy_negate() else : ({}['dD2 Not Recognized.']) cx3 = complex(dD1, dD2) if cx3 == cx1 : return dD1,dD2 ({}['No match for cx3.']) </syntaxhighlight> ===makeComplex(x)=== <syntaxhighlight lang=python> def makeComplex (x, flag = 0) : ''' result = makeComplex (x[, flag]) Input can be tuple with 1,2 or 3 members. If 1 or 2 members, 'rect' is understood. The one member or single object may be int, float, complex, CompleX or string convertible to int, float or complex. x = makeComplex(4) x = makeComplex((4,)) x = makeComplex(('4',0)) x = makeComplex((4,'0', 'rect')) x = makeComplex(4+0j) x = makeComplex('4+0j') x = makeComplex(('4+0j',)) In all seven cases above x = ( Decimal('4'), Decimal('0'), 'rect' ) output is always (modulus, phase, "polar") or (real_part, imag_part, "rect") modulus, phase, real_part, imag_part are Decimal objects. On error returns None. ''' thisName = 'makeComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, CompleX) : # New class CompleX (note the punctuation.) x.check() return (x.r, x.i, 'rect') if isinstance (x,complex) : return makeComplex (( x.real, x.imag )) try : status = 1 a,b = str_to_complex (x) except : status = 0 if status : return a,b,'rect' try : status = 1 result = makeDecimal(x) isinstance(result, Decimal) or ({}['Expecting result to be type Decimal.']) output = result,dD(0),'rect' except : status = 0 if status : return output try : status = 1 v1, = x # Allow for (( 3+4j ),) except : status = 0 if status : return makeComplex (v1) try : status = 1 ; error = '' if len(x) == 2 : v1,v2 = [ makeDecimal (v) for v in x ] str1 = 'rect' elif len(x) == 3 : v1,v2,str1 = x v1,v2 = [ makeDecimal (v) for v in (v1,v2) ] else : ({}['len(x) not in (2,3)']) output = v1,v2,str1 checkComplex(output) or ({}['output not valid complex.']) if str1[0] in 'rR' : output = v1,v2,'rect' else : output = v1,v2,'polar' except : status = 0 ; error = str(sys.exc_info()) if status : return output if flag : print_error (error) return </syntaxhighlight> =Conic sections generally= Within the two dimensional space of Cartesian Coordinate Geometry a conic section may be located anywhere and have any orientation. This section examines the parabola, ellipse and hyperbola, showing how to calculate the equation of the section, and also how to calculate the foci and directrices given the equation. ==Latera recta et cetera== "Latus rectum" is a Latin expression meaning "straight side." According to Google, the Latin plural of "latus rectum" is "latera recta," but English allows "latus rectums" or possibly "lati rectums." The title of this section is poetry to the eyes and music to the ears of a Latin student and this author hopes that the gentle reader will permit such poetic licence in a mathematical topic. The translation of the title is "Latus rectums and other things." This section describes the calculation of interesting items associated with the ellipse: latus rectums, major axis, minor axis, focal chords, directrices and various points on these lines. When given the equation of an ellipse, the first thing is to calculate eccentricity, foci and directrices as shown above. Then verify that the curve is in fact an ellipse. From these values everything about the ellipse may be calculated. For example: {{RoundBoxTop|theme=2}} [[File:0608ellipse01.png|thumb|400px|'''Graph of ellipse <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math>''' </br> </br> Axis : (-0.8)x + (-0.6)y + (9.4) = 0</br> Eccentricity = 0.9</br> </br> Directrix 2 : (0.6)x + (-0.8)y + (2) = 0</br> Latus rectum RS : (0.6)x + (-0.8)y + (-0.8) = 0</br> Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0</br> Latus rectum PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0</br> Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0</br> </br> <math>\text{ID2}</math> = (6.32, 7.24)</br> <math>\text{I2}</math> = (7.204210526315789473684, 6.061052631578947368421)</br> F2 = (8, 5)</br> M = (15.16210526315789473684, -4.54947368421052631579)</br> F1 = (22.32421052631578947368, -14.09894736842105263158)</br> <math>\text{I1}</math> = (23.12, -15.16)</br> <math>\text{ID1}</math> = (24.00421052631578947368, -16.33894736842105263158)</br> </br> P = (20.30821052631578947368, -15.61094736842105263158)</br> Q = (10.53708406832736953616, -8.018239580333420216299)</br> R = (5.984, 3.488)</br> S = (10.016, 6.512)</br> T = (19.78712645798841993752, -1.080707788087632415281)</br> U = (24.34021052631578947368, -12.58694736842105263158)</br> </br> Length of major axis: <math>\text{I1I2}</math> = 26.52631578947368421052</br> Length of minor axis: QT = 11.56255298707631300170</br> Length of latus rectum: RS = PU = 5.04 ]] Consider conic section: <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math> This curve is ellipse with random orientation. <syntaxhighlight lang=python> # python code ABCDEF = A,B,C,D,E,F = 1771, 1204, 1944, -44860, -18520, 214400 # ellipse result = calculate_abc_epq(ABCDEF) (len(result) == 2) or 1/0 # ellipse or hyperbola (abc1,epq1), (abc2,epq2) = result a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 (e1 == e2) or 2/0 (1 > e1 > 0) or 3/0 print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) A,B,C,D,E,F = ABCDEF_from_abc_epq(abc1,epq1) print ('Equation of ellipse in standard form:') print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) </syntaxhighlight> <syntaxhighlight> (1771)x^2 + (1204)y^2 + (1944)xy + (-44860)x + (-18520)y + (214400) = 0 Equation of ellipse in standard form: (-0.7084)x^2 + (-0.4816)y^2 + (-0.7776)xy + (17.944)x + (7.408)y + (-85.76) = 0 </syntaxhighlight> <syntaxhighlight lang=python> # python code def sum_zero(input) : ''' sum = sum_zero(input) If sum is close to 0 and Tolerance permits, sum is returned as 0. For example: if input contains (2, -1.999999999999999999999) this function returns sum of these 2 values as 0. ''' global Tolerance sump = sumn = 0 for v in input : if v > 0 : sump += v elif v < 0 : sumn -= v sum = sump - sumn if abs(sum) < Tolerance : return (type(Tolerance))(0) min, max = sorted((sumn,sump)) if abs(sum) <= Tolerance*min : return (type(Tolerance))(0) return sum </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Major axis=== <syntaxhighlight lang=python> # axis is perpendicular to directrix. ax,bx = b1,-a1 # axis contains foci. ax + by + c = 0 cx = reduce_Decimal_number(-(ax*p1 + bx*q1)) axis = ax,bx,cx print ( ' Axis : ({})x + ({})y + ({}) = 0'.format(ax,bx,cx) ) print ( ' Eccentricity = {}'.format(e1) ) print () print ( ' Directrix 1 : ({})x + ({})y + ({}) = 0'.format(a1,b1,c1) ) print ( ' Directrix 2 : ({})x + ({})y + ({}) = 0'.format(a2,b2,c2) ) F1 = p1,q1 # Focus 1. print ( ' F1 : ({}, {})'.format(p1,q1) ) F2 = p2,q2 # Focus 2. print ( ' F2 : ({}, {})'.format(p2,q2) ) # Direction cosines along axis from F1 towards F2: dx,dy = a1,b1 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 if dx : distance_F1_F2 = (p2 - p1)/dx else : distance_F1_F2 = (q2 - q1) if distance_F1_F2 < 0 : distance_F1_F2 *= -1 dx *= -1 ; dy *= -1 # Intercept on directrix1 distance_from_F1_to_ID1 = abs(a1*p1 + b1*q1 + c1) ID1 = xID1,yID1 = p1 - dx*distance_from_F1_to_ID1, q1 - dy*distance_from_F1_to_ID1 print ( ' Intercept ID1 : ({}, {})'.format(xID1,yID1) ) # # distance_F1_F2 # -------------------- = e # length_of_major_axis # length_of_major_axis = distance_F1_F2 / e1 # Intercept1 on curve distance_from_F1_to_curve = (length_of_major_axis - distance_F1_F2 )/2 xI1,yI1 = p1 - dx*distance_from_F1_to_curve, q1 - dy*distance_from_F1_to_curve I1 = xI1,yI1 = [ reduce_Decimal_number(v) for v in (xI1,yI1) ] print ( ' Intercept I1 : ({}, {})'.format(xI1,yI1) ) </syntaxhighlight> <syntaxhighlight> Axis : (-0.8)x + (-0.6)y + (9.4) = 0 Eccentricity = 0.9 Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0 Directrix 2 : (0.6)x + (-0.8)y + (2) = 0 F1 : (22.32421052631578947368, -14.09894736842105263158) F2 : (8, 5) Intercept ID1 : (24.00421052631578947368, -16.33894736842105263158) Intercept I1 : (23.12, -15.16) </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>I2, ID2.</math> {{RoundBoxBottom}} ===Latus rectums=== <syntaxhighlight lang=python> # direction cosines along latus rectum. dlx,dly = -dy,dx # # distance from U to F1 half_latus_rectum # ------------------------------ = ----------------------- = e1 # distance from U to directrix 1 distance_from_F1_to_ID1 # half_latus_rectum = reduce_Decimal_number(e1*distance_from_F1_to_ID1) # latus rectum 1 # Focal chord has equation (afc)x + (bfc)y + (cfc) = 0. afc,bfc = a1,b1 cfc = reduce_Decimal_number(-(afc*p1 + bfc*q1)) print ( ' Focal chord PU : ({})x + ({})y + ({}) = 0'.format(afc,bfc,cfc) ) P = xP,yP = p1 + dlx*half_latus_rectum, q1 + dly*half_latus_rectum print ( ' Point P : ({}, {})'.format(xP,yP) ) U = xU,yU = p1 - dlx*half_latus_rectum, q1 - dly*half_latus_rectum print ( ' Point U : ({}, {})'.format(xU,yU) ) distance = reduce_Decimal_number(( (xP - xU)**2 + (yP - yU)**2 ).sqrt()) print (' Length PU =', distance) print (' half_latus_rectum =', half_latus_rectum) </syntaxhighlight> <syntaxhighlight> Focal chord PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0 Point P : (20.30821052631578947368, -15.61094736842105263158) Point U : (24.34021052631578947368, -12.58694736842105263158) Length PU = 5.04 half_latus_rectum = 2.52 </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>R, S.</math> {{RoundBoxBottom}} ===Minor axis=== <syntaxhighlight lang=python> print () # Mid point between F1, F2: M = xM,yM = (p1 + p2)/2, (q1 + q2)/2 print ( ' Mid point M : ({}, {})'.format(xM,yM) ) half_major = length_of_major_axis / 2 half_distance = distance_F1_F2 / 2 # half_distance**2 + half_minor**2 = half_major**2 half_minor = ( half_major**2 - half_distance**2 ).sqrt() length_of_minor_axis = half_minor * 2 Q = xQ,yQ = xM + dlx*half_minor, yM + dly*half_minor T = xT,yT = xM - dlx*half_minor, yM - dly*half_minor print ( ' Point Q : ({}, {})'.format(xQ,yQ) ) print ( ' Point T : ({}, {})'.format(xT,yT) ) print (' length_of_major_axis =', length_of_major_axis) print (' length_of_minor_axis =', length_of_minor_axis) # # A basic check. # length_of_minor_axis**2 = (length_of_major_axis**2)(1-e**2) # # length_of_minor_axis**2 # ----------------------- = 1-e**2 # length_of_major_axis**2 # # length_of_minor_axis**2 # ----------------------- + (e**2 - 1) = 0 # length_of_major_axis**2 # values = (length_of_minor_axis/length_of_major_axis)**2, e1**2 - 1 sum_zero(values) and 3/0 aM,bM = a1,b1 # Minor axis is parallel to directrix. cM = reduce_Decimal_number(-(aM*xM + bM*yM)) print ( ' Minor axis : ({})x + ({})y + ({}) = 0'.format(aM,bM,cM) ) </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> Mid point M : (15.16210526315789473684, -4.54947368421052631579) Point Q : (10.53708406832736953616, -8.018239580333420216299) Point T : (19.78712645798841993752, -1.080707788087632415281) length_of_major_axis = 26.52631578947368421052 length_of_minor_axis = 11.56255298707631300170 Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0 </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ===Checking=== {{RoundBoxTop|theme=2}} All interesting points have been calculated without using equations of any of the relevant lines. However, equations of relevant lines are very useful for testing, for example: * Check that points <math>ID2, I2, F2, M, F1, I1, ID1</math> are on axis. * Check that points <math>R, F2, S</math> are on latus rectum through <math>F2.</math> * Check that points <math>Q, M, T</math> are on minor axis through <math>M.</math> * Check that points <math>P, F1, U</math> are on latus rectum through <math>F1.</math> Test below checks that 8 points <math>I1, I2, P, Q, R, S, T, U</math> are on ellipse and satisfy eccentricity <math>e = 0.9.</math> <math></math> <math></math> {{RoundBoxBottom}} <syntaxhighlight lang=python> t1 = ( ('I1'), ('I2'), ('P'), ('Q'), ('R'), ('S'), ('T'), ('U'), ) for name in t1 : value = eval(name) x,y = [ reduce_Decimal_number(v) for v in value ] print ('{} : ({}, {})'.format((name+' ')[:2], x,y)) values = A*x**2, B*y**2, C*x*y, D*x, E*y, F sum_zero(values) and 3/0 # Relative to Directrix 1 and Focus 1: distance_to_F1 = ( (x-p1)**2 + (y-q1)**2 ).sqrt() distance_to_directrix1 = a1*x + b1*y + c1 e1 = distance_to_F1 / distance_to_directrix1 print (' e1 =',e1) # Raw value is printed. # Relative to Directrix 2 and Focus 2: distance_to_F2 = ( (x-p2)**2 + (y-q2)**2 ).sqrt() distance_to_directrix2 = a2*x + b2*y + c2 e2 = distance_to_F2 / distance_to_directrix2 e2 = reduce_Decimal_number(e2) print (' e2 =',e2) # Clean value is printed. </syntaxhighlight> {{RoundBoxTop|theme=2}} Note the differences between "raw" values of <math>e_1</math> and "clean" values of <math>e_2.</math> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> I1 : (23.12, -15.16) e1 = -0.9000000000000000000034 e2 = 0.9 I2 : (7.204210526315789473684, 6.061052631578947368421) e1 = -0.9 e2 = 0.9 P : (20.30821052631578947368, -15.61094736842105263158) e1 = -0.9 e2 = 0.9 Q : (10.53708406832736953616, -8.018239580333420216299) e1 = -0.9000000000000000000002 e2 = 0.9 R : (5.984, 3.488) e1 = -0.9000000000000000000003 e2 = 0.9 S : (10.016, 6.512) e1 = -0.9000000000000000000003 e2 = 0.9 T : (19.78712645798841993752, -1.080707788087632415281) e1 = -0.8999999999999999999996 e2 = 0.9 U : (24.34021052631578947368, -12.58694736842105263158) e1 = -0.9 e2 = 0.9 </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> ==Traditional definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0617ellipse01.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. ]] Ellipse may be defined as the locus of a point that moves so that the sum of its distances from two fixed points is constant. In the diagram the two fixed points are the foci, Focus 1 or <math>F_1</math> and Focus 2 or <math>F_2.</math> Distance between <math>F_1</math> and <math>F_2</math>, distance <math>F_1F_2</math>, must be non-zero. Point <math>G</math> on perimeter of ellipse moves so that sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. Points <math>T_1</math> and <math>T_2</math> are on axis of ellipse and the same rule applies to these points. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> is constant. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> <math>=</math> distance <math>F_1G</math> + distance <math>F_2G</math> <math>=</math> distance <math>F_2T_2</math> + distance <math>T_1F_2</math> <math>= \text{length of major axis.}</math> Therefore the constant is <math>\text{length of major axis}</math> which must be greater than distance <math>F_1F_2.</math> From information given, calculate eccentricity <math>e</math> and equation of one directrix. Choose directrix 1 <math>dx1</math> associated with focus F1. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> {{RoundBoxBottom}} ==Ellipse at origin== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1P</math> and distance <math>F_2P</math> is constant. ]] Traditional definition of ellipse states that ellipse is locus of a point that moves so that sum of its distances from two fixed points is constant. By definition distance <math>F_2P</math> + distance <math>F_1P</math> is constant. <math>\sqrt{(x-(-p))^2 + y^2} + \sqrt{(x-p)^2 + y^2} = k\ \dots\ (1)</math> Expand <math>(1)</math> and result is <math>Ax^2 + By^2 + F = 0\ \dots\ (2)</math> where: <math>A = 4k^2 - 16p^2</math> <math>B = 4k^2</math> <math>F = 4k^2p^2 - k^4</math> When <math>y = 0,</math> point <math>B,\ Ax^2 = -F</math> <math>x^2 = \frac{-F}{A}</math> <math>= \frac{k^4 - 4k^2p^2}{4k^2 - 16p^2}</math> <math>=\frac{k^2(k^2-4p^2)}{4(k^2 - 4p^2)} = \frac{k^2}{4}.</math> Therefore: <math>x = \frac{k}{2} = a</math> <math>k = \text{length of major axis.}</math> By definition, distance <math>F_2A</math> + distance <math>F_1A = k.</math> Therefore distance <math>F_1A = a.</math> Intercept form of ellipse at origin: <math>(4k^2 - 16p^2)x^2 + (4k^2)y^2 = k^4 - 4k^2p^2</math> <math>\frac{4(k^2-4p^2)}{k^2(k^2-4p^2)}x^2 + \frac{4k^2}{k^2(k^2 - 4p^2)}y^2 = 1</math> <math>\frac{4}{(2a)^2}x^2 + \frac{4}{(2a)^2 - 4p^2}y^2 = 1</math> <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> <math></math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Second definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Graph of ellipse <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where <math>a,b = 20,12</math>.''' </br> At point <math>B,\ \frac{u}{v} = e.</math> </br> At point <math>A,\ \frac{a}{t} = e.</math> ]] Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. Let <math>\frac{p}{a} = e</math> where: * <math>p</math> is non-zero, * <math>a > p,</math> * <math>a = p + u.</math> Therefore, <math>1 > e > 0.</math> Let directrix have equation <math>x = t</math> where <math>\frac{a}{t} = e.</math> At point <math>B:</math> <math>\frac{p}{p+u} = \frac{p+u}{p+u+v} = e</math> <math>(p+u)^2 = p(p+u+v)</math> <math>pp + pu + pu + uu = pp + pu + pv</math> <math>pu + uu = pv</math> <math>u(p + u) = pv</math> <math>\frac{u}{v} = \frac{p}{p+u} = e</math> <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e\ \dots\ (3)</math> Statement <math>(3)</math> is true at point <math>A</math> also. Section under "Proof" below proves that statement (3) is true for any point <math>P</math> on ellipse. {{RoundBoxBottom}} ===Proof=== {{RoundBoxTop|theme=2}} [[File:0902ellipse00.png|thumb|400px|'''Proving that <math>\frac{\text{distance from point to focus}}{\text{distance from point to directrix}} = e</math>.''' </br> Graph is part of curve <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1.</math> </br> distance to Directrix1 <math>= t - x = \frac{a}{e} - x = \frac{a - ex}{e}.</math> </br> base = <math>x - p = x - ae</math> </br> <math>\text{(distance to Focus1)}^2 = \text{base}^2 + y^2</math> ]] As expressed above in statement <math>3,</math> second definition of ellipse states that ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. This section proves that this definition is true for any point <math>P</math> on the ellipse. At point <math>P:</math> <math>(a^2 - p^2)x^2 + a^2y^2 -a^2(a^2 - p^2) = 0</math> <math>y^2 = \frac{-(a^2 - p^2)x^2 + a^2(a^2 - p^2)}{a^2}</math> <math>= \frac{a^2e^2x^2 - a^2x^2 + a^2a^2 - a^2a^2e^2}{a^2}</math> <math>= e^2x^2 - x^2 + a^2 - a^2e^2</math> base <math>= x-p = x-ae</math> <math>(\text{distance}\ F_1P)^2 = y^2 + \text{base}^2 = y^2 + (x-ae)^2</math> <math>= a^2 - 2aex + e^2x^2</math> <math>= (a-ex)^2</math> <math>\text{distance to Focus1} = \text{distance}\ F_1P = a - ex</math> <math>\text{distance to Directrix1} = t - x = \frac{a}{e} - x = \frac{a-ex}{e}</math> <math>\frac{\text{distance to Focus1}}{\text{distance to Directrix1}}</math> <math>= (a - ex)\frac{e}{(a-ex)}</math> <math>= e</math> Similar calculations can be used to prove the case for Focus2 <math>(-p, 0)</math> and Directrix2 <math>(x = -t)</math> in which case: <math>\frac{\text{distance to Focus2}}{\text{distance to Directrix2}}</math> <math>= (a + ex)\frac{e}{(a + ex)}</math> <math>= e</math> Therefore: <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e</math> where <math>1 > e > 0.</math> Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant, called eccentricity <math>e.</math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Heading== ===Properties of ellipse=== {{RoundBoxTop|theme=2}} [[File:0822ellipse01.png|thumb|400px|'''Graph of ellipse used to illustrate and calculate certain properties of ellipses.''' </br> </br> Traditional definition of ellipse: </br> <math>\text{distance } AF_1 + \text{distance } AF_2 = \text{constant } k.</math> </br> </br> Second definition of ellipse: </br> <math>\frac{\text{distance } AF_1} {\text{distance } AG } = \text{eccentricity } e.</math> </br> </br> Triangle <math>A F_1 G</math> is right triangle. </br> <math>e = \cos \angle O F_1 A = \cos \angle F_1 A G</math> ]] Ellipse in diagram has: * Two foci: <math>F_1\ (p,0),\ F_2\ (-p,0).</math> * Length of major axis <math>= \text{distance } I_2 I_1 = 2a</math> * Length of minor axis <math>= \text{distance } A B = 2b</math> * Equation: <math>\frac {x^2} {a^2} + \frac {y^2} {b^2} = 1</math> * Length of latus rectum <math>= \text{distance } P Q</math> * Distance between directrices <math>= \text{distance } D_2 D_1 = 2t</math> Properties of ellipse: * <math>\frac{\text{length of major axis}} {\text{distance between directrices}} = e</math> * <math>\frac{\text{distance between foci}} {\text{length of major axis}} = e</math> * <math>\frac{\text{distance between foci}} {\text{distance between directrices}}= e^2</math> * <math>(\frac{\text{length of minor axis}} {\text{length of major axis}})^2 + e^2 = 1</math> * <math>\frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> * line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ====Major axis==== From traditional definition of ellipse: Distance <math>AF_2\ +</math> distance <math>AF_1</math> = distance <math>I_1F_1\ +</math> distance <math>I_1F_2</math> = distance <math>I_2F_2\ +</math> distance <math>I_2F_1</math> = <math>k.</math> Therefore: Length of major axis = distance <math>I_2I_1 = 2a = k.</math> Distance <math>AF_1 = \frac{k}{2} = a.</math> From second definition of ellipse: <math>\frac{\text{distance }AF_1}{\text{distance }AG} = \frac{a}{t} = \text{eccentricity }e</math> <math>= \frac{\text{distance }OI_1}{\text{distance }OD_1}.</math> <math>\frac{\text{length of major axis}}{\text{distance between directrices}} = e.</math> ====Foci==== From second definition of ellipse: <math>\frac{\text{distance }I_1F_1}{\text{distance }I_1D_1} = \frac{a-p}{t-a} = e.</math> <math>a - p = te - ae</math> <math>a - p = a - ae</math> Therefore: <math>p = ae</math> or <math>\frac{p}{a} = e.</math> <math>\frac{\text{distance between foci}}{\text{length of major axis}} = e.</math> <math>\frac{\text{distance between foci}}{\text{distance between directrices}} = e^2.</math> ====Minor axis==== Triangle <math>AOF_1</math> is right triangle. <math>\cos ^2 \angle OAF_1 + \sin ^2 \angle OAF_1</math> <math>= (\frac{b}{a})^2 + (\frac{p}{a})^2 </math> <math>= (\frac{b}{a})^2 + (\frac{ae}{a})^2 </math> <math>= (\frac{b}{a})^2 + e^2 = 1</math> <math>( \frac{\text{length of minor axis}} {\text{length of major axis}} )^2 + e^2 = 1</math> Triangles <math>AOF_1,\ AF_1G</math> are similar. Triangle <math>AF_1G</math> is right triangle. <math>e = \cos \angle OF_1A = \cos \angle F_1AG.</math> ====Latus rectum==== From second definition of ellipse: <math>\frac{\text{distance }PF_1} {\text{distance }F_1D_1} = \frac{\text{distance }PF_1}{t-p} = e</math> <math>\text{distance }PF_1 = te - pe = a - (ae)e = a(1-e^2).</math> <math>\frac{\text{distance }PF_1} {a} = 1 - e^2.</math> <math> \frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> ====Slope of curve==== Curve has equation: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math><math></math> <math>= \frac{-x(1-e^2)}{y}</math><math></math> At point <math>P:\ m_1 = y' = \frac{-p(1-e^2)}{-a(1-e^2)}</math> <math>= \frac{ae}{a} = e.</math><math></math> Slope of line <math>PD_1:\ m_2 = \frac{\text{distance }PF_1}{\text{distance }F_1D_1} = e.</math><math></math><math></math> <math>m_1 = m_2.</math> Therefore line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> ===Intercept form of equation=== <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1</math> <math></math> <math></math> {{RoundBoxTop|theme=2}} [[File:0625ellipse01.png|thumb|400px|'''Ellipse at origin with major axis on X axis.''' </br> </br> </br> </br> Equation of ellipse has format <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where: </br> </br> <math>\text{Length of major axis} = 2a = \text{distance}\ I_2I_1 = 40</math> </br> <math>\text{Length of minor axis} = 2b = \text{distance}\ BA = 24</math> </br> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> </br> <math>\frac{\text{Length of minor axis}}{\text{Length of major axis}} = \sqrt{1 - e^2}</math> </br> </br> <math>e = \sqrt{1 - \frac{b^2}{a^2}} = 0.8.</math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> ]] In diagram: Intercept <math>I_1</math> has coordinates <math>(a,0).</math> Intercept <math>I_2</math> has coordinates <math>(-a,0).</math> Intercept <math>A</math> has coordinates <math>(0,b).</math> Intercept <math>B</math> has coordinates <math>(0,-b).</math> Focus <math>F_1</math> has coordinates <math>(f,0)</math> where <math>f = ea.</math> Focus <math>F_2</math> has coordinates <math>(-f,0).</math> Curve has equation <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1,</math> called intercept form of equation of ellipse because intercepts are apparent as the fractional value of each coefficient. Standard form of this equation is: <math>(-0.36)x^2 + (-1)y^2 + (0)xy + (0)x + (0)y + (144) = 0.</math> While the standard form is valuable as input to a computer program, the intercept form is still attractive to the human eye because center of ellipse and intercepts are neatly contained within the equation. Slope of curve: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math> <math>= \frac{-x(1-e^2)}{y}</math> At point <math>P</math> on latus rectum <math>PQ:</math> <math>m_1 = y' = \frac{-(ea)(1-e^2)}{-(a(1-e^2))} = e</math> Slope of line <math>PD = m_2 = \frac{PF_1}{F_1D} = e</math> <math>m_1 = m_2.</math> Line <math>PD</math> is tangent to curve at latus rectum, point <math>P.</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Example=== {{RoundBoxTop|theme=2}} [[File:0618ellipse01.png|thumb|400px|'''Traditional definition of ellipse uses abc, epq.''' </br> M is mid-point between F1 and F2. </br> Point R is on minor axis. </br> </br> <math>\frac{\text{distance from R to F1}}{\text{distance from R to directrix 1}}</math> <math>= e</math> </br> </br> <math>= \frac{\text{half major axis}}{\text{distance from M to directrix 1}}</math> </br> </br> <math>\text{distance from M to directrix 1} = \frac{\text{half major axis}}{e}</math> </br> </br> <math>\text{F1:}\ (1, -7)</math> </br> <math>\text{F2:}\ (-1.24, 0.68)</math> </br> length_of_major_axis = 10 </br> <math>\text{M:}\ (-0.12, -3.16)</math> </br> length_of_minor_axis = 6 </br> <math>\text{R:}\ (2.76, -2.32)</math> </br> <math>e = 0.8</math> </br> <math>\text{D1:}\ (1.63, -9.16)</math> </br> <math>\text{Directrix 1:}\ (-0.28)x + (0.96)y + (9.25) = 0</math> </br> <math>\text{abc}\ =\ (-0.28,\ 0.96,\ 9.25)</math> </br> <math>\text{epq}\ =\ (0.8,\ 1,\ -7)</math> ]] Given: <syntaxhighlight lang=python> # python code F1 = 1, -7 # Focus 1 F2 = -1.24, 0.68 # Focus 2 length_of_major_axis = 10 </syntaxhighlight> Calculate equation of ellipse. <syntaxhighlight lang=python> F1 = p1,q1 = [ dD(str(v)) for v in F1 ] # Focus 1 F2 = p2,q2 = [ dD(str(v)) for v in F2 ] # Focus 2 length_of_major_axis = dD(length_of_major_axis) half_major_axis = length_of_major_axis / 2 # Direction cosines from F1 to F2 dx = p2-p1 ; dy = q2-q1 divider = (dx**2 + dy**2).sqrt() dx,dy = [ (v/divider) for v in (dx,dy) ] # F2 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 distance_F1_F2 = (q2-q1)/dy half_distance_F1_F2 = distance_F1_F2 / 2 # The mid-point M = xM,ym = p1 + dx*half_distance_F1_F2, q1 + dy*half_distance_F1_F2 # Eccentricity: e = distance_F1_F2 / length_of_major_axis # distance from point R to F1 half_major_axis # ------------------------------------ = e = ----------------------------------------- # distance from point R to Directrix 1 distance from point M to Directrix 1 distance_from_point_M_to_dx1 = half_major_axis / e # Intersection of axis and directrix 1 D1 = xM-dx*distance_from_point_M_to_dx1, yM-dy*distance_from_point_M_to_dx1 D1 = xD1, yD1 = [ reduce_Decimal_number(v) for v in D1 ] # Equation of Directrix 1 # dx1 = adx1,bdx1,cdx1 adx1,bdx1 = dx, dy # Perpendicular to axis. # adx1*x + bdx1*y + cdx1 = 0 # Directrix 1 contains point D1 cdx1 = reduce_Decimal_number( -( adx1*xD1 + bdx1*yD1 ) ) abc = adx1,bdx1,cdx1 epq = e,p1,q1 ABCDEF = ABCDEF_from_abc_epq (abc,epq, 1) </syntaxhighlight> Equation of ellipse in standard form: <math>(-0.949824)x^2 + (-0.410176)y^2 + (-0.344064)xy + (-1.3152)x + (-2.6336)y + (4.76) = 0</math> For more insight into method of calculation and proof: <syntaxhighlight lang=python> if 1 : print ('F1: ({}, {})'.format(p1,q1)) print ('F1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p1,q1)) print ('F2: ({}, {})'.format(p2,q2)) print ('F2: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p2,q2)) print ('length_of_major_axis =', length_of_major_axis) print ('M: ({}, {})'.format(xM,yM)) print ('M: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xM,yM)) # half_minor_axis**2 + half_distance_F1_F2**2 = half_major_axis**2 half_minor_axis = (half_major_axis**2 - half_distance_F1_F2**2).sqrt() length_of_minor_axis = half_minor_axis * 2 s1 = 'length_of_minor_axis' ; print (s1, '=', eval(s1)) # Direction cosines on major axis: print ('dx,dy =', dx,dy) # Direction cosines on minor axis: dnx,dny = dy,-dx print ('dnx,dny =', dnx,dny) # One point on minor axis: R = xR,yR = xM + dnx*half_minor_axis, yM + dny*half_minor_axis print ('R: ({}, {})'.format(xR,yR)) print ('R: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xR,yR)) # Verify that point R is on ellipse: sum_zero((A*xR**2, B*yR**2, C*xR*yR, D*xR, E*yR, F)) and 1/0 s1 = 'e' ; print (s1, '=', eval(s1)) print ('D1: ({}, {})'.format(xD1,yD1)) print ('D1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xD1,yD1)) print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(adx1, bdx1, cdx1)) print() # For proof, reverse the process: (abc1,epq1), (abc2,epq2) = calculate_abc_epq (ABCDEF) a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(a1, b1, c1)) print ('Eccentricity e1: {}'.format(e1)) print ('F1: ({}, {})'.format(p1,q1)) print() a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 print ('Directrix 2: ({})x + ({})y + ({}) = 0'.format(a2, b2, c2)) print ('Eccentricity e2: {}'.format(e2)) print ('F2: ({}, {})'.format(p2,q2)) print ('\nEquation of ellipse with integer coefficients:') A,B,C,D,E,F = [ reduce_Decimal_number(-v*1000000/64) for v in ABCDEF ] str1 = '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0' print (str1.format(A,B,C,D,E,F)) </syntaxhighlight> <syntaxhighlight> F1: (1, -7) F1: (x - (1))^2 + (y - (-7))^2 = 1 F2: (-1.24, 0.68) F2: (x - (-1.24))^2 + (y - (0.68))^2 = 1 length_of_major_axis = 10 M: (-0.12, -3.16) M: (x - (-0.12))^2 + (y - (-3.16))^2 = 1 length_of_minor_axis = 6 dx,dy = -0.28 0.96 dnx,dny = 0.96 0.28 R: (2.76, -2.32) R: (x - (2.76))^2 + (y - (-2.32))^2 = 1 e = 0.8 D1: (1.63, -9.16) D1: (x - (1.63))^2 + (y - (-9.16))^2 = 1 Directrix 1: (-0.28)x + (0.96)y + (9.25) = 0 Directrix 1: (0.28)x + (-0.96)y + (-9.25) = 0 Eccentricity e1: 0.8 F1: (1, -7) Directrix 2: (0.28)x + (-0.96)y + (3.25) = 0 Eccentricity e2: 0.8 F2: (-1.24, 0.68) Equation of ellipse with integer coefficients: </syntaxhighlight> <math>(14841)x^2 + (6409)y^2 + (5376)xy + (20550)x + (41150)y + (-74375) = 0</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} =allEqual= {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; 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We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> <syntaxhighlight lang=python> # python code. if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 : pass </syntaxhighlight> {{Robelbox/close}} {{Robelbox/close}} {{Robelbox/close}} <noinclude> [[Category: main page templates]] </noinclude> {| class="wikitable" |- ! <math>x</math> !! <math>x^2 - N</math> |- | <code></code><code>6</code> || <code>-221</code> |- | <code></code><code>7</code> || <code>-208</code> |- |- | <code>10</code> || <code>-157</code> |- | <code>11</code> || <code>-136</code> |- | <code>12</code> || <code>-113</code> |- | <code>13</code> || <code></code><code>-88</code> |- | <code>26</code> || <code></code><code>419</code> |} =Testing= ======table1====== {|style="border-left:solid 3px blue;border-right:solid 3px blue;border-top:solid 3px blue;border-bottom:solid 3px blue;" align="center" | Hello As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 </syntaxhighlight> |} {{RoundBoxTop|theme=2}} [[File:0410cubic01.png|thumb|400px|''' Graph of cubic function with coefficient a negative.''' </br> There is no absolute maximum or absolute minimum. ]] Coefficient <math>a</math> may be negative as shown in diagram. As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. Unless stated otherwise, any reference to "cubic function" on this page will assume coefficient <math>a</math> positive. {{RoundBoxBottom}} <math>x_{poi} = -1</math> <math></math> <math></math> <math></math> <math></math> =====Various planes in 3 dimensions===== {{RoundBoxTop|theme=2}} <gallery> File:0713x=4.png|<small>plane x=4.</small> File:0713y=3.png|<small>plane y=3.</small> File:0713z=-2.png|<small>plane z=-2.</small> </gallery> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 6872533965463318088296406206152583523950547457502877599617298355752203375318570113543746034084988471 6038689997069900481503054402779031645424782306849293691862158057846311159666871301301561856898723723 5288509264861249497715421833420428568606014682472077143585487415565706967765372022648544701585880162 0758474922657226002085584466521458398893944370926591800311388246468157082630100594858704003186480342 1948972782906410450726368813137398552561173220402450912277002269411275736272804957381089675040183698 6836845072579936472906076299694138047565482372899718032680247442062926912485905218100445984215059112 0249441341728531478105803603371077309182869314710171111683916581726889419758716582152128229518488472 </syntaxhighlight> <math>\theta_1</math> {{RoundBoxTop|theme=2}} [[File:0422xx_x_2.png|thumb|400px|''' Figure 1: Diagram illustrating relationship between <math>f(x) = x^2 - x - 2</math> and <math>f'(x) = 2x - 1.</math>''' </br> ]] {{RoundBoxBottom}} <math>O\ (0,0,0)</math> <math>M\ (A_1,B_1,C_1)</math> <math>N\ (A_2,B_2,C_2)</math> <math>\theta</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} (6) - (7),\ 4Apq + 2Bq =&\ 0\\ 2Ap + B =&\ 0\\ 2Ap =&\ - B\\ \\ p =&\ \frac{-B}{2A}\ \dots\ (8) \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} 1.&4141475869yugh\\ &2645er3423231sgdtrf\\ &dhcgfyrt45erwesd \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math> 4\sin 18^\circ = \sqrt{2(3 - \sqrt 5)} = \sqrt 5 - 1 </math> 8sox82ig23p8ma0zjjevs19quqvy6zk 2835147 2835145 2026-09-30T09:50:39Z ThaniosAkro 2805358 /* Calculate R */ 2835147 wikitext text/x-wiki ==Table== {| class="wikitable" |- | From <math>(3):</math> || <math>p^3</math>|| || <math>+Ap</math> || <math>+B</math>|| <math>= 0</math> || <math>\dots (5)</math> |- | From <math>(4):</math> || || <math>Cp^2</math>|| <math></math> || <math>+D</math>|| <math>= 0</math> || <math>\dots (6)</math> |- | <math>(5)*D</math> || <math>Dp^3</math>|| || <math>+DAp</math> || <math>+DB</math>|| <math>= 0</math> || <math>\dots (7)</math> |- | <math>(6)*B</math> || || <math>BCp^2</math>|| <math></math> || <math>+BD</math>|| <math>= 0</math> || <math>\dots (8)</math> |- | <math>(7)-(8)</math> || <math>Dp^3</math>||<math>-BCp^2</math> || <math>+DAp</math> || <math></math>|| <math>= 0</math> || <math>\dots (9)</math> |- | Simplify <math>(9)</math> || <math></math>||<math>Dp^2</math> || <math>-BCp</math> || <math>+DA</math>|| <math>= 0</math> || <math>\dots (10)</math> |- | <math>(6)*A</math> || || <math>ACp^2</math>|| <math></math> || <math>+AD</math>|| <math>= 0</math> || <math>\dots (11)</math> |- | <math>(10)-(11)</math> || <math></math>||<math>Dp^2-ACp^2</math> || <math>-BCp</math> || <math></math>|| <math>= 0</math> || <math>\dots (12)</math> |- | Simplify <math>(12)</math> || <math></math>|| || <math>Dp-ACp</math> || <math>-BC</math> || <math>= 0</math> || <math>\dots (13)</math> |} ====First result==== <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ====Calculate R==== <syntaxhighlight> </syntaxhighlight> Produce matrix corrected: <syntaxhighlight lang=python> print ('\nCreating new matrix with corrections:') matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> Circuit parameters: <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> Calculate 1664 values of R using floating point numbers: <syntaxhighlight lang=python> # python code: number_of_columns = 65 one = 1 ; Tolerance = 1e-14 # Following string is executable python code: exc_str1 = """ Values_of_R = [] for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = one i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) exec(exc_str_64ei) for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of tests =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR)) s1 = 'sum' ; print(s1,'=',eval(s1)) if not sum : print ('With Tolerance of {}, both minR and maxR are equal.'.format(Tolerance)) """ exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of tests = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 With Tolerance of 1e-14, both minR and maxR are equal. </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. Calculate 1664 values of R using Decimal numbers: <syntaxhighlight lang=python> Precision = dgt.prec = 60 Tolerance = dD('1e-' + str(Precision-3)) one = dD(1) exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of tests = 1664 minR = 723.928575988442547699732563335265663515838075102937503680560 maxR = 723.928575988442547699732563335265663515838075102937503680663 sum = 0 With Tolerance of 1E-57, both minR and maxR are equal. </syntaxhighlight> With tolerance of <math>1e-57</math> all values of resistance R = 723.928575988442547699732563335265663515838075102937503681. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math>\text{R}</math> is printed with precision of 60. ==Making the Decimal object== The following function verifies that we are working with Decimal objects. <syntaxhighlight lang=python> import sys import decimal getcontext = decimal.getcontext dD = D = Decimal = decimal.Decimal DT = decimal.DecimalTuple dgt = decimal.getcontext() dgt.prec = 50 def print_error (error, x=None, thisName=None) : """ Prints error derived from sys.exc_info(). """ list1 = error.split(',') v1 = ','.join(list1[1:-1]) if thisName : print (thisName) if x != None : print (' Input =', (str(x))[:60]) print (' ', list1[0]) print (' ', v1) print (' ', list1[-1]) def makeDecimal (x, flag = 0) : ''' output = makeDecimal (x [, flag]) x is a single object convertible to Decimal object. returns Decimal object or returns None on error. ''' thisName = 'makeDecimal (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, dD) : return x if isinstance(x, int) : return dD(x) if isinstance(x, float) : return dD(str(x)) if isinstance(x, str) : try : error = '' output = dD(x) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if isinstance(x, (list,tuple,DT)) : try : error = '' v1,v2,v3 = x if isinstance(v2, (tuple,list)) : output = dD(x) else : output = dD( ( v1, list(v2), v3 ) ) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if flag : print (' Input not recognized.') return None </syntaxhighlight> ===checkComplex(x)=== This function verifies that the object is a valid complex tuple. <syntaxhighlight lang=python> def checkComplex(x, flag = 0) : """ status = checkComplex(x [, flag]) x must be : (v1,v2,'rectangular') or (v1,v2,'polar') v1,v2 must be type Decimal. """ thisName = 'checkComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) try: error = '' v1,v2,str1 = x isinstance (v1,dD) or ({}['v1 must be type Decimal.']) isinstance (v2,dD) or ({}['v2 must be type Decimal.']) (isinstance (str1,str) and str1) or ({}['str1 must be valid string.']) str1 = str1.lower() if str1 == 'rectangular'[:len(str1)] : pass elif str1 == 'polar'[:len(str1)] : pass else : ({}['str1 must be "rectangular" or "polar".']) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return False return True </syntaxhighlight> ===str_to_complex (input_string)=== <syntaxhighlight lang=python> import re # The re pattern for numbers to be found in string of type complex. # In string like ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' # extracts '1234567890987654323456E-6' and '+987654321234567890987e+2J'. # eval allows ' 12_3456_7890_9876_5432_3456E-6 + 987654321234567890987e+2J '. # Conversion to Decimal allows: '__987_65432123____4567890_987___'. # eval does not allow ' 0123 ' but allows ' 2e04 '. # Conversion to Decimal allows: ' 0123 ' digits = '[_0123456789]' integer = '[_0123456789]{1,}' # Matches 1 23 345 4567 56789 exponent = '[Ee][\+\-]{{0,1}}{}'.format(integer) # Matches e8 e+8 e-8 or E8 E+8 E-8 Exponent = '({}){{0,1}}'.format(exponent) # exponent 0 or 1 times. float1 = '({})\.{{0,1}}'.format(integer) # Matches 123 2345. float2 = '{}{{0,}}\.{}'.format(digits, integer) # Matches 123.345 .345 float_ = '(({})|({}))'.format(float2,float1) rvalue = '{}({})'.format(float_,Exponent) rvalue_signed = '[\+\-]{{0,1}}{}'.format(rvalue) ivalue_signed = '{}[Jj]'.format(rvalue_signed) def str_to_complex (input_string) : """ a,b = str_to_complex (input_string) input_string could be ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' input_string could be ' ' ' ( 12345678909876543234561234567890987.654323456E-6 + 987654321234567890987987654321.23764567890987e+2J ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + # Note the '_' 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or '4', '-4', '(4)', '(-4)', '-(4)', '-(-4)' or '( +3j)', '+(-3J)', '-(3j)', '-(-3J)' or '( 4+3j)', '+(-3 + 4J)','-( 4+3j)', '-(-3 + 4J)', This function retains precision of a,b """ try : status = 0 isinstance(input_string,str) or ({}['input_string not type str.']) str1 = input_string.strip() cx1 = eval(str1) isinstance(cx1,(int,float,complex)) or ({}['cx1 not desired type.']) except : status = 1 if status : return # This code removes white lines and comments, if any, at end of each line. new_line = ''' '''[-1:] lines = [ line for Line in str1.split(new_line) for line in [ Line.rstrip() ] if line ] lines = [ v for line in lines for parts in [ line.split('#') ] for v in [ parts[0]] ] str1 = ''.join(lines) str1 = ''.join(str1.split()) if isinstance (cx1, (int,float)) : resultr = re.search(rvalue_signed, str1) resultr or ({}['rvalue not found.']) dD1 = dD(resultr[0]) v1 = eval(str(dD1)) if v1 == cx1 : return dD1,dD(0) if v1 == -cx1 : return -dD1,dD(0) ({}['dD1 not recognized.']) # cx1 must be complex. It must contain imaginary value. resulti = re.search(ivalue_signed, str1) resulti or ({}['ivalue not found.']) str2j = resulti[0] ; str2 = str2j[:-1] dD2 = dD(str2) str1 = ''.join(str1.split(str2j)) # cx1 may contain real value. resultr = re.search(rvalue_signed, str1) if resultr : dD1 = dD(resultr[0]) else : dD1 = dD(0) cx2 = complex(dD1,dD2) if cx2.real == cx1.real : pass elif cx2.real == -cx1.real : dD1 = dD1.copy_negate() else : ({}['dD1 Not Recognized.']) if cx2.imag == cx1.imag : pass elif cx2.imag == -cx1.imag : dD2 = dD2.copy_negate() else : ({}['dD2 Not Recognized.']) cx3 = complex(dD1, dD2) if cx3 == cx1 : return dD1,dD2 ({}['No match for cx3.']) </syntaxhighlight> ===makeComplex(x)=== <syntaxhighlight lang=python> def makeComplex (x, flag = 0) : ''' result = makeComplex (x[, flag]) Input can be tuple with 1,2 or 3 members. If 1 or 2 members, 'rect' is understood. The one member or single object may be int, float, complex, CompleX or string convertible to int, float or complex. x = makeComplex(4) x = makeComplex((4,)) x = makeComplex(('4',0)) x = makeComplex((4,'0', 'rect')) x = makeComplex(4+0j) x = makeComplex('4+0j') x = makeComplex(('4+0j',)) In all seven cases above x = ( Decimal('4'), Decimal('0'), 'rect' ) output is always (modulus, phase, "polar") or (real_part, imag_part, "rect") modulus, phase, real_part, imag_part are Decimal objects. On error returns None. ''' thisName = 'makeComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, CompleX) : # New class CompleX (note the punctuation.) x.check() return (x.r, x.i, 'rect') if isinstance (x,complex) : return makeComplex (( x.real, x.imag )) try : status = 1 a,b = str_to_complex (x) except : status = 0 if status : return a,b,'rect' try : status = 1 result = makeDecimal(x) isinstance(result, Decimal) or ({}['Expecting result to be type Decimal.']) output = result,dD(0),'rect' except : status = 0 if status : return output try : status = 1 v1, = x # Allow for (( 3+4j ),) except : status = 0 if status : return makeComplex (v1) try : status = 1 ; error = '' if len(x) == 2 : v1,v2 = [ makeDecimal (v) for v in x ] str1 = 'rect' elif len(x) == 3 : v1,v2,str1 = x v1,v2 = [ makeDecimal (v) for v in (v1,v2) ] else : ({}['len(x) not in (2,3)']) output = v1,v2,str1 checkComplex(output) or ({}['output not valid complex.']) if str1[0] in 'rR' : output = v1,v2,'rect' else : output = v1,v2,'polar' except : status = 0 ; error = str(sys.exc_info()) if status : return output if flag : print_error (error) return </syntaxhighlight> =Conic sections generally= Within the two dimensional space of Cartesian Coordinate Geometry a conic section may be located anywhere and have any orientation. This section examines the parabola, ellipse and hyperbola, showing how to calculate the equation of the section, and also how to calculate the foci and directrices given the equation. ==Latera recta et cetera== "Latus rectum" is a Latin expression meaning "straight side." According to Google, the Latin plural of "latus rectum" is "latera recta," but English allows "latus rectums" or possibly "lati rectums." The title of this section is poetry to the eyes and music to the ears of a Latin student and this author hopes that the gentle reader will permit such poetic licence in a mathematical topic. The translation of the title is "Latus rectums and other things." This section describes the calculation of interesting items associated with the ellipse: latus rectums, major axis, minor axis, focal chords, directrices and various points on these lines. When given the equation of an ellipse, the first thing is to calculate eccentricity, foci and directrices as shown above. Then verify that the curve is in fact an ellipse. From these values everything about the ellipse may be calculated. For example: {{RoundBoxTop|theme=2}} [[File:0608ellipse01.png|thumb|400px|'''Graph of ellipse <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math>''' </br> </br> Axis : (-0.8)x + (-0.6)y + (9.4) = 0</br> Eccentricity = 0.9</br> </br> Directrix 2 : (0.6)x + (-0.8)y + (2) = 0</br> Latus rectum RS : (0.6)x + (-0.8)y + (-0.8) = 0</br> Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0</br> Latus rectum PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0</br> Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0</br> </br> <math>\text{ID2}</math> = (6.32, 7.24)</br> <math>\text{I2}</math> = (7.204210526315789473684, 6.061052631578947368421)</br> F2 = (8, 5)</br> M = (15.16210526315789473684, -4.54947368421052631579)</br> F1 = (22.32421052631578947368, -14.09894736842105263158)</br> <math>\text{I1}</math> = (23.12, -15.16)</br> <math>\text{ID1}</math> = (24.00421052631578947368, -16.33894736842105263158)</br> </br> P = (20.30821052631578947368, -15.61094736842105263158)</br> Q = (10.53708406832736953616, -8.018239580333420216299)</br> R = (5.984, 3.488)</br> S = (10.016, 6.512)</br> T = (19.78712645798841993752, -1.080707788087632415281)</br> U = (24.34021052631578947368, -12.58694736842105263158)</br> </br> Length of major axis: <math>\text{I1I2}</math> = 26.52631578947368421052</br> Length of minor axis: QT = 11.56255298707631300170</br> Length of latus rectum: RS = PU = 5.04 ]] Consider conic section: <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math> This curve is ellipse with random orientation. <syntaxhighlight lang=python> # python code ABCDEF = A,B,C,D,E,F = 1771, 1204, 1944, -44860, -18520, 214400 # ellipse result = calculate_abc_epq(ABCDEF) (len(result) == 2) or 1/0 # ellipse or hyperbola (abc1,epq1), (abc2,epq2) = result a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 (e1 == e2) or 2/0 (1 > e1 > 0) or 3/0 print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) A,B,C,D,E,F = ABCDEF_from_abc_epq(abc1,epq1) print ('Equation of ellipse in standard form:') print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) </syntaxhighlight> <syntaxhighlight> (1771)x^2 + (1204)y^2 + (1944)xy + (-44860)x + (-18520)y + (214400) = 0 Equation of ellipse in standard form: (-0.7084)x^2 + (-0.4816)y^2 + (-0.7776)xy + (17.944)x + (7.408)y + (-85.76) = 0 </syntaxhighlight> <syntaxhighlight lang=python> # python code def sum_zero(input) : ''' sum = sum_zero(input) If sum is close to 0 and Tolerance permits, sum is returned as 0. For example: if input contains (2, -1.999999999999999999999) this function returns sum of these 2 values as 0. ''' global Tolerance sump = sumn = 0 for v in input : if v > 0 : sump += v elif v < 0 : sumn -= v sum = sump - sumn if abs(sum) < Tolerance : return (type(Tolerance))(0) min, max = sorted((sumn,sump)) if abs(sum) <= Tolerance*min : return (type(Tolerance))(0) return sum </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Major axis=== <syntaxhighlight lang=python> # axis is perpendicular to directrix. ax,bx = b1,-a1 # axis contains foci. ax + by + c = 0 cx = reduce_Decimal_number(-(ax*p1 + bx*q1)) axis = ax,bx,cx print ( ' Axis : ({})x + ({})y + ({}) = 0'.format(ax,bx,cx) ) print ( ' Eccentricity = {}'.format(e1) ) print () print ( ' Directrix 1 : ({})x + ({})y + ({}) = 0'.format(a1,b1,c1) ) print ( ' Directrix 2 : ({})x + ({})y + ({}) = 0'.format(a2,b2,c2) ) F1 = p1,q1 # Focus 1. print ( ' F1 : ({}, {})'.format(p1,q1) ) F2 = p2,q2 # Focus 2. print ( ' F2 : ({}, {})'.format(p2,q2) ) # Direction cosines along axis from F1 towards F2: dx,dy = a1,b1 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 if dx : distance_F1_F2 = (p2 - p1)/dx else : distance_F1_F2 = (q2 - q1) if distance_F1_F2 < 0 : distance_F1_F2 *= -1 dx *= -1 ; dy *= -1 # Intercept on directrix1 distance_from_F1_to_ID1 = abs(a1*p1 + b1*q1 + c1) ID1 = xID1,yID1 = p1 - dx*distance_from_F1_to_ID1, q1 - dy*distance_from_F1_to_ID1 print ( ' Intercept ID1 : ({}, {})'.format(xID1,yID1) ) # # distance_F1_F2 # -------------------- = e # length_of_major_axis # length_of_major_axis = distance_F1_F2 / e1 # Intercept1 on curve distance_from_F1_to_curve = (length_of_major_axis - distance_F1_F2 )/2 xI1,yI1 = p1 - dx*distance_from_F1_to_curve, q1 - dy*distance_from_F1_to_curve I1 = xI1,yI1 = [ reduce_Decimal_number(v) for v in (xI1,yI1) ] print ( ' Intercept I1 : ({}, {})'.format(xI1,yI1) ) </syntaxhighlight> <syntaxhighlight> Axis : (-0.8)x + (-0.6)y + (9.4) = 0 Eccentricity = 0.9 Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0 Directrix 2 : (0.6)x + (-0.8)y + (2) = 0 F1 : (22.32421052631578947368, -14.09894736842105263158) F2 : (8, 5) Intercept ID1 : (24.00421052631578947368, -16.33894736842105263158) Intercept I1 : (23.12, -15.16) </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>I2, ID2.</math> {{RoundBoxBottom}} ===Latus rectums=== <syntaxhighlight lang=python> # direction cosines along latus rectum. dlx,dly = -dy,dx # # distance from U to F1 half_latus_rectum # ------------------------------ = ----------------------- = e1 # distance from U to directrix 1 distance_from_F1_to_ID1 # half_latus_rectum = reduce_Decimal_number(e1*distance_from_F1_to_ID1) # latus rectum 1 # Focal chord has equation (afc)x + (bfc)y + (cfc) = 0. afc,bfc = a1,b1 cfc = reduce_Decimal_number(-(afc*p1 + bfc*q1)) print ( ' Focal chord PU : ({})x + ({})y + ({}) = 0'.format(afc,bfc,cfc) ) P = xP,yP = p1 + dlx*half_latus_rectum, q1 + dly*half_latus_rectum print ( ' Point P : ({}, {})'.format(xP,yP) ) U = xU,yU = p1 - dlx*half_latus_rectum, q1 - dly*half_latus_rectum print ( ' Point U : ({}, {})'.format(xU,yU) ) distance = reduce_Decimal_number(( (xP - xU)**2 + (yP - yU)**2 ).sqrt()) print (' Length PU =', distance) print (' half_latus_rectum =', half_latus_rectum) </syntaxhighlight> <syntaxhighlight> Focal chord PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0 Point P : (20.30821052631578947368, -15.61094736842105263158) Point U : (24.34021052631578947368, -12.58694736842105263158) Length PU = 5.04 half_latus_rectum = 2.52 </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>R, S.</math> {{RoundBoxBottom}} ===Minor axis=== <syntaxhighlight lang=python> print () # Mid point between F1, F2: M = xM,yM = (p1 + p2)/2, (q1 + q2)/2 print ( ' Mid point M : ({}, {})'.format(xM,yM) ) half_major = length_of_major_axis / 2 half_distance = distance_F1_F2 / 2 # half_distance**2 + half_minor**2 = half_major**2 half_minor = ( half_major**2 - half_distance**2 ).sqrt() length_of_minor_axis = half_minor * 2 Q = xQ,yQ = xM + dlx*half_minor, yM + dly*half_minor T = xT,yT = xM - dlx*half_minor, yM - dly*half_minor print ( ' Point Q : ({}, {})'.format(xQ,yQ) ) print ( ' Point T : ({}, {})'.format(xT,yT) ) print (' length_of_major_axis =', length_of_major_axis) print (' length_of_minor_axis =', length_of_minor_axis) # # A basic check. # length_of_minor_axis**2 = (length_of_major_axis**2)(1-e**2) # # length_of_minor_axis**2 # ----------------------- = 1-e**2 # length_of_major_axis**2 # # length_of_minor_axis**2 # ----------------------- + (e**2 - 1) = 0 # length_of_major_axis**2 # values = (length_of_minor_axis/length_of_major_axis)**2, e1**2 - 1 sum_zero(values) and 3/0 aM,bM = a1,b1 # Minor axis is parallel to directrix. cM = reduce_Decimal_number(-(aM*xM + bM*yM)) print ( ' Minor axis : ({})x + ({})y + ({}) = 0'.format(aM,bM,cM) ) </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> Mid point M : (15.16210526315789473684, -4.54947368421052631579) Point Q : (10.53708406832736953616, -8.018239580333420216299) Point T : (19.78712645798841993752, -1.080707788087632415281) length_of_major_axis = 26.52631578947368421052 length_of_minor_axis = 11.56255298707631300170 Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0 </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ===Checking=== {{RoundBoxTop|theme=2}} All interesting points have been calculated without using equations of any of the relevant lines. However, equations of relevant lines are very useful for testing, for example: * Check that points <math>ID2, I2, F2, M, F1, I1, ID1</math> are on axis. * Check that points <math>R, F2, S</math> are on latus rectum through <math>F2.</math> * Check that points <math>Q, M, T</math> are on minor axis through <math>M.</math> * Check that points <math>P, F1, U</math> are on latus rectum through <math>F1.</math> Test below checks that 8 points <math>I1, I2, P, Q, R, S, T, U</math> are on ellipse and satisfy eccentricity <math>e = 0.9.</math> <math></math> <math></math> {{RoundBoxBottom}} <syntaxhighlight lang=python> t1 = ( ('I1'), ('I2'), ('P'), ('Q'), ('R'), ('S'), ('T'), ('U'), ) for name in t1 : value = eval(name) x,y = [ reduce_Decimal_number(v) for v in value ] print ('{} : ({}, {})'.format((name+' ')[:2], x,y)) values = A*x**2, B*y**2, C*x*y, D*x, E*y, F sum_zero(values) and 3/0 # Relative to Directrix 1 and Focus 1: distance_to_F1 = ( (x-p1)**2 + (y-q1)**2 ).sqrt() distance_to_directrix1 = a1*x + b1*y + c1 e1 = distance_to_F1 / distance_to_directrix1 print (' e1 =',e1) # Raw value is printed. # Relative to Directrix 2 and Focus 2: distance_to_F2 = ( (x-p2)**2 + (y-q2)**2 ).sqrt() distance_to_directrix2 = a2*x + b2*y + c2 e2 = distance_to_F2 / distance_to_directrix2 e2 = reduce_Decimal_number(e2) print (' e2 =',e2) # Clean value is printed. </syntaxhighlight> {{RoundBoxTop|theme=2}} Note the differences between "raw" values of <math>e_1</math> and "clean" values of <math>e_2.</math> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> I1 : (23.12, -15.16) e1 = -0.9000000000000000000034 e2 = 0.9 I2 : (7.204210526315789473684, 6.061052631578947368421) e1 = -0.9 e2 = 0.9 P : (20.30821052631578947368, -15.61094736842105263158) e1 = -0.9 e2 = 0.9 Q : (10.53708406832736953616, -8.018239580333420216299) e1 = -0.9000000000000000000002 e2 = 0.9 R : (5.984, 3.488) e1 = -0.9000000000000000000003 e2 = 0.9 S : (10.016, 6.512) e1 = -0.9000000000000000000003 e2 = 0.9 T : (19.78712645798841993752, -1.080707788087632415281) e1 = -0.8999999999999999999996 e2 = 0.9 U : (24.34021052631578947368, -12.58694736842105263158) e1 = -0.9 e2 = 0.9 </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> ==Traditional definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0617ellipse01.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. ]] Ellipse may be defined as the locus of a point that moves so that the sum of its distances from two fixed points is constant. In the diagram the two fixed points are the foci, Focus 1 or <math>F_1</math> and Focus 2 or <math>F_2.</math> Distance between <math>F_1</math> and <math>F_2</math>, distance <math>F_1F_2</math>, must be non-zero. Point <math>G</math> on perimeter of ellipse moves so that sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. Points <math>T_1</math> and <math>T_2</math> are on axis of ellipse and the same rule applies to these points. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> is constant. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> <math>=</math> distance <math>F_1G</math> + distance <math>F_2G</math> <math>=</math> distance <math>F_2T_2</math> + distance <math>T_1F_2</math> <math>= \text{length of major axis.}</math> Therefore the constant is <math>\text{length of major axis}</math> which must be greater than distance <math>F_1F_2.</math> From information given, calculate eccentricity <math>e</math> and equation of one directrix. Choose directrix 1 <math>dx1</math> associated with focus F1. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> {{RoundBoxBottom}} ==Ellipse at origin== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1P</math> and distance <math>F_2P</math> is constant. ]] Traditional definition of ellipse states that ellipse is locus of a point that moves so that sum of its distances from two fixed points is constant. By definition distance <math>F_2P</math> + distance <math>F_1P</math> is constant. <math>\sqrt{(x-(-p))^2 + y^2} + \sqrt{(x-p)^2 + y^2} = k\ \dots\ (1)</math> Expand <math>(1)</math> and result is <math>Ax^2 + By^2 + F = 0\ \dots\ (2)</math> where: <math>A = 4k^2 - 16p^2</math> <math>B = 4k^2</math> <math>F = 4k^2p^2 - k^4</math> When <math>y = 0,</math> point <math>B,\ Ax^2 = -F</math> <math>x^2 = \frac{-F}{A}</math> <math>= \frac{k^4 - 4k^2p^2}{4k^2 - 16p^2}</math> <math>=\frac{k^2(k^2-4p^2)}{4(k^2 - 4p^2)} = \frac{k^2}{4}.</math> Therefore: <math>x = \frac{k}{2} = a</math> <math>k = \text{length of major axis.}</math> By definition, distance <math>F_2A</math> + distance <math>F_1A = k.</math> Therefore distance <math>F_1A = a.</math> Intercept form of ellipse at origin: <math>(4k^2 - 16p^2)x^2 + (4k^2)y^2 = k^4 - 4k^2p^2</math> <math>\frac{4(k^2-4p^2)}{k^2(k^2-4p^2)}x^2 + \frac{4k^2}{k^2(k^2 - 4p^2)}y^2 = 1</math> <math>\frac{4}{(2a)^2}x^2 + \frac{4}{(2a)^2 - 4p^2}y^2 = 1</math> <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> <math></math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Second definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Graph of ellipse <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where <math>a,b = 20,12</math>.''' </br> At point <math>B,\ \frac{u}{v} = e.</math> </br> At point <math>A,\ \frac{a}{t} = e.</math> ]] Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. Let <math>\frac{p}{a} = e</math> where: * <math>p</math> is non-zero, * <math>a > p,</math> * <math>a = p + u.</math> Therefore, <math>1 > e > 0.</math> Let directrix have equation <math>x = t</math> where <math>\frac{a}{t} = e.</math> At point <math>B:</math> <math>\frac{p}{p+u} = \frac{p+u}{p+u+v} = e</math> <math>(p+u)^2 = p(p+u+v)</math> <math>pp + pu + pu + uu = pp + pu + pv</math> <math>pu + uu = pv</math> <math>u(p + u) = pv</math> <math>\frac{u}{v} = \frac{p}{p+u} = e</math> <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e\ \dots\ (3)</math> Statement <math>(3)</math> is true at point <math>A</math> also. Section under "Proof" below proves that statement (3) is true for any point <math>P</math> on ellipse. {{RoundBoxBottom}} ===Proof=== {{RoundBoxTop|theme=2}} [[File:0902ellipse00.png|thumb|400px|'''Proving that <math>\frac{\text{distance from point to focus}}{\text{distance from point to directrix}} = e</math>.''' </br> Graph is part of curve <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1.</math> </br> distance to Directrix1 <math>= t - x = \frac{a}{e} - x = \frac{a - ex}{e}.</math> </br> base = <math>x - p = x - ae</math> </br> <math>\text{(distance to Focus1)}^2 = \text{base}^2 + y^2</math> ]] As expressed above in statement <math>3,</math> second definition of ellipse states that ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. This section proves that this definition is true for any point <math>P</math> on the ellipse. At point <math>P:</math> <math>(a^2 - p^2)x^2 + a^2y^2 -a^2(a^2 - p^2) = 0</math> <math>y^2 = \frac{-(a^2 - p^2)x^2 + a^2(a^2 - p^2)}{a^2}</math> <math>= \frac{a^2e^2x^2 - a^2x^2 + a^2a^2 - a^2a^2e^2}{a^2}</math> <math>= e^2x^2 - x^2 + a^2 - a^2e^2</math> base <math>= x-p = x-ae</math> <math>(\text{distance}\ F_1P)^2 = y^2 + \text{base}^2 = y^2 + (x-ae)^2</math> <math>= a^2 - 2aex + e^2x^2</math> <math>= (a-ex)^2</math> <math>\text{distance to Focus1} = \text{distance}\ F_1P = a - ex</math> <math>\text{distance to Directrix1} = t - x = \frac{a}{e} - x = \frac{a-ex}{e}</math> <math>\frac{\text{distance to Focus1}}{\text{distance to Directrix1}}</math> <math>= (a - ex)\frac{e}{(a-ex)}</math> <math>= e</math> Similar calculations can be used to prove the case for Focus2 <math>(-p, 0)</math> and Directrix2 <math>(x = -t)</math> in which case: <math>\frac{\text{distance to Focus2}}{\text{distance to Directrix2}}</math> <math>= (a + ex)\frac{e}{(a + ex)}</math> <math>= e</math> Therefore: <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e</math> where <math>1 > e > 0.</math> Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant, called eccentricity <math>e.</math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Heading== ===Properties of ellipse=== {{RoundBoxTop|theme=2}} [[File:0822ellipse01.png|thumb|400px|'''Graph of ellipse used to illustrate and calculate certain properties of ellipses.''' </br> </br> Traditional definition of ellipse: </br> <math>\text{distance } AF_1 + \text{distance } AF_2 = \text{constant } k.</math> </br> </br> Second definition of ellipse: </br> <math>\frac{\text{distance } AF_1} {\text{distance } AG } = \text{eccentricity } e.</math> </br> </br> Triangle <math>A F_1 G</math> is right triangle. </br> <math>e = \cos \angle O F_1 A = \cos \angle F_1 A G</math> ]] Ellipse in diagram has: * Two foci: <math>F_1\ (p,0),\ F_2\ (-p,0).</math> * Length of major axis <math>= \text{distance } I_2 I_1 = 2a</math> * Length of minor axis <math>= \text{distance } A B = 2b</math> * Equation: <math>\frac {x^2} {a^2} + \frac {y^2} {b^2} = 1</math> * Length of latus rectum <math>= \text{distance } P Q</math> * Distance between directrices <math>= \text{distance } D_2 D_1 = 2t</math> Properties of ellipse: * <math>\frac{\text{length of major axis}} {\text{distance between directrices}} = e</math> * <math>\frac{\text{distance between foci}} {\text{length of major axis}} = e</math> * <math>\frac{\text{distance between foci}} {\text{distance between directrices}}= e^2</math> * <math>(\frac{\text{length of minor axis}} {\text{length of major axis}})^2 + e^2 = 1</math> * <math>\frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> * line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ====Major axis==== From traditional definition of ellipse: Distance <math>AF_2\ +</math> distance <math>AF_1</math> = distance <math>I_1F_1\ +</math> distance <math>I_1F_2</math> = distance <math>I_2F_2\ +</math> distance <math>I_2F_1</math> = <math>k.</math> Therefore: Length of major axis = distance <math>I_2I_1 = 2a = k.</math> Distance <math>AF_1 = \frac{k}{2} = a.</math> From second definition of ellipse: <math>\frac{\text{distance }AF_1}{\text{distance }AG} = \frac{a}{t} = \text{eccentricity }e</math> <math>= \frac{\text{distance }OI_1}{\text{distance }OD_1}.</math> <math>\frac{\text{length of major axis}}{\text{distance between directrices}} = e.</math> ====Foci==== From second definition of ellipse: <math>\frac{\text{distance }I_1F_1}{\text{distance }I_1D_1} = \frac{a-p}{t-a} = e.</math> <math>a - p = te - ae</math> <math>a - p = a - ae</math> Therefore: <math>p = ae</math> or <math>\frac{p}{a} = e.</math> <math>\frac{\text{distance between foci}}{\text{length of major axis}} = e.</math> <math>\frac{\text{distance between foci}}{\text{distance between directrices}} = e^2.</math> ====Minor axis==== Triangle <math>AOF_1</math> is right triangle. <math>\cos ^2 \angle OAF_1 + \sin ^2 \angle OAF_1</math> <math>= (\frac{b}{a})^2 + (\frac{p}{a})^2 </math> <math>= (\frac{b}{a})^2 + (\frac{ae}{a})^2 </math> <math>= (\frac{b}{a})^2 + e^2 = 1</math> <math>( \frac{\text{length of minor axis}} {\text{length of major axis}} )^2 + e^2 = 1</math> Triangles <math>AOF_1,\ AF_1G</math> are similar. Triangle <math>AF_1G</math> is right triangle. <math>e = \cos \angle OF_1A = \cos \angle F_1AG.</math> ====Latus rectum==== From second definition of ellipse: <math>\frac{\text{distance }PF_1} {\text{distance }F_1D_1} = \frac{\text{distance }PF_1}{t-p} = e</math> <math>\text{distance }PF_1 = te - pe = a - (ae)e = a(1-e^2).</math> <math>\frac{\text{distance }PF_1} {a} = 1 - e^2.</math> <math> \frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> ====Slope of curve==== Curve has equation: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math><math></math> <math>= \frac{-x(1-e^2)}{y}</math><math></math> At point <math>P:\ m_1 = y' = \frac{-p(1-e^2)}{-a(1-e^2)}</math> <math>= \frac{ae}{a} = e.</math><math></math> Slope of line <math>PD_1:\ m_2 = \frac{\text{distance }PF_1}{\text{distance }F_1D_1} = e.</math><math></math><math></math> <math>m_1 = m_2.</math> Therefore line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> ===Intercept form of equation=== <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1</math> <math></math> <math></math> {{RoundBoxTop|theme=2}} [[File:0625ellipse01.png|thumb|400px|'''Ellipse at origin with major axis on X axis.''' </br> </br> </br> </br> Equation of ellipse has format <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where: </br> </br> <math>\text{Length of major axis} = 2a = \text{distance}\ I_2I_1 = 40</math> </br> <math>\text{Length of minor axis} = 2b = \text{distance}\ BA = 24</math> </br> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> </br> <math>\frac{\text{Length of minor axis}}{\text{Length of major axis}} = \sqrt{1 - e^2}</math> </br> </br> <math>e = \sqrt{1 - \frac{b^2}{a^2}} = 0.8.</math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> ]] In diagram: Intercept <math>I_1</math> has coordinates <math>(a,0).</math> Intercept <math>I_2</math> has coordinates <math>(-a,0).</math> Intercept <math>A</math> has coordinates <math>(0,b).</math> Intercept <math>B</math> has coordinates <math>(0,-b).</math> Focus <math>F_1</math> has coordinates <math>(f,0)</math> where <math>f = ea.</math> Focus <math>F_2</math> has coordinates <math>(-f,0).</math> Curve has equation <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1,</math> called intercept form of equation of ellipse because intercepts are apparent as the fractional value of each coefficient. Standard form of this equation is: <math>(-0.36)x^2 + (-1)y^2 + (0)xy + (0)x + (0)y + (144) = 0.</math> While the standard form is valuable as input to a computer program, the intercept form is still attractive to the human eye because center of ellipse and intercepts are neatly contained within the equation. Slope of curve: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math> <math>= \frac{-x(1-e^2)}{y}</math> At point <math>P</math> on latus rectum <math>PQ:</math> <math>m_1 = y' = \frac{-(ea)(1-e^2)}{-(a(1-e^2))} = e</math> Slope of line <math>PD = m_2 = \frac{PF_1}{F_1D} = e</math> <math>m_1 = m_2.</math> Line <math>PD</math> is tangent to curve at latus rectum, point <math>P.</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Example=== {{RoundBoxTop|theme=2}} [[File:0618ellipse01.png|thumb|400px|'''Traditional definition of ellipse uses abc, epq.''' </br> M is mid-point between F1 and F2. </br> Point R is on minor axis. </br> </br> <math>\frac{\text{distance from R to F1}}{\text{distance from R to directrix 1}}</math> <math>= e</math> </br> </br> <math>= \frac{\text{half major axis}}{\text{distance from M to directrix 1}}</math> </br> </br> <math>\text{distance from M to directrix 1} = \frac{\text{half major axis}}{e}</math> </br> </br> <math>\text{F1:}\ (1, -7)</math> </br> <math>\text{F2:}\ (-1.24, 0.68)</math> </br> length_of_major_axis = 10 </br> <math>\text{M:}\ (-0.12, -3.16)</math> </br> length_of_minor_axis = 6 </br> <math>\text{R:}\ (2.76, -2.32)</math> </br> <math>e = 0.8</math> </br> <math>\text{D1:}\ (1.63, -9.16)</math> </br> <math>\text{Directrix 1:}\ (-0.28)x + (0.96)y + (9.25) = 0</math> </br> <math>\text{abc}\ =\ (-0.28,\ 0.96,\ 9.25)</math> </br> <math>\text{epq}\ =\ (0.8,\ 1,\ -7)</math> ]] Given: <syntaxhighlight lang=python> # python code F1 = 1, -7 # Focus 1 F2 = -1.24, 0.68 # Focus 2 length_of_major_axis = 10 </syntaxhighlight> Calculate equation of ellipse. <syntaxhighlight lang=python> F1 = p1,q1 = [ dD(str(v)) for v in F1 ] # Focus 1 F2 = p2,q2 = [ dD(str(v)) for v in F2 ] # Focus 2 length_of_major_axis = dD(length_of_major_axis) half_major_axis = length_of_major_axis / 2 # Direction cosines from F1 to F2 dx = p2-p1 ; dy = q2-q1 divider = (dx**2 + dy**2).sqrt() dx,dy = [ (v/divider) for v in (dx,dy) ] # F2 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 distance_F1_F2 = (q2-q1)/dy half_distance_F1_F2 = distance_F1_F2 / 2 # The mid-point M = xM,ym = p1 + dx*half_distance_F1_F2, q1 + dy*half_distance_F1_F2 # Eccentricity: e = distance_F1_F2 / length_of_major_axis # distance from point R to F1 half_major_axis # ------------------------------------ = e = ----------------------------------------- # distance from point R to Directrix 1 distance from point M to Directrix 1 distance_from_point_M_to_dx1 = half_major_axis / e # Intersection of axis and directrix 1 D1 = xM-dx*distance_from_point_M_to_dx1, yM-dy*distance_from_point_M_to_dx1 D1 = xD1, yD1 = [ reduce_Decimal_number(v) for v in D1 ] # Equation of Directrix 1 # dx1 = adx1,bdx1,cdx1 adx1,bdx1 = dx, dy # Perpendicular to axis. # adx1*x + bdx1*y + cdx1 = 0 # Directrix 1 contains point D1 cdx1 = reduce_Decimal_number( -( adx1*xD1 + bdx1*yD1 ) ) abc = adx1,bdx1,cdx1 epq = e,p1,q1 ABCDEF = ABCDEF_from_abc_epq (abc,epq, 1) </syntaxhighlight> Equation of ellipse in standard form: <math>(-0.949824)x^2 + (-0.410176)y^2 + (-0.344064)xy + (-1.3152)x + (-2.6336)y + (4.76) = 0</math> For more insight into method of calculation and proof: <syntaxhighlight lang=python> if 1 : print ('F1: ({}, {})'.format(p1,q1)) print ('F1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p1,q1)) print ('F2: ({}, {})'.format(p2,q2)) print ('F2: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p2,q2)) print ('length_of_major_axis =', length_of_major_axis) print ('M: ({}, {})'.format(xM,yM)) print ('M: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xM,yM)) # half_minor_axis**2 + half_distance_F1_F2**2 = half_major_axis**2 half_minor_axis = (half_major_axis**2 - half_distance_F1_F2**2).sqrt() length_of_minor_axis = half_minor_axis * 2 s1 = 'length_of_minor_axis' ; print (s1, '=', eval(s1)) # Direction cosines on major axis: print ('dx,dy =', dx,dy) # Direction cosines on minor axis: dnx,dny = dy,-dx print ('dnx,dny =', dnx,dny) # One point on minor axis: R = xR,yR = xM + dnx*half_minor_axis, yM + dny*half_minor_axis print ('R: ({}, {})'.format(xR,yR)) print ('R: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xR,yR)) # Verify that point R is on ellipse: sum_zero((A*xR**2, B*yR**2, C*xR*yR, D*xR, E*yR, F)) and 1/0 s1 = 'e' ; print (s1, '=', eval(s1)) print ('D1: ({}, {})'.format(xD1,yD1)) print ('D1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xD1,yD1)) print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(adx1, bdx1, cdx1)) print() # For proof, reverse the process: (abc1,epq1), (abc2,epq2) = calculate_abc_epq (ABCDEF) a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(a1, b1, c1)) print ('Eccentricity e1: {}'.format(e1)) print ('F1: ({}, {})'.format(p1,q1)) print() a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 print ('Directrix 2: ({})x + ({})y + ({}) = 0'.format(a2, b2, c2)) print ('Eccentricity e2: {}'.format(e2)) print ('F2: ({}, {})'.format(p2,q2)) print ('\nEquation of ellipse with integer coefficients:') A,B,C,D,E,F = [ reduce_Decimal_number(-v*1000000/64) for v in ABCDEF ] str1 = '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0' print (str1.format(A,B,C,D,E,F)) </syntaxhighlight> <syntaxhighlight> F1: (1, -7) F1: (x - (1))^2 + (y - (-7))^2 = 1 F2: (-1.24, 0.68) F2: (x - (-1.24))^2 + (y - (0.68))^2 = 1 length_of_major_axis = 10 M: (-0.12, -3.16) M: (x - (-0.12))^2 + (y - (-3.16))^2 = 1 length_of_minor_axis = 6 dx,dy = -0.28 0.96 dnx,dny = 0.96 0.28 R: (2.76, -2.32) R: (x - (2.76))^2 + (y - (-2.32))^2 = 1 e = 0.8 D1: (1.63, -9.16) D1: (x - (1.63))^2 + (y - (-9.16))^2 = 1 Directrix 1: (-0.28)x + (0.96)y + (9.25) = 0 Directrix 1: (0.28)x + (-0.96)y + (-9.25) = 0 Eccentricity e1: 0.8 F1: (1, -7) Directrix 2: (0.28)x + (-0.96)y + (3.25) = 0 Eccentricity e2: 0.8 F2: (-1.24, 0.68) Equation of ellipse with integer coefficients: </syntaxhighlight> <math>(14841)x^2 + (6409)y^2 + (5376)xy + (20550)x + (41150)y + (-74375) = 0</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} =allEqual= {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em;"> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> ====Welcomee==== {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFF800; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> =====Welcomen===== {{Robelbox|title=|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFFFFF; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> <syntaxhighlight lang=python> # python code. if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 : pass </syntaxhighlight> {{Robelbox/close}} {{Robelbox/close}} {{Robelbox/close}} <noinclude> [[Category: main page templates]] </noinclude> {| class="wikitable" |- ! <math>x</math> !! <math>x^2 - N</math> |- | <code></code><code>6</code> || <code>-221</code> |- | <code></code><code>7</code> || <code>-208</code> |- |- | <code>10</code> || <code>-157</code> |- | <code>11</code> || <code>-136</code> |- | <code>12</code> || <code>-113</code> |- | <code>13</code> || <code></code><code>-88</code> |- | <code>26</code> || <code></code><code>419</code> |} =Testing= ======table1====== {|style="border-left:solid 3px blue;border-right:solid 3px blue;border-top:solid 3px blue;border-bottom:solid 3px blue;" align="center" | Hello As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 </syntaxhighlight> |} {{RoundBoxTop|theme=2}} [[File:0410cubic01.png|thumb|400px|''' Graph of cubic function with coefficient a negative.''' </br> There is no absolute maximum or absolute minimum. ]] Coefficient <math>a</math> may be negative as shown in diagram. As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. Unless stated otherwise, any reference to "cubic function" on this page will assume coefficient <math>a</math> positive. {{RoundBoxBottom}} <math>x_{poi} = -1</math> <math></math> <math></math> <math></math> <math></math> =====Various planes in 3 dimensions===== {{RoundBoxTop|theme=2}} <gallery> File:0713x=4.png|<small>plane x=4.</small> File:0713y=3.png|<small>plane y=3.</small> File:0713z=-2.png|<small>plane z=-2.</small> </gallery> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 6872533965463318088296406206152583523950547457502877599617298355752203375318570113543746034084988471 6038689997069900481503054402779031645424782306849293691862158057846311159666871301301561856898723723 5288509264861249497715421833420428568606014682472077143585487415565706967765372022648544701585880162 0758474922657226002085584466521458398893944370926591800311388246468157082630100594858704003186480342 1948972782906410450726368813137398552561173220402450912277002269411275736272804957381089675040183698 6836845072579936472906076299694138047565482372899718032680247442062926912485905218100445984215059112 0249441341728531478105803603371077309182869314710171111683916581726889419758716582152128229518488472 </syntaxhighlight> <math>\theta_1</math> {{RoundBoxTop|theme=2}} [[File:0422xx_x_2.png|thumb|400px|''' Figure 1: Diagram illustrating relationship between <math>f(x) = x^2 - x - 2</math> and <math>f'(x) = 2x - 1.</math>''' </br> ]] {{RoundBoxBottom}} <math>O\ (0,0,0)</math> <math>M\ (A_1,B_1,C_1)</math> <math>N\ (A_2,B_2,C_2)</math> <math>\theta</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} (6) - (7),\ 4Apq + 2Bq =&\ 0\\ 2Ap + B =&\ 0\\ 2Ap =&\ - B\\ \\ p =&\ \frac{-B}{2A}\ \dots\ (8) \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} 1.&4141475869yugh\\ &2645er3423231sgdtrf\\ &dhcgfyrt45erwesd \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math> 4\sin 18^\circ = \sqrt{2(3 - \sqrt 5)} = \sqrt 5 - 1 </math> 0kmkato3ryhmg5ii0d2rz3q8kaebexp 2835148 2835147 2026-09-30T09:56:23Z ThaniosAkro 2805358 /* Calculate R */ 2835148 wikitext text/x-wiki ==Table== {| class="wikitable" |- | From <math>(3):</math> || <math>p^3</math>|| || <math>+Ap</math> || <math>+B</math>|| <math>= 0</math> || <math>\dots (5)</math> |- | From <math>(4):</math> || || <math>Cp^2</math>|| <math></math> || <math>+D</math>|| <math>= 0</math> || <math>\dots (6)</math> |- | <math>(5)*D</math> || <math>Dp^3</math>|| || <math>+DAp</math> || <math>+DB</math>|| <math>= 0</math> || <math>\dots (7)</math> |- | <math>(6)*B</math> || || <math>BCp^2</math>|| <math></math> || <math>+BD</math>|| <math>= 0</math> || <math>\dots (8)</math> |- | <math>(7)-(8)</math> || <math>Dp^3</math>||<math>-BCp^2</math> || <math>+DAp</math> || <math></math>|| <math>= 0</math> || <math>\dots (9)</math> |- | Simplify <math>(9)</math> || <math></math>||<math>Dp^2</math> || <math>-BCp</math> || <math>+DA</math>|| <math>= 0</math> || <math>\dots (10)</math> |- | <math>(6)*A</math> || || <math>ACp^2</math>|| <math></math> || <math>+AD</math>|| <math>= 0</math> || <math>\dots (11)</math> |- | <math>(10)-(11)</math> || <math></math>||<math>Dp^2-ACp^2</math> || <math>-BCp</math> || <math></math>|| <math>= 0</math> || <math>\dots (12)</math> |- | Simplify <math>(12)</math> || <math></math>|| || <math>Dp-ACp</math> || <math>-BC</math> || <math>= 0</math> || <math>\dots (13)</math> |} ====First result==== <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ====Calculate R==== <syntaxhighlight> </syntaxhighlight> Produce matrix corrected: <syntaxhighlight lang=python> print ('\nCreating new matrix with corrections:') matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> Circuit parameters: <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> =====Using floating point numbers:===== <syntaxhighlight lang=python> # python code: number_of_columns = 65 one = 1 ; Tolerance = 1e-14 # Following string is executable python code: exc_str1 = """ Values_of_R = [] for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = one i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) exec(exc_str_64ei) for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of tests =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR)) s1 = 'sum' ; print(s1,'=',eval(s1)) if not sum : print ('With Tolerance of {}, both minR and maxR are equal.'.format(Tolerance)) """ exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of tests = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 With Tolerance of 1e-14, both minR and maxR are equal. </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. =====Using Decimal numbers:===== <syntaxhighlight lang=python> Precision = dgt.prec = 60 Tolerance = dD('1e-' + str(Precision-3)) one = dD(1) exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of tests = 1664 minR = 723.928575988442547699732563335265663515838075102937503680560 maxR = 723.928575988442547699732563335265663515838075102937503680663 sum = 0 With Tolerance of 1E-57, both minR and maxR are equal. </syntaxhighlight> With tolerance of <math>1e-57</math> all values of resistance R = 723.928575988442547699732563335265663515838075102937503681. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math>\text{R}</math> is printed with precision of 60. ==Making the Decimal object== The following function verifies that we are working with Decimal objects. <syntaxhighlight lang=python> import sys import decimal getcontext = decimal.getcontext dD = D = Decimal = decimal.Decimal DT = decimal.DecimalTuple dgt = decimal.getcontext() dgt.prec = 50 def print_error (error, x=None, thisName=None) : """ Prints error derived from sys.exc_info(). """ list1 = error.split(',') v1 = ','.join(list1[1:-1]) if thisName : print (thisName) if x != None : print (' Input =', (str(x))[:60]) print (' ', list1[0]) print (' ', v1) print (' ', list1[-1]) def makeDecimal (x, flag = 0) : ''' output = makeDecimal (x [, flag]) x is a single object convertible to Decimal object. returns Decimal object or returns None on error. ''' thisName = 'makeDecimal (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, dD) : return x if isinstance(x, int) : return dD(x) if isinstance(x, float) : return dD(str(x)) if isinstance(x, str) : try : error = '' output = dD(x) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if isinstance(x, (list,tuple,DT)) : try : error = '' v1,v2,v3 = x if isinstance(v2, (tuple,list)) : output = dD(x) else : output = dD( ( v1, list(v2), v3 ) ) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if flag : print (' Input not recognized.') return None </syntaxhighlight> ===checkComplex(x)=== This function verifies that the object is a valid complex tuple. <syntaxhighlight lang=python> def checkComplex(x, flag = 0) : """ status = checkComplex(x [, flag]) x must be : (v1,v2,'rectangular') or (v1,v2,'polar') v1,v2 must be type Decimal. """ thisName = 'checkComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) try: error = '' v1,v2,str1 = x isinstance (v1,dD) or ({}['v1 must be type Decimal.']) isinstance (v2,dD) or ({}['v2 must be type Decimal.']) (isinstance (str1,str) and str1) or ({}['str1 must be valid string.']) str1 = str1.lower() if str1 == 'rectangular'[:len(str1)] : pass elif str1 == 'polar'[:len(str1)] : pass else : ({}['str1 must be "rectangular" or "polar".']) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return False return True </syntaxhighlight> ===str_to_complex (input_string)=== <syntaxhighlight lang=python> import re # The re pattern for numbers to be found in string of type complex. # In string like ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' # extracts '1234567890987654323456E-6' and '+987654321234567890987e+2J'. # eval allows ' 12_3456_7890_9876_5432_3456E-6 + 987654321234567890987e+2J '. # Conversion to Decimal allows: '__987_65432123____4567890_987___'. # eval does not allow ' 0123 ' but allows ' 2e04 '. # Conversion to Decimal allows: ' 0123 ' digits = '[_0123456789]' integer = '[_0123456789]{1,}' # Matches 1 23 345 4567 56789 exponent = '[Ee][\+\-]{{0,1}}{}'.format(integer) # Matches e8 e+8 e-8 or E8 E+8 E-8 Exponent = '({}){{0,1}}'.format(exponent) # exponent 0 or 1 times. float1 = '({})\.{{0,1}}'.format(integer) # Matches 123 2345. float2 = '{}{{0,}}\.{}'.format(digits, integer) # Matches 123.345 .345 float_ = '(({})|({}))'.format(float2,float1) rvalue = '{}({})'.format(float_,Exponent) rvalue_signed = '[\+\-]{{0,1}}{}'.format(rvalue) ivalue_signed = '{}[Jj]'.format(rvalue_signed) def str_to_complex (input_string) : """ a,b = str_to_complex (input_string) input_string could be ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' input_string could be ' ' ' ( 12345678909876543234561234567890987.654323456E-6 + 987654321234567890987987654321.23764567890987e+2J ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + # Note the '_' 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or '4', '-4', '(4)', '(-4)', '-(4)', '-(-4)' or '( +3j)', '+(-3J)', '-(3j)', '-(-3J)' or '( 4+3j)', '+(-3 + 4J)','-( 4+3j)', '-(-3 + 4J)', This function retains precision of a,b """ try : status = 0 isinstance(input_string,str) or ({}['input_string not type str.']) str1 = input_string.strip() cx1 = eval(str1) isinstance(cx1,(int,float,complex)) or ({}['cx1 not desired type.']) except : status = 1 if status : return # This code removes white lines and comments, if any, at end of each line. new_line = ''' '''[-1:] lines = [ line for Line in str1.split(new_line) for line in [ Line.rstrip() ] if line ] lines = [ v for line in lines for parts in [ line.split('#') ] for v in [ parts[0]] ] str1 = ''.join(lines) str1 = ''.join(str1.split()) if isinstance (cx1, (int,float)) : resultr = re.search(rvalue_signed, str1) resultr or ({}['rvalue not found.']) dD1 = dD(resultr[0]) v1 = eval(str(dD1)) if v1 == cx1 : return dD1,dD(0) if v1 == -cx1 : return -dD1,dD(0) ({}['dD1 not recognized.']) # cx1 must be complex. It must contain imaginary value. resulti = re.search(ivalue_signed, str1) resulti or ({}['ivalue not found.']) str2j = resulti[0] ; str2 = str2j[:-1] dD2 = dD(str2) str1 = ''.join(str1.split(str2j)) # cx1 may contain real value. resultr = re.search(rvalue_signed, str1) if resultr : dD1 = dD(resultr[0]) else : dD1 = dD(0) cx2 = complex(dD1,dD2) if cx2.real == cx1.real : pass elif cx2.real == -cx1.real : dD1 = dD1.copy_negate() else : ({}['dD1 Not Recognized.']) if cx2.imag == cx1.imag : pass elif cx2.imag == -cx1.imag : dD2 = dD2.copy_negate() else : ({}['dD2 Not Recognized.']) cx3 = complex(dD1, dD2) if cx3 == cx1 : return dD1,dD2 ({}['No match for cx3.']) </syntaxhighlight> ===makeComplex(x)=== <syntaxhighlight lang=python> def makeComplex (x, flag = 0) : ''' result = makeComplex (x[, flag]) Input can be tuple with 1,2 or 3 members. If 1 or 2 members, 'rect' is understood. The one member or single object may be int, float, complex, CompleX or string convertible to int, float or complex. x = makeComplex(4) x = makeComplex((4,)) x = makeComplex(('4',0)) x = makeComplex((4,'0', 'rect')) x = makeComplex(4+0j) x = makeComplex('4+0j') x = makeComplex(('4+0j',)) In all seven cases above x = ( Decimal('4'), Decimal('0'), 'rect' ) output is always (modulus, phase, "polar") or (real_part, imag_part, "rect") modulus, phase, real_part, imag_part are Decimal objects. On error returns None. ''' thisName = 'makeComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, CompleX) : # New class CompleX (note the punctuation.) x.check() return (x.r, x.i, 'rect') if isinstance (x,complex) : return makeComplex (( x.real, x.imag )) try : status = 1 a,b = str_to_complex (x) except : status = 0 if status : return a,b,'rect' try : status = 1 result = makeDecimal(x) isinstance(result, Decimal) or ({}['Expecting result to be type Decimal.']) output = result,dD(0),'rect' except : status = 0 if status : return output try : status = 1 v1, = x # Allow for (( 3+4j ),) except : status = 0 if status : return makeComplex (v1) try : status = 1 ; error = '' if len(x) == 2 : v1,v2 = [ makeDecimal (v) for v in x ] str1 = 'rect' elif len(x) == 3 : v1,v2,str1 = x v1,v2 = [ makeDecimal (v) for v in (v1,v2) ] else : ({}['len(x) not in (2,3)']) output = v1,v2,str1 checkComplex(output) or ({}['output not valid complex.']) if str1[0] in 'rR' : output = v1,v2,'rect' else : output = v1,v2,'polar' except : status = 0 ; error = str(sys.exc_info()) if status : return output if flag : print_error (error) return </syntaxhighlight> =Conic sections generally= Within the two dimensional space of Cartesian Coordinate Geometry a conic section may be located anywhere and have any orientation. This section examines the parabola, ellipse and hyperbola, showing how to calculate the equation of the section, and also how to calculate the foci and directrices given the equation. ==Latera recta et cetera== "Latus rectum" is a Latin expression meaning "straight side." According to Google, the Latin plural of "latus rectum" is "latera recta," but English allows "latus rectums" or possibly "lati rectums." The title of this section is poetry to the eyes and music to the ears of a Latin student and this author hopes that the gentle reader will permit such poetic licence in a mathematical topic. The translation of the title is "Latus rectums and other things." This section describes the calculation of interesting items associated with the ellipse: latus rectums, major axis, minor axis, focal chords, directrices and various points on these lines. When given the equation of an ellipse, the first thing is to calculate eccentricity, foci and directrices as shown above. Then verify that the curve is in fact an ellipse. From these values everything about the ellipse may be calculated. For example: {{RoundBoxTop|theme=2}} [[File:0608ellipse01.png|thumb|400px|'''Graph of ellipse <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math>''' </br> </br> Axis : (-0.8)x + (-0.6)y + (9.4) = 0</br> Eccentricity = 0.9</br> </br> Directrix 2 : (0.6)x + (-0.8)y + (2) = 0</br> Latus rectum RS : (0.6)x + (-0.8)y + (-0.8) = 0</br> Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0</br> Latus rectum PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0</br> Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0</br> </br> <math>\text{ID2}</math> = (6.32, 7.24)</br> <math>\text{I2}</math> = (7.204210526315789473684, 6.061052631578947368421)</br> F2 = (8, 5)</br> M = (15.16210526315789473684, -4.54947368421052631579)</br> F1 = (22.32421052631578947368, -14.09894736842105263158)</br> <math>\text{I1}</math> = (23.12, -15.16)</br> <math>\text{ID1}</math> = (24.00421052631578947368, -16.33894736842105263158)</br> </br> P = (20.30821052631578947368, -15.61094736842105263158)</br> Q = (10.53708406832736953616, -8.018239580333420216299)</br> R = (5.984, 3.488)</br> S = (10.016, 6.512)</br> T = (19.78712645798841993752, -1.080707788087632415281)</br> U = (24.34021052631578947368, -12.58694736842105263158)</br> </br> Length of major axis: <math>\text{I1I2}</math> = 26.52631578947368421052</br> Length of minor axis: QT = 11.56255298707631300170</br> Length of latus rectum: RS = PU = 5.04 ]] Consider conic section: <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math> This curve is ellipse with random orientation. <syntaxhighlight lang=python> # python code ABCDEF = A,B,C,D,E,F = 1771, 1204, 1944, -44860, -18520, 214400 # ellipse result = calculate_abc_epq(ABCDEF) (len(result) == 2) or 1/0 # ellipse or hyperbola (abc1,epq1), (abc2,epq2) = result a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 (e1 == e2) or 2/0 (1 > e1 > 0) or 3/0 print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) A,B,C,D,E,F = ABCDEF_from_abc_epq(abc1,epq1) print ('Equation of ellipse in standard form:') print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) </syntaxhighlight> <syntaxhighlight> (1771)x^2 + (1204)y^2 + (1944)xy + (-44860)x + (-18520)y + (214400) = 0 Equation of ellipse in standard form: (-0.7084)x^2 + (-0.4816)y^2 + (-0.7776)xy + (17.944)x + (7.408)y + (-85.76) = 0 </syntaxhighlight> <syntaxhighlight lang=python> # python code def sum_zero(input) : ''' sum = sum_zero(input) If sum is close to 0 and Tolerance permits, sum is returned as 0. For example: if input contains (2, -1.999999999999999999999) this function returns sum of these 2 values as 0. ''' global Tolerance sump = sumn = 0 for v in input : if v > 0 : sump += v elif v < 0 : sumn -= v sum = sump - sumn if abs(sum) < Tolerance : return (type(Tolerance))(0) min, max = sorted((sumn,sump)) if abs(sum) <= Tolerance*min : return (type(Tolerance))(0) return sum </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Major axis=== <syntaxhighlight lang=python> # axis is perpendicular to directrix. ax,bx = b1,-a1 # axis contains foci. ax + by + c = 0 cx = reduce_Decimal_number(-(ax*p1 + bx*q1)) axis = ax,bx,cx print ( ' Axis : ({})x + ({})y + ({}) = 0'.format(ax,bx,cx) ) print ( ' Eccentricity = {}'.format(e1) ) print () print ( ' Directrix 1 : ({})x + ({})y + ({}) = 0'.format(a1,b1,c1) ) print ( ' Directrix 2 : ({})x + ({})y + ({}) = 0'.format(a2,b2,c2) ) F1 = p1,q1 # Focus 1. print ( ' F1 : ({}, {})'.format(p1,q1) ) F2 = p2,q2 # Focus 2. print ( ' F2 : ({}, {})'.format(p2,q2) ) # Direction cosines along axis from F1 towards F2: dx,dy = a1,b1 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 if dx : distance_F1_F2 = (p2 - p1)/dx else : distance_F1_F2 = (q2 - q1) if distance_F1_F2 < 0 : distance_F1_F2 *= -1 dx *= -1 ; dy *= -1 # Intercept on directrix1 distance_from_F1_to_ID1 = abs(a1*p1 + b1*q1 + c1) ID1 = xID1,yID1 = p1 - dx*distance_from_F1_to_ID1, q1 - dy*distance_from_F1_to_ID1 print ( ' Intercept ID1 : ({}, {})'.format(xID1,yID1) ) # # distance_F1_F2 # -------------------- = e # length_of_major_axis # length_of_major_axis = distance_F1_F2 / e1 # Intercept1 on curve distance_from_F1_to_curve = (length_of_major_axis - distance_F1_F2 )/2 xI1,yI1 = p1 - dx*distance_from_F1_to_curve, q1 - dy*distance_from_F1_to_curve I1 = xI1,yI1 = [ reduce_Decimal_number(v) for v in (xI1,yI1) ] print ( ' Intercept I1 : ({}, {})'.format(xI1,yI1) ) </syntaxhighlight> <syntaxhighlight> Axis : (-0.8)x + (-0.6)y + (9.4) = 0 Eccentricity = 0.9 Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0 Directrix 2 : (0.6)x + (-0.8)y + (2) = 0 F1 : (22.32421052631578947368, -14.09894736842105263158) F2 : (8, 5) Intercept ID1 : (24.00421052631578947368, -16.33894736842105263158) Intercept I1 : (23.12, -15.16) </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>I2, ID2.</math> {{RoundBoxBottom}} ===Latus rectums=== <syntaxhighlight lang=python> # direction cosines along latus rectum. dlx,dly = -dy,dx # # distance from U to F1 half_latus_rectum # ------------------------------ = ----------------------- = e1 # distance from U to directrix 1 distance_from_F1_to_ID1 # half_latus_rectum = reduce_Decimal_number(e1*distance_from_F1_to_ID1) # latus rectum 1 # Focal chord has equation (afc)x + (bfc)y + (cfc) = 0. afc,bfc = a1,b1 cfc = reduce_Decimal_number(-(afc*p1 + bfc*q1)) print ( ' Focal chord PU : ({})x + ({})y + ({}) = 0'.format(afc,bfc,cfc) ) P = xP,yP = p1 + dlx*half_latus_rectum, q1 + dly*half_latus_rectum print ( ' Point P : ({}, {})'.format(xP,yP) ) U = xU,yU = p1 - dlx*half_latus_rectum, q1 - dly*half_latus_rectum print ( ' Point U : ({}, {})'.format(xU,yU) ) distance = reduce_Decimal_number(( (xP - xU)**2 + (yP - yU)**2 ).sqrt()) print (' Length PU =', distance) print (' half_latus_rectum =', half_latus_rectum) </syntaxhighlight> <syntaxhighlight> Focal chord PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0 Point P : (20.30821052631578947368, -15.61094736842105263158) Point U : (24.34021052631578947368, -12.58694736842105263158) Length PU = 5.04 half_latus_rectum = 2.52 </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>R, S.</math> {{RoundBoxBottom}} ===Minor axis=== <syntaxhighlight lang=python> print () # Mid point between F1, F2: M = xM,yM = (p1 + p2)/2, (q1 + q2)/2 print ( ' Mid point M : ({}, {})'.format(xM,yM) ) half_major = length_of_major_axis / 2 half_distance = distance_F1_F2 / 2 # half_distance**2 + half_minor**2 = half_major**2 half_minor = ( half_major**2 - half_distance**2 ).sqrt() length_of_minor_axis = half_minor * 2 Q = xQ,yQ = xM + dlx*half_minor, yM + dly*half_minor T = xT,yT = xM - dlx*half_minor, yM - dly*half_minor print ( ' Point Q : ({}, {})'.format(xQ,yQ) ) print ( ' Point T : ({}, {})'.format(xT,yT) ) print (' length_of_major_axis =', length_of_major_axis) print (' length_of_minor_axis =', length_of_minor_axis) # # A basic check. # length_of_minor_axis**2 = (length_of_major_axis**2)(1-e**2) # # length_of_minor_axis**2 # ----------------------- = 1-e**2 # length_of_major_axis**2 # # length_of_minor_axis**2 # ----------------------- + (e**2 - 1) = 0 # length_of_major_axis**2 # values = (length_of_minor_axis/length_of_major_axis)**2, e1**2 - 1 sum_zero(values) and 3/0 aM,bM = a1,b1 # Minor axis is parallel to directrix. cM = reduce_Decimal_number(-(aM*xM + bM*yM)) print ( ' Minor axis : ({})x + ({})y + ({}) = 0'.format(aM,bM,cM) ) </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> Mid point M : (15.16210526315789473684, -4.54947368421052631579) Point Q : (10.53708406832736953616, -8.018239580333420216299) Point T : (19.78712645798841993752, -1.080707788087632415281) length_of_major_axis = 26.52631578947368421052 length_of_minor_axis = 11.56255298707631300170 Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0 </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ===Checking=== {{RoundBoxTop|theme=2}} All interesting points have been calculated without using equations of any of the relevant lines. However, equations of relevant lines are very useful for testing, for example: * Check that points <math>ID2, I2, F2, M, F1, I1, ID1</math> are on axis. * Check that points <math>R, F2, S</math> are on latus rectum through <math>F2.</math> * Check that points <math>Q, M, T</math> are on minor axis through <math>M.</math> * Check that points <math>P, F1, U</math> are on latus rectum through <math>F1.</math> Test below checks that 8 points <math>I1, I2, P, Q, R, S, T, U</math> are on ellipse and satisfy eccentricity <math>e = 0.9.</math> <math></math> <math></math> {{RoundBoxBottom}} <syntaxhighlight lang=python> t1 = ( ('I1'), ('I2'), ('P'), ('Q'), ('R'), ('S'), ('T'), ('U'), ) for name in t1 : value = eval(name) x,y = [ reduce_Decimal_number(v) for v in value ] print ('{} : ({}, {})'.format((name+' ')[:2], x,y)) values = A*x**2, B*y**2, C*x*y, D*x, E*y, F sum_zero(values) and 3/0 # Relative to Directrix 1 and Focus 1: distance_to_F1 = ( (x-p1)**2 + (y-q1)**2 ).sqrt() distance_to_directrix1 = a1*x + b1*y + c1 e1 = distance_to_F1 / distance_to_directrix1 print (' e1 =',e1) # Raw value is printed. # Relative to Directrix 2 and Focus 2: distance_to_F2 = ( (x-p2)**2 + (y-q2)**2 ).sqrt() distance_to_directrix2 = a2*x + b2*y + c2 e2 = distance_to_F2 / distance_to_directrix2 e2 = reduce_Decimal_number(e2) print (' e2 =',e2) # Clean value is printed. </syntaxhighlight> {{RoundBoxTop|theme=2}} Note the differences between "raw" values of <math>e_1</math> and "clean" values of <math>e_2.</math> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> I1 : (23.12, -15.16) e1 = -0.9000000000000000000034 e2 = 0.9 I2 : (7.204210526315789473684, 6.061052631578947368421) e1 = -0.9 e2 = 0.9 P : (20.30821052631578947368, -15.61094736842105263158) e1 = -0.9 e2 = 0.9 Q : (10.53708406832736953616, -8.018239580333420216299) e1 = -0.9000000000000000000002 e2 = 0.9 R : (5.984, 3.488) e1 = -0.9000000000000000000003 e2 = 0.9 S : (10.016, 6.512) e1 = -0.9000000000000000000003 e2 = 0.9 T : (19.78712645798841993752, -1.080707788087632415281) e1 = -0.8999999999999999999996 e2 = 0.9 U : (24.34021052631578947368, -12.58694736842105263158) e1 = -0.9 e2 = 0.9 </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> ==Traditional definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0617ellipse01.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. ]] Ellipse may be defined as the locus of a point that moves so that the sum of its distances from two fixed points is constant. In the diagram the two fixed points are the foci, Focus 1 or <math>F_1</math> and Focus 2 or <math>F_2.</math> Distance between <math>F_1</math> and <math>F_2</math>, distance <math>F_1F_2</math>, must be non-zero. Point <math>G</math> on perimeter of ellipse moves so that sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. Points <math>T_1</math> and <math>T_2</math> are on axis of ellipse and the same rule applies to these points. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> is constant. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> <math>=</math> distance <math>F_1G</math> + distance <math>F_2G</math> <math>=</math> distance <math>F_2T_2</math> + distance <math>T_1F_2</math> <math>= \text{length of major axis.}</math> Therefore the constant is <math>\text{length of major axis}</math> which must be greater than distance <math>F_1F_2.</math> From information given, calculate eccentricity <math>e</math> and equation of one directrix. Choose directrix 1 <math>dx1</math> associated with focus F1. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> {{RoundBoxBottom}} ==Ellipse at origin== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1P</math> and distance <math>F_2P</math> is constant. ]] Traditional definition of ellipse states that ellipse is locus of a point that moves so that sum of its distances from two fixed points is constant. By definition distance <math>F_2P</math> + distance <math>F_1P</math> is constant. <math>\sqrt{(x-(-p))^2 + y^2} + \sqrt{(x-p)^2 + y^2} = k\ \dots\ (1)</math> Expand <math>(1)</math> and result is <math>Ax^2 + By^2 + F = 0\ \dots\ (2)</math> where: <math>A = 4k^2 - 16p^2</math> <math>B = 4k^2</math> <math>F = 4k^2p^2 - k^4</math> When <math>y = 0,</math> point <math>B,\ Ax^2 = -F</math> <math>x^2 = \frac{-F}{A}</math> <math>= \frac{k^4 - 4k^2p^2}{4k^2 - 16p^2}</math> <math>=\frac{k^2(k^2-4p^2)}{4(k^2 - 4p^2)} = \frac{k^2}{4}.</math> Therefore: <math>x = \frac{k}{2} = a</math> <math>k = \text{length of major axis.}</math> By definition, distance <math>F_2A</math> + distance <math>F_1A = k.</math> Therefore distance <math>F_1A = a.</math> Intercept form of ellipse at origin: <math>(4k^2 - 16p^2)x^2 + (4k^2)y^2 = k^4 - 4k^2p^2</math> <math>\frac{4(k^2-4p^2)}{k^2(k^2-4p^2)}x^2 + \frac{4k^2}{k^2(k^2 - 4p^2)}y^2 = 1</math> <math>\frac{4}{(2a)^2}x^2 + \frac{4}{(2a)^2 - 4p^2}y^2 = 1</math> <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> <math></math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Second definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Graph of ellipse <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where <math>a,b = 20,12</math>.''' </br> At point <math>B,\ \frac{u}{v} = e.</math> </br> At point <math>A,\ \frac{a}{t} = e.</math> ]] Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. Let <math>\frac{p}{a} = e</math> where: * <math>p</math> is non-zero, * <math>a > p,</math> * <math>a = p + u.</math> Therefore, <math>1 > e > 0.</math> Let directrix have equation <math>x = t</math> where <math>\frac{a}{t} = e.</math> At point <math>B:</math> <math>\frac{p}{p+u} = \frac{p+u}{p+u+v} = e</math> <math>(p+u)^2 = p(p+u+v)</math> <math>pp + pu + pu + uu = pp + pu + pv</math> <math>pu + uu = pv</math> <math>u(p + u) = pv</math> <math>\frac{u}{v} = \frac{p}{p+u} = e</math> <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e\ \dots\ (3)</math> Statement <math>(3)</math> is true at point <math>A</math> also. Section under "Proof" below proves that statement (3) is true for any point <math>P</math> on ellipse. {{RoundBoxBottom}} ===Proof=== {{RoundBoxTop|theme=2}} [[File:0902ellipse00.png|thumb|400px|'''Proving that <math>\frac{\text{distance from point to focus}}{\text{distance from point to directrix}} = e</math>.''' </br> Graph is part of curve <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1.</math> </br> distance to Directrix1 <math>= t - x = \frac{a}{e} - x = \frac{a - ex}{e}.</math> </br> base = <math>x - p = x - ae</math> </br> <math>\text{(distance to Focus1)}^2 = \text{base}^2 + y^2</math> ]] As expressed above in statement <math>3,</math> second definition of ellipse states that ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. This section proves that this definition is true for any point <math>P</math> on the ellipse. At point <math>P:</math> <math>(a^2 - p^2)x^2 + a^2y^2 -a^2(a^2 - p^2) = 0</math> <math>y^2 = \frac{-(a^2 - p^2)x^2 + a^2(a^2 - p^2)}{a^2}</math> <math>= \frac{a^2e^2x^2 - a^2x^2 + a^2a^2 - a^2a^2e^2}{a^2}</math> <math>= e^2x^2 - x^2 + a^2 - a^2e^2</math> base <math>= x-p = x-ae</math> <math>(\text{distance}\ F_1P)^2 = y^2 + \text{base}^2 = y^2 + (x-ae)^2</math> <math>= a^2 - 2aex + e^2x^2</math> <math>= (a-ex)^2</math> <math>\text{distance to Focus1} = \text{distance}\ F_1P = a - ex</math> <math>\text{distance to Directrix1} = t - x = \frac{a}{e} - x = \frac{a-ex}{e}</math> <math>\frac{\text{distance to Focus1}}{\text{distance to Directrix1}}</math> <math>= (a - ex)\frac{e}{(a-ex)}</math> <math>= e</math> Similar calculations can be used to prove the case for Focus2 <math>(-p, 0)</math> and Directrix2 <math>(x = -t)</math> in which case: <math>\frac{\text{distance to Focus2}}{\text{distance to Directrix2}}</math> <math>= (a + ex)\frac{e}{(a + ex)}</math> <math>= e</math> Therefore: <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e</math> where <math>1 > e > 0.</math> Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant, called eccentricity <math>e.</math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Heading== ===Properties of ellipse=== {{RoundBoxTop|theme=2}} [[File:0822ellipse01.png|thumb|400px|'''Graph of ellipse used to illustrate and calculate certain properties of ellipses.''' </br> </br> Traditional definition of ellipse: </br> <math>\text{distance } AF_1 + \text{distance } AF_2 = \text{constant } k.</math> </br> </br> Second definition of ellipse: </br> <math>\frac{\text{distance } AF_1} {\text{distance } AG } = \text{eccentricity } e.</math> </br> </br> Triangle <math>A F_1 G</math> is right triangle. </br> <math>e = \cos \angle O F_1 A = \cos \angle F_1 A G</math> ]] Ellipse in diagram has: * Two foci: <math>F_1\ (p,0),\ F_2\ (-p,0).</math> * Length of major axis <math>= \text{distance } I_2 I_1 = 2a</math> * Length of minor axis <math>= \text{distance } A B = 2b</math> * Equation: <math>\frac {x^2} {a^2} + \frac {y^2} {b^2} = 1</math> * Length of latus rectum <math>= \text{distance } P Q</math> * Distance between directrices <math>= \text{distance } D_2 D_1 = 2t</math> Properties of ellipse: * <math>\frac{\text{length of major axis}} {\text{distance between directrices}} = e</math> * <math>\frac{\text{distance between foci}} {\text{length of major axis}} = e</math> * <math>\frac{\text{distance between foci}} {\text{distance between directrices}}= e^2</math> * <math>(\frac{\text{length of minor axis}} {\text{length of major axis}})^2 + e^2 = 1</math> * <math>\frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> * line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ====Major axis==== From traditional definition of ellipse: Distance <math>AF_2\ +</math> distance <math>AF_1</math> = distance <math>I_1F_1\ +</math> distance <math>I_1F_2</math> = distance <math>I_2F_2\ +</math> distance <math>I_2F_1</math> = <math>k.</math> Therefore: Length of major axis = distance <math>I_2I_1 = 2a = k.</math> Distance <math>AF_1 = \frac{k}{2} = a.</math> From second definition of ellipse: <math>\frac{\text{distance }AF_1}{\text{distance }AG} = \frac{a}{t} = \text{eccentricity }e</math> <math>= \frac{\text{distance }OI_1}{\text{distance }OD_1}.</math> <math>\frac{\text{length of major axis}}{\text{distance between directrices}} = e.</math> ====Foci==== From second definition of ellipse: <math>\frac{\text{distance }I_1F_1}{\text{distance }I_1D_1} = \frac{a-p}{t-a} = e.</math> <math>a - p = te - ae</math> <math>a - p = a - ae</math> Therefore: <math>p = ae</math> or <math>\frac{p}{a} = e.</math> <math>\frac{\text{distance between foci}}{\text{length of major axis}} = e.</math> <math>\frac{\text{distance between foci}}{\text{distance between directrices}} = e^2.</math> ====Minor axis==== Triangle <math>AOF_1</math> is right triangle. <math>\cos ^2 \angle OAF_1 + \sin ^2 \angle OAF_1</math> <math>= (\frac{b}{a})^2 + (\frac{p}{a})^2 </math> <math>= (\frac{b}{a})^2 + (\frac{ae}{a})^2 </math> <math>= (\frac{b}{a})^2 + e^2 = 1</math> <math>( \frac{\text{length of minor axis}} {\text{length of major axis}} )^2 + e^2 = 1</math> Triangles <math>AOF_1,\ AF_1G</math> are similar. Triangle <math>AF_1G</math> is right triangle. <math>e = \cos \angle OF_1A = \cos \angle F_1AG.</math> ====Latus rectum==== From second definition of ellipse: <math>\frac{\text{distance }PF_1} {\text{distance }F_1D_1} = \frac{\text{distance }PF_1}{t-p} = e</math> <math>\text{distance }PF_1 = te - pe = a - (ae)e = a(1-e^2).</math> <math>\frac{\text{distance }PF_1} {a} = 1 - e^2.</math> <math> \frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> ====Slope of curve==== Curve has equation: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math><math></math> <math>= \frac{-x(1-e^2)}{y}</math><math></math> At point <math>P:\ m_1 = y' = \frac{-p(1-e^2)}{-a(1-e^2)}</math> <math>= \frac{ae}{a} = e.</math><math></math> Slope of line <math>PD_1:\ m_2 = \frac{\text{distance }PF_1}{\text{distance }F_1D_1} = e.</math><math></math><math></math> <math>m_1 = m_2.</math> Therefore line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> ===Intercept form of equation=== <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1</math> <math></math> <math></math> {{RoundBoxTop|theme=2}} [[File:0625ellipse01.png|thumb|400px|'''Ellipse at origin with major axis on X axis.''' </br> </br> </br> </br> Equation of ellipse has format <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where: </br> </br> <math>\text{Length of major axis} = 2a = \text{distance}\ I_2I_1 = 40</math> </br> <math>\text{Length of minor axis} = 2b = \text{distance}\ BA = 24</math> </br> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> </br> <math>\frac{\text{Length of minor axis}}{\text{Length of major axis}} = \sqrt{1 - e^2}</math> </br> </br> <math>e = \sqrt{1 - \frac{b^2}{a^2}} = 0.8.</math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> ]] In diagram: Intercept <math>I_1</math> has coordinates <math>(a,0).</math> Intercept <math>I_2</math> has coordinates <math>(-a,0).</math> Intercept <math>A</math> has coordinates <math>(0,b).</math> Intercept <math>B</math> has coordinates <math>(0,-b).</math> Focus <math>F_1</math> has coordinates <math>(f,0)</math> where <math>f = ea.</math> Focus <math>F_2</math> has coordinates <math>(-f,0).</math> Curve has equation <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1,</math> called intercept form of equation of ellipse because intercepts are apparent as the fractional value of each coefficient. Standard form of this equation is: <math>(-0.36)x^2 + (-1)y^2 + (0)xy + (0)x + (0)y + (144) = 0.</math> While the standard form is valuable as input to a computer program, the intercept form is still attractive to the human eye because center of ellipse and intercepts are neatly contained within the equation. Slope of curve: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math> <math>= \frac{-x(1-e^2)}{y}</math> At point <math>P</math> on latus rectum <math>PQ:</math> <math>m_1 = y' = \frac{-(ea)(1-e^2)}{-(a(1-e^2))} = e</math> Slope of line <math>PD = m_2 = \frac{PF_1}{F_1D} = e</math> <math>m_1 = m_2.</math> Line <math>PD</math> is tangent to curve at latus rectum, point <math>P.</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Example=== {{RoundBoxTop|theme=2}} [[File:0618ellipse01.png|thumb|400px|'''Traditional definition of ellipse uses abc, epq.''' </br> M is mid-point between F1 and F2. </br> Point R is on minor axis. </br> </br> <math>\frac{\text{distance from R to F1}}{\text{distance from R to directrix 1}}</math> <math>= e</math> </br> </br> <math>= \frac{\text{half major axis}}{\text{distance from M to directrix 1}}</math> </br> </br> <math>\text{distance from M to directrix 1} = \frac{\text{half major axis}}{e}</math> </br> </br> <math>\text{F1:}\ (1, -7)</math> </br> <math>\text{F2:}\ (-1.24, 0.68)</math> </br> length_of_major_axis = 10 </br> <math>\text{M:}\ (-0.12, -3.16)</math> </br> length_of_minor_axis = 6 </br> <math>\text{R:}\ (2.76, -2.32)</math> </br> <math>e = 0.8</math> </br> <math>\text{D1:}\ (1.63, -9.16)</math> </br> <math>\text{Directrix 1:}\ (-0.28)x + (0.96)y + (9.25) = 0</math> </br> <math>\text{abc}\ =\ (-0.28,\ 0.96,\ 9.25)</math> </br> <math>\text{epq}\ =\ (0.8,\ 1,\ -7)</math> ]] Given: <syntaxhighlight lang=python> # python code F1 = 1, -7 # Focus 1 F2 = -1.24, 0.68 # Focus 2 length_of_major_axis = 10 </syntaxhighlight> Calculate equation of ellipse. <syntaxhighlight lang=python> F1 = p1,q1 = [ dD(str(v)) for v in F1 ] # Focus 1 F2 = p2,q2 = [ dD(str(v)) for v in F2 ] # Focus 2 length_of_major_axis = dD(length_of_major_axis) half_major_axis = length_of_major_axis / 2 # Direction cosines from F1 to F2 dx = p2-p1 ; dy = q2-q1 divider = (dx**2 + dy**2).sqrt() dx,dy = [ (v/divider) for v in (dx,dy) ] # F2 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 distance_F1_F2 = (q2-q1)/dy half_distance_F1_F2 = distance_F1_F2 / 2 # The mid-point M = xM,ym = p1 + dx*half_distance_F1_F2, q1 + dy*half_distance_F1_F2 # Eccentricity: e = distance_F1_F2 / length_of_major_axis # distance from point R to F1 half_major_axis # ------------------------------------ = e = ----------------------------------------- # distance from point R to Directrix 1 distance from point M to Directrix 1 distance_from_point_M_to_dx1 = half_major_axis / e # Intersection of axis and directrix 1 D1 = xM-dx*distance_from_point_M_to_dx1, yM-dy*distance_from_point_M_to_dx1 D1 = xD1, yD1 = [ reduce_Decimal_number(v) for v in D1 ] # Equation of Directrix 1 # dx1 = adx1,bdx1,cdx1 adx1,bdx1 = dx, dy # Perpendicular to axis. # adx1*x + bdx1*y + cdx1 = 0 # Directrix 1 contains point D1 cdx1 = reduce_Decimal_number( -( adx1*xD1 + bdx1*yD1 ) ) abc = adx1,bdx1,cdx1 epq = e,p1,q1 ABCDEF = ABCDEF_from_abc_epq (abc,epq, 1) </syntaxhighlight> Equation of ellipse in standard form: <math>(-0.949824)x^2 + (-0.410176)y^2 + (-0.344064)xy + (-1.3152)x + (-2.6336)y + (4.76) = 0</math> For more insight into method of calculation and proof: <syntaxhighlight lang=python> if 1 : print ('F1: ({}, {})'.format(p1,q1)) print ('F1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p1,q1)) print ('F2: ({}, {})'.format(p2,q2)) print ('F2: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p2,q2)) print ('length_of_major_axis =', length_of_major_axis) print ('M: ({}, {})'.format(xM,yM)) print ('M: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xM,yM)) # half_minor_axis**2 + half_distance_F1_F2**2 = half_major_axis**2 half_minor_axis = (half_major_axis**2 - half_distance_F1_F2**2).sqrt() length_of_minor_axis = half_minor_axis * 2 s1 = 'length_of_minor_axis' ; print (s1, '=', eval(s1)) # Direction cosines on major axis: print ('dx,dy =', dx,dy) # Direction cosines on minor axis: dnx,dny = dy,-dx print ('dnx,dny =', dnx,dny) # One point on minor axis: R = xR,yR = xM + dnx*half_minor_axis, yM + dny*half_minor_axis print ('R: ({}, {})'.format(xR,yR)) print ('R: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xR,yR)) # Verify that point R is on ellipse: sum_zero((A*xR**2, B*yR**2, C*xR*yR, D*xR, E*yR, F)) and 1/0 s1 = 'e' ; print (s1, '=', eval(s1)) print ('D1: ({}, {})'.format(xD1,yD1)) print ('D1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xD1,yD1)) print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(adx1, bdx1, cdx1)) print() # For proof, reverse the process: (abc1,epq1), (abc2,epq2) = calculate_abc_epq (ABCDEF) a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(a1, b1, c1)) print ('Eccentricity e1: {}'.format(e1)) print ('F1: ({}, {})'.format(p1,q1)) print() a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 print ('Directrix 2: ({})x + ({})y + ({}) = 0'.format(a2, b2, c2)) print ('Eccentricity e2: {}'.format(e2)) print ('F2: ({}, {})'.format(p2,q2)) print ('\nEquation of ellipse with integer coefficients:') A,B,C,D,E,F = [ reduce_Decimal_number(-v*1000000/64) for v in ABCDEF ] str1 = '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0' print (str1.format(A,B,C,D,E,F)) </syntaxhighlight> <syntaxhighlight> F1: (1, -7) F1: (x - (1))^2 + (y - (-7))^2 = 1 F2: (-1.24, 0.68) F2: (x - (-1.24))^2 + (y - (0.68))^2 = 1 length_of_major_axis = 10 M: (-0.12, -3.16) M: (x - (-0.12))^2 + (y - (-3.16))^2 = 1 length_of_minor_axis = 6 dx,dy = -0.28 0.96 dnx,dny = 0.96 0.28 R: (2.76, -2.32) R: (x - (2.76))^2 + (y - (-2.32))^2 = 1 e = 0.8 D1: (1.63, -9.16) D1: (x - (1.63))^2 + (y - (-9.16))^2 = 1 Directrix 1: (-0.28)x + (0.96)y + (9.25) = 0 Directrix 1: (0.28)x + (-0.96)y + (-9.25) = 0 Eccentricity e1: 0.8 F1: (1, -7) Directrix 2: (0.28)x + (-0.96)y + (3.25) = 0 Eccentricity e2: 0.8 F2: (-1.24, 0.68) Equation of ellipse with integer coefficients: </syntaxhighlight> <math>(14841)x^2 + (6409)y^2 + (5376)xy + (20550)x + (41150)y + (-74375) = 0</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} =allEqual= {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; 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We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> =====Welcomen===== {{Robelbox|title=|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFFFFF; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> <syntaxhighlight lang=python> # python code. if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 : pass </syntaxhighlight> {{Robelbox/close}} {{Robelbox/close}} {{Robelbox/close}} <noinclude> [[Category: main page templates]] </noinclude> {| class="wikitable" |- ! <math>x</math> !! <math>x^2 - N</math> |- | <code></code><code>6</code> || <code>-221</code> |- | <code></code><code>7</code> || <code>-208</code> |- |- | <code>10</code> || <code>-157</code> |- | <code>11</code> || <code>-136</code> |- | <code>12</code> || <code>-113</code> |- | <code>13</code> || <code></code><code>-88</code> |- | <code>26</code> || <code></code><code>419</code> |} =Testing= ======table1====== {|style="border-left:solid 3px blue;border-right:solid 3px blue;border-top:solid 3px blue;border-bottom:solid 3px blue;" align="center" | Hello As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 </syntaxhighlight> |} {{RoundBoxTop|theme=2}} [[File:0410cubic01.png|thumb|400px|''' Graph of cubic function with coefficient a negative.''' </br> There is no absolute maximum or absolute minimum. ]] Coefficient <math>a</math> may be negative as shown in diagram. As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. Unless stated otherwise, any reference to "cubic function" on this page will assume coefficient <math>a</math> positive. {{RoundBoxBottom}} <math>x_{poi} = -1</math> <math></math> <math></math> <math></math> <math></math> =====Various planes in 3 dimensions===== {{RoundBoxTop|theme=2}} <gallery> File:0713x=4.png|<small>plane x=4.</small> File:0713y=3.png|<small>plane y=3.</small> File:0713z=-2.png|<small>plane z=-2.</small> </gallery> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 6872533965463318088296406206152583523950547457502877599617298355752203375318570113543746034084988471 6038689997069900481503054402779031645424782306849293691862158057846311159666871301301561856898723723 5288509264861249497715421833420428568606014682472077143585487415565706967765372022648544701585880162 0758474922657226002085584466521458398893944370926591800311388246468157082630100594858704003186480342 1948972782906410450726368813137398552561173220402450912277002269411275736272804957381089675040183698 6836845072579936472906076299694138047565482372899718032680247442062926912485905218100445984215059112 0249441341728531478105803603371077309182869314710171111683916581726889419758716582152128229518488472 </syntaxhighlight> <math>\theta_1</math> {{RoundBoxTop|theme=2}} [[File:0422xx_x_2.png|thumb|400px|''' Figure 1: Diagram illustrating relationship between <math>f(x) = x^2 - x - 2</math> and <math>f'(x) = 2x - 1.</math>''' </br> ]] {{RoundBoxBottom}} <math>O\ (0,0,0)</math> <math>M\ (A_1,B_1,C_1)</math> <math>N\ (A_2,B_2,C_2)</math> <math>\theta</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} (6) - (7),\ 4Apq + 2Bq =&\ 0\\ 2Ap + B =&\ 0\\ 2Ap =&\ - B\\ \\ p =&\ \frac{-B}{2A}\ \dots\ (8) \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} 1.&4141475869yugh\\ &2645er3423231sgdtrf\\ &dhcgfyrt45erwesd \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math> 4\sin 18^\circ = \sqrt{2(3 - \sqrt 5)} = \sqrt 5 - 1 </math> 4flvulncz4pebkbfng0qe1lx9kz7u3b 2835149 2835148 2026-09-30T10:05:44Z ThaniosAkro 2805358 /* Using Decimal numbers: */ 2835149 wikitext text/x-wiki ==Table== {| class="wikitable" |- | From <math>(3):</math> || <math>p^3</math>|| || <math>+Ap</math> || <math>+B</math>|| <math>= 0</math> || <math>\dots (5)</math> |- | From <math>(4):</math> || || <math>Cp^2</math>|| <math></math> || <math>+D</math>|| <math>= 0</math> || <math>\dots (6)</math> |- | <math>(5)*D</math> || <math>Dp^3</math>|| || <math>+DAp</math> || <math>+DB</math>|| <math>= 0</math> || <math>\dots (7)</math> |- | <math>(6)*B</math> || || <math>BCp^2</math>|| <math></math> || <math>+BD</math>|| <math>= 0</math> || <math>\dots (8)</math> |- | <math>(7)-(8)</math> || <math>Dp^3</math>||<math>-BCp^2</math> || <math>+DAp</math> || <math></math>|| <math>= 0</math> || <math>\dots (9)</math> |- | Simplify <math>(9)</math> || <math></math>||<math>Dp^2</math> || <math>-BCp</math> || <math>+DA</math>|| <math>= 0</math> || <math>\dots (10)</math> |- | <math>(6)*A</math> || || <math>ACp^2</math>|| <math></math> || <math>+AD</math>|| <math>= 0</math> || <math>\dots (11)</math> |- | <math>(10)-(11)</math> || <math></math>||<math>Dp^2-ACp^2</math> || <math>-BCp</math> || <math></math>|| <math>= 0</math> || <math>\dots (12)</math> |- | Simplify <math>(12)</math> || <math></math>|| || <math>Dp-ACp</math> || <math>-BC</math> || <math>= 0</math> || <math>\dots (13)</math> |} ====First result==== <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ====Calculate R==== <syntaxhighlight> </syntaxhighlight> Produce matrix corrected: <syntaxhighlight lang=python> print ('\nCreating new matrix with corrections:') matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> Circuit parameters: <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> =====Using floating point numbers:===== <syntaxhighlight lang=python> # python code: number_of_columns = 65 one = 1 ; Tolerance = 1e-14 # Following string is executable python code: exc_str1 = """ Values_of_R = [] for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = one i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) exec(exc_str_64ei) for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of tests =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR)) s1 = 'sum' ; print(s1,'=',eval(s1)) if not sum : print ('With Tolerance of {}, both minR and maxR are equal.'.format(Tolerance)) """ exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of tests = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 With Tolerance of 1e-14, both minR and maxR are equal. </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. =====Using Decimal numbers:===== With <code>enable_reduceRow</code> clear : <syntaxhighlight lang=python> enable_reduceRow = 0 Precision = dgt.prec = 60 Tolerance = dD('1e-' + str(Precision-3)) one = dD(1) try : exec(exc_str1) except : pass </syntaxhighlight> <syntaxhighlight> solveMbyN (input_, level = -52) : <class 'decimal.Overflow'> Overflow([<class 'decimal.Overflow'>]) Length of input = 12 input_[0] = [-inf, inf, -inf, inf, inf, -inf, inf, -inf, inf, -inf, -inf, inf, 0.0] input_[1] = [inf, -inf, -inf, -inf, -inf, inf, -inf, -inf, -inf, -inf, inf, -inf, 0.0] input_[2] = [-inf, inf, inf, inf, -inf, -inf, inf, inf, -inf, inf, inf, inf, 0.0] input_[3] = [inf, -inf, -inf, inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, 0.0] input_[4] = [620.0, 0.0, 0.0, 0.0, 290.0, -1200.0, 240.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[5] = [0.0, 630.0, 0.0, 0.0, 0.0, 240.0, -1110.0, 190.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[6] = [inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, -inf, inf, -inf, 0.0] input_[7] = [-inf, inf, inf, inf, inf, -inf, inf, inf, inf, inf, -inf, inf, 0.0] </syntaxhighlight> With <code>enable_reduceRow</code> set : <syntaxhighlight lang=python> enable_reduceRow = 1 exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of tests = 1664 minR = 723.928575988442547699732563335265663515838075102937503680560 maxR = 723.928575988442547699732563335265663515838075102937503680663 sum = 0 With Tolerance of 1E-57, both minR and maxR are equal. </syntaxhighlight> With tolerance of <math>1e-57</math> all values of resistance R = 723.928575988442547699732563335265663515838075102937503681. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math>\text{R}</math> is printed with precision of 60. ==Making the Decimal object== The following function verifies that we are working with Decimal objects. <syntaxhighlight lang=python> import sys import decimal getcontext = decimal.getcontext dD = D = Decimal = decimal.Decimal DT = decimal.DecimalTuple dgt = decimal.getcontext() dgt.prec = 50 def print_error (error, x=None, thisName=None) : """ Prints error derived from sys.exc_info(). """ list1 = error.split(',') v1 = ','.join(list1[1:-1]) if thisName : print (thisName) if x != None : print (' Input =', (str(x))[:60]) print (' ', list1[0]) print (' ', v1) print (' ', list1[-1]) def makeDecimal (x, flag = 0) : ''' output = makeDecimal (x [, flag]) x is a single object convertible to Decimal object. returns Decimal object or returns None on error. ''' thisName = 'makeDecimal (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, dD) : return x if isinstance(x, int) : return dD(x) if isinstance(x, float) : return dD(str(x)) if isinstance(x, str) : try : error = '' output = dD(x) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if isinstance(x, (list,tuple,DT)) : try : error = '' v1,v2,v3 = x if isinstance(v2, (tuple,list)) : output = dD(x) else : output = dD( ( v1, list(v2), v3 ) ) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if flag : print (' Input not recognized.') return None </syntaxhighlight> ===checkComplex(x)=== This function verifies that the object is a valid complex tuple. <syntaxhighlight lang=python> def checkComplex(x, flag = 0) : """ status = checkComplex(x [, flag]) x must be : (v1,v2,'rectangular') or (v1,v2,'polar') v1,v2 must be type Decimal. """ thisName = 'checkComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) try: error = '' v1,v2,str1 = x isinstance (v1,dD) or ({}['v1 must be type Decimal.']) isinstance (v2,dD) or ({}['v2 must be type Decimal.']) (isinstance (str1,str) and str1) or ({}['str1 must be valid string.']) str1 = str1.lower() if str1 == 'rectangular'[:len(str1)] : pass elif str1 == 'polar'[:len(str1)] : pass else : ({}['str1 must be "rectangular" or "polar".']) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return False return True </syntaxhighlight> ===str_to_complex (input_string)=== <syntaxhighlight lang=python> import re # The re pattern for numbers to be found in string of type complex. # In string like ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' # extracts '1234567890987654323456E-6' and '+987654321234567890987e+2J'. # eval allows ' 12_3456_7890_9876_5432_3456E-6 + 987654321234567890987e+2J '. # Conversion to Decimal allows: '__987_65432123____4567890_987___'. # eval does not allow ' 0123 ' but allows ' 2e04 '. # Conversion to Decimal allows: ' 0123 ' digits = '[_0123456789]' integer = '[_0123456789]{1,}' # Matches 1 23 345 4567 56789 exponent = '[Ee][\+\-]{{0,1}}{}'.format(integer) # Matches e8 e+8 e-8 or E8 E+8 E-8 Exponent = '({}){{0,1}}'.format(exponent) # exponent 0 or 1 times. float1 = '({})\.{{0,1}}'.format(integer) # Matches 123 2345. float2 = '{}{{0,}}\.{}'.format(digits, integer) # Matches 123.345 .345 float_ = '(({})|({}))'.format(float2,float1) rvalue = '{}({})'.format(float_,Exponent) rvalue_signed = '[\+\-]{{0,1}}{}'.format(rvalue) ivalue_signed = '{}[Jj]'.format(rvalue_signed) def str_to_complex (input_string) : """ a,b = str_to_complex (input_string) input_string could be ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' input_string could be ' ' ' ( 12345678909876543234561234567890987.654323456E-6 + 987654321234567890987987654321.23764567890987e+2J ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + # Note the '_' 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or '4', '-4', '(4)', '(-4)', '-(4)', '-(-4)' or '( +3j)', '+(-3J)', '-(3j)', '-(-3J)' or '( 4+3j)', '+(-3 + 4J)','-( 4+3j)', '-(-3 + 4J)', This function retains precision of a,b """ try : status = 0 isinstance(input_string,str) or ({}['input_string not type str.']) str1 = input_string.strip() cx1 = eval(str1) isinstance(cx1,(int,float,complex)) or ({}['cx1 not desired type.']) except : status = 1 if status : return # This code removes white lines and comments, if any, at end of each line. new_line = ''' '''[-1:] lines = [ line for Line in str1.split(new_line) for line in [ Line.rstrip() ] if line ] lines = [ v for line in lines for parts in [ line.split('#') ] for v in [ parts[0]] ] str1 = ''.join(lines) str1 = ''.join(str1.split()) if isinstance (cx1, (int,float)) : resultr = re.search(rvalue_signed, str1) resultr or ({}['rvalue not found.']) dD1 = dD(resultr[0]) v1 = eval(str(dD1)) if v1 == cx1 : return dD1,dD(0) if v1 == -cx1 : return -dD1,dD(0) ({}['dD1 not recognized.']) # cx1 must be complex. It must contain imaginary value. resulti = re.search(ivalue_signed, str1) resulti or ({}['ivalue not found.']) str2j = resulti[0] ; str2 = str2j[:-1] dD2 = dD(str2) str1 = ''.join(str1.split(str2j)) # cx1 may contain real value. resultr = re.search(rvalue_signed, str1) if resultr : dD1 = dD(resultr[0]) else : dD1 = dD(0) cx2 = complex(dD1,dD2) if cx2.real == cx1.real : pass elif cx2.real == -cx1.real : dD1 = dD1.copy_negate() else : ({}['dD1 Not Recognized.']) if cx2.imag == cx1.imag : pass elif cx2.imag == -cx1.imag : dD2 = dD2.copy_negate() else : ({}['dD2 Not Recognized.']) cx3 = complex(dD1, dD2) if cx3 == cx1 : return dD1,dD2 ({}['No match for cx3.']) </syntaxhighlight> ===makeComplex(x)=== <syntaxhighlight lang=python> def makeComplex (x, flag = 0) : ''' result = makeComplex (x[, flag]) Input can be tuple with 1,2 or 3 members. If 1 or 2 members, 'rect' is understood. The one member or single object may be int, float, complex, CompleX or string convertible to int, float or complex. x = makeComplex(4) x = makeComplex((4,)) x = makeComplex(('4',0)) x = makeComplex((4,'0', 'rect')) x = makeComplex(4+0j) x = makeComplex('4+0j') x = makeComplex(('4+0j',)) In all seven cases above x = ( Decimal('4'), Decimal('0'), 'rect' ) output is always (modulus, phase, "polar") or (real_part, imag_part, "rect") modulus, phase, real_part, imag_part are Decimal objects. On error returns None. ''' thisName = 'makeComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, CompleX) : # New class CompleX (note the punctuation.) x.check() return (x.r, x.i, 'rect') if isinstance (x,complex) : return makeComplex (( x.real, x.imag )) try : status = 1 a,b = str_to_complex (x) except : status = 0 if status : return a,b,'rect' try : status = 1 result = makeDecimal(x) isinstance(result, Decimal) or ({}['Expecting result to be type Decimal.']) output = result,dD(0),'rect' except : status = 0 if status : return output try : status = 1 v1, = x # Allow for (( 3+4j ),) except : status = 0 if status : return makeComplex (v1) try : status = 1 ; error = '' if len(x) == 2 : v1,v2 = [ makeDecimal (v) for v in x ] str1 = 'rect' elif len(x) == 3 : v1,v2,str1 = x v1,v2 = [ makeDecimal (v) for v in (v1,v2) ] else : ({}['len(x) not in (2,3)']) output = v1,v2,str1 checkComplex(output) or ({}['output not valid complex.']) if str1[0] in 'rR' : output = v1,v2,'rect' else : output = v1,v2,'polar' except : status = 0 ; error = str(sys.exc_info()) if status : return output if flag : print_error (error) return </syntaxhighlight> =Conic sections generally= Within the two dimensional space of Cartesian Coordinate Geometry a conic section may be located anywhere and have any orientation. This section examines the parabola, ellipse and hyperbola, showing how to calculate the equation of the section, and also how to calculate the foci and directrices given the equation. ==Latera recta et cetera== "Latus rectum" is a Latin expression meaning "straight side." According to Google, the Latin plural of "latus rectum" is "latera recta," but English allows "latus rectums" or possibly "lati rectums." The title of this section is poetry to the eyes and music to the ears of a Latin student and this author hopes that the gentle reader will permit such poetic licence in a mathematical topic. The translation of the title is "Latus rectums and other things." This section describes the calculation of interesting items associated with the ellipse: latus rectums, major axis, minor axis, focal chords, directrices and various points on these lines. When given the equation of an ellipse, the first thing is to calculate eccentricity, foci and directrices as shown above. Then verify that the curve is in fact an ellipse. From these values everything about the ellipse may be calculated. For example: {{RoundBoxTop|theme=2}} [[File:0608ellipse01.png|thumb|400px|'''Graph of ellipse <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math>''' </br> </br> Axis : (-0.8)x + (-0.6)y + (9.4) = 0</br> Eccentricity = 0.9</br> </br> Directrix 2 : (0.6)x + (-0.8)y + (2) = 0</br> Latus rectum RS : (0.6)x + (-0.8)y + (-0.8) = 0</br> Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0</br> Latus rectum PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0</br> Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0</br> </br> <math>\text{ID2}</math> = (6.32, 7.24)</br> <math>\text{I2}</math> = (7.204210526315789473684, 6.061052631578947368421)</br> F2 = (8, 5)</br> M = (15.16210526315789473684, -4.54947368421052631579)</br> F1 = (22.32421052631578947368, -14.09894736842105263158)</br> <math>\text{I1}</math> = (23.12, -15.16)</br> <math>\text{ID1}</math> = (24.00421052631578947368, -16.33894736842105263158)</br> </br> P = (20.30821052631578947368, -15.61094736842105263158)</br> Q = (10.53708406832736953616, -8.018239580333420216299)</br> R = (5.984, 3.488)</br> S = (10.016, 6.512)</br> T = (19.78712645798841993752, -1.080707788087632415281)</br> U = (24.34021052631578947368, -12.58694736842105263158)</br> </br> Length of major axis: <math>\text{I1I2}</math> = 26.52631578947368421052</br> Length of minor axis: QT = 11.56255298707631300170</br> Length of latus rectum: RS = PU = 5.04 ]] Consider conic section: <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math> This curve is ellipse with random orientation. <syntaxhighlight lang=python> # python code ABCDEF = A,B,C,D,E,F = 1771, 1204, 1944, -44860, -18520, 214400 # ellipse result = calculate_abc_epq(ABCDEF) (len(result) == 2) or 1/0 # ellipse or hyperbola (abc1,epq1), (abc2,epq2) = result a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 (e1 == e2) or 2/0 (1 > e1 > 0) or 3/0 print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) A,B,C,D,E,F = ABCDEF_from_abc_epq(abc1,epq1) print ('Equation of ellipse in standard form:') print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) </syntaxhighlight> <syntaxhighlight> (1771)x^2 + (1204)y^2 + (1944)xy + (-44860)x + (-18520)y + (214400) = 0 Equation of ellipse in standard form: (-0.7084)x^2 + (-0.4816)y^2 + (-0.7776)xy + (17.944)x + (7.408)y + (-85.76) = 0 </syntaxhighlight> <syntaxhighlight lang=python> # python code def sum_zero(input) : ''' sum = sum_zero(input) If sum is close to 0 and Tolerance permits, sum is returned as 0. For example: if input contains (2, -1.999999999999999999999) this function returns sum of these 2 values as 0. ''' global Tolerance sump = sumn = 0 for v in input : if v > 0 : sump += v elif v < 0 : sumn -= v sum = sump - sumn if abs(sum) < Tolerance : return (type(Tolerance))(0) min, max = sorted((sumn,sump)) if abs(sum) <= Tolerance*min : return (type(Tolerance))(0) return sum </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Major axis=== <syntaxhighlight lang=python> # axis is perpendicular to directrix. ax,bx = b1,-a1 # axis contains foci. ax + by + c = 0 cx = reduce_Decimal_number(-(ax*p1 + bx*q1)) axis = ax,bx,cx print ( ' Axis : ({})x + ({})y + ({}) = 0'.format(ax,bx,cx) ) print ( ' Eccentricity = {}'.format(e1) ) print () print ( ' Directrix 1 : ({})x + ({})y + ({}) = 0'.format(a1,b1,c1) ) print ( ' Directrix 2 : ({})x + ({})y + ({}) = 0'.format(a2,b2,c2) ) F1 = p1,q1 # Focus 1. print ( ' F1 : ({}, {})'.format(p1,q1) ) F2 = p2,q2 # Focus 2. print ( ' F2 : ({}, {})'.format(p2,q2) ) # Direction cosines along axis from F1 towards F2: dx,dy = a1,b1 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 if dx : distance_F1_F2 = (p2 - p1)/dx else : distance_F1_F2 = (q2 - q1) if distance_F1_F2 < 0 : distance_F1_F2 *= -1 dx *= -1 ; dy *= -1 # Intercept on directrix1 distance_from_F1_to_ID1 = abs(a1*p1 + b1*q1 + c1) ID1 = xID1,yID1 = p1 - dx*distance_from_F1_to_ID1, q1 - dy*distance_from_F1_to_ID1 print ( ' Intercept ID1 : ({}, {})'.format(xID1,yID1) ) # # distance_F1_F2 # -------------------- = e # length_of_major_axis # length_of_major_axis = distance_F1_F2 / e1 # Intercept1 on curve distance_from_F1_to_curve = (length_of_major_axis - distance_F1_F2 )/2 xI1,yI1 = p1 - dx*distance_from_F1_to_curve, q1 - dy*distance_from_F1_to_curve I1 = xI1,yI1 = [ reduce_Decimal_number(v) for v in (xI1,yI1) ] print ( ' Intercept I1 : ({}, {})'.format(xI1,yI1) ) </syntaxhighlight> <syntaxhighlight> Axis : (-0.8)x + (-0.6)y + (9.4) = 0 Eccentricity = 0.9 Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0 Directrix 2 : (0.6)x + (-0.8)y + (2) = 0 F1 : (22.32421052631578947368, -14.09894736842105263158) F2 : (8, 5) Intercept ID1 : (24.00421052631578947368, -16.33894736842105263158) Intercept I1 : (23.12, -15.16) </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>I2, ID2.</math> {{RoundBoxBottom}} ===Latus rectums=== <syntaxhighlight lang=python> # direction cosines along latus rectum. dlx,dly = -dy,dx # # distance from U to F1 half_latus_rectum # ------------------------------ = ----------------------- = e1 # distance from U to directrix 1 distance_from_F1_to_ID1 # half_latus_rectum = reduce_Decimal_number(e1*distance_from_F1_to_ID1) # latus rectum 1 # Focal chord has equation (afc)x + (bfc)y + (cfc) = 0. afc,bfc = a1,b1 cfc = reduce_Decimal_number(-(afc*p1 + bfc*q1)) print ( ' Focal chord PU : ({})x + ({})y + ({}) = 0'.format(afc,bfc,cfc) ) P = xP,yP = p1 + dlx*half_latus_rectum, q1 + dly*half_latus_rectum print ( ' Point P : ({}, {})'.format(xP,yP) ) U = xU,yU = p1 - dlx*half_latus_rectum, q1 - dly*half_latus_rectum print ( ' Point U : ({}, {})'.format(xU,yU) ) distance = reduce_Decimal_number(( (xP - xU)**2 + (yP - yU)**2 ).sqrt()) print (' Length PU =', distance) print (' half_latus_rectum =', half_latus_rectum) </syntaxhighlight> <syntaxhighlight> Focal chord PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0 Point P : (20.30821052631578947368, -15.61094736842105263158) Point U : (24.34021052631578947368, -12.58694736842105263158) Length PU = 5.04 half_latus_rectum = 2.52 </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>R, S.</math> {{RoundBoxBottom}} ===Minor axis=== <syntaxhighlight lang=python> print () # Mid point between F1, F2: M = xM,yM = (p1 + p2)/2, (q1 + q2)/2 print ( ' Mid point M : ({}, {})'.format(xM,yM) ) half_major = length_of_major_axis / 2 half_distance = distance_F1_F2 / 2 # half_distance**2 + half_minor**2 = half_major**2 half_minor = ( half_major**2 - half_distance**2 ).sqrt() length_of_minor_axis = half_minor * 2 Q = xQ,yQ = xM + dlx*half_minor, yM + dly*half_minor T = xT,yT = xM - dlx*half_minor, yM - dly*half_minor print ( ' Point Q : ({}, {})'.format(xQ,yQ) ) print ( ' Point T : ({}, {})'.format(xT,yT) ) print (' length_of_major_axis =', length_of_major_axis) print (' length_of_minor_axis =', length_of_minor_axis) # # A basic check. # length_of_minor_axis**2 = (length_of_major_axis**2)(1-e**2) # # length_of_minor_axis**2 # ----------------------- = 1-e**2 # length_of_major_axis**2 # # length_of_minor_axis**2 # ----------------------- + (e**2 - 1) = 0 # length_of_major_axis**2 # values = (length_of_minor_axis/length_of_major_axis)**2, e1**2 - 1 sum_zero(values) and 3/0 aM,bM = a1,b1 # Minor axis is parallel to directrix. cM = reduce_Decimal_number(-(aM*xM + bM*yM)) print ( ' Minor axis : ({})x + ({})y + ({}) = 0'.format(aM,bM,cM) ) </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> Mid point M : (15.16210526315789473684, -4.54947368421052631579) Point Q : (10.53708406832736953616, -8.018239580333420216299) Point T : (19.78712645798841993752, -1.080707788087632415281) length_of_major_axis = 26.52631578947368421052 length_of_minor_axis = 11.56255298707631300170 Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0 </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ===Checking=== {{RoundBoxTop|theme=2}} All interesting points have been calculated without using equations of any of the relevant lines. However, equations of relevant lines are very useful for testing, for example: * Check that points <math>ID2, I2, F2, M, F1, I1, ID1</math> are on axis. * Check that points <math>R, F2, S</math> are on latus rectum through <math>F2.</math> * Check that points <math>Q, M, T</math> are on minor axis through <math>M.</math> * Check that points <math>P, F1, U</math> are on latus rectum through <math>F1.</math> Test below checks that 8 points <math>I1, I2, P, Q, R, S, T, U</math> are on ellipse and satisfy eccentricity <math>e = 0.9.</math> <math></math> <math></math> {{RoundBoxBottom}} <syntaxhighlight lang=python> t1 = ( ('I1'), ('I2'), ('P'), ('Q'), ('R'), ('S'), ('T'), ('U'), ) for name in t1 : value = eval(name) x,y = [ reduce_Decimal_number(v) for v in value ] print ('{} : ({}, {})'.format((name+' ')[:2], x,y)) values = A*x**2, B*y**2, C*x*y, D*x, E*y, F sum_zero(values) and 3/0 # Relative to Directrix 1 and Focus 1: distance_to_F1 = ( (x-p1)**2 + (y-q1)**2 ).sqrt() distance_to_directrix1 = a1*x + b1*y + c1 e1 = distance_to_F1 / distance_to_directrix1 print (' e1 =',e1) # Raw value is printed. # Relative to Directrix 2 and Focus 2: distance_to_F2 = ( (x-p2)**2 + (y-q2)**2 ).sqrt() distance_to_directrix2 = a2*x + b2*y + c2 e2 = distance_to_F2 / distance_to_directrix2 e2 = reduce_Decimal_number(e2) print (' e2 =',e2) # Clean value is printed. </syntaxhighlight> {{RoundBoxTop|theme=2}} Note the differences between "raw" values of <math>e_1</math> and "clean" values of <math>e_2.</math> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> I1 : (23.12, -15.16) e1 = -0.9000000000000000000034 e2 = 0.9 I2 : (7.204210526315789473684, 6.061052631578947368421) e1 = -0.9 e2 = 0.9 P : (20.30821052631578947368, -15.61094736842105263158) e1 = -0.9 e2 = 0.9 Q : (10.53708406832736953616, -8.018239580333420216299) e1 = -0.9000000000000000000002 e2 = 0.9 R : (5.984, 3.488) e1 = -0.9000000000000000000003 e2 = 0.9 S : (10.016, 6.512) e1 = -0.9000000000000000000003 e2 = 0.9 T : (19.78712645798841993752, -1.080707788087632415281) e1 = -0.8999999999999999999996 e2 = 0.9 U : (24.34021052631578947368, -12.58694736842105263158) e1 = -0.9 e2 = 0.9 </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> ==Traditional definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0617ellipse01.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. ]] Ellipse may be defined as the locus of a point that moves so that the sum of its distances from two fixed points is constant. In the diagram the two fixed points are the foci, Focus 1 or <math>F_1</math> and Focus 2 or <math>F_2.</math> Distance between <math>F_1</math> and <math>F_2</math>, distance <math>F_1F_2</math>, must be non-zero. Point <math>G</math> on perimeter of ellipse moves so that sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. Points <math>T_1</math> and <math>T_2</math> are on axis of ellipse and the same rule applies to these points. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> is constant. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> <math>=</math> distance <math>F_1G</math> + distance <math>F_2G</math> <math>=</math> distance <math>F_2T_2</math> + distance <math>T_1F_2</math> <math>= \text{length of major axis.}</math> Therefore the constant is <math>\text{length of major axis}</math> which must be greater than distance <math>F_1F_2.</math> From information given, calculate eccentricity <math>e</math> and equation of one directrix. Choose directrix 1 <math>dx1</math> associated with focus F1. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> {{RoundBoxBottom}} ==Ellipse at origin== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1P</math> and distance <math>F_2P</math> is constant. ]] Traditional definition of ellipse states that ellipse is locus of a point that moves so that sum of its distances from two fixed points is constant. By definition distance <math>F_2P</math> + distance <math>F_1P</math> is constant. <math>\sqrt{(x-(-p))^2 + y^2} + \sqrt{(x-p)^2 + y^2} = k\ \dots\ (1)</math> Expand <math>(1)</math> and result is <math>Ax^2 + By^2 + F = 0\ \dots\ (2)</math> where: <math>A = 4k^2 - 16p^2</math> <math>B = 4k^2</math> <math>F = 4k^2p^2 - k^4</math> When <math>y = 0,</math> point <math>B,\ Ax^2 = -F</math> <math>x^2 = \frac{-F}{A}</math> <math>= \frac{k^4 - 4k^2p^2}{4k^2 - 16p^2}</math> <math>=\frac{k^2(k^2-4p^2)}{4(k^2 - 4p^2)} = \frac{k^2}{4}.</math> Therefore: <math>x = \frac{k}{2} = a</math> <math>k = \text{length of major axis.}</math> By definition, distance <math>F_2A</math> + distance <math>F_1A = k.</math> Therefore distance <math>F_1A = a.</math> Intercept form of ellipse at origin: <math>(4k^2 - 16p^2)x^2 + (4k^2)y^2 = k^4 - 4k^2p^2</math> <math>\frac{4(k^2-4p^2)}{k^2(k^2-4p^2)}x^2 + \frac{4k^2}{k^2(k^2 - 4p^2)}y^2 = 1</math> <math>\frac{4}{(2a)^2}x^2 + \frac{4}{(2a)^2 - 4p^2}y^2 = 1</math> <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> <math></math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Second definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Graph of ellipse <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where <math>a,b = 20,12</math>.''' </br> At point <math>B,\ \frac{u}{v} = e.</math> </br> At point <math>A,\ \frac{a}{t} = e.</math> ]] Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. Let <math>\frac{p}{a} = e</math> where: * <math>p</math> is non-zero, * <math>a > p,</math> * <math>a = p + u.</math> Therefore, <math>1 > e > 0.</math> Let directrix have equation <math>x = t</math> where <math>\frac{a}{t} = e.</math> At point <math>B:</math> <math>\frac{p}{p+u} = \frac{p+u}{p+u+v} = e</math> <math>(p+u)^2 = p(p+u+v)</math> <math>pp + pu + pu + uu = pp + pu + pv</math> <math>pu + uu = pv</math> <math>u(p + u) = pv</math> <math>\frac{u}{v} = \frac{p}{p+u} = e</math> <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e\ \dots\ (3)</math> Statement <math>(3)</math> is true at point <math>A</math> also. Section under "Proof" below proves that statement (3) is true for any point <math>P</math> on ellipse. {{RoundBoxBottom}} ===Proof=== {{RoundBoxTop|theme=2}} [[File:0902ellipse00.png|thumb|400px|'''Proving that <math>\frac{\text{distance from point to focus}}{\text{distance from point to directrix}} = e</math>.''' </br> Graph is part of curve <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1.</math> </br> distance to Directrix1 <math>= t - x = \frac{a}{e} - x = \frac{a - ex}{e}.</math> </br> base = <math>x - p = x - ae</math> </br> <math>\text{(distance to Focus1)}^2 = \text{base}^2 + y^2</math> ]] As expressed above in statement <math>3,</math> second definition of ellipse states that ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. This section proves that this definition is true for any point <math>P</math> on the ellipse. At point <math>P:</math> <math>(a^2 - p^2)x^2 + a^2y^2 -a^2(a^2 - p^2) = 0</math> <math>y^2 = \frac{-(a^2 - p^2)x^2 + a^2(a^2 - p^2)}{a^2}</math> <math>= \frac{a^2e^2x^2 - a^2x^2 + a^2a^2 - a^2a^2e^2}{a^2}</math> <math>= e^2x^2 - x^2 + a^2 - a^2e^2</math> base <math>= x-p = x-ae</math> <math>(\text{distance}\ F_1P)^2 = y^2 + \text{base}^2 = y^2 + (x-ae)^2</math> <math>= a^2 - 2aex + e^2x^2</math> <math>= (a-ex)^2</math> <math>\text{distance to Focus1} = \text{distance}\ F_1P = a - ex</math> <math>\text{distance to Directrix1} = t - x = \frac{a}{e} - x = \frac{a-ex}{e}</math> <math>\frac{\text{distance to Focus1}}{\text{distance to Directrix1}}</math> <math>= (a - ex)\frac{e}{(a-ex)}</math> <math>= e</math> Similar calculations can be used to prove the case for Focus2 <math>(-p, 0)</math> and Directrix2 <math>(x = -t)</math> in which case: <math>\frac{\text{distance to Focus2}}{\text{distance to Directrix2}}</math> <math>= (a + ex)\frac{e}{(a + ex)}</math> <math>= e</math> Therefore: <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e</math> where <math>1 > e > 0.</math> Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant, called eccentricity <math>e.</math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Heading== ===Properties of ellipse=== {{RoundBoxTop|theme=2}} [[File:0822ellipse01.png|thumb|400px|'''Graph of ellipse used to illustrate and calculate certain properties of ellipses.''' </br> </br> Traditional definition of ellipse: </br> <math>\text{distance } AF_1 + \text{distance } AF_2 = \text{constant } k.</math> </br> </br> Second definition of ellipse: </br> <math>\frac{\text{distance } AF_1} {\text{distance } AG } = \text{eccentricity } e.</math> </br> </br> Triangle <math>A F_1 G</math> is right triangle. </br> <math>e = \cos \angle O F_1 A = \cos \angle F_1 A G</math> ]] Ellipse in diagram has: * Two foci: <math>F_1\ (p,0),\ F_2\ (-p,0).</math> * Length of major axis <math>= \text{distance } I_2 I_1 = 2a</math> * Length of minor axis <math>= \text{distance } A B = 2b</math> * Equation: <math>\frac {x^2} {a^2} + \frac {y^2} {b^2} = 1</math> * Length of latus rectum <math>= \text{distance } P Q</math> * Distance between directrices <math>= \text{distance } D_2 D_1 = 2t</math> Properties of ellipse: * <math>\frac{\text{length of major axis}} {\text{distance between directrices}} = e</math> * <math>\frac{\text{distance between foci}} {\text{length of major axis}} = e</math> * <math>\frac{\text{distance between foci}} {\text{distance between directrices}}= e^2</math> * <math>(\frac{\text{length of minor axis}} {\text{length of major axis}})^2 + e^2 = 1</math> * <math>\frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> * line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ====Major axis==== From traditional definition of ellipse: Distance <math>AF_2\ +</math> distance <math>AF_1</math> = distance <math>I_1F_1\ +</math> distance <math>I_1F_2</math> = distance <math>I_2F_2\ +</math> distance <math>I_2F_1</math> = <math>k.</math> Therefore: Length of major axis = distance <math>I_2I_1 = 2a = k.</math> Distance <math>AF_1 = \frac{k}{2} = a.</math> From second definition of ellipse: <math>\frac{\text{distance }AF_1}{\text{distance }AG} = \frac{a}{t} = \text{eccentricity }e</math> <math>= \frac{\text{distance }OI_1}{\text{distance }OD_1}.</math> <math>\frac{\text{length of major axis}}{\text{distance between directrices}} = e.</math> ====Foci==== From second definition of ellipse: <math>\frac{\text{distance }I_1F_1}{\text{distance }I_1D_1} = \frac{a-p}{t-a} = e.</math> <math>a - p = te - ae</math> <math>a - p = a - ae</math> Therefore: <math>p = ae</math> or <math>\frac{p}{a} = e.</math> <math>\frac{\text{distance between foci}}{\text{length of major axis}} = e.</math> <math>\frac{\text{distance between foci}}{\text{distance between directrices}} = e^2.</math> ====Minor axis==== Triangle <math>AOF_1</math> is right triangle. <math>\cos ^2 \angle OAF_1 + \sin ^2 \angle OAF_1</math> <math>= (\frac{b}{a})^2 + (\frac{p}{a})^2 </math> <math>= (\frac{b}{a})^2 + (\frac{ae}{a})^2 </math> <math>= (\frac{b}{a})^2 + e^2 = 1</math> <math>( \frac{\text{length of minor axis}} {\text{length of major axis}} )^2 + e^2 = 1</math> Triangles <math>AOF_1,\ AF_1G</math> are similar. Triangle <math>AF_1G</math> is right triangle. <math>e = \cos \angle OF_1A = \cos \angle F_1AG.</math> ====Latus rectum==== From second definition of ellipse: <math>\frac{\text{distance }PF_1} {\text{distance }F_1D_1} = \frac{\text{distance }PF_1}{t-p} = e</math> <math>\text{distance }PF_1 = te - pe = a - (ae)e = a(1-e^2).</math> <math>\frac{\text{distance }PF_1} {a} = 1 - e^2.</math> <math> \frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> ====Slope of curve==== Curve has equation: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math><math></math> <math>= \frac{-x(1-e^2)}{y}</math><math></math> At point <math>P:\ m_1 = y' = \frac{-p(1-e^2)}{-a(1-e^2)}</math> <math>= \frac{ae}{a} = e.</math><math></math> Slope of line <math>PD_1:\ m_2 = \frac{\text{distance }PF_1}{\text{distance }F_1D_1} = e.</math><math></math><math></math> <math>m_1 = m_2.</math> Therefore line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> ===Intercept form of equation=== <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1</math> <math></math> <math></math> {{RoundBoxTop|theme=2}} [[File:0625ellipse01.png|thumb|400px|'''Ellipse at origin with major axis on X axis.''' </br> </br> </br> </br> Equation of ellipse has format <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where: </br> </br> <math>\text{Length of major axis} = 2a = \text{distance}\ I_2I_1 = 40</math> </br> <math>\text{Length of minor axis} = 2b = \text{distance}\ BA = 24</math> </br> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> </br> <math>\frac{\text{Length of minor axis}}{\text{Length of major axis}} = \sqrt{1 - e^2}</math> </br> </br> <math>e = \sqrt{1 - \frac{b^2}{a^2}} = 0.8.</math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> ]] In diagram: Intercept <math>I_1</math> has coordinates <math>(a,0).</math> Intercept <math>I_2</math> has coordinates <math>(-a,0).</math> Intercept <math>A</math> has coordinates <math>(0,b).</math> Intercept <math>B</math> has coordinates <math>(0,-b).</math> Focus <math>F_1</math> has coordinates <math>(f,0)</math> where <math>f = ea.</math> Focus <math>F_2</math> has coordinates <math>(-f,0).</math> Curve has equation <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1,</math> called intercept form of equation of ellipse because intercepts are apparent as the fractional value of each coefficient. Standard form of this equation is: <math>(-0.36)x^2 + (-1)y^2 + (0)xy + (0)x + (0)y + (144) = 0.</math> While the standard form is valuable as input to a computer program, the intercept form is still attractive to the human eye because center of ellipse and intercepts are neatly contained within the equation. Slope of curve: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math> <math>= \frac{-x(1-e^2)}{y}</math> At point <math>P</math> on latus rectum <math>PQ:</math> <math>m_1 = y' = \frac{-(ea)(1-e^2)}{-(a(1-e^2))} = e</math> Slope of line <math>PD = m_2 = \frac{PF_1}{F_1D} = e</math> <math>m_1 = m_2.</math> Line <math>PD</math> is tangent to curve at latus rectum, point <math>P.</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Example=== {{RoundBoxTop|theme=2}} [[File:0618ellipse01.png|thumb|400px|'''Traditional definition of ellipse uses abc, epq.''' </br> M is mid-point between F1 and F2. </br> Point R is on minor axis. </br> </br> <math>\frac{\text{distance from R to F1}}{\text{distance from R to directrix 1}}</math> <math>= e</math> </br> </br> <math>= \frac{\text{half major axis}}{\text{distance from M to directrix 1}}</math> </br> </br> <math>\text{distance from M to directrix 1} = \frac{\text{half major axis}}{e}</math> </br> </br> <math>\text{F1:}\ (1, -7)</math> </br> <math>\text{F2:}\ (-1.24, 0.68)</math> </br> length_of_major_axis = 10 </br> <math>\text{M:}\ (-0.12, -3.16)</math> </br> length_of_minor_axis = 6 </br> <math>\text{R:}\ (2.76, -2.32)</math> </br> <math>e = 0.8</math> </br> <math>\text{D1:}\ (1.63, -9.16)</math> </br> <math>\text{Directrix 1:}\ (-0.28)x + (0.96)y + (9.25) = 0</math> </br> <math>\text{abc}\ =\ (-0.28,\ 0.96,\ 9.25)</math> </br> <math>\text{epq}\ =\ (0.8,\ 1,\ -7)</math> ]] Given: <syntaxhighlight lang=python> # python code F1 = 1, -7 # Focus 1 F2 = -1.24, 0.68 # Focus 2 length_of_major_axis = 10 </syntaxhighlight> Calculate equation of ellipse. <syntaxhighlight lang=python> F1 = p1,q1 = [ dD(str(v)) for v in F1 ] # Focus 1 F2 = p2,q2 = [ dD(str(v)) for v in F2 ] # Focus 2 length_of_major_axis = dD(length_of_major_axis) half_major_axis = length_of_major_axis / 2 # Direction cosines from F1 to F2 dx = p2-p1 ; dy = q2-q1 divider = (dx**2 + dy**2).sqrt() dx,dy = [ (v/divider) for v in (dx,dy) ] # F2 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 distance_F1_F2 = (q2-q1)/dy half_distance_F1_F2 = distance_F1_F2 / 2 # The mid-point M = xM,ym = p1 + dx*half_distance_F1_F2, q1 + dy*half_distance_F1_F2 # Eccentricity: e = distance_F1_F2 / length_of_major_axis # distance from point R to F1 half_major_axis # ------------------------------------ = e = ----------------------------------------- # distance from point R to Directrix 1 distance from point M to Directrix 1 distance_from_point_M_to_dx1 = half_major_axis / e # Intersection of axis and directrix 1 D1 = xM-dx*distance_from_point_M_to_dx1, yM-dy*distance_from_point_M_to_dx1 D1 = xD1, yD1 = [ reduce_Decimal_number(v) for v in D1 ] # Equation of Directrix 1 # dx1 = adx1,bdx1,cdx1 adx1,bdx1 = dx, dy # Perpendicular to axis. # adx1*x + bdx1*y + cdx1 = 0 # Directrix 1 contains point D1 cdx1 = reduce_Decimal_number( -( adx1*xD1 + bdx1*yD1 ) ) abc = adx1,bdx1,cdx1 epq = e,p1,q1 ABCDEF = ABCDEF_from_abc_epq (abc,epq, 1) </syntaxhighlight> Equation of ellipse in standard form: <math>(-0.949824)x^2 + (-0.410176)y^2 + (-0.344064)xy + (-1.3152)x + (-2.6336)y + (4.76) = 0</math> For more insight into method of calculation and proof: <syntaxhighlight lang=python> if 1 : print ('F1: ({}, {})'.format(p1,q1)) print ('F1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p1,q1)) print ('F2: ({}, {})'.format(p2,q2)) print ('F2: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p2,q2)) print ('length_of_major_axis =', length_of_major_axis) print ('M: ({}, {})'.format(xM,yM)) print ('M: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xM,yM)) # half_minor_axis**2 + half_distance_F1_F2**2 = half_major_axis**2 half_minor_axis = (half_major_axis**2 - half_distance_F1_F2**2).sqrt() length_of_minor_axis = half_minor_axis * 2 s1 = 'length_of_minor_axis' ; print (s1, '=', eval(s1)) # Direction cosines on major axis: print ('dx,dy =', dx,dy) # Direction cosines on minor axis: dnx,dny = dy,-dx print ('dnx,dny =', dnx,dny) # One point on minor axis: R = xR,yR = xM + dnx*half_minor_axis, yM + dny*half_minor_axis print ('R: ({}, {})'.format(xR,yR)) print ('R: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xR,yR)) # Verify that point R is on ellipse: sum_zero((A*xR**2, B*yR**2, C*xR*yR, D*xR, E*yR, F)) and 1/0 s1 = 'e' ; print (s1, '=', eval(s1)) print ('D1: ({}, {})'.format(xD1,yD1)) print ('D1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xD1,yD1)) print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(adx1, bdx1, cdx1)) print() # For proof, reverse the process: (abc1,epq1), (abc2,epq2) = calculate_abc_epq (ABCDEF) a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(a1, b1, c1)) print ('Eccentricity e1: {}'.format(e1)) print ('F1: ({}, {})'.format(p1,q1)) print() a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 print ('Directrix 2: ({})x + ({})y + ({}) = 0'.format(a2, b2, c2)) print ('Eccentricity e2: {}'.format(e2)) print ('F2: ({}, {})'.format(p2,q2)) print ('\nEquation of ellipse with integer coefficients:') A,B,C,D,E,F = [ reduce_Decimal_number(-v*1000000/64) for v in ABCDEF ] str1 = '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0' print (str1.format(A,B,C,D,E,F)) </syntaxhighlight> <syntaxhighlight> F1: (1, -7) F1: (x - (1))^2 + (y - (-7))^2 = 1 F2: (-1.24, 0.68) F2: (x - (-1.24))^2 + (y - (0.68))^2 = 1 length_of_major_axis = 10 M: (-0.12, -3.16) M: (x - (-0.12))^2 + (y - (-3.16))^2 = 1 length_of_minor_axis = 6 dx,dy = -0.28 0.96 dnx,dny = 0.96 0.28 R: (2.76, -2.32) R: (x - (2.76))^2 + (y - (-2.32))^2 = 1 e = 0.8 D1: (1.63, -9.16) D1: (x - (1.63))^2 + (y - (-9.16))^2 = 1 Directrix 1: (-0.28)x + (0.96)y + (9.25) = 0 Directrix 1: (0.28)x + (-0.96)y + (-9.25) = 0 Eccentricity e1: 0.8 F1: (1, -7) Directrix 2: (0.28)x + (-0.96)y + (3.25) = 0 Eccentricity e2: 0.8 F2: (-1.24, 0.68) Equation of ellipse with integer coefficients: </syntaxhighlight> <math>(14841)x^2 + (6409)y^2 + (5376)xy + (20550)x + (41150)y + (-74375) = 0</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} =allEqual= {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em;"> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> ====Welcomee==== {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFF800; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> =====Welcomen===== {{Robelbox|title=|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFFFFF; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> <syntaxhighlight lang=python> # python code. if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 : pass </syntaxhighlight> {{Robelbox/close}} {{Robelbox/close}} {{Robelbox/close}} <noinclude> [[Category: main page templates]] </noinclude> {| class="wikitable" |- ! <math>x</math> !! <math>x^2 - N</math> |- | <code></code><code>6</code> || <code>-221</code> |- | <code></code><code>7</code> || <code>-208</code> |- |- | <code>10</code> || <code>-157</code> |- | <code>11</code> || <code>-136</code> |- | <code>12</code> || <code>-113</code> |- | <code>13</code> || <code></code><code>-88</code> |- | <code>26</code> || <code></code><code>419</code> |} =Testing= ======table1====== {|style="border-left:solid 3px blue;border-right:solid 3px blue;border-top:solid 3px blue;border-bottom:solid 3px blue;" align="center" | Hello As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 </syntaxhighlight> |} {{RoundBoxTop|theme=2}} [[File:0410cubic01.png|thumb|400px|''' Graph of cubic function with coefficient a negative.''' </br> There is no absolute maximum or absolute minimum. ]] Coefficient <math>a</math> may be negative as shown in diagram. As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. Unless stated otherwise, any reference to "cubic function" on this page will assume coefficient <math>a</math> positive. {{RoundBoxBottom}} <math>x_{poi} = -1</math> <math></math> <math></math> <math></math> <math></math> =====Various planes in 3 dimensions===== {{RoundBoxTop|theme=2}} <gallery> File:0713x=4.png|<small>plane x=4.</small> File:0713y=3.png|<small>plane y=3.</small> File:0713z=-2.png|<small>plane z=-2.</small> </gallery> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 6872533965463318088296406206152583523950547457502877599617298355752203375318570113543746034084988471 6038689997069900481503054402779031645424782306849293691862158057846311159666871301301561856898723723 5288509264861249497715421833420428568606014682472077143585487415565706967765372022648544701585880162 0758474922657226002085584466521458398893944370926591800311388246468157082630100594858704003186480342 1948972782906410450726368813137398552561173220402450912277002269411275736272804957381089675040183698 6836845072579936472906076299694138047565482372899718032680247442062926912485905218100445984215059112 0249441341728531478105803603371077309182869314710171111683916581726889419758716582152128229518488472 </syntaxhighlight> <math>\theta_1</math> {{RoundBoxTop|theme=2}} [[File:0422xx_x_2.png|thumb|400px|''' Figure 1: Diagram illustrating relationship between <math>f(x) = x^2 - x - 2</math> and <math>f'(x) = 2x - 1.</math>''' </br> ]] {{RoundBoxBottom}} <math>O\ (0,0,0)</math> <math>M\ (A_1,B_1,C_1)</math> <math>N\ (A_2,B_2,C_2)</math> <math>\theta</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} (6) - (7),\ 4Apq + 2Bq =&\ 0\\ 2Ap + B =&\ 0\\ 2Ap =&\ - B\\ \\ p =&\ \frac{-B}{2A}\ \dots\ (8) \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} 1.&4141475869yugh\\ &2645er3423231sgdtrf\\ &dhcgfyrt45erwesd \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math> 4\sin 18^\circ = \sqrt{2(3 - \sqrt 5)} = \sqrt 5 - 1 </math> 6vny4gnagvjoa04rtnqk5vup1a9qi1h 2835150 2835149 2026-09-30T10:14:34Z ThaniosAkro 2805358 /* Using floating point numbers: */ 2835150 wikitext text/x-wiki ==Table== {| class="wikitable" |- | From <math>(3):</math> || <math>p^3</math>|| || <math>+Ap</math> || <math>+B</math>|| <math>= 0</math> || <math>\dots (5)</math> |- | From <math>(4):</math> || || <math>Cp^2</math>|| <math></math> || <math>+D</math>|| <math>= 0</math> || <math>\dots (6)</math> |- | <math>(5)*D</math> || <math>Dp^3</math>|| || <math>+DAp</math> || <math>+DB</math>|| <math>= 0</math> || <math>\dots (7)</math> |- | <math>(6)*B</math> || || <math>BCp^2</math>|| <math></math> || <math>+BD</math>|| <math>= 0</math> || <math>\dots (8)</math> |- | <math>(7)-(8)</math> || <math>Dp^3</math>||<math>-BCp^2</math> || <math>+DAp</math> || <math></math>|| <math>= 0</math> || <math>\dots (9)</math> |- | Simplify <math>(9)</math> || <math></math>||<math>Dp^2</math> || <math>-BCp</math> || <math>+DA</math>|| <math>= 0</math> || <math>\dots (10)</math> |- | <math>(6)*A</math> || || <math>ACp^2</math>|| <math></math> || <math>+AD</math>|| <math>= 0</math> || <math>\dots (11)</math> |- | <math>(10)-(11)</math> || <math></math>||<math>Dp^2-ACp^2</math> || <math>-BCp</math> || <math></math>|| <math>= 0</math> || <math>\dots (12)</math> |- | Simplify <math>(12)</math> || <math></math>|| || <math>Dp-ACp</math> || <math>-BC</math> || <math>= 0</math> || <math>\dots (13)</math> |} ====First result==== <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ====Calculate R==== <syntaxhighlight> </syntaxhighlight> Produce matrix corrected: <syntaxhighlight lang=python> print ('\nCreating new matrix with corrections:') matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> Circuit parameters: <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> =====Using floating point numbers:===== <syntaxhighlight lang=python> # python code: number_of_columns = 65 one = 1 ; Tolerance = 1e-14 # Following string is executable python code: exc_str1 = """ Values_of_R = [] for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = one i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) exec(exc_str_64ei) for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of calculations =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR)) s1 = 'sum' ; print(s1,'=',eval(s1)) if not sum : print ('With Tolerance of {}, both minR and maxR are equal.'.format(Tolerance)) """ exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 With Tolerance of 1e-14, both minR and maxR are equal. </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. =====Using Decimal numbers:===== With <code>enable_reduceRow</code> clear : <syntaxhighlight lang=python> enable_reduceRow = 0 Precision = dgt.prec = 60 Tolerance = dD('1e-' + str(Precision-3)) one = dD(1) try : exec(exc_str1) except : pass </syntaxhighlight> <syntaxhighlight> solveMbyN (input_, level = -52) : <class 'decimal.Overflow'> Overflow([<class 'decimal.Overflow'>]) Length of input = 12 input_[0] = [-inf, inf, -inf, inf, inf, -inf, inf, -inf, inf, -inf, -inf, inf, 0.0] input_[1] = [inf, -inf, -inf, -inf, -inf, inf, -inf, -inf, -inf, -inf, inf, -inf, 0.0] input_[2] = [-inf, inf, inf, inf, -inf, -inf, inf, inf, -inf, inf, inf, inf, 0.0] input_[3] = [inf, -inf, -inf, inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, 0.0] input_[4] = [620.0, 0.0, 0.0, 0.0, 290.0, -1200.0, 240.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[5] = [0.0, 630.0, 0.0, 0.0, 0.0, 240.0, -1110.0, 190.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[6] = [inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, -inf, inf, -inf, 0.0] input_[7] = [-inf, inf, inf, inf, inf, -inf, inf, inf, inf, inf, -inf, inf, 0.0] </syntaxhighlight> With <code>enable_reduceRow</code> set : <syntaxhighlight lang=python> enable_reduceRow = 1 exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of tests = 1664 minR = 723.928575988442547699732563335265663515838075102937503680560 maxR = 723.928575988442547699732563335265663515838075102937503680663 sum = 0 With Tolerance of 1E-57, both minR and maxR are equal. </syntaxhighlight> With tolerance of <math>1e-57</math> all values of resistance R = 723.928575988442547699732563335265663515838075102937503681. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math>\text{R}</math> is printed with precision of 60. ==Making the Decimal object== The following function verifies that we are working with Decimal objects. <syntaxhighlight lang=python> import sys import decimal getcontext = decimal.getcontext dD = D = Decimal = decimal.Decimal DT = decimal.DecimalTuple dgt = decimal.getcontext() dgt.prec = 50 def print_error (error, x=None, thisName=None) : """ Prints error derived from sys.exc_info(). """ list1 = error.split(',') v1 = ','.join(list1[1:-1]) if thisName : print (thisName) if x != None : print (' Input =', (str(x))[:60]) print (' ', list1[0]) print (' ', v1) print (' ', list1[-1]) def makeDecimal (x, flag = 0) : ''' output = makeDecimal (x [, flag]) x is a single object convertible to Decimal object. returns Decimal object or returns None on error. ''' thisName = 'makeDecimal (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, dD) : return x if isinstance(x, int) : return dD(x) if isinstance(x, float) : return dD(str(x)) if isinstance(x, str) : try : error = '' output = dD(x) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if isinstance(x, (list,tuple,DT)) : try : error = '' v1,v2,v3 = x if isinstance(v2, (tuple,list)) : output = dD(x) else : output = dD( ( v1, list(v2), v3 ) ) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if flag : print (' Input not recognized.') return None </syntaxhighlight> ===checkComplex(x)=== This function verifies that the object is a valid complex tuple. <syntaxhighlight lang=python> def checkComplex(x, flag = 0) : """ status = checkComplex(x [, flag]) x must be : (v1,v2,'rectangular') or (v1,v2,'polar') v1,v2 must be type Decimal. """ thisName = 'checkComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) try: error = '' v1,v2,str1 = x isinstance (v1,dD) or ({}['v1 must be type Decimal.']) isinstance (v2,dD) or ({}['v2 must be type Decimal.']) (isinstance (str1,str) and str1) or ({}['str1 must be valid string.']) str1 = str1.lower() if str1 == 'rectangular'[:len(str1)] : pass elif str1 == 'polar'[:len(str1)] : pass else : ({}['str1 must be "rectangular" or "polar".']) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return False return True </syntaxhighlight> ===str_to_complex (input_string)=== <syntaxhighlight lang=python> import re # The re pattern for numbers to be found in string of type complex. # In string like ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' # extracts '1234567890987654323456E-6' and '+987654321234567890987e+2J'. # eval allows ' 12_3456_7890_9876_5432_3456E-6 + 987654321234567890987e+2J '. # Conversion to Decimal allows: '__987_65432123____4567890_987___'. # eval does not allow ' 0123 ' but allows ' 2e04 '. # Conversion to Decimal allows: ' 0123 ' digits = '[_0123456789]' integer = '[_0123456789]{1,}' # Matches 1 23 345 4567 56789 exponent = '[Ee][\+\-]{{0,1}}{}'.format(integer) # Matches e8 e+8 e-8 or E8 E+8 E-8 Exponent = '({}){{0,1}}'.format(exponent) # exponent 0 or 1 times. float1 = '({})\.{{0,1}}'.format(integer) # Matches 123 2345. float2 = '{}{{0,}}\.{}'.format(digits, integer) # Matches 123.345 .345 float_ = '(({})|({}))'.format(float2,float1) rvalue = '{}({})'.format(float_,Exponent) rvalue_signed = '[\+\-]{{0,1}}{}'.format(rvalue) ivalue_signed = '{}[Jj]'.format(rvalue_signed) def str_to_complex (input_string) : """ a,b = str_to_complex (input_string) input_string could be ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' input_string could be ' ' ' ( 12345678909876543234561234567890987.654323456E-6 + 987654321234567890987987654321.23764567890987e+2J ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + # Note the '_' 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or '4', '-4', '(4)', '(-4)', '-(4)', '-(-4)' or '( +3j)', '+(-3J)', '-(3j)', '-(-3J)' or '( 4+3j)', '+(-3 + 4J)','-( 4+3j)', '-(-3 + 4J)', This function retains precision of a,b """ try : status = 0 isinstance(input_string,str) or ({}['input_string not type str.']) str1 = input_string.strip() cx1 = eval(str1) isinstance(cx1,(int,float,complex)) or ({}['cx1 not desired type.']) except : status = 1 if status : return # This code removes white lines and comments, if any, at end of each line. new_line = ''' '''[-1:] lines = [ line for Line in str1.split(new_line) for line in [ Line.rstrip() ] if line ] lines = [ v for line in lines for parts in [ line.split('#') ] for v in [ parts[0]] ] str1 = ''.join(lines) str1 = ''.join(str1.split()) if isinstance (cx1, (int,float)) : resultr = re.search(rvalue_signed, str1) resultr or ({}['rvalue not found.']) dD1 = dD(resultr[0]) v1 = eval(str(dD1)) if v1 == cx1 : return dD1,dD(0) if v1 == -cx1 : return -dD1,dD(0) ({}['dD1 not recognized.']) # cx1 must be complex. It must contain imaginary value. resulti = re.search(ivalue_signed, str1) resulti or ({}['ivalue not found.']) str2j = resulti[0] ; str2 = str2j[:-1] dD2 = dD(str2) str1 = ''.join(str1.split(str2j)) # cx1 may contain real value. resultr = re.search(rvalue_signed, str1) if resultr : dD1 = dD(resultr[0]) else : dD1 = dD(0) cx2 = complex(dD1,dD2) if cx2.real == cx1.real : pass elif cx2.real == -cx1.real : dD1 = dD1.copy_negate() else : ({}['dD1 Not Recognized.']) if cx2.imag == cx1.imag : pass elif cx2.imag == -cx1.imag : dD2 = dD2.copy_negate() else : ({}['dD2 Not Recognized.']) cx3 = complex(dD1, dD2) if cx3 == cx1 : return dD1,dD2 ({}['No match for cx3.']) </syntaxhighlight> ===makeComplex(x)=== <syntaxhighlight lang=python> def makeComplex (x, flag = 0) : ''' result = makeComplex (x[, flag]) Input can be tuple with 1,2 or 3 members. If 1 or 2 members, 'rect' is understood. The one member or single object may be int, float, complex, CompleX or string convertible to int, float or complex. x = makeComplex(4) x = makeComplex((4,)) x = makeComplex(('4',0)) x = makeComplex((4,'0', 'rect')) x = makeComplex(4+0j) x = makeComplex('4+0j') x = makeComplex(('4+0j',)) In all seven cases above x = ( Decimal('4'), Decimal('0'), 'rect' ) output is always (modulus, phase, "polar") or (real_part, imag_part, "rect") modulus, phase, real_part, imag_part are Decimal objects. On error returns None. ''' thisName = 'makeComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, CompleX) : # New class CompleX (note the punctuation.) x.check() return (x.r, x.i, 'rect') if isinstance (x,complex) : return makeComplex (( x.real, x.imag )) try : status = 1 a,b = str_to_complex (x) except : status = 0 if status : return a,b,'rect' try : status = 1 result = makeDecimal(x) isinstance(result, Decimal) or ({}['Expecting result to be type Decimal.']) output = result,dD(0),'rect' except : status = 0 if status : return output try : status = 1 v1, = x # Allow for (( 3+4j ),) except : status = 0 if status : return makeComplex (v1) try : status = 1 ; error = '' if len(x) == 2 : v1,v2 = [ makeDecimal (v) for v in x ] str1 = 'rect' elif len(x) == 3 : v1,v2,str1 = x v1,v2 = [ makeDecimal (v) for v in (v1,v2) ] else : ({}['len(x) not in (2,3)']) output = v1,v2,str1 checkComplex(output) or ({}['output not valid complex.']) if str1[0] in 'rR' : output = v1,v2,'rect' else : output = v1,v2,'polar' except : status = 0 ; error = str(sys.exc_info()) if status : return output if flag : print_error (error) return </syntaxhighlight> =Conic sections generally= Within the two dimensional space of Cartesian Coordinate Geometry a conic section may be located anywhere and have any orientation. This section examines the parabola, ellipse and hyperbola, showing how to calculate the equation of the section, and also how to calculate the foci and directrices given the equation. ==Latera recta et cetera== "Latus rectum" is a Latin expression meaning "straight side." According to Google, the Latin plural of "latus rectum" is "latera recta," but English allows "latus rectums" or possibly "lati rectums." The title of this section is poetry to the eyes and music to the ears of a Latin student and this author hopes that the gentle reader will permit such poetic licence in a mathematical topic. The translation of the title is "Latus rectums and other things." This section describes the calculation of interesting items associated with the ellipse: latus rectums, major axis, minor axis, focal chords, directrices and various points on these lines. When given the equation of an ellipse, the first thing is to calculate eccentricity, foci and directrices as shown above. Then verify that the curve is in fact an ellipse. From these values everything about the ellipse may be calculated. For example: {{RoundBoxTop|theme=2}} [[File:0608ellipse01.png|thumb|400px|'''Graph of ellipse <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math>''' </br> </br> Axis : (-0.8)x + (-0.6)y + (9.4) = 0</br> Eccentricity = 0.9</br> </br> Directrix 2 : (0.6)x + (-0.8)y + (2) = 0</br> Latus rectum RS : (0.6)x + (-0.8)y + (-0.8) = 0</br> Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0</br> Latus rectum PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0</br> Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0</br> </br> <math>\text{ID2}</math> = (6.32, 7.24)</br> <math>\text{I2}</math> = (7.204210526315789473684, 6.061052631578947368421)</br> F2 = (8, 5)</br> M = (15.16210526315789473684, -4.54947368421052631579)</br> F1 = (22.32421052631578947368, -14.09894736842105263158)</br> <math>\text{I1}</math> = (23.12, -15.16)</br> <math>\text{ID1}</math> = (24.00421052631578947368, -16.33894736842105263158)</br> </br> P = (20.30821052631578947368, -15.61094736842105263158)</br> Q = (10.53708406832736953616, -8.018239580333420216299)</br> R = (5.984, 3.488)</br> S = (10.016, 6.512)</br> T = (19.78712645798841993752, -1.080707788087632415281)</br> U = (24.34021052631578947368, -12.58694736842105263158)</br> </br> Length of major axis: <math>\text{I1I2}</math> = 26.52631578947368421052</br> Length of minor axis: QT = 11.56255298707631300170</br> Length of latus rectum: RS = PU = 5.04 ]] Consider conic section: <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math> This curve is ellipse with random orientation. <syntaxhighlight lang=python> # python code ABCDEF = A,B,C,D,E,F = 1771, 1204, 1944, -44860, -18520, 214400 # ellipse result = calculate_abc_epq(ABCDEF) (len(result) == 2) or 1/0 # ellipse or hyperbola (abc1,epq1), (abc2,epq2) = result a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 (e1 == e2) or 2/0 (1 > e1 > 0) or 3/0 print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) A,B,C,D,E,F = ABCDEF_from_abc_epq(abc1,epq1) print ('Equation of ellipse in standard form:') print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) </syntaxhighlight> <syntaxhighlight> (1771)x^2 + (1204)y^2 + (1944)xy + (-44860)x + (-18520)y + (214400) = 0 Equation of ellipse in standard form: (-0.7084)x^2 + (-0.4816)y^2 + (-0.7776)xy + (17.944)x + (7.408)y + (-85.76) = 0 </syntaxhighlight> <syntaxhighlight lang=python> # python code def sum_zero(input) : ''' sum = sum_zero(input) If sum is close to 0 and Tolerance permits, sum is returned as 0. For example: if input contains (2, -1.999999999999999999999) this function returns sum of these 2 values as 0. ''' global Tolerance sump = sumn = 0 for v in input : if v > 0 : sump += v elif v < 0 : sumn -= v sum = sump - sumn if abs(sum) < Tolerance : return (type(Tolerance))(0) min, max = sorted((sumn,sump)) if abs(sum) <= Tolerance*min : return (type(Tolerance))(0) return sum </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Major axis=== <syntaxhighlight lang=python> # axis is perpendicular to directrix. ax,bx = b1,-a1 # axis contains foci. ax + by + c = 0 cx = reduce_Decimal_number(-(ax*p1 + bx*q1)) axis = ax,bx,cx print ( ' Axis : ({})x + ({})y + ({}) = 0'.format(ax,bx,cx) ) print ( ' Eccentricity = {}'.format(e1) ) print () print ( ' Directrix 1 : ({})x + ({})y + ({}) = 0'.format(a1,b1,c1) ) print ( ' Directrix 2 : ({})x + ({})y + ({}) = 0'.format(a2,b2,c2) ) F1 = p1,q1 # Focus 1. print ( ' F1 : ({}, {})'.format(p1,q1) ) F2 = p2,q2 # Focus 2. print ( ' F2 : ({}, {})'.format(p2,q2) ) # Direction cosines along axis from F1 towards F2: dx,dy = a1,b1 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 if dx : distance_F1_F2 = (p2 - p1)/dx else : distance_F1_F2 = (q2 - q1) if distance_F1_F2 < 0 : distance_F1_F2 *= -1 dx *= -1 ; dy *= -1 # Intercept on directrix1 distance_from_F1_to_ID1 = abs(a1*p1 + b1*q1 + c1) ID1 = xID1,yID1 = p1 - dx*distance_from_F1_to_ID1, q1 - dy*distance_from_F1_to_ID1 print ( ' Intercept ID1 : ({}, {})'.format(xID1,yID1) ) # # distance_F1_F2 # -------------------- = e # length_of_major_axis # length_of_major_axis = distance_F1_F2 / e1 # Intercept1 on curve distance_from_F1_to_curve = (length_of_major_axis - distance_F1_F2 )/2 xI1,yI1 = p1 - dx*distance_from_F1_to_curve, q1 - dy*distance_from_F1_to_curve I1 = xI1,yI1 = [ reduce_Decimal_number(v) for v in (xI1,yI1) ] print ( ' Intercept I1 : ({}, {})'.format(xI1,yI1) ) </syntaxhighlight> <syntaxhighlight> Axis : (-0.8)x + (-0.6)y + (9.4) = 0 Eccentricity = 0.9 Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0 Directrix 2 : (0.6)x + (-0.8)y + (2) = 0 F1 : (22.32421052631578947368, -14.09894736842105263158) F2 : (8, 5) Intercept ID1 : (24.00421052631578947368, -16.33894736842105263158) Intercept I1 : (23.12, -15.16) </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>I2, ID2.</math> {{RoundBoxBottom}} ===Latus rectums=== <syntaxhighlight lang=python> # direction cosines along latus rectum. dlx,dly = -dy,dx # # distance from U to F1 half_latus_rectum # ------------------------------ = ----------------------- = e1 # distance from U to directrix 1 distance_from_F1_to_ID1 # half_latus_rectum = reduce_Decimal_number(e1*distance_from_F1_to_ID1) # latus rectum 1 # Focal chord has equation (afc)x + (bfc)y + (cfc) = 0. afc,bfc = a1,b1 cfc = reduce_Decimal_number(-(afc*p1 + bfc*q1)) print ( ' Focal chord PU : ({})x + ({})y + ({}) = 0'.format(afc,bfc,cfc) ) P = xP,yP = p1 + dlx*half_latus_rectum, q1 + dly*half_latus_rectum print ( ' Point P : ({}, {})'.format(xP,yP) ) U = xU,yU = p1 - dlx*half_latus_rectum, q1 - dly*half_latus_rectum print ( ' Point U : ({}, {})'.format(xU,yU) ) distance = reduce_Decimal_number(( (xP - xU)**2 + (yP - yU)**2 ).sqrt()) print (' Length PU =', distance) print (' half_latus_rectum =', half_latus_rectum) </syntaxhighlight> <syntaxhighlight> Focal chord PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0 Point P : (20.30821052631578947368, -15.61094736842105263158) Point U : (24.34021052631578947368, -12.58694736842105263158) Length PU = 5.04 half_latus_rectum = 2.52 </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>R, S.</math> {{RoundBoxBottom}} ===Minor axis=== <syntaxhighlight lang=python> print () # Mid point between F1, F2: M = xM,yM = (p1 + p2)/2, (q1 + q2)/2 print ( ' Mid point M : ({}, {})'.format(xM,yM) ) half_major = length_of_major_axis / 2 half_distance = distance_F1_F2 / 2 # half_distance**2 + half_minor**2 = half_major**2 half_minor = ( half_major**2 - half_distance**2 ).sqrt() length_of_minor_axis = half_minor * 2 Q = xQ,yQ = xM + dlx*half_minor, yM + dly*half_minor T = xT,yT = xM - dlx*half_minor, yM - dly*half_minor print ( ' Point Q : ({}, {})'.format(xQ,yQ) ) print ( ' Point T : ({}, {})'.format(xT,yT) ) print (' length_of_major_axis =', length_of_major_axis) print (' length_of_minor_axis =', length_of_minor_axis) # # A basic check. # length_of_minor_axis**2 = (length_of_major_axis**2)(1-e**2) # # length_of_minor_axis**2 # ----------------------- = 1-e**2 # length_of_major_axis**2 # # length_of_minor_axis**2 # ----------------------- + (e**2 - 1) = 0 # length_of_major_axis**2 # values = (length_of_minor_axis/length_of_major_axis)**2, e1**2 - 1 sum_zero(values) and 3/0 aM,bM = a1,b1 # Minor axis is parallel to directrix. cM = reduce_Decimal_number(-(aM*xM + bM*yM)) print ( ' Minor axis : ({})x + ({})y + ({}) = 0'.format(aM,bM,cM) ) </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> Mid point M : (15.16210526315789473684, -4.54947368421052631579) Point Q : (10.53708406832736953616, -8.018239580333420216299) Point T : (19.78712645798841993752, -1.080707788087632415281) length_of_major_axis = 26.52631578947368421052 length_of_minor_axis = 11.56255298707631300170 Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0 </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ===Checking=== {{RoundBoxTop|theme=2}} All interesting points have been calculated without using equations of any of the relevant lines. However, equations of relevant lines are very useful for testing, for example: * Check that points <math>ID2, I2, F2, M, F1, I1, ID1</math> are on axis. * Check that points <math>R, F2, S</math> are on latus rectum through <math>F2.</math> * Check that points <math>Q, M, T</math> are on minor axis through <math>M.</math> * Check that points <math>P, F1, U</math> are on latus rectum through <math>F1.</math> Test below checks that 8 points <math>I1, I2, P, Q, R, S, T, U</math> are on ellipse and satisfy eccentricity <math>e = 0.9.</math> <math></math> <math></math> {{RoundBoxBottom}} <syntaxhighlight lang=python> t1 = ( ('I1'), ('I2'), ('P'), ('Q'), ('R'), ('S'), ('T'), ('U'), ) for name in t1 : value = eval(name) x,y = [ reduce_Decimal_number(v) for v in value ] print ('{} : ({}, {})'.format((name+' ')[:2], x,y)) values = A*x**2, B*y**2, C*x*y, D*x, E*y, F sum_zero(values) and 3/0 # Relative to Directrix 1 and Focus 1: distance_to_F1 = ( (x-p1)**2 + (y-q1)**2 ).sqrt() distance_to_directrix1 = a1*x + b1*y + c1 e1 = distance_to_F1 / distance_to_directrix1 print (' e1 =',e1) # Raw value is printed. # Relative to Directrix 2 and Focus 2: distance_to_F2 = ( (x-p2)**2 + (y-q2)**2 ).sqrt() distance_to_directrix2 = a2*x + b2*y + c2 e2 = distance_to_F2 / distance_to_directrix2 e2 = reduce_Decimal_number(e2) print (' e2 =',e2) # Clean value is printed. </syntaxhighlight> {{RoundBoxTop|theme=2}} Note the differences between "raw" values of <math>e_1</math> and "clean" values of <math>e_2.</math> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> I1 : (23.12, -15.16) e1 = -0.9000000000000000000034 e2 = 0.9 I2 : (7.204210526315789473684, 6.061052631578947368421) e1 = -0.9 e2 = 0.9 P : (20.30821052631578947368, -15.61094736842105263158) e1 = -0.9 e2 = 0.9 Q : (10.53708406832736953616, -8.018239580333420216299) e1 = -0.9000000000000000000002 e2 = 0.9 R : (5.984, 3.488) e1 = -0.9000000000000000000003 e2 = 0.9 S : (10.016, 6.512) e1 = -0.9000000000000000000003 e2 = 0.9 T : (19.78712645798841993752, -1.080707788087632415281) e1 = -0.8999999999999999999996 e2 = 0.9 U : (24.34021052631578947368, -12.58694736842105263158) e1 = -0.9 e2 = 0.9 </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> ==Traditional definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0617ellipse01.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. ]] Ellipse may be defined as the locus of a point that moves so that the sum of its distances from two fixed points is constant. In the diagram the two fixed points are the foci, Focus 1 or <math>F_1</math> and Focus 2 or <math>F_2.</math> Distance between <math>F_1</math> and <math>F_2</math>, distance <math>F_1F_2</math>, must be non-zero. Point <math>G</math> on perimeter of ellipse moves so that sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. Points <math>T_1</math> and <math>T_2</math> are on axis of ellipse and the same rule applies to these points. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> is constant. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> <math>=</math> distance <math>F_1G</math> + distance <math>F_2G</math> <math>=</math> distance <math>F_2T_2</math> + distance <math>T_1F_2</math> <math>= \text{length of major axis.}</math> Therefore the constant is <math>\text{length of major axis}</math> which must be greater than distance <math>F_1F_2.</math> From information given, calculate eccentricity <math>e</math> and equation of one directrix. Choose directrix 1 <math>dx1</math> associated with focus F1. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> {{RoundBoxBottom}} ==Ellipse at origin== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1P</math> and distance <math>F_2P</math> is constant. ]] Traditional definition of ellipse states that ellipse is locus of a point that moves so that sum of its distances from two fixed points is constant. By definition distance <math>F_2P</math> + distance <math>F_1P</math> is constant. <math>\sqrt{(x-(-p))^2 + y^2} + \sqrt{(x-p)^2 + y^2} = k\ \dots\ (1)</math> Expand <math>(1)</math> and result is <math>Ax^2 + By^2 + F = 0\ \dots\ (2)</math> where: <math>A = 4k^2 - 16p^2</math> <math>B = 4k^2</math> <math>F = 4k^2p^2 - k^4</math> When <math>y = 0,</math> point <math>B,\ Ax^2 = -F</math> <math>x^2 = \frac{-F}{A}</math> <math>= \frac{k^4 - 4k^2p^2}{4k^2 - 16p^2}</math> <math>=\frac{k^2(k^2-4p^2)}{4(k^2 - 4p^2)} = \frac{k^2}{4}.</math> Therefore: <math>x = \frac{k}{2} = a</math> <math>k = \text{length of major axis.}</math> By definition, distance <math>F_2A</math> + distance <math>F_1A = k.</math> Therefore distance <math>F_1A = a.</math> Intercept form of ellipse at origin: <math>(4k^2 - 16p^2)x^2 + (4k^2)y^2 = k^4 - 4k^2p^2</math> <math>\frac{4(k^2-4p^2)}{k^2(k^2-4p^2)}x^2 + \frac{4k^2}{k^2(k^2 - 4p^2)}y^2 = 1</math> <math>\frac{4}{(2a)^2}x^2 + \frac{4}{(2a)^2 - 4p^2}y^2 = 1</math> <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> <math></math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Second definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Graph of ellipse <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where <math>a,b = 20,12</math>.''' </br> At point <math>B,\ \frac{u}{v} = e.</math> </br> At point <math>A,\ \frac{a}{t} = e.</math> ]] Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. Let <math>\frac{p}{a} = e</math> where: * <math>p</math> is non-zero, * <math>a > p,</math> * <math>a = p + u.</math> Therefore, <math>1 > e > 0.</math> Let directrix have equation <math>x = t</math> where <math>\frac{a}{t} = e.</math> At point <math>B:</math> <math>\frac{p}{p+u} = \frac{p+u}{p+u+v} = e</math> <math>(p+u)^2 = p(p+u+v)</math> <math>pp + pu + pu + uu = pp + pu + pv</math> <math>pu + uu = pv</math> <math>u(p + u) = pv</math> <math>\frac{u}{v} = \frac{p}{p+u} = e</math> <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e\ \dots\ (3)</math> Statement <math>(3)</math> is true at point <math>A</math> also. Section under "Proof" below proves that statement (3) is true for any point <math>P</math> on ellipse. {{RoundBoxBottom}} ===Proof=== {{RoundBoxTop|theme=2}} [[File:0902ellipse00.png|thumb|400px|'''Proving that <math>\frac{\text{distance from point to focus}}{\text{distance from point to directrix}} = e</math>.''' </br> Graph is part of curve <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1.</math> </br> distance to Directrix1 <math>= t - x = \frac{a}{e} - x = \frac{a - ex}{e}.</math> </br> base = <math>x - p = x - ae</math> </br> <math>\text{(distance to Focus1)}^2 = \text{base}^2 + y^2</math> ]] As expressed above in statement <math>3,</math> second definition of ellipse states that ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. This section proves that this definition is true for any point <math>P</math> on the ellipse. At point <math>P:</math> <math>(a^2 - p^2)x^2 + a^2y^2 -a^2(a^2 - p^2) = 0</math> <math>y^2 = \frac{-(a^2 - p^2)x^2 + a^2(a^2 - p^2)}{a^2}</math> <math>= \frac{a^2e^2x^2 - a^2x^2 + a^2a^2 - a^2a^2e^2}{a^2}</math> <math>= e^2x^2 - x^2 + a^2 - a^2e^2</math> base <math>= x-p = x-ae</math> <math>(\text{distance}\ F_1P)^2 = y^2 + \text{base}^2 = y^2 + (x-ae)^2</math> <math>= a^2 - 2aex + e^2x^2</math> <math>= (a-ex)^2</math> <math>\text{distance to Focus1} = \text{distance}\ F_1P = a - ex</math> <math>\text{distance to Directrix1} = t - x = \frac{a}{e} - x = \frac{a-ex}{e}</math> <math>\frac{\text{distance to Focus1}}{\text{distance to Directrix1}}</math> <math>= (a - ex)\frac{e}{(a-ex)}</math> <math>= e</math> Similar calculations can be used to prove the case for Focus2 <math>(-p, 0)</math> and Directrix2 <math>(x = -t)</math> in which case: <math>\frac{\text{distance to Focus2}}{\text{distance to Directrix2}}</math> <math>= (a + ex)\frac{e}{(a + ex)}</math> <math>= e</math> Therefore: <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e</math> where <math>1 > e > 0.</math> Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant, called eccentricity <math>e.</math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Heading== ===Properties of ellipse=== {{RoundBoxTop|theme=2}} [[File:0822ellipse01.png|thumb|400px|'''Graph of ellipse used to illustrate and calculate certain properties of ellipses.''' </br> </br> Traditional definition of ellipse: </br> <math>\text{distance } AF_1 + \text{distance } AF_2 = \text{constant } k.</math> </br> </br> Second definition of ellipse: </br> <math>\frac{\text{distance } AF_1} {\text{distance } AG } = \text{eccentricity } e.</math> </br> </br> Triangle <math>A F_1 G</math> is right triangle. </br> <math>e = \cos \angle O F_1 A = \cos \angle F_1 A G</math> ]] Ellipse in diagram has: * Two foci: <math>F_1\ (p,0),\ F_2\ (-p,0).</math> * Length of major axis <math>= \text{distance } I_2 I_1 = 2a</math> * Length of minor axis <math>= \text{distance } A B = 2b</math> * Equation: <math>\frac {x^2} {a^2} + \frac {y^2} {b^2} = 1</math> * Length of latus rectum <math>= \text{distance } P Q</math> * Distance between directrices <math>= \text{distance } D_2 D_1 = 2t</math> Properties of ellipse: * <math>\frac{\text{length of major axis}} {\text{distance between directrices}} = e</math> * <math>\frac{\text{distance between foci}} {\text{length of major axis}} = e</math> * <math>\frac{\text{distance between foci}} {\text{distance between directrices}}= e^2</math> * <math>(\frac{\text{length of minor axis}} {\text{length of major axis}})^2 + e^2 = 1</math> * <math>\frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> * line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ====Major axis==== From traditional definition of ellipse: Distance <math>AF_2\ +</math> distance <math>AF_1</math> = distance <math>I_1F_1\ +</math> distance <math>I_1F_2</math> = distance <math>I_2F_2\ +</math> distance <math>I_2F_1</math> = <math>k.</math> Therefore: Length of major axis = distance <math>I_2I_1 = 2a = k.</math> Distance <math>AF_1 = \frac{k}{2} = a.</math> From second definition of ellipse: <math>\frac{\text{distance }AF_1}{\text{distance }AG} = \frac{a}{t} = \text{eccentricity }e</math> <math>= \frac{\text{distance }OI_1}{\text{distance }OD_1}.</math> <math>\frac{\text{length of major axis}}{\text{distance between directrices}} = e.</math> ====Foci==== From second definition of ellipse: <math>\frac{\text{distance }I_1F_1}{\text{distance }I_1D_1} = \frac{a-p}{t-a} = e.</math> <math>a - p = te - ae</math> <math>a - p = a - ae</math> Therefore: <math>p = ae</math> or <math>\frac{p}{a} = e.</math> <math>\frac{\text{distance between foci}}{\text{length of major axis}} = e.</math> <math>\frac{\text{distance between foci}}{\text{distance between directrices}} = e^2.</math> ====Minor axis==== Triangle <math>AOF_1</math> is right triangle. <math>\cos ^2 \angle OAF_1 + \sin ^2 \angle OAF_1</math> <math>= (\frac{b}{a})^2 + (\frac{p}{a})^2 </math> <math>= (\frac{b}{a})^2 + (\frac{ae}{a})^2 </math> <math>= (\frac{b}{a})^2 + e^2 = 1</math> <math>( \frac{\text{length of minor axis}} {\text{length of major axis}} )^2 + e^2 = 1</math> Triangles <math>AOF_1,\ AF_1G</math> are similar. Triangle <math>AF_1G</math> is right triangle. <math>e = \cos \angle OF_1A = \cos \angle F_1AG.</math> ====Latus rectum==== From second definition of ellipse: <math>\frac{\text{distance }PF_1} {\text{distance }F_1D_1} = \frac{\text{distance }PF_1}{t-p} = e</math> <math>\text{distance }PF_1 = te - pe = a - (ae)e = a(1-e^2).</math> <math>\frac{\text{distance }PF_1} {a} = 1 - e^2.</math> <math> \frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> ====Slope of curve==== Curve has equation: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math><math></math> <math>= \frac{-x(1-e^2)}{y}</math><math></math> At point <math>P:\ m_1 = y' = \frac{-p(1-e^2)}{-a(1-e^2)}</math> <math>= \frac{ae}{a} = e.</math><math></math> Slope of line <math>PD_1:\ m_2 = \frac{\text{distance }PF_1}{\text{distance }F_1D_1} = e.</math><math></math><math></math> <math>m_1 = m_2.</math> Therefore line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> ===Intercept form of equation=== <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1</math> <math></math> <math></math> {{RoundBoxTop|theme=2}} [[File:0625ellipse01.png|thumb|400px|'''Ellipse at origin with major axis on X axis.''' </br> </br> </br> </br> Equation of ellipse has format <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where: </br> </br> <math>\text{Length of major axis} = 2a = \text{distance}\ I_2I_1 = 40</math> </br> <math>\text{Length of minor axis} = 2b = \text{distance}\ BA = 24</math> </br> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> </br> <math>\frac{\text{Length of minor axis}}{\text{Length of major axis}} = \sqrt{1 - e^2}</math> </br> </br> <math>e = \sqrt{1 - \frac{b^2}{a^2}} = 0.8.</math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> ]] In diagram: Intercept <math>I_1</math> has coordinates <math>(a,0).</math> Intercept <math>I_2</math> has coordinates <math>(-a,0).</math> Intercept <math>A</math> has coordinates <math>(0,b).</math> Intercept <math>B</math> has coordinates <math>(0,-b).</math> Focus <math>F_1</math> has coordinates <math>(f,0)</math> where <math>f = ea.</math> Focus <math>F_2</math> has coordinates <math>(-f,0).</math> Curve has equation <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1,</math> called intercept form of equation of ellipse because intercepts are apparent as the fractional value of each coefficient. Standard form of this equation is: <math>(-0.36)x^2 + (-1)y^2 + (0)xy + (0)x + (0)y + (144) = 0.</math> While the standard form is valuable as input to a computer program, the intercept form is still attractive to the human eye because center of ellipse and intercepts are neatly contained within the equation. Slope of curve: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math> <math>= \frac{-x(1-e^2)}{y}</math> At point <math>P</math> on latus rectum <math>PQ:</math> <math>m_1 = y' = \frac{-(ea)(1-e^2)}{-(a(1-e^2))} = e</math> Slope of line <math>PD = m_2 = \frac{PF_1}{F_1D} = e</math> <math>m_1 = m_2.</math> Line <math>PD</math> is tangent to curve at latus rectum, point <math>P.</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Example=== {{RoundBoxTop|theme=2}} [[File:0618ellipse01.png|thumb|400px|'''Traditional definition of ellipse uses abc, epq.''' </br> M is mid-point between F1 and F2. </br> Point R is on minor axis. </br> </br> <math>\frac{\text{distance from R to F1}}{\text{distance from R to directrix 1}}</math> <math>= e</math> </br> </br> <math>= \frac{\text{half major axis}}{\text{distance from M to directrix 1}}</math> </br> </br> <math>\text{distance from M to directrix 1} = \frac{\text{half major axis}}{e}</math> </br> </br> <math>\text{F1:}\ (1, -7)</math> </br> <math>\text{F2:}\ (-1.24, 0.68)</math> </br> length_of_major_axis = 10 </br> <math>\text{M:}\ (-0.12, -3.16)</math> </br> length_of_minor_axis = 6 </br> <math>\text{R:}\ (2.76, -2.32)</math> </br> <math>e = 0.8</math> </br> <math>\text{D1:}\ (1.63, -9.16)</math> </br> <math>\text{Directrix 1:}\ (-0.28)x + (0.96)y + (9.25) = 0</math> </br> <math>\text{abc}\ =\ (-0.28,\ 0.96,\ 9.25)</math> </br> <math>\text{epq}\ =\ (0.8,\ 1,\ -7)</math> ]] Given: <syntaxhighlight lang=python> # python code F1 = 1, -7 # Focus 1 F2 = -1.24, 0.68 # Focus 2 length_of_major_axis = 10 </syntaxhighlight> Calculate equation of ellipse. <syntaxhighlight lang=python> F1 = p1,q1 = [ dD(str(v)) for v in F1 ] # Focus 1 F2 = p2,q2 = [ dD(str(v)) for v in F2 ] # Focus 2 length_of_major_axis = dD(length_of_major_axis) half_major_axis = length_of_major_axis / 2 # Direction cosines from F1 to F2 dx = p2-p1 ; dy = q2-q1 divider = (dx**2 + dy**2).sqrt() dx,dy = [ (v/divider) for v in (dx,dy) ] # F2 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 distance_F1_F2 = (q2-q1)/dy half_distance_F1_F2 = distance_F1_F2 / 2 # The mid-point M = xM,ym = p1 + dx*half_distance_F1_F2, q1 + dy*half_distance_F1_F2 # Eccentricity: e = distance_F1_F2 / length_of_major_axis # distance from point R to F1 half_major_axis # ------------------------------------ = e = ----------------------------------------- # distance from point R to Directrix 1 distance from point M to Directrix 1 distance_from_point_M_to_dx1 = half_major_axis / e # Intersection of axis and directrix 1 D1 = xM-dx*distance_from_point_M_to_dx1, yM-dy*distance_from_point_M_to_dx1 D1 = xD1, yD1 = [ reduce_Decimal_number(v) for v in D1 ] # Equation of Directrix 1 # dx1 = adx1,bdx1,cdx1 adx1,bdx1 = dx, dy # Perpendicular to axis. # adx1*x + bdx1*y + cdx1 = 0 # Directrix 1 contains point D1 cdx1 = reduce_Decimal_number( -( adx1*xD1 + bdx1*yD1 ) ) abc = adx1,bdx1,cdx1 epq = e,p1,q1 ABCDEF = ABCDEF_from_abc_epq (abc,epq, 1) </syntaxhighlight> Equation of ellipse in standard form: <math>(-0.949824)x^2 + (-0.410176)y^2 + (-0.344064)xy + (-1.3152)x + (-2.6336)y + (4.76) = 0</math> For more insight into method of calculation and proof: <syntaxhighlight lang=python> if 1 : print ('F1: ({}, {})'.format(p1,q1)) print ('F1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p1,q1)) print ('F2: ({}, {})'.format(p2,q2)) print ('F2: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p2,q2)) print ('length_of_major_axis =', length_of_major_axis) print ('M: ({}, {})'.format(xM,yM)) print ('M: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xM,yM)) # half_minor_axis**2 + half_distance_F1_F2**2 = half_major_axis**2 half_minor_axis = (half_major_axis**2 - half_distance_F1_F2**2).sqrt() length_of_minor_axis = half_minor_axis * 2 s1 = 'length_of_minor_axis' ; print (s1, '=', eval(s1)) # Direction cosines on major axis: print ('dx,dy =', dx,dy) # Direction cosines on minor axis: dnx,dny = dy,-dx print ('dnx,dny =', dnx,dny) # One point on minor axis: R = xR,yR = xM + dnx*half_minor_axis, yM + dny*half_minor_axis print ('R: ({}, {})'.format(xR,yR)) print ('R: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xR,yR)) # Verify that point R is on ellipse: sum_zero((A*xR**2, B*yR**2, C*xR*yR, D*xR, E*yR, F)) and 1/0 s1 = 'e' ; print (s1, '=', eval(s1)) print ('D1: ({}, {})'.format(xD1,yD1)) print ('D1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xD1,yD1)) print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(adx1, bdx1, cdx1)) print() # For proof, reverse the process: (abc1,epq1), (abc2,epq2) = calculate_abc_epq (ABCDEF) a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(a1, b1, c1)) print ('Eccentricity e1: {}'.format(e1)) print ('F1: ({}, {})'.format(p1,q1)) print() a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 print ('Directrix 2: ({})x + ({})y + ({}) = 0'.format(a2, b2, c2)) print ('Eccentricity e2: {}'.format(e2)) print ('F2: ({}, {})'.format(p2,q2)) print ('\nEquation of ellipse with integer coefficients:') A,B,C,D,E,F = [ reduce_Decimal_number(-v*1000000/64) for v in ABCDEF ] str1 = '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0' print (str1.format(A,B,C,D,E,F)) </syntaxhighlight> <syntaxhighlight> F1: (1, -7) F1: (x - (1))^2 + (y - (-7))^2 = 1 F2: (-1.24, 0.68) F2: (x - (-1.24))^2 + (y - (0.68))^2 = 1 length_of_major_axis = 10 M: (-0.12, -3.16) M: (x - (-0.12))^2 + (y - (-3.16))^2 = 1 length_of_minor_axis = 6 dx,dy = -0.28 0.96 dnx,dny = 0.96 0.28 R: (2.76, -2.32) R: (x - (2.76))^2 + (y - (-2.32))^2 = 1 e = 0.8 D1: (1.63, -9.16) D1: (x - (1.63))^2 + (y - (-9.16))^2 = 1 Directrix 1: (-0.28)x + (0.96)y + (9.25) = 0 Directrix 1: (0.28)x + (-0.96)y + (-9.25) = 0 Eccentricity e1: 0.8 F1: (1, -7) Directrix 2: (0.28)x + (-0.96)y + (3.25) = 0 Eccentricity e2: 0.8 F2: (-1.24, 0.68) Equation of ellipse with integer coefficients: </syntaxhighlight> <math>(14841)x^2 + (6409)y^2 + (5376)xy + (20550)x + (41150)y + (-74375) = 0</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} =allEqual= {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em;"> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> ====Welcomee==== {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFF800; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> =====Welcomen===== {{Robelbox|title=|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFFFFF; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> <syntaxhighlight lang=python> # python code. if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 : pass </syntaxhighlight> {{Robelbox/close}} {{Robelbox/close}} {{Robelbox/close}} <noinclude> [[Category: main page templates]] </noinclude> {| class="wikitable" |- ! <math>x</math> !! <math>x^2 - N</math> |- | <code></code><code>6</code> || <code>-221</code> |- | <code></code><code>7</code> || <code>-208</code> |- |- | <code>10</code> || <code>-157</code> |- | <code>11</code> || <code>-136</code> |- | <code>12</code> || <code>-113</code> |- | <code>13</code> || <code></code><code>-88</code> |- | <code>26</code> || <code></code><code>419</code> |} =Testing= ======table1====== {|style="border-left:solid 3px blue;border-right:solid 3px blue;border-top:solid 3px blue;border-bottom:solid 3px blue;" align="center" | Hello As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 </syntaxhighlight> |} {{RoundBoxTop|theme=2}} [[File:0410cubic01.png|thumb|400px|''' Graph of cubic function with coefficient a negative.''' </br> There is no absolute maximum or absolute minimum. ]] Coefficient <math>a</math> may be negative as shown in diagram. As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. Unless stated otherwise, any reference to "cubic function" on this page will assume coefficient <math>a</math> positive. {{RoundBoxBottom}} <math>x_{poi} = -1</math> <math></math> <math></math> <math></math> <math></math> =====Various planes in 3 dimensions===== {{RoundBoxTop|theme=2}} <gallery> File:0713x=4.png|<small>plane x=4.</small> File:0713y=3.png|<small>plane y=3.</small> File:0713z=-2.png|<small>plane z=-2.</small> </gallery> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 6872533965463318088296406206152583523950547457502877599617298355752203375318570113543746034084988471 6038689997069900481503054402779031645424782306849293691862158057846311159666871301301561856898723723 5288509264861249497715421833420428568606014682472077143585487415565706967765372022648544701585880162 0758474922657226002085584466521458398893944370926591800311388246468157082630100594858704003186480342 1948972782906410450726368813137398552561173220402450912277002269411275736272804957381089675040183698 6836845072579936472906076299694138047565482372899718032680247442062926912485905218100445984215059112 0249441341728531478105803603371077309182869314710171111683916581726889419758716582152128229518488472 </syntaxhighlight> <math>\theta_1</math> {{RoundBoxTop|theme=2}} [[File:0422xx_x_2.png|thumb|400px|''' Figure 1: Diagram illustrating relationship between <math>f(x) = x^2 - x - 2</math> and <math>f'(x) = 2x - 1.</math>''' </br> ]] {{RoundBoxBottom}} <math>O\ (0,0,0)</math> <math>M\ (A_1,B_1,C_1)</math> <math>N\ (A_2,B_2,C_2)</math> <math>\theta</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} (6) - (7),\ 4Apq + 2Bq =&\ 0\\ 2Ap + B =&\ 0\\ 2Ap =&\ - B\\ \\ p =&\ \frac{-B}{2A}\ \dots\ (8) \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} 1.&4141475869yugh\\ &2645er3423231sgdtrf\\ &dhcgfyrt45erwesd \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math> 4\sin 18^\circ = \sqrt{2(3 - \sqrt 5)} = \sqrt 5 - 1 </math> 98umq6ni448ew5y0y73olo292tqannp 2835151 2835150 2026-09-30T10:15:49Z ThaniosAkro 2805358 /* Using Decimal numbers: */ 2835151 wikitext text/x-wiki ==Table== {| class="wikitable" |- | From <math>(3):</math> || <math>p^3</math>|| || <math>+Ap</math> || <math>+B</math>|| <math>= 0</math> || <math>\dots (5)</math> |- | From <math>(4):</math> || || <math>Cp^2</math>|| <math></math> || <math>+D</math>|| <math>= 0</math> || <math>\dots (6)</math> |- | <math>(5)*D</math> || <math>Dp^3</math>|| || <math>+DAp</math> || <math>+DB</math>|| <math>= 0</math> || <math>\dots (7)</math> |- | <math>(6)*B</math> || || <math>BCp^2</math>|| <math></math> || <math>+BD</math>|| <math>= 0</math> || <math>\dots (8)</math> |- | <math>(7)-(8)</math> || <math>Dp^3</math>||<math>-BCp^2</math> || <math>+DAp</math> || <math></math>|| <math>= 0</math> || <math>\dots (9)</math> |- | Simplify <math>(9)</math> || <math></math>||<math>Dp^2</math> || <math>-BCp</math> || <math>+DA</math>|| <math>= 0</math> || <math>\dots (10)</math> |- | <math>(6)*A</math> || || <math>ACp^2</math>|| <math></math> || <math>+AD</math>|| <math>= 0</math> || <math>\dots (11)</math> |- | <math>(10)-(11)</math> || <math></math>||<math>Dp^2-ACp^2</math> || <math>-BCp</math> || <math></math>|| <math>= 0</math> || <math>\dots (12)</math> |- | Simplify <math>(12)</math> || <math></math>|| || <math>Dp-ACp</math> || <math>-BC</math> || <math>= 0</math> || <math>\dots (13)</math> |} ====First result==== <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> Calculate values_of_i : <syntaxhighlight lang=python> print ('\nWhen ints become huge:') values_of_i = solveMbyN (matrix) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> When ints become huge: solveMbyN (input_, level = -41) : <class 'OverflowError'> OverflowError('int too large to convert to float') Length of input = 23 input_[0] = Error in this row. input_[1] = Error in this row. input_[2] = Error in this row. input_[3] = [-7.048390979785929e+176, 1.1003906499643917e+176, 1.5070856217200028e+174, 1.955699032422673e+173, ...... 0.0] input_[4] = [510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[5] = [0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[6] = [0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, 220.0, ...... 0.0] input_[7] = Error in this row. values_of_i = None </syntaxhighlight> <syntaxhighlight lang=python> print ('\nConvert input to floats:') matrix1 = [ list(v) for v in matrix ] matrix1[0][0] = float(matrix1[0][0]) values_of_i = solveMbyN (matrix1) sx = 'values_of_i' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> Convert input to floats: solveMbyN (input_, level = -40) : <class 'KeyError'> KeyError('Internal error. input[1][0] = nan, should be 0.') Length of input = 24 input_[0] = [-1.7360455505275518e+174, 1.4096781959571856e+174, -2.2007812999287836e+173, -3.014171243439967e+171, ...... 0.0] input_[1] = [-3.7974175914221006e+162, 3.309163202261842e+161, 2.4114748810711523e+162, -4.426635506031073e+161, ...... 0.0] input_[2] = [-2.4975968400753463e+139, 5.704494025143264e+138, -2.7146889822895123e+138, 1.4057733058789272e+139, ...... 0.0] input_[3] = [7.667237322891148e+182, -1.7692205437935546e+182, -2.341735229706114e+180, 4.1615580570562045e+181, ...... -0.0] input_[4] = [-500.0, 0.0, 0.0, 0.0, 0.0, 1240.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, 0.0, 0.0, 0.0, 690.0, -320.0, ...... 0.0] input_[5] = [0.0, 510.0, 0.0, 0.0, 0.0, 320.0, -1150.0, 270.0, 0.0, 0.0, 320.0, -590.0, 270.0, 0.0, 0.0, 320.0, -590.0, ...... 0.0] input_[6] = [0.0, 0.0, 520.0, 0.0, 0.0, 0.0, 270.0, -1060.0, 220.0, 0.0, 0.0, 270.0, -490.0, 220.0, 0.0, 0.0, 270.0, ...... 0.0] input_[7] = [0.0, 0.0, 0.0, 530.0, 0.0, 0.0, 0.0, 220.0, -970.0, 170.0, 0.0, 0.0, 220.0, -390.0, 170.0, 0.0, 0.0, ...... 0.0] values_of_i = None </syntaxhighlight> =====Success===== <syntaxhighlight lang=python> print ('\nSet global variable enable_reduceRow:') enable_reduceRow = 1 values_of_i = solveMbyN (matrix1) </syntaxhighlight> Success: <syntaxhighlight> Set global variable enable_reduceRow: i10 = 1.0000000000000049 ; i11 = 1.643236374952256 ; i12 = 2.316468657232291 ; i13 = 3.0507456069545116 i14 = 3.908085797412319 ; i15 = 0.5970301043016677 ; i16 = 0.8274774533758196; i17 = 1.225283946841065 i18 = 1.5617922630400025 ; i19 = 0.369273540611037 ; i20 = 0.3858385105885722; i21 = 0.6270001063825295 i22 = 0.7040607630623028 ; i23 = 0.6129764173251202 ; i24 = 0.298576896960036 ; i25 = 0.44960726241462035 i26 = 0.7812212615819403 ; i27 = 0.7165761045550649 ; i28 = 0.5186812635664733; i29 = 0.266770119423805 i30 = 0.5896680016803755 ; i31 = 1.475274068751303 ; i32 = 0.9632057010422588; i33 = 0.5801910619990465 i34 = 0.30799558703953794; i35 = 2.4693659910366916 ; i36 = 1.583773707944257 ; i37 = 1.0123878002551232 i38 = 0.6135963601029517 ; i39 = 0.3175434839291887 ; i40 = 2.7147355593758107; i41 = 2.125067557695435 i42 = 1.6754602952808149 ; i43 = 1.2896217846922426 ; i44 = 0.692591680390575 ; i45 = 0.8855922830924343 i46 = 1.7538676385971101 ; i47 = 1.4222536394297902 ; i48 = 1.181092043635833 ; i49 = 0.6432363749522512 i50 = 0.5713859076891339 ; i51 = 1.0834542753981782 ; i52 = 1.1480994324250535; i53 = 1.0710387757452802 i54 = 0.6732322822800348 ; i55 = 0.39879144015217155; i56 = 0.7818060791953839; i57 = 0.9797009201839757 i58 = 1.0707852659211583 ; i59 = 0.7342769497222208 ; i60 = 0.2960528761737631; i61 = 0.6419329634235106 i62 = 0.8938441075661789 ; i63 = 1.2082436279312632 ; i64 = 0.8573401904578074; i65 = 0.2438588716389498 i66 = 0.5518544586784879 ; i67 = 0.8186245781022927 ; i68 = 1.1172014750623287; i69 = 1.4864750156733657 i70 = -0.3074083196094299; i71 = 1.5434221599024214 ; i72 = 1.7538814225756034; i73 = -0.07368461229023889 # Notice that i70, i73 are negative. </syntaxhighlight> =====Check all conditions===== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", """+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 = e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69""", """+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 = e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14""", """+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 = e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14""", """+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 = e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14""", """+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 = e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14""" ] </syntaxhighlight> Two Auxiliary Functions: <syntaxhighlight lang=python> def sum_zero (values, tolerance = None) : ''' This function calculates sum of all values in input. If sum is very close to zero, sum is returned as zero. For example: sum_zero((2, -1.99999999999999999999999)) is returned as 0. ''' if tolerance == None : tolerance = Tolerance sump = sumn = 0 for v in values : if v > 0 : sump += v elif v < 0 : sumn -= v max = (sumn, sump)[sump > sumn] sum = sump - sumn if abs(sum) < tolerance: return type(sum)(0) if abs(sum) < tolerance*max : return type(sum)(0) return sum def convert_str_to_tuple (input_str) : ''' input is str like "+ i35 + i40 + i72 - i14 - i69 - i71" or "+ i35 + i40 + i72 == i14 + i69 + i71" This function returns tuple : (i35, i40, i72, - i14, - i69, - i71) ''' str0 = ' '.join(input_str.split()) if '=' in str0 : if '==' in str0 : splitter = '==' else : splitter = '=' str1,str2 = str0.split(splitter) t1 = convert_str_to_tuple (str1) t2 = convert_str_to_tuple (str2) return t1 + tuple(-v for v in t2) str1 = ';+'.join(str0.split('+')) str2 = ';-'.join(str1.split('-')) str3 = ','.join([ v for v in str2.split(';') if v.strip() ]) return eval(str3 + ',') </syntaxhighlight> Check 83 conditions: <syntaxhighlight lang=python> all_conditions = (iconditions + econditions + more_econditions + extra_test_conditions) # Following string is executable python code. exc_str_64ei = """ ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = [ i*R for i,R in zip ( values_of_i, values_of_R ) ] ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = values_of_e """ exec(exc_str_64ei) tolerance = 1e-15 count = errors = 0 for condition in all_conditions : t1 = convert_str_to_tuple (condition) sum = sum_zero(t1, tolerance) count += 1 if sum : sx = 'sum, condition' ; print (sx, '=', eval(sx)) errors += 1 print ('Number of tests =', count) print ('Number of errors =', errors) </syntaxhighlight> With tolerance of <math>1e-15</math> there are 21 errors: <syntaxhighlight> sum, condition = (1.2505552149377763e-12, '+ e48 + e16 - e21 - e53') sum, condition = (1.2505552149377763e-12, '+ e49 + e11 - e16 - e54') sum, condition = (7.958078640513122e-13, '+ e52 + e22 - e27 - e57') sum, condition = (1.1368683772161603e-12, '+ e53 + e17 - e22 - e58') sum, condition = (2.2737367544323206e-12, '+ e54 + e12 - e17 - e59') ...... ...... Number of tests = 83 Number of errors = 21 </syntaxhighlight> With tolerance of <math>1e-14</math> there are no errors. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ====Calculate R==== <syntaxhighlight> </syntaxhighlight> Produce matrix corrected: <syntaxhighlight lang=python> print ('\nCreating new matrix with corrections:') matrix1 = [ list(v) for v in matrix ] # Deep copy. # e70, i70 are at position 60 in each row of matrix1. # e73, i73 are at position 63 in each row of matrix1. for row in matrix1 : for p in (60,63) : if row[p] : row[p] *= -1 </syntaxhighlight> Circuit parameters: <syntaxhighlight> values_of_circuit_current = ('i40 + i72 + i35', 'i14 + i71 + i69') values_of_circuit_voltage = ( 'e72 + e46 + e47 + e48 + e70 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e73 + e61 + e62 + e63 + e71', 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14', 'e35 + e36 + e37 + e38 + e39 + e65 + e66 + e67 + e68 + e69', 'e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69', 'e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69', 'e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69', 'e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69', 'e35 + e45 + e46 + e47 + e48 + e49 + e11 + e12 + e13 + e14', 'e35 + e36 + e50 + e51 + e52 + e53 + e54 + e12 + e13 + e14', 'e35 + e36 + e37 + e55 + e56 + e57 + e58 + e59 + e13 + e14', 'e35 + e36 + e37 + e38 + e60 + e61 + e62 + e63 + e64 + e14', 'e72 + e31 - e50 + e37 + e38 + e39 + e73 + e61 - e28 + e57' + ( '- e22 + e53 - e16 + e70 + e10 + e11 + e12 + e13 + e14') ) </syntaxhighlight> =====Using floating point numbers:===== <syntaxhighlight lang=python> # python code: number_of_columns = 65 one = 1 ; Tolerance = 1e-14 # Following string is executable python code: exc_str1 = """ Values_of_R = [] for I in range(10, 74): new_line = [ 0 ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = one i = (I)/10 new_line[-1] = -i matrix1[-1] = new_line values_of_i = solveMbyN (matrix1) exec(exc_str_64ei) for Istr in values_of_circuit_current : I = eval(Istr) for Estr in values_of_circuit_voltage : E = eval(Estr) ; R = E/I ; Values_of_R += [R] print ('Number of calculations =', len(Values_of_R)) tmp = sorted(Values_of_R) minR = tmp[0] ; maxR = tmp[-1] s1 = 'minR' ; print(s1,'=',eval(s1)) s1 = 'maxR' ; print(s1,'=',eval(s1)) sum = sum_zero((minR, -maxR)) s1 = 'sum' ; print(s1,'=',eval(s1)) if not sum : print ('With Tolerance of {}, both minR and maxR are equal.'.format(Tolerance)) """ exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.9285759884408 maxR = 723.9285759884439 sum = 0.0 With Tolerance of 1e-14, both minR and maxR are equal. </syntaxhighlight> This code produced 1664 values of R from minR through maxR, both included. With tolerance of <math>1e-14</math> all values of resistance R = 723.92857598844. =====Using Decimal numbers:===== With <code>enable_reduceRow</code> clear : <syntaxhighlight lang=python> enable_reduceRow = 0 Precision = dgt.prec = 60 Tolerance = dD('1e-' + str(Precision-3)) one = dD(1) try : exec(exc_str1) except : pass </syntaxhighlight> <syntaxhighlight> solveMbyN (input_, level = -52) : <class 'decimal.Overflow'> Overflow([<class 'decimal.Overflow'>]) Length of input = 12 input_[0] = [-inf, inf, -inf, inf, inf, -inf, inf, -inf, inf, -inf, -inf, inf, 0.0] input_[1] = [inf, -inf, -inf, -inf, -inf, inf, -inf, -inf, -inf, -inf, inf, -inf, 0.0] input_[2] = [-inf, inf, inf, inf, -inf, -inf, inf, inf, -inf, inf, inf, inf, 0.0] input_[3] = [inf, -inf, -inf, inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, 0.0] input_[4] = [620.0, 0.0, 0.0, 0.0, 290.0, -1200.0, 240.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[5] = [0.0, 630.0, 0.0, 0.0, 0.0, 240.0, -1110.0, 190.0, 0.0, 0.0, 0.0, 0.0, 0.0] input_[6] = [inf, -inf, inf, -inf, -inf, inf, -inf, -inf, inf, -inf, inf, -inf, 0.0] input_[7] = [-inf, inf, inf, inf, inf, -inf, inf, inf, inf, inf, -inf, inf, 0.0] </syntaxhighlight> With <code>enable_reduceRow</code> set : <syntaxhighlight lang=python> enable_reduceRow = 1 exec(exc_str1) </syntaxhighlight> <syntaxhighlight> Number of calculations = 1664 minR = 723.928575988442547699732563335265663515838075102937503680560 maxR = 723.928575988442547699732563335265663515838075102937503680663 sum = 0 With Tolerance of 1E-57, both minR and maxR are equal. </syntaxhighlight> With tolerance of <math>1e-57</math> all values of resistance R = 723.928575988442547699732563335265663515838075102937503681. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math>\text{R}</math> is printed with precision of 60. ==Making the Decimal object== The following function verifies that we are working with Decimal objects. <syntaxhighlight lang=python> import sys import decimal getcontext = decimal.getcontext dD = D = Decimal = decimal.Decimal DT = decimal.DecimalTuple dgt = decimal.getcontext() dgt.prec = 50 def print_error (error, x=None, thisName=None) : """ Prints error derived from sys.exc_info(). """ list1 = error.split(',') v1 = ','.join(list1[1:-1]) if thisName : print (thisName) if x != None : print (' Input =', (str(x))[:60]) print (' ', list1[0]) print (' ', v1) print (' ', list1[-1]) def makeDecimal (x, flag = 0) : ''' output = makeDecimal (x [, flag]) x is a single object convertible to Decimal object. returns Decimal object or returns None on error. ''' thisName = 'makeDecimal (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, dD) : return x if isinstance(x, int) : return dD(x) if isinstance(x, float) : return dD(str(x)) if isinstance(x, str) : try : error = '' output = dD(x) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if isinstance(x, (list,tuple,DT)) : try : error = '' v1,v2,v3 = x if isinstance(v2, (tuple,list)) : output = dD(x) else : output = dD( ( v1, list(v2), v3 ) ) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return None return output if flag : print (' Input not recognized.') return None </syntaxhighlight> ===checkComplex(x)=== This function verifies that the object is a valid complex tuple. <syntaxhighlight lang=python> def checkComplex(x, flag = 0) : """ status = checkComplex(x [, flag]) x must be : (v1,v2,'rectangular') or (v1,v2,'polar') v1,v2 must be type Decimal. """ thisName = 'checkComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) try: error = '' v1,v2,str1 = x isinstance (v1,dD) or ({}['v1 must be type Decimal.']) isinstance (v2,dD) or ({}['v2 must be type Decimal.']) (isinstance (str1,str) and str1) or ({}['str1 must be valid string.']) str1 = str1.lower() if str1 == 'rectangular'[:len(str1)] : pass elif str1 == 'polar'[:len(str1)] : pass else : ({}['str1 must be "rectangular" or "polar".']) except : error = str(sys.exc_info()) if error : if flag : print_error (error) return False return True </syntaxhighlight> ===str_to_complex (input_string)=== <syntaxhighlight lang=python> import re # The re pattern for numbers to be found in string of type complex. # In string like ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' # extracts '1234567890987654323456E-6' and '+987654321234567890987e+2J'. # eval allows ' 12_3456_7890_9876_5432_3456E-6 + 987654321234567890987e+2J '. # Conversion to Decimal allows: '__987_65432123____4567890_987___'. # eval does not allow ' 0123 ' but allows ' 2e04 '. # Conversion to Decimal allows: ' 0123 ' digits = '[_0123456789]' integer = '[_0123456789]{1,}' # Matches 1 23 345 4567 56789 exponent = '[Ee][\+\-]{{0,1}}{}'.format(integer) # Matches e8 e+8 e-8 or E8 E+8 E-8 Exponent = '({}){{0,1}}'.format(exponent) # exponent 0 or 1 times. float1 = '({})\.{{0,1}}'.format(integer) # Matches 123 2345. float2 = '{}{{0,}}\.{}'.format(digits, integer) # Matches 123.345 .345 float_ = '(({})|({}))'.format(float2,float1) rvalue = '{}({})'.format(float_,Exponent) rvalue_signed = '[\+\-]{{0,1}}{}'.format(rvalue) ivalue_signed = '{}[Jj]'.format(rvalue_signed) def str_to_complex (input_string) : """ a,b = str_to_complex (input_string) input_string could be ' 1234567890987654323456E-6 + 987654321234567890987e+2J ' input_string could be ' ' ' ( 12345678909876543234561234567890987.654323456E-6 + 987654321234567890987987654321.23764567890987e+2J ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or ' ' ' - ( ( 12345678_90543123456789054_312345678905431234567890543e-014 + # Note the '_' 543123456789054_3123456789054312345_67890543654327453E-1_3J ) ) ' ' ' or '4', '-4', '(4)', '(-4)', '-(4)', '-(-4)' or '( +3j)', '+(-3J)', '-(3j)', '-(-3J)' or '( 4+3j)', '+(-3 + 4J)','-( 4+3j)', '-(-3 + 4J)', This function retains precision of a,b """ try : status = 0 isinstance(input_string,str) or ({}['input_string not type str.']) str1 = input_string.strip() cx1 = eval(str1) isinstance(cx1,(int,float,complex)) or ({}['cx1 not desired type.']) except : status = 1 if status : return # This code removes white lines and comments, if any, at end of each line. new_line = ''' '''[-1:] lines = [ line for Line in str1.split(new_line) for line in [ Line.rstrip() ] if line ] lines = [ v for line in lines for parts in [ line.split('#') ] for v in [ parts[0]] ] str1 = ''.join(lines) str1 = ''.join(str1.split()) if isinstance (cx1, (int,float)) : resultr = re.search(rvalue_signed, str1) resultr or ({}['rvalue not found.']) dD1 = dD(resultr[0]) v1 = eval(str(dD1)) if v1 == cx1 : return dD1,dD(0) if v1 == -cx1 : return -dD1,dD(0) ({}['dD1 not recognized.']) # cx1 must be complex. It must contain imaginary value. resulti = re.search(ivalue_signed, str1) resulti or ({}['ivalue not found.']) str2j = resulti[0] ; str2 = str2j[:-1] dD2 = dD(str2) str1 = ''.join(str1.split(str2j)) # cx1 may contain real value. resultr = re.search(rvalue_signed, str1) if resultr : dD1 = dD(resultr[0]) else : dD1 = dD(0) cx2 = complex(dD1,dD2) if cx2.real == cx1.real : pass elif cx2.real == -cx1.real : dD1 = dD1.copy_negate() else : ({}['dD1 Not Recognized.']) if cx2.imag == cx1.imag : pass elif cx2.imag == -cx1.imag : dD2 = dD2.copy_negate() else : ({}['dD2 Not Recognized.']) cx3 = complex(dD1, dD2) if cx3 == cx1 : return dD1,dD2 ({}['No match for cx3.']) </syntaxhighlight> ===makeComplex(x)=== <syntaxhighlight lang=python> def makeComplex (x, flag = 0) : ''' result = makeComplex (x[, flag]) Input can be tuple with 1,2 or 3 members. If 1 or 2 members, 'rect' is understood. The one member or single object may be int, float, complex, CompleX or string convertible to int, float or complex. x = makeComplex(4) x = makeComplex((4,)) x = makeComplex(('4',0)) x = makeComplex((4,'0', 'rect')) x = makeComplex(4+0j) x = makeComplex('4+0j') x = makeComplex(('4+0j',)) In all seven cases above x = ( Decimal('4'), Decimal('0'), 'rect' ) output is always (modulus, phase, "polar") or (real_part, imag_part, "rect") modulus, phase, real_part, imag_part are Decimal objects. On error returns None. ''' thisName = 'makeComplex (x) :' if flag : print () print (thisName) print (' Input x =', type(x), (str(x))[:60]) if isinstance(x, CompleX) : # New class CompleX (note the punctuation.) x.check() return (x.r, x.i, 'rect') if isinstance (x,complex) : return makeComplex (( x.real, x.imag )) try : status = 1 a,b = str_to_complex (x) except : status = 0 if status : return a,b,'rect' try : status = 1 result = makeDecimal(x) isinstance(result, Decimal) or ({}['Expecting result to be type Decimal.']) output = result,dD(0),'rect' except : status = 0 if status : return output try : status = 1 v1, = x # Allow for (( 3+4j ),) except : status = 0 if status : return makeComplex (v1) try : status = 1 ; error = '' if len(x) == 2 : v1,v2 = [ makeDecimal (v) for v in x ] str1 = 'rect' elif len(x) == 3 : v1,v2,str1 = x v1,v2 = [ makeDecimal (v) for v in (v1,v2) ] else : ({}['len(x) not in (2,3)']) output = v1,v2,str1 checkComplex(output) or ({}['output not valid complex.']) if str1[0] in 'rR' : output = v1,v2,'rect' else : output = v1,v2,'polar' except : status = 0 ; error = str(sys.exc_info()) if status : return output if flag : print_error (error) return </syntaxhighlight> =Conic sections generally= Within the two dimensional space of Cartesian Coordinate Geometry a conic section may be located anywhere and have any orientation. This section examines the parabola, ellipse and hyperbola, showing how to calculate the equation of the section, and also how to calculate the foci and directrices given the equation. ==Latera recta et cetera== "Latus rectum" is a Latin expression meaning "straight side." According to Google, the Latin plural of "latus rectum" is "latera recta," but English allows "latus rectums" or possibly "lati rectums." The title of this section is poetry to the eyes and music to the ears of a Latin student and this author hopes that the gentle reader will permit such poetic licence in a mathematical topic. The translation of the title is "Latus rectums and other things." This section describes the calculation of interesting items associated with the ellipse: latus rectums, major axis, minor axis, focal chords, directrices and various points on these lines. When given the equation of an ellipse, the first thing is to calculate eccentricity, foci and directrices as shown above. Then verify that the curve is in fact an ellipse. From these values everything about the ellipse may be calculated. For example: {{RoundBoxTop|theme=2}} [[File:0608ellipse01.png|thumb|400px|'''Graph of ellipse <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math>''' </br> </br> Axis : (-0.8)x + (-0.6)y + (9.4) = 0</br> Eccentricity = 0.9</br> </br> Directrix 2 : (0.6)x + (-0.8)y + (2) = 0</br> Latus rectum RS : (0.6)x + (-0.8)y + (-0.8) = 0</br> Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0</br> Latus rectum PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0</br> Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0</br> </br> <math>\text{ID2}</math> = (6.32, 7.24)</br> <math>\text{I2}</math> = (7.204210526315789473684, 6.061052631578947368421)</br> F2 = (8, 5)</br> M = (15.16210526315789473684, -4.54947368421052631579)</br> F1 = (22.32421052631578947368, -14.09894736842105263158)</br> <math>\text{I1}</math> = (23.12, -15.16)</br> <math>\text{ID1}</math> = (24.00421052631578947368, -16.33894736842105263158)</br> </br> P = (20.30821052631578947368, -15.61094736842105263158)</br> Q = (10.53708406832736953616, -8.018239580333420216299)</br> R = (5.984, 3.488)</br> S = (10.016, 6.512)</br> T = (19.78712645798841993752, -1.080707788087632415281)</br> U = (24.34021052631578947368, -12.58694736842105263158)</br> </br> Length of major axis: <math>\text{I1I2}</math> = 26.52631578947368421052</br> Length of minor axis: QT = 11.56255298707631300170</br> Length of latus rectum: RS = PU = 5.04 ]] Consider conic section: <math>1771x^2 + 1204y^2 + 1944xy -44860x - 18520y + 214400 = 0.</math> This curve is ellipse with random orientation. <syntaxhighlight lang=python> # python code ABCDEF = A,B,C,D,E,F = 1771, 1204, 1944, -44860, -18520, 214400 # ellipse result = calculate_abc_epq(ABCDEF) (len(result) == 2) or 1/0 # ellipse or hyperbola (abc1,epq1), (abc2,epq2) = result a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 (e1 == e2) or 2/0 (1 > e1 > 0) or 3/0 print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) A,B,C,D,E,F = ABCDEF_from_abc_epq(abc1,epq1) print ('Equation of ellipse in standard form:') print ( '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0'.format(A,B,C,D,E,F) ) </syntaxhighlight> <syntaxhighlight> (1771)x^2 + (1204)y^2 + (1944)xy + (-44860)x + (-18520)y + (214400) = 0 Equation of ellipse in standard form: (-0.7084)x^2 + (-0.4816)y^2 + (-0.7776)xy + (17.944)x + (7.408)y + (-85.76) = 0 </syntaxhighlight> <syntaxhighlight lang=python> # python code def sum_zero(input) : ''' sum = sum_zero(input) If sum is close to 0 and Tolerance permits, sum is returned as 0. For example: if input contains (2, -1.999999999999999999999) this function returns sum of these 2 values as 0. ''' global Tolerance sump = sumn = 0 for v in input : if v > 0 : sump += v elif v < 0 : sumn -= v sum = sump - sumn if abs(sum) < Tolerance : return (type(Tolerance))(0) min, max = sorted((sumn,sump)) if abs(sum) <= Tolerance*min : return (type(Tolerance))(0) return sum </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Major axis=== <syntaxhighlight lang=python> # axis is perpendicular to directrix. ax,bx = b1,-a1 # axis contains foci. ax + by + c = 0 cx = reduce_Decimal_number(-(ax*p1 + bx*q1)) axis = ax,bx,cx print ( ' Axis : ({})x + ({})y + ({}) = 0'.format(ax,bx,cx) ) print ( ' Eccentricity = {}'.format(e1) ) print () print ( ' Directrix 1 : ({})x + ({})y + ({}) = 0'.format(a1,b1,c1) ) print ( ' Directrix 2 : ({})x + ({})y + ({}) = 0'.format(a2,b2,c2) ) F1 = p1,q1 # Focus 1. print ( ' F1 : ({}, {})'.format(p1,q1) ) F2 = p2,q2 # Focus 2. print ( ' F2 : ({}, {})'.format(p2,q2) ) # Direction cosines along axis from F1 towards F2: dx,dy = a1,b1 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 if dx : distance_F1_F2 = (p2 - p1)/dx else : distance_F1_F2 = (q2 - q1) if distance_F1_F2 < 0 : distance_F1_F2 *= -1 dx *= -1 ; dy *= -1 # Intercept on directrix1 distance_from_F1_to_ID1 = abs(a1*p1 + b1*q1 + c1) ID1 = xID1,yID1 = p1 - dx*distance_from_F1_to_ID1, q1 - dy*distance_from_F1_to_ID1 print ( ' Intercept ID1 : ({}, {})'.format(xID1,yID1) ) # # distance_F1_F2 # -------------------- = e # length_of_major_axis # length_of_major_axis = distance_F1_F2 / e1 # Intercept1 on curve distance_from_F1_to_curve = (length_of_major_axis - distance_F1_F2 )/2 xI1,yI1 = p1 - dx*distance_from_F1_to_curve, q1 - dy*distance_from_F1_to_curve I1 = xI1,yI1 = [ reduce_Decimal_number(v) for v in (xI1,yI1) ] print ( ' Intercept I1 : ({}, {})'.format(xI1,yI1) ) </syntaxhighlight> <syntaxhighlight> Axis : (-0.8)x + (-0.6)y + (9.4) = 0 Eccentricity = 0.9 Directrix 1 : (0.6)x + (-0.8)y + (-27.47368421052631578947) = 0 Directrix 2 : (0.6)x + (-0.8)y + (2) = 0 F1 : (22.32421052631578947368, -14.09894736842105263158) F2 : (8, 5) Intercept ID1 : (24.00421052631578947368, -16.33894736842105263158) Intercept I1 : (23.12, -15.16) </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>I2, ID2.</math> {{RoundBoxBottom}} ===Latus rectums=== <syntaxhighlight lang=python> # direction cosines along latus rectum. dlx,dly = -dy,dx # # distance from U to F1 half_latus_rectum # ------------------------------ = ----------------------- = e1 # distance from U to directrix 1 distance_from_F1_to_ID1 # half_latus_rectum = reduce_Decimal_number(e1*distance_from_F1_to_ID1) # latus rectum 1 # Focal chord has equation (afc)x + (bfc)y + (cfc) = 0. afc,bfc = a1,b1 cfc = reduce_Decimal_number(-(afc*p1 + bfc*q1)) print ( ' Focal chord PU : ({})x + ({})y + ({}) = 0'.format(afc,bfc,cfc) ) P = xP,yP = p1 + dlx*half_latus_rectum, q1 + dly*half_latus_rectum print ( ' Point P : ({}, {})'.format(xP,yP) ) U = xU,yU = p1 - dlx*half_latus_rectum, q1 - dly*half_latus_rectum print ( ' Point U : ({}, {})'.format(xU,yU) ) distance = reduce_Decimal_number(( (xP - xU)**2 + (yP - yU)**2 ).sqrt()) print (' Length PU =', distance) print (' half_latus_rectum =', half_latus_rectum) </syntaxhighlight> <syntaxhighlight> Focal chord PU : (0.6)x + (-0.8)y + (-24.67368421052631578947) = 0 Point P : (20.30821052631578947368, -15.61094736842105263158) Point U : (24.34021052631578947368, -12.58694736842105263158) Length PU = 5.04 half_latus_rectum = 2.52 </syntaxhighlight> {{RoundBoxTop|theme=2}} Techniques similar to above can be used to calculate points <math>R, S.</math> {{RoundBoxBottom}} ===Minor axis=== <syntaxhighlight lang=python> print () # Mid point between F1, F2: M = xM,yM = (p1 + p2)/2, (q1 + q2)/2 print ( ' Mid point M : ({}, {})'.format(xM,yM) ) half_major = length_of_major_axis / 2 half_distance = distance_F1_F2 / 2 # half_distance**2 + half_minor**2 = half_major**2 half_minor = ( half_major**2 - half_distance**2 ).sqrt() length_of_minor_axis = half_minor * 2 Q = xQ,yQ = xM + dlx*half_minor, yM + dly*half_minor T = xT,yT = xM - dlx*half_minor, yM - dly*half_minor print ( ' Point Q : ({}, {})'.format(xQ,yQ) ) print ( ' Point T : ({}, {})'.format(xT,yT) ) print (' length_of_major_axis =', length_of_major_axis) print (' length_of_minor_axis =', length_of_minor_axis) # # A basic check. # length_of_minor_axis**2 = (length_of_major_axis**2)(1-e**2) # # length_of_minor_axis**2 # ----------------------- = 1-e**2 # length_of_major_axis**2 # # length_of_minor_axis**2 # ----------------------- + (e**2 - 1) = 0 # length_of_major_axis**2 # values = (length_of_minor_axis/length_of_major_axis)**2, e1**2 - 1 sum_zero(values) and 3/0 aM,bM = a1,b1 # Minor axis is parallel to directrix. cM = reduce_Decimal_number(-(aM*xM + bM*yM)) print ( ' Minor axis : ({})x + ({})y + ({}) = 0'.format(aM,bM,cM) ) </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> Mid point M : (15.16210526315789473684, -4.54947368421052631579) Point Q : (10.53708406832736953616, -8.018239580333420216299) Point T : (19.78712645798841993752, -1.080707788087632415281) length_of_major_axis = 26.52631578947368421052 length_of_minor_axis = 11.56255298707631300170 Minor axis : (0.6)x + (-0.8)y + (-12.73684210526315789474) = 0 </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> ===Checking=== {{RoundBoxTop|theme=2}} All interesting points have been calculated without using equations of any of the relevant lines. However, equations of relevant lines are very useful for testing, for example: * Check that points <math>ID2, I2, F2, M, F1, I1, ID1</math> are on axis. * Check that points <math>R, F2, S</math> are on latus rectum through <math>F2.</math> * Check that points <math>Q, M, T</math> are on minor axis through <math>M.</math> * Check that points <math>P, F1, U</math> are on latus rectum through <math>F1.</math> Test below checks that 8 points <math>I1, I2, P, Q, R, S, T, U</math> are on ellipse and satisfy eccentricity <math>e = 0.9.</math> <math></math> <math></math> {{RoundBoxBottom}} <syntaxhighlight lang=python> t1 = ( ('I1'), ('I2'), ('P'), ('Q'), ('R'), ('S'), ('T'), ('U'), ) for name in t1 : value = eval(name) x,y = [ reduce_Decimal_number(v) for v in value ] print ('{} : ({}, {})'.format((name+' ')[:2], x,y)) values = A*x**2, B*y**2, C*x*y, D*x, E*y, F sum_zero(values) and 3/0 # Relative to Directrix 1 and Focus 1: distance_to_F1 = ( (x-p1)**2 + (y-q1)**2 ).sqrt() distance_to_directrix1 = a1*x + b1*y + c1 e1 = distance_to_F1 / distance_to_directrix1 print (' e1 =',e1) # Raw value is printed. # Relative to Directrix 2 and Focus 2: distance_to_F2 = ( (x-p2)**2 + (y-q2)**2 ).sqrt() distance_to_directrix2 = a2*x + b2*y + c2 e2 = distance_to_F2 / distance_to_directrix2 e2 = reduce_Decimal_number(e2) print (' e2 =',e2) # Clean value is printed. </syntaxhighlight> {{RoundBoxTop|theme=2}} Note the differences between "raw" values of <math>e_1</math> and "clean" values of <math>e_2.</math> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> I1 : (23.12, -15.16) e1 = -0.9000000000000000000034 e2 = 0.9 I2 : (7.204210526315789473684, 6.061052631578947368421) e1 = -0.9 e2 = 0.9 P : (20.30821052631578947368, -15.61094736842105263158) e1 = -0.9 e2 = 0.9 Q : (10.53708406832736953616, -8.018239580333420216299) e1 = -0.9000000000000000000002 e2 = 0.9 R : (5.984, 3.488) e1 = -0.9000000000000000000003 e2 = 0.9 S : (10.016, 6.512) e1 = -0.9000000000000000000003 e2 = 0.9 T : (19.78712645798841993752, -1.080707788087632415281) e1 = -0.8999999999999999999996 e2 = 0.9 U : (24.34021052631578947368, -12.58694736842105263158) e1 = -0.9 e2 = 0.9 </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> ==Traditional definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0617ellipse01.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. ]] Ellipse may be defined as the locus of a point that moves so that the sum of its distances from two fixed points is constant. In the diagram the two fixed points are the foci, Focus 1 or <math>F_1</math> and Focus 2 or <math>F_2.</math> Distance between <math>F_1</math> and <math>F_2</math>, distance <math>F_1F_2</math>, must be non-zero. Point <math>G</math> on perimeter of ellipse moves so that sum of distance <math>F_1G</math> and distance <math>F_2G</math> is constant. Points <math>T_1</math> and <math>T_2</math> are on axis of ellipse and the same rule applies to these points. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> is constant. distance <math>F_1T_1</math> + distance <math>T_1F_2</math> <math>=</math> distance <math>F_1G</math> + distance <math>F_2G</math> <math>=</math> distance <math>F_2T_2</math> + distance <math>T_1F_2</math> <math>= \text{length of major axis.}</math> Therefore the constant is <math>\text{length of major axis}</math> which must be greater than distance <math>F_1F_2.</math> From information given, calculate eccentricity <math>e</math> and equation of one directrix. Choose directrix 1 <math>dx1</math> associated with focus F1. <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> {{RoundBoxBottom}} ==Ellipse at origin== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Traditional definition of ellipse.''' </br> Sum of distance <math>F_1P</math> and distance <math>F_2P</math> is constant. ]] Traditional definition of ellipse states that ellipse is locus of a point that moves so that sum of its distances from two fixed points is constant. By definition distance <math>F_2P</math> + distance <math>F_1P</math> is constant. <math>\sqrt{(x-(-p))^2 + y^2} + \sqrt{(x-p)^2 + y^2} = k\ \dots\ (1)</math> Expand <math>(1)</math> and result is <math>Ax^2 + By^2 + F = 0\ \dots\ (2)</math> where: <math>A = 4k^2 - 16p^2</math> <math>B = 4k^2</math> <math>F = 4k^2p^2 - k^4</math> When <math>y = 0,</math> point <math>B,\ Ax^2 = -F</math> <math>x^2 = \frac{-F}{A}</math> <math>= \frac{k^4 - 4k^2p^2}{4k^2 - 16p^2}</math> <math>=\frac{k^2(k^2-4p^2)}{4(k^2 - 4p^2)} = \frac{k^2}{4}.</math> Therefore: <math>x = \frac{k}{2} = a</math> <math>k = \text{length of major axis.}</math> By definition, distance <math>F_2A</math> + distance <math>F_1A = k.</math> Therefore distance <math>F_1A = a.</math> Intercept form of ellipse at origin: <math>(4k^2 - 16p^2)x^2 + (4k^2)y^2 = k^4 - 4k^2p^2</math> <math>\frac{4(k^2-4p^2)}{k^2(k^2-4p^2)}x^2 + \frac{4k^2}{k^2(k^2 - 4p^2)}y^2 = 1</math> <math>\frac{4}{(2a)^2}x^2 + \frac{4}{(2a)^2 - 4p^2}y^2 = 1</math> <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> <math></math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Second definition of ellipse== {{RoundBoxTop|theme=2}} [[File:0901ellipse00.png|thumb|400px|'''Graph of ellipse <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where <math>a,b = 20,12</math>.''' </br> At point <math>B,\ \frac{u}{v} = e.</math> </br> At point <math>A,\ \frac{a}{t} = e.</math> ]] Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. Let <math>\frac{p}{a} = e</math> where: * <math>p</math> is non-zero, * <math>a > p,</math> * <math>a = p + u.</math> Therefore, <math>1 > e > 0.</math> Let directrix have equation <math>x = t</math> where <math>\frac{a}{t} = e.</math> At point <math>B:</math> <math>\frac{p}{p+u} = \frac{p+u}{p+u+v} = e</math> <math>(p+u)^2 = p(p+u+v)</math> <math>pp + pu + pu + uu = pp + pu + pv</math> <math>pu + uu = pv</math> <math>u(p + u) = pv</math> <math>\frac{u}{v} = \frac{p}{p+u} = e</math> <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e\ \dots\ (3)</math> Statement <math>(3)</math> is true at point <math>A</math> also. Section under "Proof" below proves that statement (3) is true for any point <math>P</math> on ellipse. {{RoundBoxBottom}} ===Proof=== {{RoundBoxTop|theme=2}} [[File:0902ellipse00.png|thumb|400px|'''Proving that <math>\frac{\text{distance from point to focus}}{\text{distance from point to directrix}} = e</math>.''' </br> Graph is part of curve <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1.</math> </br> distance to Directrix1 <math>= t - x = \frac{a}{e} - x = \frac{a - ex}{e}.</math> </br> base = <math>x - p = x - ae</math> </br> <math>\text{(distance to Focus1)}^2 = \text{base}^2 + y^2</math> ]] As expressed above in statement <math>3,</math> second definition of ellipse states that ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant. This section proves that this definition is true for any point <math>P</math> on the ellipse. At point <math>P:</math> <math>(a^2 - p^2)x^2 + a^2y^2 -a^2(a^2 - p^2) = 0</math> <math>y^2 = \frac{-(a^2 - p^2)x^2 + a^2(a^2 - p^2)}{a^2}</math> <math>= \frac{a^2e^2x^2 - a^2x^2 + a^2a^2 - a^2a^2e^2}{a^2}</math> <math>= e^2x^2 - x^2 + a^2 - a^2e^2</math> base <math>= x-p = x-ae</math> <math>(\text{distance}\ F_1P)^2 = y^2 + \text{base}^2 = y^2 + (x-ae)^2</math> <math>= a^2 - 2aex + e^2x^2</math> <math>= (a-ex)^2</math> <math>\text{distance to Focus1} = \text{distance}\ F_1P = a - ex</math> <math>\text{distance to Directrix1} = t - x = \frac{a}{e} - x = \frac{a-ex}{e}</math> <math>\frac{\text{distance to Focus1}}{\text{distance to Directrix1}}</math> <math>= (a - ex)\frac{e}{(a-ex)}</math> <math>= e</math> Similar calculations can be used to prove the case for Focus2 <math>(-p, 0)</math> and Directrix2 <math>(x = -t)</math> in which case: <math>\frac{\text{distance to Focus2}}{\text{distance to Directrix2}}</math> <math>= (a + ex)\frac{e}{(a + ex)}</math> <math>= e</math> Therefore: <math>\frac{\text{distance to focus}}{\text{distance to directrix}} = e</math> where <math>1 > e > 0.</math> Ellipse is path of point that moves so that ratio of distance to fixed point and distance to fixed line is constant, called eccentricity <math>e.</math> <math></math> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ==Heading== ===Properties of ellipse=== {{RoundBoxTop|theme=2}} [[File:0822ellipse01.png|thumb|400px|'''Graph of ellipse used to illustrate and calculate certain properties of ellipses.''' </br> </br> Traditional definition of ellipse: </br> <math>\text{distance } AF_1 + \text{distance } AF_2 = \text{constant } k.</math> </br> </br> Second definition of ellipse: </br> <math>\frac{\text{distance } AF_1} {\text{distance } AG } = \text{eccentricity } e.</math> </br> </br> Triangle <math>A F_1 G</math> is right triangle. </br> <math>e = \cos \angle O F_1 A = \cos \angle F_1 A G</math> ]] Ellipse in diagram has: * Two foci: <math>F_1\ (p,0),\ F_2\ (-p,0).</math> * Length of major axis <math>= \text{distance } I_2 I_1 = 2a</math> * Length of minor axis <math>= \text{distance } A B = 2b</math> * Equation: <math>\frac {x^2} {a^2} + \frac {y^2} {b^2} = 1</math> * Length of latus rectum <math>= \text{distance } P Q</math> * Distance between directrices <math>= \text{distance } D_2 D_1 = 2t</math> Properties of ellipse: * <math>\frac{\text{length of major axis}} {\text{distance between directrices}} = e</math> * <math>\frac{\text{distance between foci}} {\text{length of major axis}} = e</math> * <math>\frac{\text{distance between foci}} {\text{distance between directrices}}= e^2</math> * <math>(\frac{\text{length of minor axis}} {\text{length of major axis}})^2 + e^2 = 1</math> * <math>\frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> * line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ====Major axis==== From traditional definition of ellipse: Distance <math>AF_2\ +</math> distance <math>AF_1</math> = distance <math>I_1F_1\ +</math> distance <math>I_1F_2</math> = distance <math>I_2F_2\ +</math> distance <math>I_2F_1</math> = <math>k.</math> Therefore: Length of major axis = distance <math>I_2I_1 = 2a = k.</math> Distance <math>AF_1 = \frac{k}{2} = a.</math> From second definition of ellipse: <math>\frac{\text{distance }AF_1}{\text{distance }AG} = \frac{a}{t} = \text{eccentricity }e</math> <math>= \frac{\text{distance }OI_1}{\text{distance }OD_1}.</math> <math>\frac{\text{length of major axis}}{\text{distance between directrices}} = e.</math> ====Foci==== From second definition of ellipse: <math>\frac{\text{distance }I_1F_1}{\text{distance }I_1D_1} = \frac{a-p}{t-a} = e.</math> <math>a - p = te - ae</math> <math>a - p = a - ae</math> Therefore: <math>p = ae</math> or <math>\frac{p}{a} = e.</math> <math>\frac{\text{distance between foci}}{\text{length of major axis}} = e.</math> <math>\frac{\text{distance between foci}}{\text{distance between directrices}} = e^2.</math> ====Minor axis==== Triangle <math>AOF_1</math> is right triangle. <math>\cos ^2 \angle OAF_1 + \sin ^2 \angle OAF_1</math> <math>= (\frac{b}{a})^2 + (\frac{p}{a})^2 </math> <math>= (\frac{b}{a})^2 + (\frac{ae}{a})^2 </math> <math>= (\frac{b}{a})^2 + e^2 = 1</math> <math>( \frac{\text{length of minor axis}} {\text{length of major axis}} )^2 + e^2 = 1</math> Triangles <math>AOF_1,\ AF_1G</math> are similar. Triangle <math>AF_1G</math> is right triangle. <math>e = \cos \angle OF_1A = \cos \angle F_1AG.</math> ====Latus rectum==== From second definition of ellipse: <math>\frac{\text{distance }PF_1} {\text{distance }F_1D_1} = \frac{\text{distance }PF_1}{t-p} = e</math> <math>\text{distance }PF_1 = te - pe = a - (ae)e = a(1-e^2).</math> <math>\frac{\text{distance }PF_1} {a} = 1 - e^2.</math> <math> \frac{\text{length of latus rectum}} {\text{length of major axis}} + e^2 = 1</math> ====Slope of curve==== Curve has equation: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math><math></math> <math>= \frac{-x(1-e^2)}{y}</math><math></math> At point <math>P:\ m_1 = y' = \frac{-p(1-e^2)}{-a(1-e^2)}</math> <math>= \frac{ae}{a} = e.</math><math></math> Slope of line <math>PD_1:\ m_2 = \frac{\text{distance }PF_1}{\text{distance }F_1D_1} = e.</math><math></math><math></math> <math>m_1 = m_2.</math> Therefore line <math>PD_1</math> is tangent to curve at latus rectum, point <math>P.</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> ===Intercept form of equation=== <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1</math> <math></math> <math></math> {{RoundBoxTop|theme=2}} [[File:0625ellipse01.png|thumb|400px|'''Ellipse at origin with major axis on X axis.''' </br> </br> </br> </br> Equation of ellipse has format <math>\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1</math> where: </br> </br> <math>\text{Length of major axis} = 2a = \text{distance}\ I_2I_1 = 40</math> </br> <math>\text{Length of minor axis} = 2b = \text{distance}\ BA = 24</math> </br> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> </br> <math>\frac{\text{Length of minor axis}}{\text{Length of major axis}} = \sqrt{1 - e^2}</math> </br> </br> <math>e = \sqrt{1 - \frac{b^2}{a^2}} = 0.8.</math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> ]] In diagram: Intercept <math>I_1</math> has coordinates <math>(a,0).</math> Intercept <math>I_2</math> has coordinates <math>(-a,0).</math> Intercept <math>A</math> has coordinates <math>(0,b).</math> Intercept <math>B</math> has coordinates <math>(0,-b).</math> Focus <math>F_1</math> has coordinates <math>(f,0)</math> where <math>f = ea.</math> Focus <math>F_2</math> has coordinates <math>(-f,0).</math> Curve has equation <math>\frac{x^2}{20^2} + \frac{y^2}{12^2} = 1,</math> called intercept form of equation of ellipse because intercepts are apparent as the fractional value of each coefficient. Standard form of this equation is: <math>(-0.36)x^2 + (-1)y^2 + (0)xy + (0)x + (0)y + (144) = 0.</math> While the standard form is valuable as input to a computer program, the intercept form is still attractive to the human eye because center of ellipse and intercepts are neatly contained within the equation. Slope of curve: <math>b^2x^2 + a^2y^2 = a^2b^2</math> Derivative of both sides: <math>b^22x + a^22yy' = 0</math> <math>y' = \frac{-xb^2}{ya^2}</math> <math>= \frac{-x(1-e^2)}{y}</math> At point <math>P</math> on latus rectum <math>PQ:</math> <math>m_1 = y' = \frac{-(ea)(1-e^2)}{-(a(1-e^2))} = e</math> Slope of line <math>PD = m_2 = \frac{PF_1}{F_1D} = e</math> <math>m_1 = m_2.</math> Line <math>PD</math> is tangent to curve at latus rectum, point <math>P.</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math>\text{ }</math> <math></math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} ===Example=== {{RoundBoxTop|theme=2}} [[File:0618ellipse01.png|thumb|400px|'''Traditional definition of ellipse uses abc, epq.''' </br> M is mid-point between F1 and F2. </br> Point R is on minor axis. </br> </br> <math>\frac{\text{distance from R to F1}}{\text{distance from R to directrix 1}}</math> <math>= e</math> </br> </br> <math>= \frac{\text{half major axis}}{\text{distance from M to directrix 1}}</math> </br> </br> <math>\text{distance from M to directrix 1} = \frac{\text{half major axis}}{e}</math> </br> </br> <math>\text{F1:}\ (1, -7)</math> </br> <math>\text{F2:}\ (-1.24, 0.68)</math> </br> length_of_major_axis = 10 </br> <math>\text{M:}\ (-0.12, -3.16)</math> </br> length_of_minor_axis = 6 </br> <math>\text{R:}\ (2.76, -2.32)</math> </br> <math>e = 0.8</math> </br> <math>\text{D1:}\ (1.63, -9.16)</math> </br> <math>\text{Directrix 1:}\ (-0.28)x + (0.96)y + (9.25) = 0</math> </br> <math>\text{abc}\ =\ (-0.28,\ 0.96,\ 9.25)</math> </br> <math>\text{epq}\ =\ (0.8,\ 1,\ -7)</math> ]] Given: <syntaxhighlight lang=python> # python code F1 = 1, -7 # Focus 1 F2 = -1.24, 0.68 # Focus 2 length_of_major_axis = 10 </syntaxhighlight> Calculate equation of ellipse. <syntaxhighlight lang=python> F1 = p1,q1 = [ dD(str(v)) for v in F1 ] # Focus 1 F2 = p2,q2 = [ dD(str(v)) for v in F2 ] # Focus 2 length_of_major_axis = dD(length_of_major_axis) half_major_axis = length_of_major_axis / 2 # Direction cosines from F1 to F2 dx = p2-p1 ; dy = q2-q1 divider = (dx**2 + dy**2).sqrt() dx,dy = [ (v/divider) for v in (dx,dy) ] # F2 # p2 = p1 + dx*distance_F1_F2 # q2 = q1 + dy*distance_F1_F2 distance_F1_F2 = (q2-q1)/dy half_distance_F1_F2 = distance_F1_F2 / 2 # The mid-point M = xM,ym = p1 + dx*half_distance_F1_F2, q1 + dy*half_distance_F1_F2 # Eccentricity: e = distance_F1_F2 / length_of_major_axis # distance from point R to F1 half_major_axis # ------------------------------------ = e = ----------------------------------------- # distance from point R to Directrix 1 distance from point M to Directrix 1 distance_from_point_M_to_dx1 = half_major_axis / e # Intersection of axis and directrix 1 D1 = xM-dx*distance_from_point_M_to_dx1, yM-dy*distance_from_point_M_to_dx1 D1 = xD1, yD1 = [ reduce_Decimal_number(v) for v in D1 ] # Equation of Directrix 1 # dx1 = adx1,bdx1,cdx1 adx1,bdx1 = dx, dy # Perpendicular to axis. # adx1*x + bdx1*y + cdx1 = 0 # Directrix 1 contains point D1 cdx1 = reduce_Decimal_number( -( adx1*xD1 + bdx1*yD1 ) ) abc = adx1,bdx1,cdx1 epq = e,p1,q1 ABCDEF = ABCDEF_from_abc_epq (abc,epq, 1) </syntaxhighlight> Equation of ellipse in standard form: <math>(-0.949824)x^2 + (-0.410176)y^2 + (-0.344064)xy + (-1.3152)x + (-2.6336)y + (4.76) = 0</math> For more insight into method of calculation and proof: <syntaxhighlight lang=python> if 1 : print ('F1: ({}, {})'.format(p1,q1)) print ('F1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p1,q1)) print ('F2: ({}, {})'.format(p2,q2)) print ('F2: (x - ({}))^2 + (y - ({}))^2 = 1'.format(p2,q2)) print ('length_of_major_axis =', length_of_major_axis) print ('M: ({}, {})'.format(xM,yM)) print ('M: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xM,yM)) # half_minor_axis**2 + half_distance_F1_F2**2 = half_major_axis**2 half_minor_axis = (half_major_axis**2 - half_distance_F1_F2**2).sqrt() length_of_minor_axis = half_minor_axis * 2 s1 = 'length_of_minor_axis' ; print (s1, '=', eval(s1)) # Direction cosines on major axis: print ('dx,dy =', dx,dy) # Direction cosines on minor axis: dnx,dny = dy,-dx print ('dnx,dny =', dnx,dny) # One point on minor axis: R = xR,yR = xM + dnx*half_minor_axis, yM + dny*half_minor_axis print ('R: ({}, {})'.format(xR,yR)) print ('R: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xR,yR)) # Verify that point R is on ellipse: sum_zero((A*xR**2, B*yR**2, C*xR*yR, D*xR, E*yR, F)) and 1/0 s1 = 'e' ; print (s1, '=', eval(s1)) print ('D1: ({}, {})'.format(xD1,yD1)) print ('D1: (x - ({}))^2 + (y - ({}))^2 = 1'.format(xD1,yD1)) print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(adx1, bdx1, cdx1)) print() # For proof, reverse the process: (abc1,epq1), (abc2,epq2) = calculate_abc_epq (ABCDEF) a1,b1,c1 = abc1 ; e1,p1,q1 = epq1 print ('Directrix 1: ({})x + ({})y + ({}) = 0'.format(a1, b1, c1)) print ('Eccentricity e1: {}'.format(e1)) print ('F1: ({}, {})'.format(p1,q1)) print() a2,b2,c2 = abc2 ; e2,p2,q2 = epq2 print ('Directrix 2: ({})x + ({})y + ({}) = 0'.format(a2, b2, c2)) print ('Eccentricity e2: {}'.format(e2)) print ('F2: ({}, {})'.format(p2,q2)) print ('\nEquation of ellipse with integer coefficients:') A,B,C,D,E,F = [ reduce_Decimal_number(-v*1000000/64) for v in ABCDEF ] str1 = '({})x^2 + ({})y^2 + ({})xy + ({})x + ({})y + ({}) = 0' print (str1.format(A,B,C,D,E,F)) </syntaxhighlight> <syntaxhighlight> F1: (1, -7) F1: (x - (1))^2 + (y - (-7))^2 = 1 F2: (-1.24, 0.68) F2: (x - (-1.24))^2 + (y - (0.68))^2 = 1 length_of_major_axis = 10 M: (-0.12, -3.16) M: (x - (-0.12))^2 + (y - (-3.16))^2 = 1 length_of_minor_axis = 6 dx,dy = -0.28 0.96 dnx,dny = 0.96 0.28 R: (2.76, -2.32) R: (x - (2.76))^2 + (y - (-2.32))^2 = 1 e = 0.8 D1: (1.63, -9.16) D1: (x - (1.63))^2 + (y - (-9.16))^2 = 1 Directrix 1: (-0.28)x + (0.96)y + (9.25) = 0 Directrix 1: (0.28)x + (-0.96)y + (-9.25) = 0 Eccentricity e1: 0.8 F1: (1, -7) Directrix 2: (0.28)x + (-0.96)y + (3.25) = 0 Eccentricity e2: 0.8 F2: (-1.24, 0.68) Equation of ellipse with integer coefficients: </syntaxhighlight> <math>(14841)x^2 + (6409)y^2 + (5376)xy + (20550)x + (41150)y + (-74375) = 0</math> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <math></math> <math></math> <math></math> <math></math> <math></math> {{RoundBoxBottom}} =allEqual= {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em;"> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> ====Welcomee==== {{Robelbox|title=[[Wikiversity:Welcome|Welcome]]|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFF800; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> =====Welcomen===== {{Robelbox|title=|theme={{{theme|9}}}}} <div style="padding-top:0.25em; padding-bottom:0.2em; padding-left:0.5em; padding-right:0.75em; background-color: #FFFFFF; "> [[Wikiversity:Welcome|Wikiversity]] is a [[Wikiversity:Sister projects|Wikimedia Foundation]] project devoted to [[learning resource]]s, [[learning projects]], and [[Portal:Research|research]] for use in all [[:Category:Resources by level|levels]], types, and styles of education from pre-school to university, including professional training and informal learning. We invite [[Wikiversity:Wikiversity teachers|teachers]], [[Wikiversity:Learning goals|students]], and [[Portal:Research|researchers]] to join us in creating [[open educational resources]] and collaborative [[Wikiversity:Learning community|learning communities]]. To learn more about Wikiversity, try a [[Help:Guides|guided tour]], learn about [[Wikiversity:Adding content|adding content]], or [[Wikiversity:Introduction|start editing now]]. </div> <syntaxhighlight lang=python> # python code. if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 :if a == b == c == d == e == f == g == h == 0 : pass </syntaxhighlight> {{Robelbox/close}} {{Robelbox/close}} {{Robelbox/close}} <noinclude> [[Category: main page templates]] </noinclude> {| class="wikitable" |- ! <math>x</math> !! <math>x^2 - N</math> |- | <code></code><code>6</code> || <code>-221</code> |- | <code></code><code>7</code> || <code>-208</code> |- |- | <code>10</code> || <code>-157</code> |- | <code>11</code> || <code>-136</code> |- | <code>12</code> || <code>-113</code> |- | <code>13</code> || <code></code><code>-88</code> |- | <code>26</code> || <code></code><code>419</code> |} =Testing= ======table1====== {|style="border-left:solid 3px blue;border-right:solid 3px blue;border-top:solid 3px blue;border-bottom:solid 3px blue;" align="center" | Hello As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 </syntaxhighlight> |} {{RoundBoxTop|theme=2}} [[File:0410cubic01.png|thumb|400px|''' Graph of cubic function with coefficient a negative.''' </br> There is no absolute maximum or absolute minimum. ]] Coefficient <math>a</math> may be negative as shown in diagram. As <math>abs(x)</math> increases, the value of <math>f(x)</math> is dominated by the term <math>-ax^3.</math> When <math>x</math> has a very large negative value, <math>f(x)</math> is always positive. When <math>x</math> has a very large positive value, <math>f(x)</math> is always negative. Unless stated otherwise, any reference to "cubic function" on this page will assume coefficient <math>a</math> positive. {{RoundBoxBottom}} <math>x_{poi} = -1</math> <math></math> <math></math> <math></math> <math></math> =====Various planes in 3 dimensions===== {{RoundBoxTop|theme=2}} <gallery> File:0713x=4.png|<small>plane x=4.</small> File:0713y=3.png|<small>plane y=3.</small> File:0713z=-2.png|<small>plane z=-2.</small> </gallery> {{RoundBoxBottom}} <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight lang=python> </syntaxhighlight> <syntaxhighlight> </syntaxhighlight> <syntaxhighlight> 1.4142135623730950488016887242096980785696718753769480731766797379907324784621070388503875343276415727 3501384623091229702492483605585073721264412149709993583141322266592750559275579995050115278206057147 0109559971605970274534596862014728517418640889198609552329230484308714321450839762603627995251407989 6872533965463318088296406206152583523950547457502877599617298355752203375318570113543746034084988471 6038689997069900481503054402779031645424782306849293691862158057846311159666871301301561856898723723 5288509264861249497715421833420428568606014682472077143585487415565706967765372022648544701585880162 0758474922657226002085584466521458398893944370926591800311388246468157082630100594858704003186480342 1948972782906410450726368813137398552561173220402450912277002269411275736272804957381089675040183698 6836845072579936472906076299694138047565482372899718032680247442062926912485905218100445984215059112 0249441341728531478105803603371077309182869314710171111683916581726889419758716582152128229518488472 </syntaxhighlight> <math>\theta_1</math> {{RoundBoxTop|theme=2}} [[File:0422xx_x_2.png|thumb|400px|''' Figure 1: Diagram illustrating relationship between <math>f(x) = x^2 - x - 2</math> and <math>f'(x) = 2x - 1.</math>''' </br> ]] {{RoundBoxBottom}} <math>O\ (0,0,0)</math> <math>M\ (A_1,B_1,C_1)</math> <math>N\ (A_2,B_2,C_2)</math> <math>\theta</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} (6) - (7),\ 4Apq + 2Bq =&\ 0\\ 2Ap + B =&\ 0\\ 2Ap =&\ - B\\ \\ p =&\ \frac{-B}{2A}\ \dots\ (8) \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math>\begin{align} 1.&4141475869yugh\\ &2645er3423231sgdtrf\\ &dhcgfyrt45erwesd \end{align}</math> <math>\ \ \ \ \ \ \ \ </math> :<math> 4\sin 18^\circ = \sqrt{2(3 - \sqrt 5)} = \sqrt 5 - 1 </math> 8mpg23v0ppe0id7i6vjkmwmu0vjhcvp 2 250057 2835064 2834277 2026-09-29T15:53:50Z Platos Cave (physics) 2562653 2835064 wikitext text/x-wiki {{Original research}} '''Simulating gravitational and atomic orbits via n-body rotating particle-particle orbital pairs at the Planck scale''' The following describes a geometrical method for simulating gravitational orbits <ref>Macleod, Malcolm J.; {{Cite journal |title=3. Gravitational orbits from n-body rotating particle-particle orbital pairs |journal=SSRN |date=Dec 2021 | doi=10.2139/ssrn.3444571}}</ref><ref>https://simulationuniverse.org/3-Gravity_via_n-body_particle_orbitals.html M. Macleod Gravitational orbitals (uploaded Sept.2026)</ref> and atomic orbitals <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref><ref>https://simulationuniverse.org/4-Atomic-orbital_transition_using_Gravity_simulator.html M. Macleod Atomic orbital transitions (uploaded May.2026)</ref> via an n-body network of rotating individual particle-particle orbital pairs . Although the simulation is dimensionless (the only physical constant used is the [[w:fine structure constant |fine structure constant alpha]]), it can translate via the [[w:Planck_units |Planck units]] for comparisons with real world orbits. The orbits generated by this dimensionless geometrical approach can be formulated, and despite not using Newtonian physics these formulas demonstrate consistency; for example the derived formulas for radius R, period T and (M + m) will reduce [[v:Quantum_gravity_(Planck)#Kepler's_formula_=_G |Kepler's formula]] to '''G''' <ref>https://codingthecosmos.com/orbitals/maple-code-Kepler.html maple code</ref>. Likewise the atomic orbital shells naturally quantize according to pi without relying on built-in postulates. [[File:Gravitational-regular-3body-orbit.gif|thumb|right|640px|A regular 3-body orbit. The simulation begins with the start (x, y) co-ordinates of each point. No other parameters are required. r0=2*α; x1=1789.5722983; y1=0; x2=cos(pi*2/3)*r0; y2=sin(pi*2/3)*r0; x3=cos(pi*2/3)*r0; y3=sin(pi*2/3)*r0]] :<math>\frac{4 \pi^2 R^3}{(M+m) T^2} = \frac{l_p c^2}{m_P} = G</math> The simulation source code(s) used here are listed below, these give a precise description of this orbital model and so can be used as reference <ref>https://codingthecosmos.com/orbitals/ Orbital model simulation source codes</ref>. For simulating gravity, orbiting objects ''A'', ''B'', ''C''... are sub-divided into discrete points, each point can be represented as 1 unit of [[w:Planck mass |Planck mass]] ''m''_P (for example, a 1kg satellite would be divided into 1kg/''m''_P = 45940509 points). Each point in object ''A'' then forms an orbital pair with every point in objects ''B'', ''C''..., resulting in a universe-wide, n-body network of rotating point-to-point orbital pairs . Each orbital pair rotates 1 unit of length per unit of time, when these orbital pair rotations are summed and mapped over time, gravitational orbits emerge between the objects ''A'', ''B'', ''C''... The base simulation requires only the start position (''x'', ''y'' coordinates) of each point, as it maps only rotations of the points within their respective orbital pairs then information regarding the macro objects ''A'', ''B'', ''C''...; momentum, center of mass, barycenter etc ... is not required (each orbital is calculated independently of all other orbitals). For simulating electron transition within the atom, the same program is used. The electron is assigned as a single point, the nucleus as multiple points clustered together (a 2-body orbit), and an incoming 'photon' (a unit of length) is added to (increases) the electron - proton orbital radius in a series of discrete steps (rather than a single 'jump' between orbital shells). As the electron continues to orbit the nucleus during this transition phase, the electron path traces a [[w:hyperbolic spiral |hyperbolic spiral]]. Although we are mapping the electron transition as a gravitational orbit on a 2-D plane, periodically the transition spiral angles converge to give an integer orbital radius (360°=4''r'', 360+120°=9''r'', 360+180°=16''r'', 360+216°=25''r'' ... 720°=∞''r''), a radial quantization (as a function of pi and so of geometrical origin) naturally emerges. Furthermore, the transition steps between these radius can then be used to solve the transition frequency, replicating the Bohr model. The gravitational orbit returns results analogous to the Bohr model and the 2-photon orbital model approach complements the (electric wave-state) [[w:Schrodinger equation |Schrodinger wave equation]]. [[File:complex-orbit-pts26-r17-1-7-1.gif|thumb|right|640px|By selecting the start co-ordinates on a 2-D plane for each point accordingly, we can 'design' the required orbits. The 26 points orbit each other resulting in 325 point-point orbitals.]] === Theory === In the simulation, particles are treated as an electric wave-state to (Planck) mass point-state oscillation, the wave-state as the duration of particle frequency in Planck time units, the point-state duration as 1 unit of Planck time (as a point, this state can be assigned mapping coordinates), the particle itself is a continuous oscillation between these 2 states (i.e.: the particle is not a fixed entity). For example, an electron has a frequency (wave-state duration) = 10²³ units of Planck time followed by the mass state (1 unit of Planck time). The background to this oscillation is given in the [[v:Electron (mathematical) |mathematical electron]] model. If the electron '''has (is)''' mass (1 unit of Planck mass) for 1 unit of Planck time, and then '''no''' mass for 10²³ units of Planck time (the wave-state), then in order for a (hypothetical) object composed only of electrons to '''have (be)''' 1 unit of Planck mass at every unit of Planck time, the object will require 10²³ electrons. This is because orbital rotation occurs at each unit of Planck time and so the simulation requires this object to have a unit of Planck mass at each unit of Planck time (i.e.: on average there will always be 1 electron in the mass point state). We would then measure the mass of this object as 1 Planck mass (the measured mass of an object reflects the average number of units of Planck mass per unit of Planck time). For the simulation program, this Planck mass object can now be defined as a point (it will have point co-ordinates at each unit of Planck time and so can be mapped). As the simulation is dividing the mass of objects into these Planck mass size points and then rotating these points around each other as point-to-point orbital pairs, then by definition gravity is a mass to mass interaction. Nevertheless, although this is a mass-point to mass-point rotation, and so referred to here as a point-point orbital, it is still a particle to particle orbital, albeit the particles are both in the mass state. We can also map individual particle to particle orbitals albeit as gravitational orbits, the H atom is a well-researched particle-to-particle orbital pair (an electron orbiting a proton) and so can be used as reference. To map orbital transitions between energy levels, the simulation uses the [[v:Quantum_gravity_(Planck)#Photon_orbital_model |photon-orbital model]], in which the orbital (Bohr) radius is treated as a 'physical wave' akin to the photon albeit of inverse or reverse phase. The photon can be considered as a moving wave, the orbital radius as a standing/rotating wave (trapped between the electron and proton). Orbital momentum derives from this orbital radius, it is the rotation of the orbital radius that pulls the electron, resulting in the electron orbit around the nucleus. Furthermore, orbital transition (between orbitals) occurs between the orbital radius and the photon, the electron has a passive role. Transition (the electron path) follows a specific [[v:Fine-structure_constant_(spiral) |hyperbolic spiral]] for which the angle component periodically converges to give integer radius where ''r'' = Bohr radius; at 360° radius =4''r'', 360+120°=9''r'', 360+180°=16''r'', 360+216°=25''r'' ... 720°=∞''r''. As these spiral angles (360°, 360+120°, 360+180°, 360+216° ...) are linked directly to pi, and as the electron is following a semi-classical gravitational orbit, this particular quantization has a geometrical origin. Although the simulation is not optimized for atomic orbitals (the nucleus is treated simply as a cluster of points), the transition period '''t''' measured between these integer radius can be used to solve the transition frequencies '''f''' via the general formula <math>f/c = t \lambda_H/(n_f^2-n_i^2)</math>. In summary, both gravitational and atomic orbitals reflect the same particle-to-particle orbital pairing, the distinction being the state of the particles; gravitational orbitals are mass to mass whereas atomic orbitals are predominately wave to wave. There are not 2 separate forces used by the simulation, instead particles are treated as oscillations between the 2 states (electric wave and mass point). The transition spiral provides the geometric structure; the photon-orbital hybrid (2-Photon model) provides the angular momentum content. === N-body orbitals === [[File:8body-27orbital-gravitational-orbit.gif|thumb|right|640px|8-body (8 mass points, 28 orbitals), the resulting orbit is a function of the start positions of each point]] The simulation universe is a 4-axis hypersphere expanding in increments <ref>Macleod, Malcolm; {{Cite journal |title=1. Planck unit scaffolding correlates with the Cosmic Microwave Background |journal=SSRN |date=26 March 2014 | doi=10.2139/ssrn.3333513 }}</ref> with 3-axis (the [[v:User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_unit_scaffolding |hypersphere surface]]) projected onto an (''x'', ''y'') plane with the ''z'' axis as the simulation timeline (the expansion axis). Each point is assigned start (''x'', ''y'', ''z'' = 0) co-ordinates and forms pairs with all other points, resulting in a universe-wide n-body network of point-point orbital pairs. The barycenter for each orbital pairing is its center, the points located at each orbital 'pole'. The simulation itself is dimensionless, simply rotating circles. To translate to dimensioned gravitational or atomic orbits, we can use the Planck units ([[w:Planck mass |Planck mass m_P]], [[w:Planck length |Planck length l_p]], [[w:Planck time |Planck time t_p]]), such that the simulation increments in discrete steps (each step assigned as 1 unit of Planck time), during each step (for each unit of Planck time), the orbitals rotate 1 unit of (Planck) length (at velocity ''c'' = ''l''_p/''t''_p) in hyper-sphere co-ordinates. These rotations are then all summed and averaged to give new point co-ordinates. As this occurs for every point before the next increment to the simulation clock (the next unit of Planck time), the orbits can be updated in 'real time' (simulation time) on a serial processor. Setting <math>\alpha_{inv} = \frac{1}{\alpha}</math> = 137.035999177⁠ (CODATA 2022) Orbital pair rotation on the (''x'', ''y'') plane occurs in discrete steps according to an angle '''β''' as defined by the orbital pair radius (the atomic orbital '''β''' has an additional alpha term). :<math>\beta_{gravity} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>\beta_{atomic} = \frac{1}{\sqrt{2\alpha_{inv}} r_{orbital} \sqrt{r_{orbital}}}</math> As the simulation treats each (point-point) orbital independently (independent of all other orbitals), no information regarding the points (other than their initial start coordinates) is required by the simulation. Although orbital and so point rotation occurs at ''c'', the [[v:Relativity (Planck) |hyper-sphere expansion]] <ref>Macleod, Malcolm; {{Cite journal |title=2. Relativity as the mathematics of perspective in a hyper-sphere universe |journal=SSRN |date=26 March 2014 | doi=10.2139/ssrn.3334282 }}</ref> is equidistant and so `invisible' to the observer. Instead observers (being constrained to 3D space) will register these 4-axis orbits (in hyper-sphere co-ordinates) as a circular motion on a 2-D plane (in 3-D space). An apparent [[w:Time_dilation |time dilation]] effect emerges as a consequence. [[File:4body-orbital-3x10x-gravitational-orbit.gif|thumb|right|640px|Symmetrical 4 body orbit; (3 center mass points, 1 orbiting point, 6 orbital pairs). Note that all points orbit each other.]] ==== 2 body orbits ('''x, y''' plane) ==== For simple 2-body orbits, to reduce computation only 1 point is assigned as the orbiting point and the remaining points are assigned as the central mass. For example the ratio of earth mass to moon mass is 81:1 and so we can simulate this orbit accordingly. However we note that the only actual distinction between a 2-body orbit and a complex orbit being that the central mass points are assigned ('''x, y''') co-ordinates relatively close to each other, and the orbiting point is assigned ('''x, y''') co-ordinates distant from the central points (this becomes the orbital radius) ... this is because the simulation treats all points equally, the center points also orbiting each other according to their orbital radius, for the simulation itself there is no difference between simple 2-body and complex n-body orbits. The [[w:Schwarzschild radius |Schwarzschild radius]] formula in Planck units :<math>r_s = \frac{2 l_p M}{m_P}</math> As the simulation itself is dimensionless, we can remove the dimensioned length component <math>2 l_p</math>, and as each point is analogous to 1 unit of Planck mass <math>m_P</math>, then the Schwarzschild radius for the simulation becomes the number of central mass points. We then assign ('''x, y''') co-ordinates (to the central mass points) within a circle radius <math>r_s</math> = number of central points = total points - 1 (the orbiting point). After every orbital has rotated 1 length unit (anti-clockwise in these examples), the new co-ordinates for each rotation per point are then averaged and summed, the process then repeats. After 1 complete orbit (return to the start position by the orbiting point), the period '''t''' (as the number of increments to the simulation clock) and the ('''x, y''') plane orbit length '''l''' (distance as measured on the 2-D plane) are noted. '''Key''': 1. '''i''' = r<sub>s</sub>; the number of center mass points (the orbited object). 2. '''j''' = total number of points, as here there is only 1 orbiting point; '''j''' = '''i''' + 1 3. '''k<sub>r</sub>''' is a mass to radius co-efficient in the form <math>j_{max} = (k_r i + 1)</math>. This function defines orbital radius in terms of the central mass Schwarzschild radius (<math>i</math>) and the orbiting point (1), thus quantizing the radius. When <math>k_r</math> = 1 then <math>j_{max} = j</math>, and the radius is at a minimum giving an analogue gravitational principal quantum number <math>n_g = j_{max}/j</math>. 4. '''x, y''' = start co-ordinates for each point (on a 2-D plane), '''z''' = 0. 5. '''r<sub>α</sub>''' = a radius constant, here r<sub>α</sub> = sqrt(2/α) = 16.55512; where alpha = inverse [[w:fine structure constant |fine structure constant]] = 137.035 999 084 (CODATA 2018). This constant adapts the simulation specifically to gravitational and atomic orbitals. :<math>r_{\alpha} = \sqrt{2\alpha_{inv}} </math> :<math>r_{orbit} = {r_{\alpha_{inv}}}^2 \;*\; r_{wavelength} </math> 6. Rotation angle β :<math>\beta_{orbital} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>r_{ij} = \sqrt{\frac{2 j}{i}}</math> (for each gravitational orbital in the simulation) :<math>r_{ij} = \sqrt{2 \alpha_{inv}}</math> (for each atomic orbital in the simulation) ==== Orbital formulas (2-D plane)==== :<math>j = i + 1</math> :<math>r_{orbit} = 2 \alpha_{inv} 2 \frac{(k_r i + 1)^2}{i^2}</math>, orbital radius (center mass to point) :<math>r_{ij} = \sqrt{\frac{i}{j}}</math> (averaged for each orbit) :<math>t_{orbit} = \frac{2\pi}{ \beta_{orbit}} = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} j^{1/2}}</math>, orbiting point period :<math>r_{barycenter} = \frac{r_{orbit}}{j}</math> :<math>l_{orbit} = 2 \pi (r_{orbit} - r_{barycenter})</math>, distance travelled by orbiting point :<math>v_{orbit} = \sqrt{\frac{i}{r_{orbit}j}}</math>, orbiting point velocity Example (dimensionless). The simulation parameters agree closely with the calculated parameters: :points = 8 (1 orbiting point and 7 center mass points) <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-simulation-2body.c</ref> :i = 7, j = 8 :k<sub>r</sub> = 32 :<math>\sqrt{2j/i}</math> = 1.511858 Calculated :calculated orbit period = 2504836149.00059 :calculated orbit radius = 566322.241497 :calculated orbit length = 3113519.13854 :calculated orbit barycenter = 70790.280187, 0 :n<sub>g</sub> = (k<sub>r</sub> i + 1)/j = 28.125 Simulation simulation orbit period = 2504836141 simulation orbit length = 3113519.130546298 simulation orbit barycenter; x = 70790.28092, y = 0.000732 ===== Earth moon orbit===== The earth to moon mass ratio approximates 81:1 and so can be simulated as a 2-body orbit with the moon as a single orbiting point as in the above example. Here we use the orbital parameters to determine the value for the mass to radius coefficient k<sub>r</sub>. Planck length <math>l_p</math>, Planck mass <math>m_P</math> and <math>c</math> are used to convert between the dimensionless formulas and dimensioned SI units. Reference values :<math>M</math> = 5.9722 x 10<sup>24</sup>kg (earth) :<math>m</math> = 7.346 x 10<sup>22</sup>kg (moon) :<math>T_{orbit}</math> = 27.321661*86400 = 2360591.51s To simplify, we assume a circular orbit which then gives us this radius :<math>R_{orbit} = (\frac{G (M+m) T_{orbit}^2}{4 \pi^2})^{(1/3)}</math> = 384714027m :<math>G = \frac{l_p c^2}{m_P}</math> = 0.66725e-10 The mass ratio :<math>i = \frac{M}{m}</math> = 81.298666, j = i + 1 We then find a value for <math>k_r</math> using T<sub>orbit</sub> as our reference (reversing the orbit period equation). :<math>T_o = T_{orbit} \frac{m_P}{M} \frac{c}{l_p} = 16 \pi {\alpha_{inv}}^{3/2} \frac{(k_r i + 1)^3}{i^{5/2} j^{1/2}}</math> (dimensionless orbital period) :<math>k_r = \frac{1}{i} {(\frac{T_o i^{5/2} j^{1/2}}{16 \pi {\alpha_{inv}}^{3/2}})}^{(1/3)} - \frac{1}{i}</math> = 12581.4468 Dimensionless solutions :<math>r_{orbit} = 2 \alpha_{inv} 2 \frac{(k_r i + 1)^2}{i^2}</math> = 86767420100 :<math>t_{orbit} = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} j^{1/2}}</math> = 0.159610040233 x 10<sup>18</sup> :<math>r_{barycenter} = \frac{r_{orbit}}{j}</math> = 1054299229.62 :<math>l_{orbit} = 2 \pi (r_{orbit} - r_{barycenter})</math> = 538551421685 :<math>v = \sqrt{\frac{i}{r_{orbit}j}}</math> = 0.33741701 x 10<sup>-5</sup> Converting back to dimensioned values :<math>R = r_{orbit} l_p \frac{M}{m_P} = R_{orbit}</math> = 384714027m :<math>T = t_{orbit} \frac{l_p}{c} \frac{M}{m_P} = T_{orbit}</math> = 2360591.51s :<math>B = \frac{R}{j}</math> = 4674608.301m (barycenter) :<math>L = 2\pi (R - B)</math> = 2387858091.51m (distance moon travelled around the barycenter) :<math>V = c \sqrt{\frac{i}{r_{orbit}j}}</math> = 1011.551m/s (velocity of the moon around the barycenter) If we expand the velocity term :<math>v_{orbit} = c \sqrt{\frac{i}{r_{orbit}j}}</math> :<math>v_{orbit}^3 = \frac{G M}{T_{orbit}} 2\pi \frac{i^2}{j^2}</math> Note: The [[w:standard gravitational parameter | standard gravitational parameter]] ''μ'' is the product of the gravitational constant ''G'' and the mass ''M'' of that body. For several objects in the Solar System, the value of ''μ'' is known to greater accuracy than either ''G'' or ''M''. :<math>\mu_{earth}</math> = 3.986004418(8)e14 :<math>\mu_{moon}</math> = 4.9048695(9)e12 :<math>i = \frac{\mu_{earth}}{\mu_{moon}}</math> = 81.2662685 :<math>k_r = \frac{c}{2 \sqrt{\alpha_{inv}}} {(\frac{T_{orbit}}{2 \pi \mu_{earth}})}^{1/3} \frac{(i+1)}{i}^{1/6} - \frac{1}{i}</math> = 12580.3462 :<math>t_{orbit}</math> = 0.15956776936 x 10<sup>18</sup> :<math>r_{orbit}</math> = 86752239934 ===== Kepler's formula = G===== Kepler's formula reduces to G <ref>https://codingthecosmos.com/orbitals/maple-code-Kepler.html maple code</ref> :<math>R = 2 \alpha_{inv} 2 (\frac{k_r i + 1}{i})^2 l_p \frac{M}{m_P}</math> :<math>T = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} (i+1)^{1/2}} \frac{l_p}{c} \frac{M}{m_P}</math> :<math>M+m = M (\frac{i+1}{i})</math> :<math>\frac{4 \pi^2 R^3}{(M+m) T^2} = \frac{l_p c^2}{m_P} = G</math> Maple code : R:=(2/alpha_{inv})*2*((kr*i+1)^2/i^2)*lp*(M/mP): : T:=(16*Pi/alpha_{inv}^(3/2))*((kr*i+1)^3/(i^(5/2)*(i+1)^(1/2)))*(lp/c)*(M/mP): : Mm:=M*(i+1)/i: : simplify(4*Pi^2*R^3/(Mm*T^2)); : Output: lp*c^2/mP [[File:Gravitational-potential-energy-8body-1-2.gif|thumb|right|640px|8-body circular orbit plus 1-body with opposing orbitals 1:2]] ==== Orbital alignment ==== Orbital trajectory is a measure of alignment of the orbitals. In the above examples, all orbitals rotate in the same direction = aligned. If all orbitals are unaligned the object will appear to 'fall' = straight line orbit. In this example, for comparison, onto an 8-body orbit (blue circle orbiting the center mass green circle), is imposed a single point (yellow dot) with a ratio of 1 orbital (anti-clockwise around the center mass) to 2 orbitals (clockwise around the center mass) giving an elliptical orbit. The change in orbit velocity (acceleration towards the center and deceleration from the center) derives automatically from the change in the orbital radius (there is no barycenter). An orbital drift (as determined where the blue and yellow meet) naturally occurs; the eccentricity (shape) of the orbit a function of center mass and the ratio of alignment of the orbitals. A near straight line orbit will have a greater drift and a greater eccentricity than a near circular orbit. The elliptical orbit has a longer period than the circular orbit (which has a 360 degree orbit, the sidereal period). The additional period is known as the anomalistic period and includes the precession angle (360 + precession angle). Note: in these simulations there are only 2 orbital types; clock-wise and anti-clockwise ... in a real world orbit there will be a mixture. ===== Precession ===== Precession is a change in the orientation of the rotational axis of a rotating body. The first of three tests to establish observational evidence for the theory of general relativity, as proposed by Albert Einstein in 1915, concerned the "anomalous" precession of the[[w:Tests_of_general_relativity | perihelion of Mercury]]. This precession is not predicted by Newtonian gravity. The formula for precession uses the semi-major axis ''a'' (the maximum distance between center of mass) and the semi-minor axis ''b'' (the minimum distance between center of mass). :<math>e = \sqrt{1-\frac{b^2}{a^2}}</math> :<math>\theta = \frac{6\pi G M}{a (1-e^2) c^2}</math> Where ''e'' is the eccentricity of the orbit and θ is the precession angle The frequency of the center mass Schwarzschild radius = <math>i 2 l_p</math>, where ''i'' is the number of Planck mass points in the center mass and ''l''<sub>p</sub> is Planck length; ''a'' and ''b'' become :<math>a = r_a i 2 l_p</math> :<math>b = r_b i 2 l_p</math> The formula for <math>r_a</math> :<math>r_a = 2 \alpha 2 \frac{(k_r i + 1)^2}{i^2}</math> For example, the precession angle for Mercury :<math>\theta = \frac{6\pi G M}{a (1-e^2) c^2} = \frac{6\pi \lambda_{sun} a}{2 b^2}</math> = 0.501866 x 10-6 radians The Schwarzschild radius of the sun <math>\lambda_{sun} = i 2 l_p</math> = 2953.25m The eccentricity of Mercury :<math>e = \sqrt{1-\frac{b^2}{a^2}}</math> = 0.203225 (where a = 57909050km and b = 56671523km) In this simulation the ratio of anti-clockwise:clockwise orbitals = 108:1 with orbiting mass = 1 mass unit (k<sub>r</sub> = 12) <ref>https://codingthecosmos.com/orbitals/ Orbital model source code repository</ref>. {| class="wikitable" !Center mass!!angle θ!!θ*i!!eccentricity!!''r''<sub>a</sub>, ''r''<sub>b</sub> |- | 24 | 0.001175503 | 0.028212072 | 0.194749592 | 79481.8311615, 77959.9920879 |- | 28 | 0.001009240 | 0.028022688 | 0.195433743 | 79403.2724007, 77872.1317383 |- | 32 | 0.000884077 | 0.028290464 | 0.197440737 | 79344.3788203, 77782.4708225 |- | 36 | 0.000786489 | 0.028313604 | 0.197813449 | 79298.5878077, 77731.6227135 |- | 40 | 0.000708274 | 0.028330960 | 0.198373657 | 79261.9645140, 77686.7492830 |- | 44 | 0.000644252 | 0.028347088 | 0.199144931 | 79232.0062928, 77644.9930740 |- | 48 | 0.000590779 | 0.028357392 | 0.200476249 | 79207.0454340, 77599.0285567 |- | 52 | 0.000545493 | 0.028365636 | 0.200748008 | 79185.9277789, 77573.9329729 |- | ... | | | | |- | ∞ | 0.000005888 | | 0.205660603 | |} [[File:Ellipse-extrapolation.png|thumb|right|379px|Extrapolation of simulated elliptical data using the rotating orbital gravity simulator]] At a low mass ratio the mass influences the eccentricity, this influence reduces as mass increases and so the ratio 108:1 was chosen because extrapolating to infinity (the sun:mercury mass ratio = 6025000:1) gives an eccentricity ''e'' = 0.20566 close to that of the Mercury orbit ''e'' = 0.20563. Likewise the extrapolated precession angle = 0.000005888 is only slightly greater than the Mercury orbit angle θ = 0.000005019. Due to computational limitations, only a short radius ''r''<sub>a</sub> and low central masses (''M'' 24...52) were simulated. A longer radius and larger central mass values are required for greater precision. Extrapolating over this scale is imprecise however the it does appear that the correlation is within 1-2 orders of magnitude. For the simulation program code <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-elliptical-orbits.cpp</ref> and the extrapolation code used <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-ellipse-extrapolate.py</ref>. [[w:Frame-dragging |Frame dragging]] can also impact the results as the central mass is still of itself a gravitational orbit (the center points also orbit each other), and so the center mass rotates at a relatively high velocity when compared with the orbiting point. Lense-Thirring in dimensionless form; :<math>T = T_d \frac{m_P c}{M l_p}</math> :<math>R = R_d \frac{M l_p}{m_P}</math> :<math>J = J_d \frac{M R^2}{T}</math> :<math>\theta_f = \frac{2 G J T}{c^2 r^2} = 2\frac{J_d}{R_d}</math> ==== Gravitational coupling constant ==== In the above, the points were assigned a mass as a theoretical unit of Planck mass. Conventionally, the [[w:Gravitational coupling constant | Gravitational coupling constant]] ''α<sub>G</sub>'' characterizes the gravitational attraction between a given pair of elementary particles in terms of a particle (i.e.: electron) mass to Planck mass ratio; :<math>\alpha_G = \frac{G m_e^2}{\hbar c} = (\frac{m_e}{m_P})(\frac{m_e}{m_P}) = 1.75... x10^{-45}</math> For the purposes of this simulation, particles are treated as an oscillation between an electric wave-state (duration particle frequency) and a mass point-state (duration 1 unit of Planck time). This inverse α<sub>G</sub> then represents the probability that any 2 electrons will be in the mass point-state at any unit of Planck time ([[v:Electron_(mathematical) |wave-mass oscillation at the Planck scale]] <ref>Macleod, M.J. {{Cite journal |title= Programming Planck units from a mathematical electron; a Simulation Hypothesis |journal=Eur. Phys. J. Plus |volume=113 |pages=278 |date=22 March 2018 | doi=10.1140/epjp/i2018-12094-x }}</ref>). :<math>{\alpha_G}^{-1} = \frac{m_P^2}{m_e^2} = 0.57... x10^{45}</math> As mass is not treated as a constant property of the particle, measured particle mass becomes the averaged frequency of discrete point mass at the Planck level. If 2 dice are thrown simultaneously and a win is 2 'sixes', then approximately every (1/6)x(1/6) = (1/36) = 36 throws (frequency) of the dice will result in a win. Likewise, the inverse of α<sub>G</sub> is the frequency of occurrence of the mass point-state between the 2 electrons. As 1 second requires 10<sup>42</sup> units of Planck time (<math>t_p = 10^{-42}s</math>), this occurs about once every 3 minutes. :<math>\frac{{\alpha_G}^{-1}}{t_p}</math> Gravity now has a similar magnitude to the strong force (at this, the Planck level), albeit this interaction occurs seldom (only once every 3 minutes between 2 electrons), and so when averaged over time (the macro level), gravity appears weak. If particles oscillate between an electric wave state to Planck mass (for 1 unit of Planck-time) point-state, then at any discrete unit of Planck time, a number of particles will simultaneously be in the mass point-state. If an assigned point contains only electrons, and as the frequency of the electron = f<sub>e</sub>, then the point will require 10<sup>23</sup> electrons so that, on average for each unit of Planck time there will be 1 electron in the mass point state, and so the point will have a mass equal to Planck mass (i.e.: experience continuous gravity at every unit of Planck time). :<math>f_e = \frac{m_P}{m_e} = 10^{23}</math> For example a 1kg satellite orbits the earth, for any given unit of Planck time, satellite (B) will have <math>1kg/m_P = 45940509</math> particles in the point-state. The earth (A) will have <math>5.9738 \;x10^{24} kg/m_P = 0.274 \;x10^{33}</math> particles in the point-state, and so the earth-satellite coupling constant becomes the number of rotating orbital pairs (at unit of Planck time) between earth and the satellite; :<math>N_{orbitals} = (\frac{m_A}{m_P})(\frac{m_B}{m_P}) = 0.1261\; x10^{41}</math> Earthe parameters: :<math>i = \frac{M_{earth}}{m_P} = 0.27444 \;x10^{33}</math> (earth as the center mass) :<math>i 2 l_p = 0.00887</math> (earth Schwarzschild radius) :<math>s = \frac{1kg}{m_P} = 45940509</math> (1kg orbiting satellite) :<math>N_{orbitals} = i*s = 0.1261 \;x10^{41}</math> The energy required to lift a 1 kg satellite into geosynchronous orbit is the difference between the energy of each of the 2 orbits (geosynchronous and earth). :<math>E_{orbital} = \frac{h c}{2 \pi r_{6371}} - \frac{h c}{2 \pi r_{42164}} = 0.412 x10^{-32}J</math> (energy per orbital) :<math>E_{total} = E_{orbital} N_{orbitals} = 53 MJ/kg</math> The orbital angular momentum of the planets derived from the angular momentum of the respective orbital pairs. :<math>N_{orbitals} = \frac{M_{sun}}{m_P} \frac{M_{planet}}{m_P}</math> :<math>n_g = \sqrt{\frac{R_{radius} m_P}{2 \alpha l_p M_{sun}}} </math> :<math>L_{oam} = 2\pi \frac{M r^2}{T} = N_{orbitals} n_g\frac{h}{2\pi} \sqrt{2 \alpha_{inv}},\;\frac{kg m^2}{s} </math> The orbital angular momentum of the planets; mercury = .9153 x10<sup>39</sup> venus = .1844 x10<sup>41</sup> earth = .2662 x10<sup>41</sup> mars = .3530 x10<sup>40</sup> jupiter = .1929 x10<sup>44</sup> pluto = .365 x10<sup>39</sup> [[File:Newton-vs-Orbital-trajectory_comparison.png|thumb|right|479px|Comparison of Newtonian and Orbital model simulations]] ==== Orbital vs. Newton ==== A 3-body orbit <ref>https://codingthecosmos.com/orbitals/ Newton-vs-Orbital_Newton.py</ref><ref>https://codingthecosmos.com/orbitals/ Newton-vs-Orbital_Orbital.py</ref> is compared with the equivalent orbit using Newtonian dynamics. The start positions are the same r0=2*α; x1=3490.3069; y1=0; x2=cos(pi*2/3)*r0; y2=sin(pi*2/3)*r0; x3=cos(pi*2/3)*r0; y3=sin(pi*2/3)*r0 The orbiting point was used to determine the optimal G for the Newtonian orbit (G = 0.4956). Period of orbit (<math>k_r</math> = 2.19006) :<math>t_{calc}</math> = 1122034 :<math>t_{orbital}</math> = 1121397 :<math>t_{newton}</math> = 1125633 [[File:orbit-points32-orbitals496-clumping-over-time.gif|thumb|right|640px|32 mass points (496 orbitals) begin with random co-ordinates, after 2<sup>32</sup> steps they have clumped to form 1 large mass and 2 orbiting masses.]] ==== Freely moving points ==== The simulation calculates each point as if freely moving in space, and so is useful with 'dust' clouds where the freedom of movement is not restricted. In this animation, 32 mass points begin with random co-ordinates (the only input parameter here are the start (''x'', ''y'') coordinates of each point). We then fast-forward 2<sup>32</sup> steps to see that the points have now clumped to form 1 larger mass and 2 orbiting masses. The larger center mass is then zoomed in on to show the component points are still orbiting each other, there are still 32 freely orbiting points, only the proximity between them has changed, they have formed ''planets''. [[File:relativistic-quantum-gravity-orbitals-codingthecosmos.png|thumb|right|480px|Illustration of B's cylindrical orbit relative to A's time-line axis]] ==== Hyper-sphere orbit ==== {{main|User:Platos_Cave_(physics)/Simulation_Hypothesis/Relativity}} Each point moves 1 unit of (Planck) length per 1 unit of (Planck) time in '''x, y, z''' (hyper-sphere) co-ordinates, the simulation 4-axis hyper-sphere universe expanding in uniform (Planck) steps (the simulation clock-rate) as the origin of the speed of light, and so (hyper-sphere) time and velocity are constants. Particles are pulled along by this expansion, the expansion as the origin of motion, and so all objects, including orbiting objects, travel at, and only at, the speed of light in these hyper-sphere co-ordinates <ref>Macleod, Malcolm; {{Cite journal |title=2. Relativity as the mathematics of perspective in a hyper-sphere universe |journal=SSRN |date=2014 | doi=10.2139/ssrn.3334282 }}</ref>. Time becomes [[v:User:Platos Cave (physics)/Simulation_Hypothesis/God_(programmer)#Universe_time-line |time-line]]. While ''B'' (satellite) has a circular orbit period on a 2-axis plane (the horizontal axis representing 3-D space) around ''A'' (planet), it also follows a cylindrical orbit (from B<sup>1</sup> to B<sup>11</sup>) around the ''A'' time-line (vertical expansion) axis ('''t<sub>d</sub>''') in hyper-sphere co-ordinates. ''A'' is moving with the universe expansion (along the time-line axis) at (''v = c''), but is stationary in 3-D space (''v'' = 0). ''B'' is orbiting ''A'' at (''v = c''), but the time-line axis motion is equivalent (and so `invisible') to both ''A'' and ''B'', as a result the orbital period and velocity measures will be defined in terms of 3-D space co-ordinates by observers on ''A'' and ''B''. === Atomic orbitals === [[File:H-orbit-transitions-n1-n2-n3-n1.gif|thumb|right|640px|fig 5. H atom orbital transitions from n1-n2, n2-n3, n3-n1 via 2 photon capture, photons expand/contract the orbital radius. The spiral pattern emerges because the electron is continuously pulled in an anti-clockwise direction by the rotating orbital.]] ==== Gravitational orbit ==== In the context of the gravitational orbital pair model, the atomic orbital is treated as a 2-body orbit (the electron as a point orbiting an n-body central mass 'nucleus'). To simulate electron transition between orbitals, at each step a unit of length is added. As the electron still continues its orbit, instead of a circular path, it traces a spiral path outwards. Notes: 1. Seen from the wave-point oscillation cycle model, the electron is predominately in the electric wave-state (which is a locally undefined state), the simulation program can only calculate the mass point-states, and so we are mapping only the gravitational orbital component of the electron orbit. For the gravitational orbit, the orbit co-ordinates were updated per unit of Planck time (with orbitals rotating 1 unit of Planck length). In the atomic orbital we have only 1 point (the electron), and it occurs as a point only after every wavelength cycle, and so we are updating our orbit only after every wavelength cycle. For example we find that at the lowest (''n'' = 1) orbit, there are about 471964 wave-point oscillations, and so we will map a polygon with 471964 sides (the wave state cannot be mapped). To compensate, the orbital rotation angle is modified such that 471964 steps are required to map 1 complete orbit ; :<math>\beta_{orbital} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>r_{ij} = \sqrt{2 \alpha}</math> 2. During transition, at each step 1 unit of the photon is absorbed by the orbital radius, this continues until the photon is completely absorbed, the orbital radius extending proportionately. Photon absorption is not instantaneous, but instead occurs over time according to the photon wavelength. The number of steps required for this absorption then gives us the transition frequency. Notably, at integer (''Bohr'') radius (4''r'', 9''r'', 16''r''...) the spiral angle is a function of pi (2pi, (8/3)pi, 3pi ...), and as this is a linear extrapolation (the orbital radius grows in steps), ''n'' level orbits can be interpreted as specific orbits (which are inherently stable) occurring along the semi-continuous transition orbital path traced by the electron. The electron does not jump between n-levels, but the interim state (the transition phase) between these quantized n-levels is an orbital-photon hybrid state and thus difficult to detect. We may then have the equivalent of a non-integer ''n'', but as it is interchangeable with spiral angle and radius, we need only 1 parameter to calculate the other 2, and as transition frequency can also be determined in terms of angle and radius, we have a simple geometrical model that provides a framework for the transition process yet uses only pi and alpha as inputs. ==== 2-Photon orbital model ==== The Lyman series energy formula can be decomposed: :<math>\frac{1}{\lambda} = R_\infty\left(1 - \frac{1}{n^2}\right) = R_\infty - \frac{R_\infty}{n^2}</math> Mathematically (if not physically) we can divide into 2 waves :<math>\text{Photon}_{n1} = R_\infty</math> :<math>\text{Photon}_{nfinal} = (- \frac{R_\infty}{n^2})</math> :<math>\text{Photon}_{\text{total}} = \text{Photon}_{n1} + (-\text{Photon}_{n\text{final}})</math> This (mathematical) approach permits us to divide the transition into two distinct geometric processes taking place between the incoming photon and the orbital radius, with the electron taking a relatively passive role. Rather than 2 actual distinct photons, we may presume two geometric phases of a single photon absorption, nevertheless the 2-photon image is easier to conceptualize. Note these processes are not instantaneous but rather occur over time in discrete steps; '''Process 1 (Cancellation):''' A photon with energy corresponding to the ''n''=1 orbital frequency '''cancels''' the existing orbital structure. :<math>\text{Photon}_{n1} + \text{Orbital}_{n1} == zero</math> '''Process 2 (Creation):''' A (-) photon with energy corresponding to the <math>n_{\text{final}}</math> orbital '''creates''' the new orbital structure. :<math>\text{Photon}_{nfinal} == \text{Orbital}_{nfinal}</math> During transition, the system exists in a photon-orbital hybrid state. This is not a quantum superposition but a geometric intermediate configuration where: : The incoming photon’s momentum is being transferred incrementally : The orbital structure is simultaneously being dismantled and reconstructed : The electron mediates the momentum transfer through its position : Each steps transfers a quantum of momentum The gravitational orbit returns results analogous to the Bohr model and the 2-photon approach complements the (electric wave-state) Schrodinger equation <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref>. ==== Theory ==== =====Hyperbolic spiral===== [[File:Hyperbol-spiral-1.svg|thumb|right|320px|Hyperbolic spiral]] A [[w:hyperbolic spiral |hyperbolic spiral]] is a type of [[w:spiral|spiral]] with a pitch angle that increases with distance from its center. As this curve widens (radius '''r''' increases), it approaches an [[w:asymptotic line|asymptotic line]] (the '''y'''-axis) with the limit set by a scaling factor '''a''' (as '''r''' approaches infinity, the '''y''' axis approaches '''a'''). For the particular spiral that the electron transition path maps, periodically the spiral angles converge to give integer radius, the general form for this type of spiral (beginning at the outer limit ranging inwards); :<math>x = a^2 \frac{cos(\varphi)}{\varphi^2},\; y = a^2 \frac{sin(\varphi)}{\varphi^2},\;0 < \varphi < 4\pi</math> :radius = <math>\sqrt(x^2 + y^2) r</math> :<math>\varphi = (2)\pi, \; 4r</math> (360°) :<math>\varphi = (4/3)\pi,\; 9r</math> (240°) :<math>\varphi = (1)\pi, \; 16r</math> (180°) :<math>\varphi = (4/5)\pi, \; 25r</math> (144°) :<math>\varphi = (2/3)\pi, \; 36r</math> (120°) [[File:Bohr atom model (mul).svg|thumb|right|320px|Electron at different ''n'' level orbitals]] =====Principal quantum number '''n'''===== The H atom has 1 proton and 1 electron orbiting the proton, in the [[w:Bohr model |Bohr model]] (which approximates a gravitational orbit), the electron can be found at select radius ([[w:Bohr radius |the Bohr radius]]) from the proton (nucleus), these radius represent the permitted energy levels (orbital regions) at which the electron may orbit the proton. Electron transition (to a higher energy level) occurs when an incoming photon provides the required energy (momentum). Conversely emission of a photon will result in electron transition to a lower energy level. The [[w:principal quantum number |principal quantum number ''n'']] denotes the energy level for each orbital. As ''n'' increases, the electron is at a higher energy level and is therefore less tightly bound to the nucleus (as ''n'' increases, the electron orbit is further from the nucleus). Each shell can accommodate up to ''n''² (1, 4, 9, 16 ... ) electrons. Accounting for two states of spin this becomes 2''n''² electrons. As these energy levels are fixed according to this integer ''n'', the orbitals may be said to be quantized. =====(Bohr) orbital===== Setting <math>\alpha_{inv} = \frac{1}{\alpha}</math> = 137.035999177⁠ (CODATA 2022) The Bohr radius has 2 components, the dimensionless (the [[w:fine structure constant|fine structure constant alpha]]) and the dimensioned (electron wavelength); :<math>a_0 = \alpha_{inv} \times \lambda_e</math> The orbital radius of this model also includes the proton wavelength and so is slightly greater than 2x the Bohr radius :<math>\lambda_0 = \lambda_p + \lambda_e</math> :<math>r_0 = 2 \alpha_{inv} \times \lambda_0</math> To reduce simulation computing time, only the alpha component is described here, the dimensioned components added later. :<math>r_{orbital} = 2 \alpha_{inv} n^2</math> As a mass point, the electron orbits the proton at a fixed radius (<math>r_{orbital}</math>) in a series of steps (the duration of each step corresponds to the wavelength component). The distance travelled per step (per wave-point oscillation) equates to the distance between mass point states and is the inverse of the radius. [[File:atomic-orbital-rotation-step.png|thumb|right|208px|electron (blue dot) moving 1 step anti-clockwise along the alpha orbital circumference]] length = <math>l_{step} = \frac{1}{r_{orbital}}</math> Duration = 1 step per wavelength and so velocity velocity = <math>v_{orbital} = v_{step} = \frac{1}{2\alpha_{inv} n}</math> Giving period of orbit period = <math>t_{orbital} = \frac{2\pi r_{orbital}} {v_{orbital}} = 2\pi 2\alpha_{inv} 2\alpha_{inv} n^3 </math> The (reference) orbital (''n'' = 1) :<math>t_{n1} = 2\pi 4 \alpha_{inv}^2</math> = 471964.356... The angle of rotation depends on the orbital radius :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}}\sqrt{2\alpha_{inv}}}</math> ===== 2-Photon orbitals ===== The electron can jump between ''n'' energy levels via the absorption or emission of a photon. In the 2-photon orbital model <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref>, the orbital (Bohr) radius is treated as a 'physical wave' (has physical properties) akin to the photon albeit an inverse such that <math>orbital \;radius + photon = zero</math> (they cancel). As such it is the orbital radius itself that absorbs or emits the photon during transition, in the process the orbital radius is extended or reduced (until the photon is completely absorbed/emitted). The electron has a `passive' role in the transition phase (mediating the exchange of momentun between the orbital and the photon). It is the rotation of the orbital radius that drives the electron motion, resulting in the electron orbit around the nucleus (orbital momentum comes from the orbital radius), and this rotation continues also during the transition phase resulting in the electron following a hyperbolic spiral path. ====== Spiral (mass point) ====== The photon is divided into 2 photons as per the Rydberg formula (denoted initial and final). :<math>\lambda_{photon} = (+\lambda_i) - (+\lambda_f)</math> The wavelength of the (<math>\lambda_i</math>) photon corresponds to the wavelength of the orbital radius. The (+<math>\lambda_i</math>) will then delete the orbital radius as described above (''orbital'' + ''photon'' = ''zero''), however the (-<math>\lambda_f</math>), because of the Rydberg minus term, will be equivalent to the orbital radius, and so conversely will increase the orbital radius. And so for the duration of the (+<math>\lambda_i</math>) photon wavelength, the orbital radius does not change as the 2 photons cancel each other; :<math>r_{orbital} = r_{orbital} + (\lambda_i - \lambda_f)</math> However, the (<math>\lambda_f</math>) has the longer wavelength, and so after the (<math>\lambda_i</math>) photon has been absorbed, and for the remaining duration of this (<math>\lambda_f</math>) photon wavelength, the orbital radius will be extended until the (<math>\lambda_f</math>) is also absorbed (the '''transition phase'''). For example, the electron is at the ''n'' = 1 orbital. To jump from an initial <math>n_i = 1</math> orbital to a final <math>n_f = 2</math> orbital, first the (<math>\lambda_i</math>) photon is absorbed by the orbital radius (<math>\lambda_i + \lambda_{orbital} = zero</math>), but simultaneously the (-<math>\lambda_f</math>) photon adds to the orbital radius, and so the electron follows a normal ''n'' = 1 orbit (the '''orbital phase'''), then the remaining (<math>\lambda_f</math>) photon continues until it too is absorbed (the '''transition phase'''). :<math>\lambda_i = 1 \times t_{n1}</math> (initial orbital) :<math>\lambda_f = n^2 \times t_{n1}</math> (final orbital) After the (<math>\lambda_i</math>) photon is absorbed, the (<math>\lambda_f</math>) photon still has <math>\lambda_f = (n_f^2 - n_i^2)t_{n1} = 3 t_{n1}</math> steps remaining until it too is absorbed. [[File:atomic-orbital-transition-alpha-steps.png|thumb|right|277px|orbital transition during orbital rotation]] This process does not occur as a single `jump' between energy levels by the electron, but rather absorption/emission of the photon takes place in discrete steps, each step corresponds to a unit of <math>r_{incr}</math> (both photon and orbital radius may be considered as constructs from multiple units of this geometry); :<math>r_{incr} = -\frac{1}{2 \pi 2\alpha_{inv}}</math> At each step 1 unit of <math>r_{incr}</math> is transferred from each photon to the orbital radius. During the orbital phase the <math>r_{incr}</math> unit from the (<math>\lambda_i</math>) photon is canceled by the (-)<math>r_{incr}</math> unit from the (<math>\lambda_f</math>) photon (<math>r_{incr}</math> + (-)<math>r_{incr}</math> = zero) and so the orbital radius does not change. After the (<math>\lambda_i</math>) photon is fully absorbed, the orbital radius continues to absorb (-)<math>r_{incr}</math> units from (what remains of) the (<math>\lambda_f</math>) photon, and as the (<math>\lambda_f</math>) photon is equivalent to the orbital radius, the orbital radius extends in these steps as a consequence. The number of steps <math>N_{steps}</math> required determines (and so can be used to calculate) the transition frequency. Furthermore at each step the orbital radius itself continues to rotate, the electron, being pulled along by this rotation according to angle β, thereby traces a spiral path as the orbital radius length changes. :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} r_{\alpha}}</math> The (accumulated) spiral angle <math>\Phi</math> at each <math>n^2</math> :n = 1 to 2: <math>\Phi = 2\pi \; (r = 4 \times \; r_{orbital}) </math> :n = 1 to 3: <math>\Phi = \frac{8}{3} \pi \; (r = 9 \times \; r_{orbital}) </math> :n = 1 to 4: <math>\Phi = 3\pi \; (r = 16 \times \; r_{orbital}) </math> :n = 1 to 5: <math>\Phi = \frac{16}{5}\pi \; (r = 25 \times \; r_{orbital}) </math> :n = 1 to 6: <math>\Phi = \frac{10}{3}\pi \; (r = 36 \times \; r_{orbital}) </math> :n = 1 to 7: <math>\Phi = \frac{7}{4}\pi \; (r = 49 \times \; r_{orbital}) </math> :n = 1 to 8: <math>\Phi = \frac{7}{2}\pi \; (r = 64 \times \; r_{orbital}) </math> In the mass state we can divide the photon into 2 mathematical structures, the transition frequency is defined as the inverse of one oscillation period at the Compton scale, multiplied by the geometric phase factor (including the dimensioned terms). This gives us the solution for the transition frequency and the Bohr radius with a pi-based spiral acting as the transition 'guard-rail'. We are using only alpha and pi, yet the transition frequency can be solved with high precision using the gravity simulator. This gives a geometrical derivation for the Bohr model, which in this context is the gravitational component of the electron orbit. ====== Photon-Orbital Hybrid (wave-state) ====== In this model, atomic orbitals are '''physical rotating structures''' rather than probability distributions. The orbital possesses: :Angular momentum: Quantized by discrete rotation steps :Energy: Stored in the rotating configuration The orbital rotates in discrete steps (β radians per step) rather than continuously. During transition, the system exists in a '''photon-orbital hybrid state'''. This is not a quantum superposition but a '''geometric intermediate configuration''' where: :The incoming photon's momentum is being transferred incrementally :The orbital structure is simultaneously being dismantled and reconstructed :The electron mediates the momentum transfer through its position :Each step transfers a quantum of momentum We then note. '''Standard QM''': Anti-realist---the wavefunction is a calculation tool, not a physical entity. Reality emerges only upon measurement. '''2-photon model''': Realist---orbitals are real rotating structures. The electron follows definite trajectories, even when unobserved. The geometric model thus establishes a '''two-layer architecture''' for encoding quantum states: :Geometric Framework Layer: The hyperbolic spiral structure provides the spatial scaffold <math>(r, \theta, \phi)</math> coordinates with built-in radial quantization <math>r \propto n^2</math> :Photon Information Layer: The absorbed photon carries angular momentum quantum numbers <math>(l, m_l)</math> that modulate this scaffold This separation offers that the Bohr model is not replaced by the Schrodinger equation but rather complements it (the mass-state provides the geometric structure; the photon-orbital hybrid provides the angular momentum content). ===== Simulation ===== [[File:Alpha-hyperbolic-spiral.gif|thumb|right|640px|Bohr radius during ionization, as the H atom electron reaches each ''n'' level, it completes 1 orbit (for illustration) then continues outward (actual velocity will become slower as radius increases according to angle β)]] The gravity simulation (<ref>https://codingthecosmos.com/orbitals/ source code</ref>) was setup with the electron as the orbiting point and 65 mass points to represent the nucleus (although the proton-electron mass ratio is 1836:1, this would be become a 1837-body set of orbiting points which is too computationally intensive). The program was modified with the rotational angle β as :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} r_{\alpha}}</math> To simulate the transition phase, at each step 1 unit of <math>r_{incr} = \frac{1}{2 \pi 2\alpha_{inv}}</math> was added to the proton-electron orbital radius. To convert to frequency in Hz, the dimension components were added :<math>f_H = \frac{2c}{\lambda_e + \lambda_p}</math> = 0.155184298 10²²s^-1 For n = 1 to n = n² :<math>f_n = 2\pi f_H \;\frac{n^2 - 1}{N_{steps}} </math> '''Results''' {| class="wikitable" !<math>r/r_{orbital}</math> !! <math>r/r_{orbital}</math> !! N-steps !! <math>\Phi</math> (deg) !! frequency Hz |- | 4.000000115 | 2.000004018 | 1887860.649 | 0.000017120 | 2466034304131826.5 |- | 8.999994875 | 4.000003286 | 4247681.247 | 120.000001964 | 2922708926063928.0 |- | 15.999987119 | 6.000002004 | 7551428.532 | 180.000002514 | 3082545855782738.5 |} Experimental values for H(1s-ns) transitions. :H(1s-2s) = 2466 061 413 187.035 kHz <ref>http://www2.mpq.mpg.de/~haensch/pdf/Improved%20Measurement%20of%20the%20Hydrogen%201S-2S%20Transition%20Frequency.pdf</ref> :H(1s-3s) = 2922 743 278 665.79 kHz <ref>https://pubmed.ncbi.nlm.nih.gov/33243883/</ref> :H(1s-4s) = 3082 581 563 822.63 kHz <ref>https://codata.org/</ref> Although the simulation was a standard gravitational orbit (charge-less) and without a relativistic correction, the results were quite close; :n = 1 to n = 2: margin = 100 * (experimental - simulated)/experimental = 0.001099% :n = 1 to n = 3: margin = 0.001175% :n = 1 to n = 4: margin = 0.001158% ====== Rydberg atom ====== Here a Rydberg atom is defined as an (idealized) atom with a nucleus of point size and an infinite mass and so the barycenter = atom center at co-ordinates (0, 0). We can simulate this as a simple transition beginning at the initial (''n''_i = 1) orbital. :<math>\varphi = 0</math> (start angle) :<math>r_{orbital} = r_0 = 2\alpha</math> (nb. Bohr radius = <math>\alpha \lambda_e</math> = α*electron wavelength) :<math>x = r_{orbital},\; y = 0</math> (start co-ordinates) For each step during transition, setting t = step number (FOR t = 1 TO ...), we can calculate the radius ''r'' and <math>n_f</math>. :<math>r = r_{orbital} + \frac{t}{2\pi 2\alpha}</math> (number of increments ''t'' of <math>r_{incr}</math>) :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} \sqrt{2\alpha}}</math> :<math>\varphi = \varphi + \beta</math> :<math>n_f^2 = 1 + \frac{t}{2\pi 4\alpha^2}</math> (<math>n_f^2</math> as a function of ''t'') The spiral angle and <math>n_f^2</math> are interchangeable :<math>\varphi = 4 \pi (1 - \frac{1}{{n_f}^2})</math> We can then re-write (<math>n_f</math> is only an integer at prescribed spiral angles); :<math>\beta = \frac{1}{{r_{orbital}}^2 n_f^3}</math> ''n'' orbital transition periods are multiples of the ''n'' = 1 orbital. If we include a relativistic term; :<math>t_{n1} = 2\pi 4 \alpha_{inv}^2 \sqrt{(1 - \frac{1}{4 \alpha_{inv}^2})}</math> = 471961.21478 Then we can compare a theoretical Rydberg (also without including charge) and find a further improvement. For ionization, the second photon is of such long wavelength that its momentum contribution is negligible, and so the ionization transition frequency should correspond closely to the ''n'' = 1 orbital. :H(1s-∞s) = 3288 086 857 127.60 kHz <ref>https://codata.org/ (109678.77174307cm-1)</ref> (''n'' = ∞) This would give us a H(n1) = 471959.2427762 :n = 1: margin = 100 * (H(n1) - t_{n1})/H(n1) = 0.001099% :n = 1 to n = 2: margin = 100 * (experimental - 4 t_{n1})/experimental = 0.000267% :n = 1 to n = 3: margin = 100 * (experimental - 9 t_{n1})/experimental = 0.000398% :n = 1 to n = 4: margin = 100 * (experimental - 16 t_{n1})/experimental = 0.000422% If we use the non-relativistic <math>t_{n1}</math>, then our results are remarkably close to the results from the gravity simulation suggesting that central mass size does not have the major role in determining the transition frequency. :n = 1 to n = 2: margin = 0.000932% :n = 1 to n = 3: margin = 0.001063% :n = 1 to n = 4: margin = 0.001088% ====== Barycenter correction ====== The experimental hydrogen transition frequencies deviate slightly from the ideal Rydberg formula. When normalized, these deviations exhibit a characteristic pattern: a minimum near ''n'' = 2, followed by a rising trend toward the ionization limit as the radius increases. :H(n1) = 471959.242776 :H(n2) = 471959.956565 :H(n3) = 471959.338749 :H(n4) = 471959.222066 The gravity simulation results showed a similar trend suggesting in both cases a barycenter 'wobble'. :sim(n1) = 471964.35638 :sim(n2) = 471965.14481 :sim(n3) = 471964.88601 :sim(n4) = 471964.68921 Therefore, given the possibilities of this gravity simulator as a research tool, the next step is to divide the proton into 3 parts resembling the 3 quarks, and then experiment with different configurations. For example, we could form a U quark cluster and a D quark cluster and then test different arrangements of the clusters (and also different mass ratios) to determine which, if any, reduces the margin. This could give potential insights into the protons internal structure. We can also give the electron further mass points to determine if it also becomes constrained and relaxed. ==Article series== The following are HTML transcripts of journal articles * [[https://simulationuniverse.org/ simulationuniverse.org]]: Home page ===The 3 levels=== A model overview from the sub Planck scale to the container universe * [[https://codingthecosmos.org/1a-CMB_from_Planck_unit_scaffolding.html 1a. Planck unit CMB.html]]: Part 1. A CMB from Planck units * [[https://codingthecosmos.org/1b-Sub_Planck_scale_from_tau_loop.html 1b. The Minimal Complexity Algorithm of the Planck Scaffolding]]: Part 2. The sub-Planck scale and the tau-loop * [[https://codingthecosmos.org/1c-the_Heavens_a_container_universe.html 1c. the Heavens.html]]: Part 3. The Heavens (the container universe) ===General articles=== * [[https://codingthecosmos.org/2-Relativity_as_mathematics_of_perspective.html 2-Relativity-hypersphere.html]]: Relativity as the mathematics of perspective * [[https://codingthecosmos.org/3-Gravity_via_n-body_particle_orbitals.html 3-Gravitational-orbitals.html]]: Gravity as sum of n-body rotating orbital particle-particle pairs * [[https://codingthecosmos.org/4-Atomic-orbital_transition_using_Gravity_simulator.html 4-Atomic-orbitals.html]]: Atomic orbitals as single rotating orbital particle-particle pairs * [[https://codingthecosmos.org/5-Atomic_transition_via_photon_orbital_hybrid.html 5-w_axis.html]]: Imaginary number axis (radiation domain) * [[https://codingthecosmos.org/6-Natural_Planck_units_MTP_Fine_Structure_Constant_alpha.html 6-Physical-constant-anomalies.html]]: Derivation of the fine structure constant alpha from physical constant anomalies * [[https://codingthecosmos.org/7-Mathematical_electron_magnetic_monopole-quarks.html 7-Monopole-quarks.html]]: Quarks as magnetic monopoles * [[https://codingthecosmos.org/8-Holographic_universe_2D_plus_Compton_wavelength.html 8-Holographic-universe.html]]: Hypersphere surface as 2-D analogue ===Wiki series=== Introductions to principle concepts (for more detailed discussion see General articles) * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_units_(geometrical)]]: Planck units MLTPA as geometrical objects * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Electron_(mathematical)]]: Mathematical electron formula * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Relativity]]: Relativity as a translation between 2 co-ordinate systems * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_unit_scaffolding]]: CMB and a Planck unit universe scaffolding * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Sqrt_Planck_momentum]]: Link between charge and mass * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/God_(programmer)]]: Introduction to a Planck scale Programmer God Simulation Hypothesis model == External links == * [https://codingthecosmos.com/ Planck scale modelling using geometrical objects] * [https://www.amazon.com/Our-Mathematical-Universe-Ultimate-Reality/dp/0307599809 Our Mathematical Universe: My Quest for the Ultimate Nature of Reality] -Max Tegmark (Book) * [https://link.springer.com/article/10.1134/S0202289308020011/ Dirac-Kerr-Newman black-hole electron] -Alexander Burinskii (article) * [https://plato.stanford.edu/entries/pythagoras/ Pythagoras "all is number"] - Stanford University * [[w:Mathematical universe hypothesis | Mathematical universe hypothesis]] * [[w:Philosophy of mathematics | Philosophy of mathematics]] * [[w:Philosophy of physics | Philosophy of physics]] * [[w:Platonism | Platonism]] ==References== {{Reflist}} __INDEX__ qm26f9zuoii7etjqn3opa0gik8r4vd5 2835111 2835064 2026-09-30T03:56:07Z Platos Cave (physics) 2562653 2835111 wikitext text/x-wiki {{Original research}} '''Simulating gravitational and atomic orbits via n-body rotating particle-particle orbital pairs at the Planck scale''' The following describes a geometrical method for simulating gravitational orbits <ref>Macleod, Malcolm J.; {{Cite journal |title=3. Gravitational orbits from n-body rotating particle-particle orbital pairs |journal=SSRN |date=Dec 2021 | doi=10.2139/ssrn.3444571}}</ref><ref>https://simulationuniverse.org/9-Source-codes.html Gravitational orbital simulation source codes in C</ref> and atomic orbitals <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref><ref>https://simulationuniverse.org/9-Source-codes.html Atomic orbital transitions simulation source codes in C</ref> via an n-body network of rotating individual particle-particle orbital pairs . Although the simulation is dimensionless (the only physical constant used is the [[w:fine structure constant |fine structure constant alpha]]), it can translate via the [[w:Planck_units |Planck units]] for comparisons with real world orbits. The orbits generated by this dimensionless geometrical approach can be formulated, and despite not using Newtonian physics these formulas demonstrate consistency; for example the derived formulas for radius R, period T and (M + m) will reduce [[v:Quantum_gravity_(Planck)#Kepler's_formula_=_G |Kepler's formula]] to '''G''' <ref>https://codingthecosmos.com/orbitals/maple-code-Kepler.html maple code</ref>. Likewise the atomic orbital shells naturally quantize according to pi without relying on built-in postulates. [[File:Gravitational-regular-3body-orbit.gif|thumb|right|640px|A regular 3-body orbit. The simulation begins with the start (x, y) co-ordinates of each point. No other parameters are required. r0=2*α; x1=1789.5722983; y1=0; x2=cos(pi*2/3)*r0; y2=sin(pi*2/3)*r0; x3=cos(pi*2/3)*r0; y3=sin(pi*2/3)*r0]] :<math>\frac{4 \pi^2 R^3}{(M+m) T^2} = \frac{l_p c^2}{m_P} = G</math> The simulation source code(s) used here are listed below, these give a precise description of this orbital model and so can be used as reference <ref>https://codingthecosmos.com/orbitals/ Orbital model simulation source codes</ref>. For simulating gravity, orbiting objects ''A'', ''B'', ''C''... are sub-divided into discrete points, each point can be represented as 1 unit of [[w:Planck mass |Planck mass]] ''m''_P (for example, a 1kg satellite would be divided into 1kg/''m''_P = 45940509 points). Each point in object ''A'' then forms an orbital pair with every point in objects ''B'', ''C''..., resulting in a universe-wide, n-body network of rotating point-to-point orbital pairs . Each orbital pair rotates 1 unit of length per unit of time, when these orbital pair rotations are summed and mapped over time, gravitational orbits emerge between the objects ''A'', ''B'', ''C''... The base simulation requires only the start position (''x'', ''y'' coordinates) of each point, as it maps only rotations of the points within their respective orbital pairs then information regarding the macro objects ''A'', ''B'', ''C''...; momentum, center of mass, barycenter etc ... is not required (each orbital is calculated independently of all other orbitals). For simulating electron transition within the atom, the same program is used. The electron is assigned as a single point, the nucleus as multiple points clustered together (a 2-body orbit), and an incoming 'photon' (a unit of length) is added to (increases) the electron - proton orbital radius in a series of discrete steps (rather than a single 'jump' between orbital shells). As the electron continues to orbit the nucleus during this transition phase, the electron path traces a [[w:hyperbolic spiral |hyperbolic spiral]]. Although we are mapping the electron transition as a gravitational orbit on a 2-D plane, periodically the transition spiral angles converge to give an integer orbital radius (360°=4''r'', 360+120°=9''r'', 360+180°=16''r'', 360+216°=25''r'' ... 720°=∞''r''), a radial quantization (as a function of pi and so of geometrical origin) naturally emerges. Furthermore, the transition steps between these radius can then be used to solve the transition frequency, replicating the Bohr model. The gravitational orbit returns results analogous to the Bohr model and the 2-photon orbital model approach complements the (electric wave-state) [[w:Schrodinger equation |Schrodinger wave equation]]. [[File:complex-orbit-pts26-r17-1-7-1.gif|thumb|right|640px|By selecting the start co-ordinates on a 2-D plane for each point accordingly, we can 'design' the required orbits. The 26 points orbit each other resulting in 325 point-point orbitals.]] === Theory === In the simulation, particles are treated as an electric wave-state to (Planck) mass point-state oscillation, the wave-state as the duration of particle frequency in Planck time units, the point-state duration as 1 unit of Planck time (as a point, this state can be assigned mapping coordinates), the particle itself is a continuous oscillation between these 2 states (i.e.: the particle is not a fixed entity). For example, an electron has a frequency (wave-state duration) = 10²³ units of Planck time followed by the mass state (1 unit of Planck time). The background to this oscillation is given in the [[v:Electron (mathematical) |mathematical electron]] model. If the electron '''has (is)''' mass (1 unit of Planck mass) for 1 unit of Planck time, and then '''no''' mass for 10²³ units of Planck time (the wave-state), then in order for a (hypothetical) object composed only of electrons to '''have (be)''' 1 unit of Planck mass at every unit of Planck time, the object will require 10²³ electrons. This is because orbital rotation occurs at each unit of Planck time and so the simulation requires this object to have a unit of Planck mass at each unit of Planck time (i.e.: on average there will always be 1 electron in the mass point state). We would then measure the mass of this object as 1 Planck mass (the measured mass of an object reflects the average number of units of Planck mass per unit of Planck time). For the simulation program, this Planck mass object can now be defined as a point (it will have point co-ordinates at each unit of Planck time and so can be mapped). As the simulation is dividing the mass of objects into these Planck mass size points and then rotating these points around each other as point-to-point orbital pairs, then by definition gravity is a mass to mass interaction. Nevertheless, although this is a mass-point to mass-point rotation, and so referred to here as a point-point orbital, it is still a particle to particle orbital, albeit the particles are both in the mass state. We can also map individual particle to particle orbitals albeit as gravitational orbits, the H atom is a well-researched particle-to-particle orbital pair (an electron orbiting a proton) and so can be used as reference. To map orbital transitions between energy levels, the simulation uses the [[v:Quantum_gravity_(Planck)#Photon_orbital_model |photon-orbital model]], in which the orbital (Bohr) radius is treated as a 'physical wave' akin to the photon albeit of inverse or reverse phase. The photon can be considered as a moving wave, the orbital radius as a standing/rotating wave (trapped between the electron and proton). Orbital momentum derives from this orbital radius, it is the rotation of the orbital radius that pulls the electron, resulting in the electron orbit around the nucleus. Furthermore, orbital transition (between orbitals) occurs between the orbital radius and the photon, the electron has a passive role. Transition (the electron path) follows a specific [[v:Fine-structure_constant_(spiral) |hyperbolic spiral]] for which the angle component periodically converges to give integer radius where ''r'' = Bohr radius; at 360° radius =4''r'', 360+120°=9''r'', 360+180°=16''r'', 360+216°=25''r'' ... 720°=∞''r''. As these spiral angles (360°, 360+120°, 360+180°, 360+216° ...) are linked directly to pi, and as the electron is following a semi-classical gravitational orbit, this particular quantization has a geometrical origin. Although the simulation is not optimized for atomic orbitals (the nucleus is treated simply as a cluster of points), the transition period '''t''' measured between these integer radius can be used to solve the transition frequencies '''f''' via the general formula <math>f/c = t \lambda_H/(n_f^2-n_i^2)</math>. In summary, both gravitational and atomic orbitals reflect the same particle-to-particle orbital pairing, the distinction being the state of the particles; gravitational orbitals are mass to mass whereas atomic orbitals are predominately wave to wave. There are not 2 separate forces used by the simulation, instead particles are treated as oscillations between the 2 states (electric wave and mass point). The transition spiral provides the geometric structure; the photon-orbital hybrid (2-Photon model) provides the angular momentum content. === N-body orbitals === [[File:8body-27orbital-gravitational-orbit.gif|thumb|right|640px|8-body (8 mass points, 28 orbitals), the resulting orbit is a function of the start positions of each point]] The simulation universe is a 4-axis hypersphere expanding in increments <ref>Macleod, Malcolm; {{Cite journal |title=1. Planck unit scaffolding correlates with the Cosmic Microwave Background |journal=SSRN |date=26 March 2014 | doi=10.2139/ssrn.3333513 }}</ref> with 3-axis (the [[v:User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_unit_scaffolding |hypersphere surface]]) projected onto an (''x'', ''y'') plane with the ''z'' axis as the simulation timeline (the expansion axis). Each point is assigned start (''x'', ''y'', ''z'' = 0) co-ordinates and forms pairs with all other points, resulting in a universe-wide n-body network of point-point orbital pairs. The barycenter for each orbital pairing is its center, the points located at each orbital 'pole'. The simulation itself is dimensionless, simply rotating circles. To translate to dimensioned gravitational or atomic orbits, we can use the Planck units ([[w:Planck mass |Planck mass m_P]], [[w:Planck length |Planck length l_p]], [[w:Planck time |Planck time t_p]]), such that the simulation increments in discrete steps (each step assigned as 1 unit of Planck time), during each step (for each unit of Planck time), the orbitals rotate 1 unit of (Planck) length (at velocity ''c'' = ''l''_p/''t''_p) in hyper-sphere co-ordinates. These rotations are then all summed and averaged to give new point co-ordinates. As this occurs for every point before the next increment to the simulation clock (the next unit of Planck time), the orbits can be updated in 'real time' (simulation time) on a serial processor. Setting <math>\alpha_{inv} = \frac{1}{\alpha}</math> = 137.035999177⁠ (CODATA 2022) Orbital pair rotation on the (''x'', ''y'') plane occurs in discrete steps according to an angle '''β''' as defined by the orbital pair radius (the atomic orbital '''β''' has an additional alpha term). :<math>\beta_{gravity} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>\beta_{atomic} = \frac{1}{\sqrt{2\alpha_{inv}} r_{orbital} \sqrt{r_{orbital}}}</math> As the simulation treats each (point-point) orbital independently (independent of all other orbitals), no information regarding the points (other than their initial start coordinates) is required by the simulation. Although orbital and so point rotation occurs at ''c'', the [[v:Relativity (Planck) |hyper-sphere expansion]] <ref>Macleod, Malcolm; {{Cite journal |title=2. Relativity as the mathematics of perspective in a hyper-sphere universe |journal=SSRN |date=26 March 2014 | doi=10.2139/ssrn.3334282 }}</ref> is equidistant and so `invisible' to the observer. Instead observers (being constrained to 3D space) will register these 4-axis orbits (in hyper-sphere co-ordinates) as a circular motion on a 2-D plane (in 3-D space). An apparent [[w:Time_dilation |time dilation]] effect emerges as a consequence. [[File:4body-orbital-3x10x-gravitational-orbit.gif|thumb|right|640px|Symmetrical 4 body orbit; (3 center mass points, 1 orbiting point, 6 orbital pairs). Note that all points orbit each other.]] ==== 2 body orbits ('''x, y''' plane) ==== For simple 2-body orbits, to reduce computation only 1 point is assigned as the orbiting point and the remaining points are assigned as the central mass. For example the ratio of earth mass to moon mass is 81:1 and so we can simulate this orbit accordingly. However we note that the only actual distinction between a 2-body orbit and a complex orbit being that the central mass points are assigned ('''x, y''') co-ordinates relatively close to each other, and the orbiting point is assigned ('''x, y''') co-ordinates distant from the central points (this becomes the orbital radius) ... this is because the simulation treats all points equally, the center points also orbiting each other according to their orbital radius, for the simulation itself there is no difference between simple 2-body and complex n-body orbits. The [[w:Schwarzschild radius |Schwarzschild radius]] formula in Planck units :<math>r_s = \frac{2 l_p M}{m_P}</math> As the simulation itself is dimensionless, we can remove the dimensioned length component <math>2 l_p</math>, and as each point is analogous to 1 unit of Planck mass <math>m_P</math>, then the Schwarzschild radius for the simulation becomes the number of central mass points. We then assign ('''x, y''') co-ordinates (to the central mass points) within a circle radius <math>r_s</math> = number of central points = total points - 1 (the orbiting point). After every orbital has rotated 1 length unit (anti-clockwise in these examples), the new co-ordinates for each rotation per point are then averaged and summed, the process then repeats. After 1 complete orbit (return to the start position by the orbiting point), the period '''t''' (as the number of increments to the simulation clock) and the ('''x, y''') plane orbit length '''l''' (distance as measured on the 2-D plane) are noted. '''Key''': 1. '''i''' = r<sub>s</sub>; the number of center mass points (the orbited object). 2. '''j''' = total number of points, as here there is only 1 orbiting point; '''j''' = '''i''' + 1 3. '''k<sub>r</sub>''' is a mass to radius co-efficient in the form <math>j_{max} = (k_r i + 1)</math>. This function defines orbital radius in terms of the central mass Schwarzschild radius (<math>i</math>) and the orbiting point (1), thus quantizing the radius. When <math>k_r</math> = 1 then <math>j_{max} = j</math>, and the radius is at a minimum giving an analogue gravitational principal quantum number <math>n_g = j_{max}/j</math>. 4. '''x, y''' = start co-ordinates for each point (on a 2-D plane), '''z''' = 0. 5. '''r<sub>α</sub>''' = a radius constant, here r<sub>α</sub> = sqrt(2/α) = 16.55512; where alpha = inverse [[w:fine structure constant |fine structure constant]] = 137.035 999 084 (CODATA 2018). This constant adapts the simulation specifically to gravitational and atomic orbitals. :<math>r_{\alpha} = \sqrt{2\alpha_{inv}} </math> :<math>r_{orbit} = {r_{\alpha_{inv}}}^2 \;*\; r_{wavelength} </math> 6. Rotation angle β :<math>\beta_{orbital} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>r_{ij} = \sqrt{\frac{2 j}{i}}</math> (for each gravitational orbital in the simulation) :<math>r_{ij} = \sqrt{2 \alpha_{inv}}</math> (for each atomic orbital in the simulation) ==== Orbital formulas (2-D plane)==== :<math>j = i + 1</math> :<math>r_{orbit} = 2 \alpha_{inv} 2 \frac{(k_r i + 1)^2}{i^2}</math>, orbital radius (center mass to point) :<math>r_{ij} = \sqrt{\frac{i}{j}}</math> (averaged for each orbit) :<math>t_{orbit} = \frac{2\pi}{ \beta_{orbit}} = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} j^{1/2}}</math>, orbiting point period :<math>r_{barycenter} = \frac{r_{orbit}}{j}</math> :<math>l_{orbit} = 2 \pi (r_{orbit} - r_{barycenter})</math>, distance travelled by orbiting point :<math>v_{orbit} = \sqrt{\frac{i}{r_{orbit}j}}</math>, orbiting point velocity Example (dimensionless). The simulation parameters agree closely with the calculated parameters: :points = 8 (1 orbiting point and 7 center mass points) <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-simulation-2body.c</ref> :i = 7, j = 8 :k<sub>r</sub> = 32 :<math>\sqrt{2j/i}</math> = 1.511858 Calculated :calculated orbit period = 2504836149.00059 :calculated orbit radius = 566322.241497 :calculated orbit length = 3113519.13854 :calculated orbit barycenter = 70790.280187, 0 :n<sub>g</sub> = (k<sub>r</sub> i + 1)/j = 28.125 Simulation simulation orbit period = 2504836141 simulation orbit length = 3113519.130546298 simulation orbit barycenter; x = 70790.28092, y = 0.000732 ===== Earth moon orbit===== The earth to moon mass ratio approximates 81:1 and so can be simulated as a 2-body orbit with the moon as a single orbiting point as in the above example. Here we use the orbital parameters to determine the value for the mass to radius coefficient k<sub>r</sub>. Planck length <math>l_p</math>, Planck mass <math>m_P</math> and <math>c</math> are used to convert between the dimensionless formulas and dimensioned SI units. Reference values :<math>M</math> = 5.9722 x 10<sup>24</sup>kg (earth) :<math>m</math> = 7.346 x 10<sup>22</sup>kg (moon) :<math>T_{orbit}</math> = 27.321661*86400 = 2360591.51s To simplify, we assume a circular orbit which then gives us this radius :<math>R_{orbit} = (\frac{G (M+m) T_{orbit}^2}{4 \pi^2})^{(1/3)}</math> = 384714027m :<math>G = \frac{l_p c^2}{m_P}</math> = 0.66725e-10 The mass ratio :<math>i = \frac{M}{m}</math> = 81.298666, j = i + 1 We then find a value for <math>k_r</math> using T<sub>orbit</sub> as our reference (reversing the orbit period equation). :<math>T_o = T_{orbit} \frac{m_P}{M} \frac{c}{l_p} = 16 \pi {\alpha_{inv}}^{3/2} \frac{(k_r i + 1)^3}{i^{5/2} j^{1/2}}</math> (dimensionless orbital period) :<math>k_r = \frac{1}{i} {(\frac{T_o i^{5/2} j^{1/2}}{16 \pi {\alpha_{inv}}^{3/2}})}^{(1/3)} - \frac{1}{i}</math> = 12581.4468 Dimensionless solutions :<math>r_{orbit} = 2 \alpha_{inv} 2 \frac{(k_r i + 1)^2}{i^2}</math> = 86767420100 :<math>t_{orbit} = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} j^{1/2}}</math> = 0.159610040233 x 10<sup>18</sup> :<math>r_{barycenter} = \frac{r_{orbit}}{j}</math> = 1054299229.62 :<math>l_{orbit} = 2 \pi (r_{orbit} - r_{barycenter})</math> = 538551421685 :<math>v = \sqrt{\frac{i}{r_{orbit}j}}</math> = 0.33741701 x 10<sup>-5</sup> Converting back to dimensioned values :<math>R = r_{orbit} l_p \frac{M}{m_P} = R_{orbit}</math> = 384714027m :<math>T = t_{orbit} \frac{l_p}{c} \frac{M}{m_P} = T_{orbit}</math> = 2360591.51s :<math>B = \frac{R}{j}</math> = 4674608.301m (barycenter) :<math>L = 2\pi (R - B)</math> = 2387858091.51m (distance moon travelled around the barycenter) :<math>V = c \sqrt{\frac{i}{r_{orbit}j}}</math> = 1011.551m/s (velocity of the moon around the barycenter) If we expand the velocity term :<math>v_{orbit} = c \sqrt{\frac{i}{r_{orbit}j}}</math> :<math>v_{orbit}^3 = \frac{G M}{T_{orbit}} 2\pi \frac{i^2}{j^2}</math> Note: The [[w:standard gravitational parameter | standard gravitational parameter]] ''μ'' is the product of the gravitational constant ''G'' and the mass ''M'' of that body. For several objects in the Solar System, the value of ''μ'' is known to greater accuracy than either ''G'' or ''M''. :<math>\mu_{earth}</math> = 3.986004418(8)e14 :<math>\mu_{moon}</math> = 4.9048695(9)e12 :<math>i = \frac{\mu_{earth}}{\mu_{moon}}</math> = 81.2662685 :<math>k_r = \frac{c}{2 \sqrt{\alpha_{inv}}} {(\frac{T_{orbit}}{2 \pi \mu_{earth}})}^{1/3} \frac{(i+1)}{i}^{1/6} - \frac{1}{i}</math> = 12580.3462 :<math>t_{orbit}</math> = 0.15956776936 x 10<sup>18</sup> :<math>r_{orbit}</math> = 86752239934 ===== Kepler's formula = G===== Kepler's formula reduces to G <ref>https://codingthecosmos.com/orbitals/maple-code-Kepler.html maple code</ref> :<math>R = 2 \alpha_{inv} 2 (\frac{k_r i + 1}{i})^2 l_p \frac{M}{m_P}</math> :<math>T = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} (i+1)^{1/2}} \frac{l_p}{c} \frac{M}{m_P}</math> :<math>M+m = M (\frac{i+1}{i})</math> :<math>\frac{4 \pi^2 R^3}{(M+m) T^2} = \frac{l_p c^2}{m_P} = G</math> Maple code : R:=(2/alpha_{inv})*2*((kr*i+1)^2/i^2)*lp*(M/mP): : T:=(16*Pi/alpha_{inv}^(3/2))*((kr*i+1)^3/(i^(5/2)*(i+1)^(1/2)))*(lp/c)*(M/mP): : Mm:=M*(i+1)/i: : simplify(4*Pi^2*R^3/(Mm*T^2)); : Output: lp*c^2/mP [[File:Gravitational-potential-energy-8body-1-2.gif|thumb|right|640px|8-body circular orbit plus 1-body with opposing orbitals 1:2]] ==== Orbital alignment ==== Orbital trajectory is a measure of alignment of the orbitals. In the above examples, all orbitals rotate in the same direction = aligned. If all orbitals are unaligned the object will appear to 'fall' = straight line orbit. In this example, for comparison, onto an 8-body orbit (blue circle orbiting the center mass green circle), is imposed a single point (yellow dot) with a ratio of 1 orbital (anti-clockwise around the center mass) to 2 orbitals (clockwise around the center mass) giving an elliptical orbit. The change in orbit velocity (acceleration towards the center and deceleration from the center) derives automatically from the change in the orbital radius (there is no barycenter). An orbital drift (as determined where the blue and yellow meet) naturally occurs; the eccentricity (shape) of the orbit a function of center mass and the ratio of alignment of the orbitals. A near straight line orbit will have a greater drift and a greater eccentricity than a near circular orbit. The elliptical orbit has a longer period than the circular orbit (which has a 360 degree orbit, the sidereal period). The additional period is known as the anomalistic period and includes the precession angle (360 + precession angle). Note: in these simulations there are only 2 orbital types; clock-wise and anti-clockwise ... in a real world orbit there will be a mixture. ===== Precession ===== Precession is a change in the orientation of the rotational axis of a rotating body. The first of three tests to establish observational evidence for the theory of general relativity, as proposed by Albert Einstein in 1915, concerned the "anomalous" precession of the[[w:Tests_of_general_relativity | perihelion of Mercury]]. This precession is not predicted by Newtonian gravity. The formula for precession uses the semi-major axis ''a'' (the maximum distance between center of mass) and the semi-minor axis ''b'' (the minimum distance between center of mass). :<math>e = \sqrt{1-\frac{b^2}{a^2}}</math> :<math>\theta = \frac{6\pi G M}{a (1-e^2) c^2}</math> Where ''e'' is the eccentricity of the orbit and θ is the precession angle The frequency of the center mass Schwarzschild radius = <math>i 2 l_p</math>, where ''i'' is the number of Planck mass points in the center mass and ''l''<sub>p</sub> is Planck length; ''a'' and ''b'' become :<math>a = r_a i 2 l_p</math> :<math>b = r_b i 2 l_p</math> The formula for <math>r_a</math> :<math>r_a = 2 \alpha 2 \frac{(k_r i + 1)^2}{i^2}</math> For example, the precession angle for Mercury :<math>\theta = \frac{6\pi G M}{a (1-e^2) c^2} = \frac{6\pi \lambda_{sun} a}{2 b^2}</math> = 0.501866 x 10-6 radians The Schwarzschild radius of the sun <math>\lambda_{sun} = i 2 l_p</math> = 2953.25m The eccentricity of Mercury :<math>e = \sqrt{1-\frac{b^2}{a^2}}</math> = 0.203225 (where a = 57909050km and b = 56671523km) In this simulation the ratio of anti-clockwise:clockwise orbitals = 108:1 with orbiting mass = 1 mass unit (k<sub>r</sub> = 12) <ref>https://codingthecosmos.com/orbitals/ Orbital model source code repository</ref>. {| class="wikitable" !Center mass!!angle θ!!θ*i!!eccentricity!!''r''<sub>a</sub>, ''r''<sub>b</sub> |- | 24 | 0.001175503 | 0.028212072 | 0.194749592 | 79481.8311615, 77959.9920879 |- | 28 | 0.001009240 | 0.028022688 | 0.195433743 | 79403.2724007, 77872.1317383 |- | 32 | 0.000884077 | 0.028290464 | 0.197440737 | 79344.3788203, 77782.4708225 |- | 36 | 0.000786489 | 0.028313604 | 0.197813449 | 79298.5878077, 77731.6227135 |- | 40 | 0.000708274 | 0.028330960 | 0.198373657 | 79261.9645140, 77686.7492830 |- | 44 | 0.000644252 | 0.028347088 | 0.199144931 | 79232.0062928, 77644.9930740 |- | 48 | 0.000590779 | 0.028357392 | 0.200476249 | 79207.0454340, 77599.0285567 |- | 52 | 0.000545493 | 0.028365636 | 0.200748008 | 79185.9277789, 77573.9329729 |- | ... | | | | |- | ∞ | 0.000005888 | | 0.205660603 | |} [[File:Ellipse-extrapolation.png|thumb|right|379px|Extrapolation of simulated elliptical data using the rotating orbital gravity simulator]] At a low mass ratio the mass influences the eccentricity, this influence reduces as mass increases and so the ratio 108:1 was chosen because extrapolating to infinity (the sun:mercury mass ratio = 6025000:1) gives an eccentricity ''e'' = 0.20566 close to that of the Mercury orbit ''e'' = 0.20563. Likewise the extrapolated precession angle = 0.000005888 is only slightly greater than the Mercury orbit angle θ = 0.000005019. Due to computational limitations, only a short radius ''r''<sub>a</sub> and low central masses (''M'' 24...52) were simulated. A longer radius and larger central mass values are required for greater precision. Extrapolating over this scale is imprecise however the it does appear that the correlation is within 1-2 orders of magnitude. For the simulation program code <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-elliptical-orbits.cpp</ref> and the extrapolation code used <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-ellipse-extrapolate.py</ref>. [[w:Frame-dragging |Frame dragging]] can also impact the results as the central mass is still of itself a gravitational orbit (the center points also orbit each other), and so the center mass rotates at a relatively high velocity when compared with the orbiting point. Lense-Thirring in dimensionless form; :<math>T = T_d \frac{m_P c}{M l_p}</math> :<math>R = R_d \frac{M l_p}{m_P}</math> :<math>J = J_d \frac{M R^2}{T}</math> :<math>\theta_f = \frac{2 G J T}{c^2 r^2} = 2\frac{J_d}{R_d}</math> ==== Gravitational coupling constant ==== In the above, the points were assigned a mass as a theoretical unit of Planck mass. Conventionally, the [[w:Gravitational coupling constant | Gravitational coupling constant]] ''α<sub>G</sub>'' characterizes the gravitational attraction between a given pair of elementary particles in terms of a particle (i.e.: electron) mass to Planck mass ratio; :<math>\alpha_G = \frac{G m_e^2}{\hbar c} = (\frac{m_e}{m_P})(\frac{m_e}{m_P}) = 1.75... x10^{-45}</math> For the purposes of this simulation, particles are treated as an oscillation between an electric wave-state (duration particle frequency) and a mass point-state (duration 1 unit of Planck time). This inverse α<sub>G</sub> then represents the probability that any 2 electrons will be in the mass point-state at any unit of Planck time ([[v:Electron_(mathematical) |wave-mass oscillation at the Planck scale]] <ref>Macleod, M.J. {{Cite journal |title= Programming Planck units from a mathematical electron; a Simulation Hypothesis |journal=Eur. Phys. J. Plus |volume=113 |pages=278 |date=22 March 2018 | doi=10.1140/epjp/i2018-12094-x }}</ref>). :<math>{\alpha_G}^{-1} = \frac{m_P^2}{m_e^2} = 0.57... x10^{45}</math> As mass is not treated as a constant property of the particle, measured particle mass becomes the averaged frequency of discrete point mass at the Planck level. If 2 dice are thrown simultaneously and a win is 2 'sixes', then approximately every (1/6)x(1/6) = (1/36) = 36 throws (frequency) of the dice will result in a win. Likewise, the inverse of α<sub>G</sub> is the frequency of occurrence of the mass point-state between the 2 electrons. As 1 second requires 10<sup>42</sup> units of Planck time (<math>t_p = 10^{-42}s</math>), this occurs about once every 3 minutes. :<math>\frac{{\alpha_G}^{-1}}{t_p}</math> Gravity now has a similar magnitude to the strong force (at this, the Planck level), albeit this interaction occurs seldom (only once every 3 minutes between 2 electrons), and so when averaged over time (the macro level), gravity appears weak. If particles oscillate between an electric wave state to Planck mass (for 1 unit of Planck-time) point-state, then at any discrete unit of Planck time, a number of particles will simultaneously be in the mass point-state. If an assigned point contains only electrons, and as the frequency of the electron = f<sub>e</sub>, then the point will require 10<sup>23</sup> electrons so that, on average for each unit of Planck time there will be 1 electron in the mass point state, and so the point will have a mass equal to Planck mass (i.e.: experience continuous gravity at every unit of Planck time). :<math>f_e = \frac{m_P}{m_e} = 10^{23}</math> For example a 1kg satellite orbits the earth, for any given unit of Planck time, satellite (B) will have <math>1kg/m_P = 45940509</math> particles in the point-state. The earth (A) will have <math>5.9738 \;x10^{24} kg/m_P = 0.274 \;x10^{33}</math> particles in the point-state, and so the earth-satellite coupling constant becomes the number of rotating orbital pairs (at unit of Planck time) between earth and the satellite; :<math>N_{orbitals} = (\frac{m_A}{m_P})(\frac{m_B}{m_P}) = 0.1261\; x10^{41}</math> Earthe parameters: :<math>i = \frac{M_{earth}}{m_P} = 0.27444 \;x10^{33}</math> (earth as the center mass) :<math>i 2 l_p = 0.00887</math> (earth Schwarzschild radius) :<math>s = \frac{1kg}{m_P} = 45940509</math> (1kg orbiting satellite) :<math>N_{orbitals} = i*s = 0.1261 \;x10^{41}</math> The energy required to lift a 1 kg satellite into geosynchronous orbit is the difference between the energy of each of the 2 orbits (geosynchronous and earth). :<math>E_{orbital} = \frac{h c}{2 \pi r_{6371}} - \frac{h c}{2 \pi r_{42164}} = 0.412 x10^{-32}J</math> (energy per orbital) :<math>E_{total} = E_{orbital} N_{orbitals} = 53 MJ/kg</math> The orbital angular momentum of the planets derived from the angular momentum of the respective orbital pairs. :<math>N_{orbitals} = \frac{M_{sun}}{m_P} \frac{M_{planet}}{m_P}</math> :<math>n_g = \sqrt{\frac{R_{radius} m_P}{2 \alpha l_p M_{sun}}} </math> :<math>L_{oam} = 2\pi \frac{M r^2}{T} = N_{orbitals} n_g\frac{h}{2\pi} \sqrt{2 \alpha_{inv}},\;\frac{kg m^2}{s} </math> The orbital angular momentum of the planets; mercury = .9153 x10<sup>39</sup> venus = .1844 x10<sup>41</sup> earth = .2662 x10<sup>41</sup> mars = .3530 x10<sup>40</sup> jupiter = .1929 x10<sup>44</sup> pluto = .365 x10<sup>39</sup> [[File:Newton-vs-Orbital-trajectory_comparison.png|thumb|right|479px|Comparison of Newtonian and Orbital model simulations]] ==== Orbital vs. Newton ==== A 3-body orbit <ref>https://codingthecosmos.com/orbitals/ Newton-vs-Orbital_Newton.py</ref><ref>https://codingthecosmos.com/orbitals/ Newton-vs-Orbital_Orbital.py</ref> is compared with the equivalent orbit using Newtonian dynamics. The start positions are the same r0=2*α; x1=3490.3069; y1=0; x2=cos(pi*2/3)*r0; y2=sin(pi*2/3)*r0; x3=cos(pi*2/3)*r0; y3=sin(pi*2/3)*r0 The orbiting point was used to determine the optimal G for the Newtonian orbit (G = 0.4956). Period of orbit (<math>k_r</math> = 2.19006) :<math>t_{calc}</math> = 1122034 :<math>t_{orbital}</math> = 1121397 :<math>t_{newton}</math> = 1125633 [[File:orbit-points32-orbitals496-clumping-over-time.gif|thumb|right|640px|32 mass points (496 orbitals) begin with random co-ordinates, after 2<sup>32</sup> steps they have clumped to form 1 large mass and 2 orbiting masses.]] ==== Freely moving points ==== The simulation calculates each point as if freely moving in space, and so is useful with 'dust' clouds where the freedom of movement is not restricted. In this animation, 32 mass points begin with random co-ordinates (the only input parameter here are the start (''x'', ''y'') coordinates of each point). We then fast-forward 2<sup>32</sup> steps to see that the points have now clumped to form 1 larger mass and 2 orbiting masses. The larger center mass is then zoomed in on to show the component points are still orbiting each other, there are still 32 freely orbiting points, only the proximity between them has changed, they have formed ''planets''. [[File:relativistic-quantum-gravity-orbitals-codingthecosmos.png|thumb|right|480px|Illustration of B's cylindrical orbit relative to A's time-line axis]] ==== Hyper-sphere orbit ==== {{main|User:Platos_Cave_(physics)/Simulation_Hypothesis/Relativity}} Each point moves 1 unit of (Planck) length per 1 unit of (Planck) time in '''x, y, z''' (hyper-sphere) co-ordinates, the simulation 4-axis hyper-sphere universe expanding in uniform (Planck) steps (the simulation clock-rate) as the origin of the speed of light, and so (hyper-sphere) time and velocity are constants. Particles are pulled along by this expansion, the expansion as the origin of motion, and so all objects, including orbiting objects, travel at, and only at, the speed of light in these hyper-sphere co-ordinates <ref>Macleod, Malcolm; {{Cite journal |title=2. Relativity as the mathematics of perspective in a hyper-sphere universe |journal=SSRN |date=2014 | doi=10.2139/ssrn.3334282 }}</ref>. Time becomes [[v:User:Platos Cave (physics)/Simulation_Hypothesis/God_(programmer)#Universe_time-line |time-line]]. While ''B'' (satellite) has a circular orbit period on a 2-axis plane (the horizontal axis representing 3-D space) around ''A'' (planet), it also follows a cylindrical orbit (from B<sup>1</sup> to B<sup>11</sup>) around the ''A'' time-line (vertical expansion) axis ('''t<sub>d</sub>''') in hyper-sphere co-ordinates. ''A'' is moving with the universe expansion (along the time-line axis) at (''v = c''), but is stationary in 3-D space (''v'' = 0). ''B'' is orbiting ''A'' at (''v = c''), but the time-line axis motion is equivalent (and so `invisible') to both ''A'' and ''B'', as a result the orbital period and velocity measures will be defined in terms of 3-D space co-ordinates by observers on ''A'' and ''B''. === Atomic orbitals === [[File:H-orbit-transitions-n1-n2-n3-n1.gif|thumb|right|640px|fig 5. H atom orbital transitions from n1-n2, n2-n3, n3-n1 via 2 photon capture, photons expand/contract the orbital radius. The spiral pattern emerges because the electron is continuously pulled in an anti-clockwise direction by the rotating orbital.]] ==== Gravitational orbit ==== In the context of the gravitational orbital pair model, the atomic orbital is treated as a 2-body orbit (the electron as a point orbiting an n-body central mass 'nucleus'). To simulate electron transition between orbitals, at each step a unit of length is added. As the electron still continues its orbit, instead of a circular path, it traces a spiral path outwards. Notes: 1. Seen from the wave-point oscillation cycle model, the electron is predominately in the electric wave-state (which is a locally undefined state), the simulation program can only calculate the mass point-states, and so we are mapping only the gravitational orbital component of the electron orbit. For the gravitational orbit, the orbit co-ordinates were updated per unit of Planck time (with orbitals rotating 1 unit of Planck length). In the atomic orbital we have only 1 point (the electron), and it occurs as a point only after every wavelength cycle, and so we are updating our orbit only after every wavelength cycle. For example we find that at the lowest (''n'' = 1) orbit, there are about 471964 wave-point oscillations, and so we will map a polygon with 471964 sides (the wave state cannot be mapped). To compensate, the orbital rotation angle is modified such that 471964 steps are required to map 1 complete orbit ; :<math>\beta_{orbital} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>r_{ij} = \sqrt{2 \alpha}</math> 2. During transition, at each step 1 unit of the photon is absorbed by the orbital radius, this continues until the photon is completely absorbed, the orbital radius extending proportionately. Photon absorption is not instantaneous, but instead occurs over time according to the photon wavelength. The number of steps required for this absorption then gives us the transition frequency. Notably, at integer (''Bohr'') radius (4''r'', 9''r'', 16''r''...) the spiral angle is a function of pi (2pi, (8/3)pi, 3pi ...), and as this is a linear extrapolation (the orbital radius grows in steps), ''n'' level orbits can be interpreted as specific orbits (which are inherently stable) occurring along the semi-continuous transition orbital path traced by the electron. The electron does not jump between n-levels, but the interim state (the transition phase) between these quantized n-levels is an orbital-photon hybrid state and thus difficult to detect. We may then have the equivalent of a non-integer ''n'', but as it is interchangeable with spiral angle and radius, we need only 1 parameter to calculate the other 2, and as transition frequency can also be determined in terms of angle and radius, we have a simple geometrical model that provides a framework for the transition process yet uses only pi and alpha as inputs. ==== 2-Photon orbital model ==== The Lyman series energy formula can be decomposed: :<math>\frac{1}{\lambda} = R_\infty\left(1 - \frac{1}{n^2}\right) = R_\infty - \frac{R_\infty}{n^2}</math> Mathematically (if not physically) we can divide into 2 waves :<math>\text{Photon}_{n1} = R_\infty</math> :<math>\text{Photon}_{nfinal} = (- \frac{R_\infty}{n^2})</math> :<math>\text{Photon}_{\text{total}} = \text{Photon}_{n1} + (-\text{Photon}_{n\text{final}})</math> This (mathematical) approach permits us to divide the transition into two distinct geometric processes taking place between the incoming photon and the orbital radius, with the electron taking a relatively passive role. Rather than 2 actual distinct photons, we may presume two geometric phases of a single photon absorption, nevertheless the 2-photon image is easier to conceptualize. Note these processes are not instantaneous but rather occur over time in discrete steps; '''Process 1 (Cancellation):''' A photon with energy corresponding to the ''n''=1 orbital frequency '''cancels''' the existing orbital structure. :<math>\text{Photon}_{n1} + \text{Orbital}_{n1} == zero</math> '''Process 2 (Creation):''' A (-) photon with energy corresponding to the <math>n_{\text{final}}</math> orbital '''creates''' the new orbital structure. :<math>\text{Photon}_{nfinal} == \text{Orbital}_{nfinal}</math> During transition, the system exists in a photon-orbital hybrid state. This is not a quantum superposition but a geometric intermediate configuration where: : The incoming photon’s momentum is being transferred incrementally : The orbital structure is simultaneously being dismantled and reconstructed : The electron mediates the momentum transfer through its position : Each steps transfers a quantum of momentum The gravitational orbit returns results analogous to the Bohr model and the 2-photon approach complements the (electric wave-state) Schrodinger equation <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref>. ==== Theory ==== =====Hyperbolic spiral===== [[File:Hyperbol-spiral-1.svg|thumb|right|320px|Hyperbolic spiral]] A [[w:hyperbolic spiral |hyperbolic spiral]] is a type of [[w:spiral|spiral]] with a pitch angle that increases with distance from its center. As this curve widens (radius '''r''' increases), it approaches an [[w:asymptotic line|asymptotic line]] (the '''y'''-axis) with the limit set by a scaling factor '''a''' (as '''r''' approaches infinity, the '''y''' axis approaches '''a'''). For the particular spiral that the electron transition path maps, periodically the spiral angles converge to give integer radius, the general form for this type of spiral (beginning at the outer limit ranging inwards); :<math>x = a^2 \frac{cos(\varphi)}{\varphi^2},\; y = a^2 \frac{sin(\varphi)}{\varphi^2},\;0 < \varphi < 4\pi</math> :radius = <math>\sqrt(x^2 + y^2) r</math> :<math>\varphi = (2)\pi, \; 4r</math> (360°) :<math>\varphi = (4/3)\pi,\; 9r</math> (240°) :<math>\varphi = (1)\pi, \; 16r</math> (180°) :<math>\varphi = (4/5)\pi, \; 25r</math> (144°) :<math>\varphi = (2/3)\pi, \; 36r</math> (120°) [[File:Bohr atom model (mul).svg|thumb|right|320px|Electron at different ''n'' level orbitals]] =====Principal quantum number '''n'''===== The H atom has 1 proton and 1 electron orbiting the proton, in the [[w:Bohr model |Bohr model]] (which approximates a gravitational orbit), the electron can be found at select radius ([[w:Bohr radius |the Bohr radius]]) from the proton (nucleus), these radius represent the permitted energy levels (orbital regions) at which the electron may orbit the proton. Electron transition (to a higher energy level) occurs when an incoming photon provides the required energy (momentum). Conversely emission of a photon will result in electron transition to a lower energy level. The [[w:principal quantum number |principal quantum number ''n'']] denotes the energy level for each orbital. As ''n'' increases, the electron is at a higher energy level and is therefore less tightly bound to the nucleus (as ''n'' increases, the electron orbit is further from the nucleus). Each shell can accommodate up to ''n''² (1, 4, 9, 16 ... ) electrons. Accounting for two states of spin this becomes 2''n''² electrons. As these energy levels are fixed according to this integer ''n'', the orbitals may be said to be quantized. =====(Bohr) orbital===== Setting <math>\alpha_{inv} = \frac{1}{\alpha}</math> = 137.035999177⁠ (CODATA 2022) The Bohr radius has 2 components, the dimensionless (the [[w:fine structure constant|fine structure constant alpha]]) and the dimensioned (electron wavelength); :<math>a_0 = \alpha_{inv} \times \lambda_e</math> The orbital radius of this model also includes the proton wavelength and so is slightly greater than 2x the Bohr radius :<math>\lambda_0 = \lambda_p + \lambda_e</math> :<math>r_0 = 2 \alpha_{inv} \times \lambda_0</math> To reduce simulation computing time, only the alpha component is described here, the dimensioned components added later. :<math>r_{orbital} = 2 \alpha_{inv} n^2</math> As a mass point, the electron orbits the proton at a fixed radius (<math>r_{orbital}</math>) in a series of steps (the duration of each step corresponds to the wavelength component). The distance travelled per step (per wave-point oscillation) equates to the distance between mass point states and is the inverse of the radius. [[File:atomic-orbital-rotation-step.png|thumb|right|208px|electron (blue dot) moving 1 step anti-clockwise along the alpha orbital circumference]] length = <math>l_{step} = \frac{1}{r_{orbital}}</math> Duration = 1 step per wavelength and so velocity velocity = <math>v_{orbital} = v_{step} = \frac{1}{2\alpha_{inv} n}</math> Giving period of orbit period = <math>t_{orbital} = \frac{2\pi r_{orbital}} {v_{orbital}} = 2\pi 2\alpha_{inv} 2\alpha_{inv} n^3 </math> The (reference) orbital (''n'' = 1) :<math>t_{n1} = 2\pi 4 \alpha_{inv}^2</math> = 471964.356... The angle of rotation depends on the orbital radius :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}}\sqrt{2\alpha_{inv}}}</math> ===== 2-Photon orbitals ===== The electron can jump between ''n'' energy levels via the absorption or emission of a photon. In the 2-photon orbital model <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref>, the orbital (Bohr) radius is treated as a 'physical wave' (has physical properties) akin to the photon albeit an inverse such that <math>orbital \;radius + photon = zero</math> (they cancel). As such it is the orbital radius itself that absorbs or emits the photon during transition, in the process the orbital radius is extended or reduced (until the photon is completely absorbed/emitted). The electron has a `passive' role in the transition phase (mediating the exchange of momentun between the orbital and the photon). It is the rotation of the orbital radius that drives the electron motion, resulting in the electron orbit around the nucleus (orbital momentum comes from the orbital radius), and this rotation continues also during the transition phase resulting in the electron following a hyperbolic spiral path. ====== Spiral (mass point) ====== The photon is divided into 2 photons as per the Rydberg formula (denoted initial and final). :<math>\lambda_{photon} = (+\lambda_i) - (+\lambda_f)</math> The wavelength of the (<math>\lambda_i</math>) photon corresponds to the wavelength of the orbital radius. The (+<math>\lambda_i</math>) will then delete the orbital radius as described above (''orbital'' + ''photon'' = ''zero''), however the (-<math>\lambda_f</math>), because of the Rydberg minus term, will be equivalent to the orbital radius, and so conversely will increase the orbital radius. And so for the duration of the (+<math>\lambda_i</math>) photon wavelength, the orbital radius does not change as the 2 photons cancel each other; :<math>r_{orbital} = r_{orbital} + (\lambda_i - \lambda_f)</math> However, the (<math>\lambda_f</math>) has the longer wavelength, and so after the (<math>\lambda_i</math>) photon has been absorbed, and for the remaining duration of this (<math>\lambda_f</math>) photon wavelength, the orbital radius will be extended until the (<math>\lambda_f</math>) is also absorbed (the '''transition phase'''). For example, the electron is at the ''n'' = 1 orbital. To jump from an initial <math>n_i = 1</math> orbital to a final <math>n_f = 2</math> orbital, first the (<math>\lambda_i</math>) photon is absorbed by the orbital radius (<math>\lambda_i + \lambda_{orbital} = zero</math>), but simultaneously the (-<math>\lambda_f</math>) photon adds to the orbital radius, and so the electron follows a normal ''n'' = 1 orbit (the '''orbital phase'''), then the remaining (<math>\lambda_f</math>) photon continues until it too is absorbed (the '''transition phase'''). :<math>\lambda_i = 1 \times t_{n1}</math> (initial orbital) :<math>\lambda_f = n^2 \times t_{n1}</math> (final orbital) After the (<math>\lambda_i</math>) photon is absorbed, the (<math>\lambda_f</math>) photon still has <math>\lambda_f = (n_f^2 - n_i^2)t_{n1} = 3 t_{n1}</math> steps remaining until it too is absorbed. [[File:atomic-orbital-transition-alpha-steps.png|thumb|right|277px|orbital transition during orbital rotation]] This process does not occur as a single `jump' between energy levels by the electron, but rather absorption/emission of the photon takes place in discrete steps, each step corresponds to a unit of <math>r_{incr}</math> (both photon and orbital radius may be considered as constructs from multiple units of this geometry); :<math>r_{incr} = -\frac{1}{2 \pi 2\alpha_{inv}}</math> At each step 1 unit of <math>r_{incr}</math> is transferred from each photon to the orbital radius. During the orbital phase the <math>r_{incr}</math> unit from the (<math>\lambda_i</math>) photon is canceled by the (-)<math>r_{incr}</math> unit from the (<math>\lambda_f</math>) photon (<math>r_{incr}</math> + (-)<math>r_{incr}</math> = zero) and so the orbital radius does not change. After the (<math>\lambda_i</math>) photon is fully absorbed, the orbital radius continues to absorb (-)<math>r_{incr}</math> units from (what remains of) the (<math>\lambda_f</math>) photon, and as the (<math>\lambda_f</math>) photon is equivalent to the orbital radius, the orbital radius extends in these steps as a consequence. The number of steps <math>N_{steps}</math> required determines (and so can be used to calculate) the transition frequency. Furthermore at each step the orbital radius itself continues to rotate, the electron, being pulled along by this rotation according to angle β, thereby traces a spiral path as the orbital radius length changes. :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} r_{\alpha}}</math> The (accumulated) spiral angle <math>\Phi</math> at each <math>n^2</math> :n = 1 to 2: <math>\Phi = 2\pi \; (r = 4 \times \; r_{orbital}) </math> :n = 1 to 3: <math>\Phi = \frac{8}{3} \pi \; (r = 9 \times \; r_{orbital}) </math> :n = 1 to 4: <math>\Phi = 3\pi \; (r = 16 \times \; r_{orbital}) </math> :n = 1 to 5: <math>\Phi = \frac{16}{5}\pi \; (r = 25 \times \; r_{orbital}) </math> :n = 1 to 6: <math>\Phi = \frac{10}{3}\pi \; (r = 36 \times \; r_{orbital}) </math> :n = 1 to 7: <math>\Phi = \frac{7}{4}\pi \; (r = 49 \times \; r_{orbital}) </math> :n = 1 to 8: <math>\Phi = \frac{7}{2}\pi \; (r = 64 \times \; r_{orbital}) </math> In the mass state we can divide the photon into 2 mathematical structures, the transition frequency is defined as the inverse of one oscillation period at the Compton scale, multiplied by the geometric phase factor (including the dimensioned terms). This gives us the solution for the transition frequency and the Bohr radius with a pi-based spiral acting as the transition 'guard-rail'. We are using only alpha and pi, yet the transition frequency can be solved with high precision using the gravity simulator. This gives a geometrical derivation for the Bohr model, which in this context is the gravitational component of the electron orbit. ====== Photon-Orbital Hybrid (wave-state) ====== In this model, atomic orbitals are '''physical rotating structures''' rather than probability distributions. The orbital possesses: :Angular momentum: Quantized by discrete rotation steps :Energy: Stored in the rotating configuration The orbital rotates in discrete steps (β radians per step) rather than continuously. During transition, the system exists in a '''photon-orbital hybrid state'''. This is not a quantum superposition but a '''geometric intermediate configuration''' where: :The incoming photon's momentum is being transferred incrementally :The orbital structure is simultaneously being dismantled and reconstructed :The electron mediates the momentum transfer through its position :Each step transfers a quantum of momentum We then note. '''Standard QM''': Anti-realist---the wavefunction is a calculation tool, not a physical entity. Reality emerges only upon measurement. '''2-photon model''': Realist---orbitals are real rotating structures. The electron follows definite trajectories, even when unobserved. The geometric model thus establishes a '''two-layer architecture''' for encoding quantum states: :Geometric Framework Layer: The hyperbolic spiral structure provides the spatial scaffold <math>(r, \theta, \phi)</math> coordinates with built-in radial quantization <math>r \propto n^2</math> :Photon Information Layer: The absorbed photon carries angular momentum quantum numbers <math>(l, m_l)</math> that modulate this scaffold This separation offers that the Bohr model is not replaced by the Schrodinger equation but rather complements it (the mass-state provides the geometric structure; the photon-orbital hybrid provides the angular momentum content). ===== Simulation ===== [[File:Alpha-hyperbolic-spiral.gif|thumb|right|640px|Bohr radius during ionization, as the H atom electron reaches each ''n'' level, it completes 1 orbit (for illustration) then continues outward (actual velocity will become slower as radius increases according to angle β)]] The gravity simulation (<ref>https://codingthecosmos.com/orbitals/ source code</ref>) was setup with the electron as the orbiting point and 65 mass points to represent the nucleus (although the proton-electron mass ratio is 1836:1, this would be become a 1837-body set of orbiting points which is too computationally intensive). The program was modified with the rotational angle β as :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} r_{\alpha}}</math> To simulate the transition phase, at each step 1 unit of <math>r_{incr} = \frac{1}{2 \pi 2\alpha_{inv}}</math> was added to the proton-electron orbital radius. To convert to frequency in Hz, the dimension components were added :<math>f_H = \frac{2c}{\lambda_e + \lambda_p}</math> = 0.155184298 10²²s^-1 For n = 1 to n = n² :<math>f_n = 2\pi f_H \;\frac{n^2 - 1}{N_{steps}} </math> '''Results''' {| class="wikitable" !<math>r/r_{orbital}</math> !! <math>r/r_{orbital}</math> !! N-steps !! <math>\Phi</math> (deg) !! frequency Hz |- | 4.000000115 | 2.000004018 | 1887860.649 | 0.000017120 | 2466034304131826.5 |- | 8.999994875 | 4.000003286 | 4247681.247 | 120.000001964 | 2922708926063928.0 |- | 15.999987119 | 6.000002004 | 7551428.532 | 180.000002514 | 3082545855782738.5 |} Experimental values for H(1s-ns) transitions. :H(1s-2s) = 2466 061 413 187.035 kHz <ref>http://www2.mpq.mpg.de/~haensch/pdf/Improved%20Measurement%20of%20the%20Hydrogen%201S-2S%20Transition%20Frequency.pdf</ref> :H(1s-3s) = 2922 743 278 665.79 kHz <ref>https://pubmed.ncbi.nlm.nih.gov/33243883/</ref> :H(1s-4s) = 3082 581 563 822.63 kHz <ref>https://codata.org/</ref> Although the simulation was a standard gravitational orbit (charge-less) and without a relativistic correction, the results were quite close; :n = 1 to n = 2: margin = 100 * (experimental - simulated)/experimental = 0.001099% :n = 1 to n = 3: margin = 0.001175% :n = 1 to n = 4: margin = 0.001158% ====== Rydberg atom ====== Here a Rydberg atom is defined as an (idealized) atom with a nucleus of point size and an infinite mass and so the barycenter = atom center at co-ordinates (0, 0). We can simulate this as a simple transition beginning at the initial (''n''_i = 1) orbital. :<math>\varphi = 0</math> (start angle) :<math>r_{orbital} = r_0 = 2\alpha</math> (nb. Bohr radius = <math>\alpha \lambda_e</math> = α*electron wavelength) :<math>x = r_{orbital},\; y = 0</math> (start co-ordinates) For each step during transition, setting t = step number (FOR t = 1 TO ...), we can calculate the radius ''r'' and <math>n_f</math>. :<math>r = r_{orbital} + \frac{t}{2\pi 2\alpha}</math> (number of increments ''t'' of <math>r_{incr}</math>) :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} \sqrt{2\alpha}}</math> :<math>\varphi = \varphi + \beta</math> :<math>n_f^2 = 1 + \frac{t}{2\pi 4\alpha^2}</math> (<math>n_f^2</math> as a function of ''t'') The spiral angle and <math>n_f^2</math> are interchangeable :<math>\varphi = 4 \pi (1 - \frac{1}{{n_f}^2})</math> We can then re-write (<math>n_f</math> is only an integer at prescribed spiral angles); :<math>\beta = \frac{1}{{r_{orbital}}^2 n_f^3}</math> ''n'' orbital transition periods are multiples of the ''n'' = 1 orbital. If we include a relativistic term; :<math>t_{n1} = 2\pi 4 \alpha_{inv}^2 \sqrt{(1 - \frac{1}{4 \alpha_{inv}^2})}</math> = 471961.21478 Then we can compare a theoretical Rydberg (also without including charge) and find a further improvement. For ionization, the second photon is of such long wavelength that its momentum contribution is negligible, and so the ionization transition frequency should correspond closely to the ''n'' = 1 orbital. :H(1s-∞s) = 3288 086 857 127.60 kHz <ref>https://codata.org/ (109678.77174307cm-1)</ref> (''n'' = ∞) This would give us a H(n1) = 471959.2427762 :n = 1: margin = 100 * (H(n1) - t_{n1})/H(n1) = 0.001099% :n = 1 to n = 2: margin = 100 * (experimental - 4 t_{n1})/experimental = 0.000267% :n = 1 to n = 3: margin = 100 * (experimental - 9 t_{n1})/experimental = 0.000398% :n = 1 to n = 4: margin = 100 * (experimental - 16 t_{n1})/experimental = 0.000422% If we use the non-relativistic <math>t_{n1}</math>, then our results are remarkably close to the results from the gravity simulation suggesting that central mass size does not have the major role in determining the transition frequency. :n = 1 to n = 2: margin = 0.000932% :n = 1 to n = 3: margin = 0.001063% :n = 1 to n = 4: margin = 0.001088% ====== Barycenter correction ====== The experimental hydrogen transition frequencies deviate slightly from the ideal Rydberg formula. When normalized, these deviations exhibit a characteristic pattern: a minimum near ''n'' = 2, followed by a rising trend toward the ionization limit as the radius increases. :H(n1) = 471959.242776 :H(n2) = 471959.956565 :H(n3) = 471959.338749 :H(n4) = 471959.222066 The gravity simulation results showed a similar trend suggesting in both cases a barycenter 'wobble'. :sim(n1) = 471964.35638 :sim(n2) = 471965.14481 :sim(n3) = 471964.88601 :sim(n4) = 471964.68921 Therefore, given the possibilities of this gravity simulator as a research tool, the next step is to divide the proton into 3 parts resembling the 3 quarks, and then experiment with different configurations. For example, we could form a U quark cluster and a D quark cluster and then test different arrangements of the clusters (and also different mass ratios) to determine which, if any, reduces the margin. This could give potential insights into the protons internal structure. We can also give the electron further mass points to determine if it also becomes constrained and relaxed. ==Article series== The following are HTML transcripts of journal articles * [[https://simulationuniverse.org/ simulationuniverse.org]]: Home page ===The 3 levels=== A model overview from the sub Planck scale to the container universe * [[https://codingthecosmos.org/1a-CMB_from_Planck_unit_scaffolding.html 1a. Planck unit CMB.html]]: Part 1. A CMB from Planck units * [[https://codingthecosmos.org/1b-Sub_Planck_scale_from_tau_loop.html 1b. The Minimal Complexity Algorithm of the Planck Scaffolding]]: Part 2. The sub-Planck scale and the tau-loop * [[https://codingthecosmos.org/1c-the_Heavens_a_container_universe.html 1c. the Heavens.html]]: Part 3. The Heavens (the container universe) ===General articles=== * [[https://codingthecosmos.org/2-Relativity_as_mathematics_of_perspective.html 2-Relativity-hypersphere.html]]: Relativity as the mathematics of perspective * [[https://codingthecosmos.org/3-Gravity_via_n-body_particle_orbitals.html 3-Gravitational-orbitals.html]]: Gravity as sum of n-body rotating orbital particle-particle pairs * [[https://codingthecosmos.org/4-Atomic-orbital_transition_using_Gravity_simulator.html 4-Atomic-orbitals.html]]: Atomic orbitals as single rotating orbital particle-particle pairs * [[https://codingthecosmos.org/5-Atomic_transition_via_photon_orbital_hybrid.html 5-w_axis.html]]: Imaginary number axis (radiation domain) * [[https://codingthecosmos.org/6-Natural_Planck_units_MTP_Fine_Structure_Constant_alpha.html 6-Physical-constant-anomalies.html]]: Derivation of the fine structure constant alpha from physical constant anomalies * [[https://codingthecosmos.org/7-Mathematical_electron_magnetic_monopole-quarks.html 7-Monopole-quarks.html]]: Quarks as magnetic monopoles * [[https://codingthecosmos.org/8-Holographic_universe_2D_plus_Compton_wavelength.html 8-Holographic-universe.html]]: Hypersphere surface as 2-D analogue ===Wiki series=== Introductions to principle concepts (for more detailed discussion see General articles) * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_units_(geometrical)]]: Planck units MLTPA as geometrical objects * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Electron_(mathematical)]]: Mathematical electron formula * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Relativity]]: Relativity as a translation between 2 co-ordinate systems * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_unit_scaffolding]]: CMB and a Planck unit universe scaffolding * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Sqrt_Planck_momentum]]: Link between charge and mass * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/God_(programmer)]]: Introduction to a Planck scale Programmer God Simulation Hypothesis model == External links == * [https://codingthecosmos.com/ Planck scale modelling using geometrical objects] * [https://www.amazon.com/Our-Mathematical-Universe-Ultimate-Reality/dp/0307599809 Our Mathematical Universe: My Quest for the Ultimate Nature of Reality] -Max Tegmark (Book) * [https://link.springer.com/article/10.1134/S0202289308020011/ Dirac-Kerr-Newman black-hole electron] -Alexander Burinskii (article) * [https://plato.stanford.edu/entries/pythagoras/ Pythagoras "all is number"] - Stanford University * [[w:Mathematical universe hypothesis | Mathematical universe hypothesis]] * [[w:Philosophy of mathematics | Philosophy of mathematics]] * [[w:Philosophy of physics | Philosophy of physics]] * [[w:Platonism | Platonism]] ==References== {{Reflist}} __INDEX__ r1c9nmll1yogz5gnepeapyi9wmv7tjn 2835112 2835111 2026-09-30T03:58:19Z Platos Cave (physics) 2562653 2835112 wikitext text/x-wiki {{Original research}} '''Simulating gravitational and atomic orbits via n-body rotating particle-particle orbital pairs at the Planck scale''' The following describes a geometrical method for simulating gravitational orbits <ref>Macleod, Malcolm J.; {{Cite journal |title=3. Gravitational orbits from n-body rotating particle-particle orbital pairs |journal=SSRN |date=Dec 2021 | doi=10.2139/ssrn.3444571}}</ref><ref>https://simulationuniverse.org/9-Source-codes.html Gravitational orbital simulation source codes in C</ref> and atomic orbitals <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref><ref>https://simulationuniverse.org/9-Source-codes.html Atomic orbital transitions simulation source codes in C</ref> via an n-body network of rotating individual particle-particle orbital pairs . Although the simulation is dimensionless (the only physical constant used is the [[w:fine structure constant |fine structure constant alpha]]), it can translate via the [[w:Planck_units |Planck units]] for comparisons with real world orbits. The orbits generated by this dimensionless geometrical approach can be formulated, and despite not using Newtonian physics these formulas demonstrate consistency; for example the derived formulas for radius R, period T and (M + m) will reduce [[v:Quantum_gravity_(Planck)#Kepler's_formula_=_G |Kepler's formula]] to '''G''' <ref>https://codingthecosmos.com/orbitals/maple-code-Kepler.html maple code</ref>. Likewise the atomic orbital shells naturally quantize according to pi without relying on built-in postulates. [[File:Gravitational-regular-3body-orbit.gif|thumb|right|640px|A regular 3-body orbit. The simulation begins with the start (x, y) co-ordinates of each point. No other parameters are required. r0=2*α; x1=1789.5722983; y1=0; x2=cos(pi*2/3)*r0; y2=sin(pi*2/3)*r0; x3=cos(pi*2/3)*r0; y3=sin(pi*2/3)*r0]] :<math>\frac{4 \pi^2 R^3}{(M+m) T^2} = \frac{l_p c^2}{m_P} = G</math> The simulation source code(s) used here are listed below, these give a precise description of this orbital model and so can be used as reference <ref>https://simulationuniverse.org/9-Source-codes.html simulation source codes in C</ref>. For simulating gravity, orbiting objects ''A'', ''B'', ''C''... are sub-divided into discrete points, each point can be represented as 1 unit of [[w:Planck mass |Planck mass]] ''m''_P (for example, a 1kg satellite would be divided into 1kg/''m''_P = 45940509 points). Each point in object ''A'' then forms an orbital pair with every point in objects ''B'', ''C''..., resulting in a universe-wide, n-body network of rotating point-to-point orbital pairs . Each orbital pair rotates 1 unit of length per unit of time, when these orbital pair rotations are summed and mapped over time, gravitational orbits emerge between the objects ''A'', ''B'', ''C''... The base simulation requires only the start position (''x'', ''y'' coordinates) of each point, as it maps only rotations of the points within their respective orbital pairs then information regarding the macro objects ''A'', ''B'', ''C''...; momentum, center of mass, barycenter etc ... is not required (each orbital is calculated independently of all other orbitals). For simulating electron transition within the atom, the same program is used. The electron is assigned as a single point, the nucleus as multiple points clustered together (a 2-body orbit), and an incoming 'photon' (a unit of length) is added to (increases) the electron - proton orbital radius in a series of discrete steps (rather than a single 'jump' between orbital shells). As the electron continues to orbit the nucleus during this transition phase, the electron path traces a [[w:hyperbolic spiral |hyperbolic spiral]]. Although we are mapping the electron transition as a gravitational orbit on a 2-D plane, periodically the transition spiral angles converge to give an integer orbital radius (360°=4''r'', 360+120°=9''r'', 360+180°=16''r'', 360+216°=25''r'' ... 720°=∞''r''), a radial quantization (as a function of pi and so of geometrical origin) naturally emerges. Furthermore, the transition steps between these radius can then be used to solve the transition frequency, replicating the Bohr model. The gravitational orbit returns results analogous to the Bohr model and the 2-photon orbital model approach complements the (electric wave-state) [[w:Schrodinger equation |Schrodinger wave equation]]. [[File:complex-orbit-pts26-r17-1-7-1.gif|thumb|right|640px|By selecting the start co-ordinates on a 2-D plane for each point accordingly, we can 'design' the required orbits. The 26 points orbit each other resulting in 325 point-point orbitals.]] === Theory === In the simulation, particles are treated as an electric wave-state to (Planck) mass point-state oscillation, the wave-state as the duration of particle frequency in Planck time units, the point-state duration as 1 unit of Planck time (as a point, this state can be assigned mapping coordinates), the particle itself is a continuous oscillation between these 2 states (i.e.: the particle is not a fixed entity). For example, an electron has a frequency (wave-state duration) = 10²³ units of Planck time followed by the mass state (1 unit of Planck time). The background to this oscillation is given in the [[v:Electron (mathematical) |mathematical electron]] model. If the electron '''has (is)''' mass (1 unit of Planck mass) for 1 unit of Planck time, and then '''no''' mass for 10²³ units of Planck time (the wave-state), then in order for a (hypothetical) object composed only of electrons to '''have (be)''' 1 unit of Planck mass at every unit of Planck time, the object will require 10²³ electrons. This is because orbital rotation occurs at each unit of Planck time and so the simulation requires this object to have a unit of Planck mass at each unit of Planck time (i.e.: on average there will always be 1 electron in the mass point state). We would then measure the mass of this object as 1 Planck mass (the measured mass of an object reflects the average number of units of Planck mass per unit of Planck time). For the simulation program, this Planck mass object can now be defined as a point (it will have point co-ordinates at each unit of Planck time and so can be mapped). As the simulation is dividing the mass of objects into these Planck mass size points and then rotating these points around each other as point-to-point orbital pairs, then by definition gravity is a mass to mass interaction. Nevertheless, although this is a mass-point to mass-point rotation, and so referred to here as a point-point orbital, it is still a particle to particle orbital, albeit the particles are both in the mass state. We can also map individual particle to particle orbitals albeit as gravitational orbits, the H atom is a well-researched particle-to-particle orbital pair (an electron orbiting a proton) and so can be used as reference. To map orbital transitions between energy levels, the simulation uses the [[v:Quantum_gravity_(Planck)#Photon_orbital_model |photon-orbital model]], in which the orbital (Bohr) radius is treated as a 'physical wave' akin to the photon albeit of inverse or reverse phase. The photon can be considered as a moving wave, the orbital radius as a standing/rotating wave (trapped between the electron and proton). Orbital momentum derives from this orbital radius, it is the rotation of the orbital radius that pulls the electron, resulting in the electron orbit around the nucleus. Furthermore, orbital transition (between orbitals) occurs between the orbital radius and the photon, the electron has a passive role. Transition (the electron path) follows a specific [[v:Fine-structure_constant_(spiral) |hyperbolic spiral]] for which the angle component periodically converges to give integer radius where ''r'' = Bohr radius; at 360° radius =4''r'', 360+120°=9''r'', 360+180°=16''r'', 360+216°=25''r'' ... 720°=∞''r''. As these spiral angles (360°, 360+120°, 360+180°, 360+216° ...) are linked directly to pi, and as the electron is following a semi-classical gravitational orbit, this particular quantization has a geometrical origin. Although the simulation is not optimized for atomic orbitals (the nucleus is treated simply as a cluster of points), the transition period '''t''' measured between these integer radius can be used to solve the transition frequencies '''f''' via the general formula <math>f/c = t \lambda_H/(n_f^2-n_i^2)</math>. In summary, both gravitational and atomic orbitals reflect the same particle-to-particle orbital pairing, the distinction being the state of the particles; gravitational orbitals are mass to mass whereas atomic orbitals are predominately wave to wave. There are not 2 separate forces used by the simulation, instead particles are treated as oscillations between the 2 states (electric wave and mass point). The transition spiral provides the geometric structure; the photon-orbital hybrid (2-Photon model) provides the angular momentum content. === N-body orbitals === [[File:8body-27orbital-gravitational-orbit.gif|thumb|right|640px|8-body (8 mass points, 28 orbitals), the resulting orbit is a function of the start positions of each point]] The simulation universe is a 4-axis hypersphere expanding in increments <ref>Macleod, Malcolm; {{Cite journal |title=1. Planck unit scaffolding correlates with the Cosmic Microwave Background |journal=SSRN |date=26 March 2014 | doi=10.2139/ssrn.3333513 }}</ref> with 3-axis (the [[v:User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_unit_scaffolding |hypersphere surface]]) projected onto an (''x'', ''y'') plane with the ''z'' axis as the simulation timeline (the expansion axis). Each point is assigned start (''x'', ''y'', ''z'' = 0) co-ordinates and forms pairs with all other points, resulting in a universe-wide n-body network of point-point orbital pairs. The barycenter for each orbital pairing is its center, the points located at each orbital 'pole'. The simulation itself is dimensionless, simply rotating circles. To translate to dimensioned gravitational or atomic orbits, we can use the Planck units ([[w:Planck mass |Planck mass m_P]], [[w:Planck length |Planck length l_p]], [[w:Planck time |Planck time t_p]]), such that the simulation increments in discrete steps (each step assigned as 1 unit of Planck time), during each step (for each unit of Planck time), the orbitals rotate 1 unit of (Planck) length (at velocity ''c'' = ''l''_p/''t''_p) in hyper-sphere co-ordinates. These rotations are then all summed and averaged to give new point co-ordinates. As this occurs for every point before the next increment to the simulation clock (the next unit of Planck time), the orbits can be updated in 'real time' (simulation time) on a serial processor. Setting <math>\alpha_{inv} = \frac{1}{\alpha}</math> = 137.035999177⁠ (CODATA 2022) Orbital pair rotation on the (''x'', ''y'') plane occurs in discrete steps according to an angle '''β''' as defined by the orbital pair radius (the atomic orbital '''β''' has an additional alpha term). :<math>\beta_{gravity} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>\beta_{atomic} = \frac{1}{\sqrt{2\alpha_{inv}} r_{orbital} \sqrt{r_{orbital}}}</math> As the simulation treats each (point-point) orbital independently (independent of all other orbitals), no information regarding the points (other than their initial start coordinates) is required by the simulation. Although orbital and so point rotation occurs at ''c'', the [[v:Relativity (Planck) |hyper-sphere expansion]] <ref>Macleod, Malcolm; {{Cite journal |title=2. Relativity as the mathematics of perspective in a hyper-sphere universe |journal=SSRN |date=26 March 2014 | doi=10.2139/ssrn.3334282 }}</ref> is equidistant and so `invisible' to the observer. Instead observers (being constrained to 3D space) will register these 4-axis orbits (in hyper-sphere co-ordinates) as a circular motion on a 2-D plane (in 3-D space). An apparent [[w:Time_dilation |time dilation]] effect emerges as a consequence. [[File:4body-orbital-3x10x-gravitational-orbit.gif|thumb|right|640px|Symmetrical 4 body orbit; (3 center mass points, 1 orbiting point, 6 orbital pairs). Note that all points orbit each other.]] ==== 2 body orbits ('''x, y''' plane) ==== For simple 2-body orbits, to reduce computation only 1 point is assigned as the orbiting point and the remaining points are assigned as the central mass. For example the ratio of earth mass to moon mass is 81:1 and so we can simulate this orbit accordingly. However we note that the only actual distinction between a 2-body orbit and a complex orbit being that the central mass points are assigned ('''x, y''') co-ordinates relatively close to each other, and the orbiting point is assigned ('''x, y''') co-ordinates distant from the central points (this becomes the orbital radius) ... this is because the simulation treats all points equally, the center points also orbiting each other according to their orbital radius, for the simulation itself there is no difference between simple 2-body and complex n-body orbits. The [[w:Schwarzschild radius |Schwarzschild radius]] formula in Planck units :<math>r_s = \frac{2 l_p M}{m_P}</math> As the simulation itself is dimensionless, we can remove the dimensioned length component <math>2 l_p</math>, and as each point is analogous to 1 unit of Planck mass <math>m_P</math>, then the Schwarzschild radius for the simulation becomes the number of central mass points. We then assign ('''x, y''') co-ordinates (to the central mass points) within a circle radius <math>r_s</math> = number of central points = total points - 1 (the orbiting point). After every orbital has rotated 1 length unit (anti-clockwise in these examples), the new co-ordinates for each rotation per point are then averaged and summed, the process then repeats. After 1 complete orbit (return to the start position by the orbiting point), the period '''t''' (as the number of increments to the simulation clock) and the ('''x, y''') plane orbit length '''l''' (distance as measured on the 2-D plane) are noted. '''Key''': 1. '''i''' = r<sub>s</sub>; the number of center mass points (the orbited object). 2. '''j''' = total number of points, as here there is only 1 orbiting point; '''j''' = '''i''' + 1 3. '''k<sub>r</sub>''' is a mass to radius co-efficient in the form <math>j_{max} = (k_r i + 1)</math>. This function defines orbital radius in terms of the central mass Schwarzschild radius (<math>i</math>) and the orbiting point (1), thus quantizing the radius. When <math>k_r</math> = 1 then <math>j_{max} = j</math>, and the radius is at a minimum giving an analogue gravitational principal quantum number <math>n_g = j_{max}/j</math>. 4. '''x, y''' = start co-ordinates for each point (on a 2-D plane), '''z''' = 0. 5. '''r<sub>α</sub>''' = a radius constant, here r<sub>α</sub> = sqrt(2/α) = 16.55512; where alpha = inverse [[w:fine structure constant |fine structure constant]] = 137.035 999 084 (CODATA 2018). This constant adapts the simulation specifically to gravitational and atomic orbitals. :<math>r_{\alpha} = \sqrt{2\alpha_{inv}} </math> :<math>r_{orbit} = {r_{\alpha_{inv}}}^2 \;*\; r_{wavelength} </math> 6. Rotation angle β :<math>\beta_{orbital} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>r_{ij} = \sqrt{\frac{2 j}{i}}</math> (for each gravitational orbital in the simulation) :<math>r_{ij} = \sqrt{2 \alpha_{inv}}</math> (for each atomic orbital in the simulation) ==== Orbital formulas (2-D plane)==== :<math>j = i + 1</math> :<math>r_{orbit} = 2 \alpha_{inv} 2 \frac{(k_r i + 1)^2}{i^2}</math>, orbital radius (center mass to point) :<math>r_{ij} = \sqrt{\frac{i}{j}}</math> (averaged for each orbit) :<math>t_{orbit} = \frac{2\pi}{ \beta_{orbit}} = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} j^{1/2}}</math>, orbiting point period :<math>r_{barycenter} = \frac{r_{orbit}}{j}</math> :<math>l_{orbit} = 2 \pi (r_{orbit} - r_{barycenter})</math>, distance travelled by orbiting point :<math>v_{orbit} = \sqrt{\frac{i}{r_{orbit}j}}</math>, orbiting point velocity Example (dimensionless). The simulation parameters agree closely with the calculated parameters: :points = 8 (1 orbiting point and 7 center mass points) <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-simulation-2body.c</ref> :i = 7, j = 8 :k<sub>r</sub> = 32 :<math>\sqrt{2j/i}</math> = 1.511858 Calculated :calculated orbit period = 2504836149.00059 :calculated orbit radius = 566322.241497 :calculated orbit length = 3113519.13854 :calculated orbit barycenter = 70790.280187, 0 :n<sub>g</sub> = (k<sub>r</sub> i + 1)/j = 28.125 Simulation simulation orbit period = 2504836141 simulation orbit length = 3113519.130546298 simulation orbit barycenter; x = 70790.28092, y = 0.000732 ===== Earth moon orbit===== The earth to moon mass ratio approximates 81:1 and so can be simulated as a 2-body orbit with the moon as a single orbiting point as in the above example. Here we use the orbital parameters to determine the value for the mass to radius coefficient k<sub>r</sub>. Planck length <math>l_p</math>, Planck mass <math>m_P</math> and <math>c</math> are used to convert between the dimensionless formulas and dimensioned SI units. Reference values :<math>M</math> = 5.9722 x 10<sup>24</sup>kg (earth) :<math>m</math> = 7.346 x 10<sup>22</sup>kg (moon) :<math>T_{orbit}</math> = 27.321661*86400 = 2360591.51s To simplify, we assume a circular orbit which then gives us this radius :<math>R_{orbit} = (\frac{G (M+m) T_{orbit}^2}{4 \pi^2})^{(1/3)}</math> = 384714027m :<math>G = \frac{l_p c^2}{m_P}</math> = 0.66725e-10 The mass ratio :<math>i = \frac{M}{m}</math> = 81.298666, j = i + 1 We then find a value for <math>k_r</math> using T<sub>orbit</sub> as our reference (reversing the orbit period equation). :<math>T_o = T_{orbit} \frac{m_P}{M} \frac{c}{l_p} = 16 \pi {\alpha_{inv}}^{3/2} \frac{(k_r i + 1)^3}{i^{5/2} j^{1/2}}</math> (dimensionless orbital period) :<math>k_r = \frac{1}{i} {(\frac{T_o i^{5/2} j^{1/2}}{16 \pi {\alpha_{inv}}^{3/2}})}^{(1/3)} - \frac{1}{i}</math> = 12581.4468 Dimensionless solutions :<math>r_{orbit} = 2 \alpha_{inv} 2 \frac{(k_r i + 1)^2}{i^2}</math> = 86767420100 :<math>t_{orbit} = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} j^{1/2}}</math> = 0.159610040233 x 10<sup>18</sup> :<math>r_{barycenter} = \frac{r_{orbit}}{j}</math> = 1054299229.62 :<math>l_{orbit} = 2 \pi (r_{orbit} - r_{barycenter})</math> = 538551421685 :<math>v = \sqrt{\frac{i}{r_{orbit}j}}</math> = 0.33741701 x 10<sup>-5</sup> Converting back to dimensioned values :<math>R = r_{orbit} l_p \frac{M}{m_P} = R_{orbit}</math> = 384714027m :<math>T = t_{orbit} \frac{l_p}{c} \frac{M}{m_P} = T_{orbit}</math> = 2360591.51s :<math>B = \frac{R}{j}</math> = 4674608.301m (barycenter) :<math>L = 2\pi (R - B)</math> = 2387858091.51m (distance moon travelled around the barycenter) :<math>V = c \sqrt{\frac{i}{r_{orbit}j}}</math> = 1011.551m/s (velocity of the moon around the barycenter) If we expand the velocity term :<math>v_{orbit} = c \sqrt{\frac{i}{r_{orbit}j}}</math> :<math>v_{orbit}^3 = \frac{G M}{T_{orbit}} 2\pi \frac{i^2}{j^2}</math> Note: The [[w:standard gravitational parameter | standard gravitational parameter]] ''μ'' is the product of the gravitational constant ''G'' and the mass ''M'' of that body. For several objects in the Solar System, the value of ''μ'' is known to greater accuracy than either ''G'' or ''M''. :<math>\mu_{earth}</math> = 3.986004418(8)e14 :<math>\mu_{moon}</math> = 4.9048695(9)e12 :<math>i = \frac{\mu_{earth}}{\mu_{moon}}</math> = 81.2662685 :<math>k_r = \frac{c}{2 \sqrt{\alpha_{inv}}} {(\frac{T_{orbit}}{2 \pi \mu_{earth}})}^{1/3} \frac{(i+1)}{i}^{1/6} - \frac{1}{i}</math> = 12580.3462 :<math>t_{orbit}</math> = 0.15956776936 x 10<sup>18</sup> :<math>r_{orbit}</math> = 86752239934 ===== Kepler's formula = G===== Kepler's formula reduces to G <ref>https://codingthecosmos.com/orbitals/maple-code-Kepler.html maple code</ref> :<math>R = 2 \alpha_{inv} 2 (\frac{k_r i + 1}{i})^2 l_p \frac{M}{m_P}</math> :<math>T = 16 \pi {\alpha_{inv}}^{3/2} \frac{{(k_r i + 1)}^3}{i^{5/2} (i+1)^{1/2}} \frac{l_p}{c} \frac{M}{m_P}</math> :<math>M+m = M (\frac{i+1}{i})</math> :<math>\frac{4 \pi^2 R^3}{(M+m) T^2} = \frac{l_p c^2}{m_P} = G</math> Maple code : R:=(2/alpha_{inv})*2*((kr*i+1)^2/i^2)*lp*(M/mP): : T:=(16*Pi/alpha_{inv}^(3/2))*((kr*i+1)^3/(i^(5/2)*(i+1)^(1/2)))*(lp/c)*(M/mP): : Mm:=M*(i+1)/i: : simplify(4*Pi^2*R^3/(Mm*T^2)); : Output: lp*c^2/mP [[File:Gravitational-potential-energy-8body-1-2.gif|thumb|right|640px|8-body circular orbit plus 1-body with opposing orbitals 1:2]] ==== Orbital alignment ==== Orbital trajectory is a measure of alignment of the orbitals. In the above examples, all orbitals rotate in the same direction = aligned. If all orbitals are unaligned the object will appear to 'fall' = straight line orbit. In this example, for comparison, onto an 8-body orbit (blue circle orbiting the center mass green circle), is imposed a single point (yellow dot) with a ratio of 1 orbital (anti-clockwise around the center mass) to 2 orbitals (clockwise around the center mass) giving an elliptical orbit. The change in orbit velocity (acceleration towards the center and deceleration from the center) derives automatically from the change in the orbital radius (there is no barycenter). An orbital drift (as determined where the blue and yellow meet) naturally occurs; the eccentricity (shape) of the orbit a function of center mass and the ratio of alignment of the orbitals. A near straight line orbit will have a greater drift and a greater eccentricity than a near circular orbit. The elliptical orbit has a longer period than the circular orbit (which has a 360 degree orbit, the sidereal period). The additional period is known as the anomalistic period and includes the precession angle (360 + precession angle). Note: in these simulations there are only 2 orbital types; clock-wise and anti-clockwise ... in a real world orbit there will be a mixture. ===== Precession ===== Precession is a change in the orientation of the rotational axis of a rotating body. The first of three tests to establish observational evidence for the theory of general relativity, as proposed by Albert Einstein in 1915, concerned the "anomalous" precession of the[[w:Tests_of_general_relativity | perihelion of Mercury]]. This precession is not predicted by Newtonian gravity. The formula for precession uses the semi-major axis ''a'' (the maximum distance between center of mass) and the semi-minor axis ''b'' (the minimum distance between center of mass). :<math>e = \sqrt{1-\frac{b^2}{a^2}}</math> :<math>\theta = \frac{6\pi G M}{a (1-e^2) c^2}</math> Where ''e'' is the eccentricity of the orbit and θ is the precession angle The frequency of the center mass Schwarzschild radius = <math>i 2 l_p</math>, where ''i'' is the number of Planck mass points in the center mass and ''l''<sub>p</sub> is Planck length; ''a'' and ''b'' become :<math>a = r_a i 2 l_p</math> :<math>b = r_b i 2 l_p</math> The formula for <math>r_a</math> :<math>r_a = 2 \alpha 2 \frac{(k_r i + 1)^2}{i^2}</math> For example, the precession angle for Mercury :<math>\theta = \frac{6\pi G M}{a (1-e^2) c^2} = \frac{6\pi \lambda_{sun} a}{2 b^2}</math> = 0.501866 x 10-6 radians The Schwarzschild radius of the sun <math>\lambda_{sun} = i 2 l_p</math> = 2953.25m The eccentricity of Mercury :<math>e = \sqrt{1-\frac{b^2}{a^2}}</math> = 0.203225 (where a = 57909050km and b = 56671523km) In this simulation the ratio of anti-clockwise:clockwise orbitals = 108:1 with orbiting mass = 1 mass unit (k<sub>r</sub> = 12) <ref>https://codingthecosmos.com/orbitals/ Orbital model source code repository</ref>. {| class="wikitable" !Center mass!!angle θ!!θ*i!!eccentricity!!''r''<sub>a</sub>, ''r''<sub>b</sub> |- | 24 | 0.001175503 | 0.028212072 | 0.194749592 | 79481.8311615, 77959.9920879 |- | 28 | 0.001009240 | 0.028022688 | 0.195433743 | 79403.2724007, 77872.1317383 |- | 32 | 0.000884077 | 0.028290464 | 0.197440737 | 79344.3788203, 77782.4708225 |- | 36 | 0.000786489 | 0.028313604 | 0.197813449 | 79298.5878077, 77731.6227135 |- | 40 | 0.000708274 | 0.028330960 | 0.198373657 | 79261.9645140, 77686.7492830 |- | 44 | 0.000644252 | 0.028347088 | 0.199144931 | 79232.0062928, 77644.9930740 |- | 48 | 0.000590779 | 0.028357392 | 0.200476249 | 79207.0454340, 77599.0285567 |- | 52 | 0.000545493 | 0.028365636 | 0.200748008 | 79185.9277789, 77573.9329729 |- | ... | | | | |- | ∞ | 0.000005888 | | 0.205660603 | |} [[File:Ellipse-extrapolation.png|thumb|right|379px|Extrapolation of simulated elliptical data using the rotating orbital gravity simulator]] At a low mass ratio the mass influences the eccentricity, this influence reduces as mass increases and so the ratio 108:1 was chosen because extrapolating to infinity (the sun:mercury mass ratio = 6025000:1) gives an eccentricity ''e'' = 0.20566 close to that of the Mercury orbit ''e'' = 0.20563. Likewise the extrapolated precession angle = 0.000005888 is only slightly greater than the Mercury orbit angle θ = 0.000005019. Due to computational limitations, only a short radius ''r''<sub>a</sub> and low central masses (''M'' 24...52) were simulated. A longer radius and larger central mass values are required for greater precision. Extrapolating over this scale is imprecise however the it does appear that the correlation is within 1-2 orders of magnitude. For the simulation program code <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-elliptical-orbits.cpp</ref> and the extrapolation code used <ref>https://codingthecosmos.com/orbitals/ Gravitational-orbital-ellipse-extrapolate.py</ref>. [[w:Frame-dragging |Frame dragging]] can also impact the results as the central mass is still of itself a gravitational orbit (the center points also orbit each other), and so the center mass rotates at a relatively high velocity when compared with the orbiting point. Lense-Thirring in dimensionless form; :<math>T = T_d \frac{m_P c}{M l_p}</math> :<math>R = R_d \frac{M l_p}{m_P}</math> :<math>J = J_d \frac{M R^2}{T}</math> :<math>\theta_f = \frac{2 G J T}{c^2 r^2} = 2\frac{J_d}{R_d}</math> ==== Gravitational coupling constant ==== In the above, the points were assigned a mass as a theoretical unit of Planck mass. Conventionally, the [[w:Gravitational coupling constant | Gravitational coupling constant]] ''α<sub>G</sub>'' characterizes the gravitational attraction between a given pair of elementary particles in terms of a particle (i.e.: electron) mass to Planck mass ratio; :<math>\alpha_G = \frac{G m_e^2}{\hbar c} = (\frac{m_e}{m_P})(\frac{m_e}{m_P}) = 1.75... x10^{-45}</math> For the purposes of this simulation, particles are treated as an oscillation between an electric wave-state (duration particle frequency) and a mass point-state (duration 1 unit of Planck time). This inverse α<sub>G</sub> then represents the probability that any 2 electrons will be in the mass point-state at any unit of Planck time ([[v:Electron_(mathematical) |wave-mass oscillation at the Planck scale]] <ref>Macleod, M.J. {{Cite journal |title= Programming Planck units from a mathematical electron; a Simulation Hypothesis |journal=Eur. Phys. J. Plus |volume=113 |pages=278 |date=22 March 2018 | doi=10.1140/epjp/i2018-12094-x }}</ref>). :<math>{\alpha_G}^{-1} = \frac{m_P^2}{m_e^2} = 0.57... x10^{45}</math> As mass is not treated as a constant property of the particle, measured particle mass becomes the averaged frequency of discrete point mass at the Planck level. If 2 dice are thrown simultaneously and a win is 2 'sixes', then approximately every (1/6)x(1/6) = (1/36) = 36 throws (frequency) of the dice will result in a win. Likewise, the inverse of α<sub>G</sub> is the frequency of occurrence of the mass point-state between the 2 electrons. As 1 second requires 10<sup>42</sup> units of Planck time (<math>t_p = 10^{-42}s</math>), this occurs about once every 3 minutes. :<math>\frac{{\alpha_G}^{-1}}{t_p}</math> Gravity now has a similar magnitude to the strong force (at this, the Planck level), albeit this interaction occurs seldom (only once every 3 minutes between 2 electrons), and so when averaged over time (the macro level), gravity appears weak. If particles oscillate between an electric wave state to Planck mass (for 1 unit of Planck-time) point-state, then at any discrete unit of Planck time, a number of particles will simultaneously be in the mass point-state. If an assigned point contains only electrons, and as the frequency of the electron = f<sub>e</sub>, then the point will require 10<sup>23</sup> electrons so that, on average for each unit of Planck time there will be 1 electron in the mass point state, and so the point will have a mass equal to Planck mass (i.e.: experience continuous gravity at every unit of Planck time). :<math>f_e = \frac{m_P}{m_e} = 10^{23}</math> For example a 1kg satellite orbits the earth, for any given unit of Planck time, satellite (B) will have <math>1kg/m_P = 45940509</math> particles in the point-state. The earth (A) will have <math>5.9738 \;x10^{24} kg/m_P = 0.274 \;x10^{33}</math> particles in the point-state, and so the earth-satellite coupling constant becomes the number of rotating orbital pairs (at unit of Planck time) between earth and the satellite; :<math>N_{orbitals} = (\frac{m_A}{m_P})(\frac{m_B}{m_P}) = 0.1261\; x10^{41}</math> Earthe parameters: :<math>i = \frac{M_{earth}}{m_P} = 0.27444 \;x10^{33}</math> (earth as the center mass) :<math>i 2 l_p = 0.00887</math> (earth Schwarzschild radius) :<math>s = \frac{1kg}{m_P} = 45940509</math> (1kg orbiting satellite) :<math>N_{orbitals} = i*s = 0.1261 \;x10^{41}</math> The energy required to lift a 1 kg satellite into geosynchronous orbit is the difference between the energy of each of the 2 orbits (geosynchronous and earth). :<math>E_{orbital} = \frac{h c}{2 \pi r_{6371}} - \frac{h c}{2 \pi r_{42164}} = 0.412 x10^{-32}J</math> (energy per orbital) :<math>E_{total} = E_{orbital} N_{orbitals} = 53 MJ/kg</math> The orbital angular momentum of the planets derived from the angular momentum of the respective orbital pairs. :<math>N_{orbitals} = \frac{M_{sun}}{m_P} \frac{M_{planet}}{m_P}</math> :<math>n_g = \sqrt{\frac{R_{radius} m_P}{2 \alpha l_p M_{sun}}} </math> :<math>L_{oam} = 2\pi \frac{M r^2}{T} = N_{orbitals} n_g\frac{h}{2\pi} \sqrt{2 \alpha_{inv}},\;\frac{kg m^2}{s} </math> The orbital angular momentum of the planets; mercury = .9153 x10<sup>39</sup> venus = .1844 x10<sup>41</sup> earth = .2662 x10<sup>41</sup> mars = .3530 x10<sup>40</sup> jupiter = .1929 x10<sup>44</sup> pluto = .365 x10<sup>39</sup> [[File:Newton-vs-Orbital-trajectory_comparison.png|thumb|right|479px|Comparison of Newtonian and Orbital model simulations]] ==== Orbital vs. Newton ==== A 3-body orbit <ref>https://codingthecosmos.com/orbitals/ Newton-vs-Orbital_Newton.py</ref><ref>https://codingthecosmos.com/orbitals/ Newton-vs-Orbital_Orbital.py</ref> is compared with the equivalent orbit using Newtonian dynamics. The start positions are the same r0=2*α; x1=3490.3069; y1=0; x2=cos(pi*2/3)*r0; y2=sin(pi*2/3)*r0; x3=cos(pi*2/3)*r0; y3=sin(pi*2/3)*r0 The orbiting point was used to determine the optimal G for the Newtonian orbit (G = 0.4956). Period of orbit (<math>k_r</math> = 2.19006) :<math>t_{calc}</math> = 1122034 :<math>t_{orbital}</math> = 1121397 :<math>t_{newton}</math> = 1125633 [[File:orbit-points32-orbitals496-clumping-over-time.gif|thumb|right|640px|32 mass points (496 orbitals) begin with random co-ordinates, after 2<sup>32</sup> steps they have clumped to form 1 large mass and 2 orbiting masses.]] ==== Freely moving points ==== The simulation calculates each point as if freely moving in space, and so is useful with 'dust' clouds where the freedom of movement is not restricted. In this animation, 32 mass points begin with random co-ordinates (the only input parameter here are the start (''x'', ''y'') coordinates of each point). We then fast-forward 2<sup>32</sup> steps to see that the points have now clumped to form 1 larger mass and 2 orbiting masses. The larger center mass is then zoomed in on to show the component points are still orbiting each other, there are still 32 freely orbiting points, only the proximity between them has changed, they have formed ''planets''. [[File:relativistic-quantum-gravity-orbitals-codingthecosmos.png|thumb|right|480px|Illustration of B's cylindrical orbit relative to A's time-line axis]] ==== Hyper-sphere orbit ==== {{main|User:Platos_Cave_(physics)/Simulation_Hypothesis/Relativity}} Each point moves 1 unit of (Planck) length per 1 unit of (Planck) time in '''x, y, z''' (hyper-sphere) co-ordinates, the simulation 4-axis hyper-sphere universe expanding in uniform (Planck) steps (the simulation clock-rate) as the origin of the speed of light, and so (hyper-sphere) time and velocity are constants. Particles are pulled along by this expansion, the expansion as the origin of motion, and so all objects, including orbiting objects, travel at, and only at, the speed of light in these hyper-sphere co-ordinates <ref>Macleod, Malcolm; {{Cite journal |title=2. Relativity as the mathematics of perspective in a hyper-sphere universe |journal=SSRN |date=2014 | doi=10.2139/ssrn.3334282 }}</ref>. Time becomes [[v:User:Platos Cave (physics)/Simulation_Hypothesis/God_(programmer)#Universe_time-line |time-line]]. While ''B'' (satellite) has a circular orbit period on a 2-axis plane (the horizontal axis representing 3-D space) around ''A'' (planet), it also follows a cylindrical orbit (from B<sup>1</sup> to B<sup>11</sup>) around the ''A'' time-line (vertical expansion) axis ('''t<sub>d</sub>''') in hyper-sphere co-ordinates. ''A'' is moving with the universe expansion (along the time-line axis) at (''v = c''), but is stationary in 3-D space (''v'' = 0). ''B'' is orbiting ''A'' at (''v = c''), but the time-line axis motion is equivalent (and so `invisible') to both ''A'' and ''B'', as a result the orbital period and velocity measures will be defined in terms of 3-D space co-ordinates by observers on ''A'' and ''B''. === Atomic orbitals === [[File:H-orbit-transitions-n1-n2-n3-n1.gif|thumb|right|640px|fig 5. H atom orbital transitions from n1-n2, n2-n3, n3-n1 via 2 photon capture, photons expand/contract the orbital radius. The spiral pattern emerges because the electron is continuously pulled in an anti-clockwise direction by the rotating orbital.]] ==== Gravitational orbit ==== In the context of the gravitational orbital pair model, the atomic orbital is treated as a 2-body orbit (the electron as a point orbiting an n-body central mass 'nucleus'). To simulate electron transition between orbitals, at each step a unit of length is added. As the electron still continues its orbit, instead of a circular path, it traces a spiral path outwards. Notes: 1. Seen from the wave-point oscillation cycle model, the electron is predominately in the electric wave-state (which is a locally undefined state), the simulation program can only calculate the mass point-states, and so we are mapping only the gravitational orbital component of the electron orbit. For the gravitational orbit, the orbit co-ordinates were updated per unit of Planck time (with orbitals rotating 1 unit of Planck length). In the atomic orbital we have only 1 point (the electron), and it occurs as a point only after every wavelength cycle, and so we are updating our orbit only after every wavelength cycle. For example we find that at the lowest (''n'' = 1) orbit, there are about 471964 wave-point oscillations, and so we will map a polygon with 471964 sides (the wave state cannot be mapped). To compensate, the orbital rotation angle is modified such that 471964 steps are required to map 1 complete orbit ; :<math>\beta_{orbital} = \frac{1}{r_{ij} r_{orbital} \sqrt{r_{orbital}}}</math> :<math>r_{ij} = \sqrt{2 \alpha}</math> 2. During transition, at each step 1 unit of the photon is absorbed by the orbital radius, this continues until the photon is completely absorbed, the orbital radius extending proportionately. Photon absorption is not instantaneous, but instead occurs over time according to the photon wavelength. The number of steps required for this absorption then gives us the transition frequency. Notably, at integer (''Bohr'') radius (4''r'', 9''r'', 16''r''...) the spiral angle is a function of pi (2pi, (8/3)pi, 3pi ...), and as this is a linear extrapolation (the orbital radius grows in steps), ''n'' level orbits can be interpreted as specific orbits (which are inherently stable) occurring along the semi-continuous transition orbital path traced by the electron. The electron does not jump between n-levels, but the interim state (the transition phase) between these quantized n-levels is an orbital-photon hybrid state and thus difficult to detect. We may then have the equivalent of a non-integer ''n'', but as it is interchangeable with spiral angle and radius, we need only 1 parameter to calculate the other 2, and as transition frequency can also be determined in terms of angle and radius, we have a simple geometrical model that provides a framework for the transition process yet uses only pi and alpha as inputs. ==== 2-Photon orbital model ==== The Lyman series energy formula can be decomposed: :<math>\frac{1}{\lambda} = R_\infty\left(1 - \frac{1}{n^2}\right) = R_\infty - \frac{R_\infty}{n^2}</math> Mathematically (if not physically) we can divide into 2 waves :<math>\text{Photon}_{n1} = R_\infty</math> :<math>\text{Photon}_{nfinal} = (- \frac{R_\infty}{n^2})</math> :<math>\text{Photon}_{\text{total}} = \text{Photon}_{n1} + (-\text{Photon}_{n\text{final}})</math> This (mathematical) approach permits us to divide the transition into two distinct geometric processes taking place between the incoming photon and the orbital radius, with the electron taking a relatively passive role. Rather than 2 actual distinct photons, we may presume two geometric phases of a single photon absorption, nevertheless the 2-photon image is easier to conceptualize. Note these processes are not instantaneous but rather occur over time in discrete steps; '''Process 1 (Cancellation):''' A photon with energy corresponding to the ''n''=1 orbital frequency '''cancels''' the existing orbital structure. :<math>\text{Photon}_{n1} + \text{Orbital}_{n1} == zero</math> '''Process 2 (Creation):''' A (-) photon with energy corresponding to the <math>n_{\text{final}}</math> orbital '''creates''' the new orbital structure. :<math>\text{Photon}_{nfinal} == \text{Orbital}_{nfinal}</math> During transition, the system exists in a photon-orbital hybrid state. This is not a quantum superposition but a geometric intermediate configuration where: : The incoming photon’s momentum is being transferred incrementally : The orbital structure is simultaneously being dismantled and reconstructed : The electron mediates the momentum transfer through its position : Each steps transfers a quantum of momentum The gravitational orbit returns results analogous to the Bohr model and the 2-photon approach complements the (electric wave-state) Schrodinger equation <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref>. ==== Theory ==== =====Hyperbolic spiral===== [[File:Hyperbol-spiral-1.svg|thumb|right|320px|Hyperbolic spiral]] A [[w:hyperbolic spiral |hyperbolic spiral]] is a type of [[w:spiral|spiral]] with a pitch angle that increases with distance from its center. As this curve widens (radius '''r''' increases), it approaches an [[w:asymptotic line|asymptotic line]] (the '''y'''-axis) with the limit set by a scaling factor '''a''' (as '''r''' approaches infinity, the '''y''' axis approaches '''a'''). For the particular spiral that the electron transition path maps, periodically the spiral angles converge to give integer radius, the general form for this type of spiral (beginning at the outer limit ranging inwards); :<math>x = a^2 \frac{cos(\varphi)}{\varphi^2},\; y = a^2 \frac{sin(\varphi)}{\varphi^2},\;0 < \varphi < 4\pi</math> :radius = <math>\sqrt(x^2 + y^2) r</math> :<math>\varphi = (2)\pi, \; 4r</math> (360°) :<math>\varphi = (4/3)\pi,\; 9r</math> (240°) :<math>\varphi = (1)\pi, \; 16r</math> (180°) :<math>\varphi = (4/5)\pi, \; 25r</math> (144°) :<math>\varphi = (2/3)\pi, \; 36r</math> (120°) [[File:Bohr atom model (mul).svg|thumb|right|320px|Electron at different ''n'' level orbitals]] =====Principal quantum number '''n'''===== The H atom has 1 proton and 1 electron orbiting the proton, in the [[w:Bohr model |Bohr model]] (which approximates a gravitational orbit), the electron can be found at select radius ([[w:Bohr radius |the Bohr radius]]) from the proton (nucleus), these radius represent the permitted energy levels (orbital regions) at which the electron may orbit the proton. Electron transition (to a higher energy level) occurs when an incoming photon provides the required energy (momentum). Conversely emission of a photon will result in electron transition to a lower energy level. The [[w:principal quantum number |principal quantum number ''n'']] denotes the energy level for each orbital. As ''n'' increases, the electron is at a higher energy level and is therefore less tightly bound to the nucleus (as ''n'' increases, the electron orbit is further from the nucleus). Each shell can accommodate up to ''n''² (1, 4, 9, 16 ... ) electrons. Accounting for two states of spin this becomes 2''n''² electrons. As these energy levels are fixed according to this integer ''n'', the orbitals may be said to be quantized. =====(Bohr) orbital===== Setting <math>\alpha_{inv} = \frac{1}{\alpha}</math> = 137.035999177⁠ (CODATA 2022) The Bohr radius has 2 components, the dimensionless (the [[w:fine structure constant|fine structure constant alpha]]) and the dimensioned (electron wavelength); :<math>a_0 = \alpha_{inv} \times \lambda_e</math> The orbital radius of this model also includes the proton wavelength and so is slightly greater than 2x the Bohr radius :<math>\lambda_0 = \lambda_p + \lambda_e</math> :<math>r_0 = 2 \alpha_{inv} \times \lambda_0</math> To reduce simulation computing time, only the alpha component is described here, the dimensioned components added later. :<math>r_{orbital} = 2 \alpha_{inv} n^2</math> As a mass point, the electron orbits the proton at a fixed radius (<math>r_{orbital}</math>) in a series of steps (the duration of each step corresponds to the wavelength component). The distance travelled per step (per wave-point oscillation) equates to the distance between mass point states and is the inverse of the radius. [[File:atomic-orbital-rotation-step.png|thumb|right|208px|electron (blue dot) moving 1 step anti-clockwise along the alpha orbital circumference]] length = <math>l_{step} = \frac{1}{r_{orbital}}</math> Duration = 1 step per wavelength and so velocity velocity = <math>v_{orbital} = v_{step} = \frac{1}{2\alpha_{inv} n}</math> Giving period of orbit period = <math>t_{orbital} = \frac{2\pi r_{orbital}} {v_{orbital}} = 2\pi 2\alpha_{inv} 2\alpha_{inv} n^3 </math> The (reference) orbital (''n'' = 1) :<math>t_{n1} = 2\pi 4 \alpha_{inv}^2</math> = 471964.356... The angle of rotation depends on the orbital radius :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}}\sqrt{2\alpha_{inv}}}</math> ===== 2-Photon orbitals ===== The electron can jump between ''n'' energy levels via the absorption or emission of a photon. In the 2-photon orbital model <ref>Macleod, Malcolm J.; {{Cite journal |title=4. Geometrical origins of quantization in H atom electron transitions |journal=SSRN |date=Dec 2022 | doi=10.2139/ssrn.3703266}}</ref>, the orbital (Bohr) radius is treated as a 'physical wave' (has physical properties) akin to the photon albeit an inverse such that <math>orbital \;radius + photon = zero</math> (they cancel). As such it is the orbital radius itself that absorbs or emits the photon during transition, in the process the orbital radius is extended or reduced (until the photon is completely absorbed/emitted). The electron has a `passive' role in the transition phase (mediating the exchange of momentun between the orbital and the photon). It is the rotation of the orbital radius that drives the electron motion, resulting in the electron orbit around the nucleus (orbital momentum comes from the orbital radius), and this rotation continues also during the transition phase resulting in the electron following a hyperbolic spiral path. ====== Spiral (mass point) ====== The photon is divided into 2 photons as per the Rydberg formula (denoted initial and final). :<math>\lambda_{photon} = (+\lambda_i) - (+\lambda_f)</math> The wavelength of the (<math>\lambda_i</math>) photon corresponds to the wavelength of the orbital radius. The (+<math>\lambda_i</math>) will then delete the orbital radius as described above (''orbital'' + ''photon'' = ''zero''), however the (-<math>\lambda_f</math>), because of the Rydberg minus term, will be equivalent to the orbital radius, and so conversely will increase the orbital radius. And so for the duration of the (+<math>\lambda_i</math>) photon wavelength, the orbital radius does not change as the 2 photons cancel each other; :<math>r_{orbital} = r_{orbital} + (\lambda_i - \lambda_f)</math> However, the (<math>\lambda_f</math>) has the longer wavelength, and so after the (<math>\lambda_i</math>) photon has been absorbed, and for the remaining duration of this (<math>\lambda_f</math>) photon wavelength, the orbital radius will be extended until the (<math>\lambda_f</math>) is also absorbed (the '''transition phase'''). For example, the electron is at the ''n'' = 1 orbital. To jump from an initial <math>n_i = 1</math> orbital to a final <math>n_f = 2</math> orbital, first the (<math>\lambda_i</math>) photon is absorbed by the orbital radius (<math>\lambda_i + \lambda_{orbital} = zero</math>), but simultaneously the (-<math>\lambda_f</math>) photon adds to the orbital radius, and so the electron follows a normal ''n'' = 1 orbit (the '''orbital phase'''), then the remaining (<math>\lambda_f</math>) photon continues until it too is absorbed (the '''transition phase'''). :<math>\lambda_i = 1 \times t_{n1}</math> (initial orbital) :<math>\lambda_f = n^2 \times t_{n1}</math> (final orbital) After the (<math>\lambda_i</math>) photon is absorbed, the (<math>\lambda_f</math>) photon still has <math>\lambda_f = (n_f^2 - n_i^2)t_{n1} = 3 t_{n1}</math> steps remaining until it too is absorbed. [[File:atomic-orbital-transition-alpha-steps.png|thumb|right|277px|orbital transition during orbital rotation]] This process does not occur as a single `jump' between energy levels by the electron, but rather absorption/emission of the photon takes place in discrete steps, each step corresponds to a unit of <math>r_{incr}</math> (both photon and orbital radius may be considered as constructs from multiple units of this geometry); :<math>r_{incr} = -\frac{1}{2 \pi 2\alpha_{inv}}</math> At each step 1 unit of <math>r_{incr}</math> is transferred from each photon to the orbital radius. During the orbital phase the <math>r_{incr}</math> unit from the (<math>\lambda_i</math>) photon is canceled by the (-)<math>r_{incr}</math> unit from the (<math>\lambda_f</math>) photon (<math>r_{incr}</math> + (-)<math>r_{incr}</math> = zero) and so the orbital radius does not change. After the (<math>\lambda_i</math>) photon is fully absorbed, the orbital radius continues to absorb (-)<math>r_{incr}</math> units from (what remains of) the (<math>\lambda_f</math>) photon, and as the (<math>\lambda_f</math>) photon is equivalent to the orbital radius, the orbital radius extends in these steps as a consequence. The number of steps <math>N_{steps}</math> required determines (and so can be used to calculate) the transition frequency. Furthermore at each step the orbital radius itself continues to rotate, the electron, being pulled along by this rotation according to angle β, thereby traces a spiral path as the orbital radius length changes. :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} r_{\alpha}}</math> The (accumulated) spiral angle <math>\Phi</math> at each <math>n^2</math> :n = 1 to 2: <math>\Phi = 2\pi \; (r = 4 \times \; r_{orbital}) </math> :n = 1 to 3: <math>\Phi = \frac{8}{3} \pi \; (r = 9 \times \; r_{orbital}) </math> :n = 1 to 4: <math>\Phi = 3\pi \; (r = 16 \times \; r_{orbital}) </math> :n = 1 to 5: <math>\Phi = \frac{16}{5}\pi \; (r = 25 \times \; r_{orbital}) </math> :n = 1 to 6: <math>\Phi = \frac{10}{3}\pi \; (r = 36 \times \; r_{orbital}) </math> :n = 1 to 7: <math>\Phi = \frac{7}{4}\pi \; (r = 49 \times \; r_{orbital}) </math> :n = 1 to 8: <math>\Phi = \frac{7}{2}\pi \; (r = 64 \times \; r_{orbital}) </math> In the mass state we can divide the photon into 2 mathematical structures, the transition frequency is defined as the inverse of one oscillation period at the Compton scale, multiplied by the geometric phase factor (including the dimensioned terms). This gives us the solution for the transition frequency and the Bohr radius with a pi-based spiral acting as the transition 'guard-rail'. We are using only alpha and pi, yet the transition frequency can be solved with high precision using the gravity simulator. This gives a geometrical derivation for the Bohr model, which in this context is the gravitational component of the electron orbit. ====== Photon-Orbital Hybrid (wave-state) ====== In this model, atomic orbitals are '''physical rotating structures''' rather than probability distributions. The orbital possesses: :Angular momentum: Quantized by discrete rotation steps :Energy: Stored in the rotating configuration The orbital rotates in discrete steps (β radians per step) rather than continuously. During transition, the system exists in a '''photon-orbital hybrid state'''. This is not a quantum superposition but a '''geometric intermediate configuration''' where: :The incoming photon's momentum is being transferred incrementally :The orbital structure is simultaneously being dismantled and reconstructed :The electron mediates the momentum transfer through its position :Each step transfers a quantum of momentum We then note. '''Standard QM''': Anti-realist---the wavefunction is a calculation tool, not a physical entity. Reality emerges only upon measurement. '''2-photon model''': Realist---orbitals are real rotating structures. The electron follows definite trajectories, even when unobserved. The geometric model thus establishes a '''two-layer architecture''' for encoding quantum states: :Geometric Framework Layer: The hyperbolic spiral structure provides the spatial scaffold <math>(r, \theta, \phi)</math> coordinates with built-in radial quantization <math>r \propto n^2</math> :Photon Information Layer: The absorbed photon carries angular momentum quantum numbers <math>(l, m_l)</math> that modulate this scaffold This separation offers that the Bohr model is not replaced by the Schrodinger equation but rather complements it (the mass-state provides the geometric structure; the photon-orbital hybrid provides the angular momentum content). ===== Simulation ===== [[File:Alpha-hyperbolic-spiral.gif|thumb|right|640px|Bohr radius during ionization, as the H atom electron reaches each ''n'' level, it completes 1 orbit (for illustration) then continues outward (actual velocity will become slower as radius increases according to angle β)]] The gravity simulation (<ref>https://codingthecosmos.com/orbitals/ source code</ref>) was setup with the electron as the orbiting point and 65 mass points to represent the nucleus (although the proton-electron mass ratio is 1836:1, this would be become a 1837-body set of orbiting points which is too computationally intensive). The program was modified with the rotational angle β as :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} r_{\alpha}}</math> To simulate the transition phase, at each step 1 unit of <math>r_{incr} = \frac{1}{2 \pi 2\alpha_{inv}}</math> was added to the proton-electron orbital radius. To convert to frequency in Hz, the dimension components were added :<math>f_H = \frac{2c}{\lambda_e + \lambda_p}</math> = 0.155184298 10²²s^-1 For n = 1 to n = n² :<math>f_n = 2\pi f_H \;\frac{n^2 - 1}{N_{steps}} </math> '''Results''' {| class="wikitable" !<math>r/r_{orbital}</math> !! <math>r/r_{orbital}</math> !! N-steps !! <math>\Phi</math> (deg) !! frequency Hz |- | 4.000000115 | 2.000004018 | 1887860.649 | 0.000017120 | 2466034304131826.5 |- | 8.999994875 | 4.000003286 | 4247681.247 | 120.000001964 | 2922708926063928.0 |- | 15.999987119 | 6.000002004 | 7551428.532 | 180.000002514 | 3082545855782738.5 |} Experimental values for H(1s-ns) transitions. :H(1s-2s) = 2466 061 413 187.035 kHz <ref>http://www2.mpq.mpg.de/~haensch/pdf/Improved%20Measurement%20of%20the%20Hydrogen%201S-2S%20Transition%20Frequency.pdf</ref> :H(1s-3s) = 2922 743 278 665.79 kHz <ref>https://pubmed.ncbi.nlm.nih.gov/33243883/</ref> :H(1s-4s) = 3082 581 563 822.63 kHz <ref>https://codata.org/</ref> Although the simulation was a standard gravitational orbit (charge-less) and without a relativistic correction, the results were quite close; :n = 1 to n = 2: margin = 100 * (experimental - simulated)/experimental = 0.001099% :n = 1 to n = 3: margin = 0.001175% :n = 1 to n = 4: margin = 0.001158% ====== Rydberg atom ====== Here a Rydberg atom is defined as an (idealized) atom with a nucleus of point size and an infinite mass and so the barycenter = atom center at co-ordinates (0, 0). We can simulate this as a simple transition beginning at the initial (''n''_i = 1) orbital. :<math>\varphi = 0</math> (start angle) :<math>r_{orbital} = r_0 = 2\alpha</math> (nb. Bohr radius = <math>\alpha \lambda_e</math> = α*electron wavelength) :<math>x = r_{orbital},\; y = 0</math> (start co-ordinates) For each step during transition, setting t = step number (FOR t = 1 TO ...), we can calculate the radius ''r'' and <math>n_f</math>. :<math>r = r_{orbital} + \frac{t}{2\pi 2\alpha}</math> (number of increments ''t'' of <math>r_{incr}</math>) :<math>\beta = \frac{1}{r_{orbital} \sqrt{r_{orbital}} \sqrt{2\alpha}}</math> :<math>\varphi = \varphi + \beta</math> :<math>n_f^2 = 1 + \frac{t}{2\pi 4\alpha^2}</math> (<math>n_f^2</math> as a function of ''t'') The spiral angle and <math>n_f^2</math> are interchangeable :<math>\varphi = 4 \pi (1 - \frac{1}{{n_f}^2})</math> We can then re-write (<math>n_f</math> is only an integer at prescribed spiral angles); :<math>\beta = \frac{1}{{r_{orbital}}^2 n_f^3}</math> ''n'' orbital transition periods are multiples of the ''n'' = 1 orbital. If we include a relativistic term; :<math>t_{n1} = 2\pi 4 \alpha_{inv}^2 \sqrt{(1 - \frac{1}{4 \alpha_{inv}^2})}</math> = 471961.21478 Then we can compare a theoretical Rydberg (also without including charge) and find a further improvement. For ionization, the second photon is of such long wavelength that its momentum contribution is negligible, and so the ionization transition frequency should correspond closely to the ''n'' = 1 orbital. :H(1s-∞s) = 3288 086 857 127.60 kHz <ref>https://codata.org/ (109678.77174307cm-1)</ref> (''n'' = ∞) This would give us a H(n1) = 471959.2427762 :n = 1: margin = 100 * (H(n1) - t_{n1})/H(n1) = 0.001099% :n = 1 to n = 2: margin = 100 * (experimental - 4 t_{n1})/experimental = 0.000267% :n = 1 to n = 3: margin = 100 * (experimental - 9 t_{n1})/experimental = 0.000398% :n = 1 to n = 4: margin = 100 * (experimental - 16 t_{n1})/experimental = 0.000422% If we use the non-relativistic <math>t_{n1}</math>, then our results are remarkably close to the results from the gravity simulation suggesting that central mass size does not have the major role in determining the transition frequency. :n = 1 to n = 2: margin = 0.000932% :n = 1 to n = 3: margin = 0.001063% :n = 1 to n = 4: margin = 0.001088% ====== Barycenter correction ====== The experimental hydrogen transition frequencies deviate slightly from the ideal Rydberg formula. When normalized, these deviations exhibit a characteristic pattern: a minimum near ''n'' = 2, followed by a rising trend toward the ionization limit as the radius increases. :H(n1) = 471959.242776 :H(n2) = 471959.956565 :H(n3) = 471959.338749 :H(n4) = 471959.222066 The gravity simulation results showed a similar trend suggesting in both cases a barycenter 'wobble'. :sim(n1) = 471964.35638 :sim(n2) = 471965.14481 :sim(n3) = 471964.88601 :sim(n4) = 471964.68921 Therefore, given the possibilities of this gravity simulator as a research tool, the next step is to divide the proton into 3 parts resembling the 3 quarks, and then experiment with different configurations. For example, we could form a U quark cluster and a D quark cluster and then test different arrangements of the clusters (and also different mass ratios) to determine which, if any, reduces the margin. This could give potential insights into the protons internal structure. We can also give the electron further mass points to determine if it also becomes constrained and relaxed. ==Article series== The following are HTML transcripts of journal articles * [[https://simulationuniverse.org/ simulationuniverse.org]]: Home page ===The 3 levels=== A model overview from the sub Planck scale to the container universe * [[https://codingthecosmos.org/1a-CMB_from_Planck_unit_scaffolding.html 1a. Planck unit CMB.html]]: Part 1. A CMB from Planck units * [[https://codingthecosmos.org/1b-Sub_Planck_scale_from_tau_loop.html 1b. The Minimal Complexity Algorithm of the Planck Scaffolding]]: Part 2. The sub-Planck scale and the tau-loop * [[https://codingthecosmos.org/1c-the_Heavens_a_container_universe.html 1c. the Heavens.html]]: Part 3. The Heavens (the container universe) ===General articles=== * [[https://codingthecosmos.org/2-Relativity_as_mathematics_of_perspective.html 2-Relativity-hypersphere.html]]: Relativity as the mathematics of perspective * [[https://codingthecosmos.org/3-Gravity_via_n-body_particle_orbitals.html 3-Gravitational-orbitals.html]]: Gravity as sum of n-body rotating orbital particle-particle pairs * [[https://codingthecosmos.org/4-Atomic-orbital_transition_using_Gravity_simulator.html 4-Atomic-orbitals.html]]: Atomic orbitals as single rotating orbital particle-particle pairs * [[https://codingthecosmos.org/5-Atomic_transition_via_photon_orbital_hybrid.html 5-w_axis.html]]: Imaginary number axis (radiation domain) * [[https://codingthecosmos.org/6-Natural_Planck_units_MTP_Fine_Structure_Constant_alpha.html 6-Physical-constant-anomalies.html]]: Derivation of the fine structure constant alpha from physical constant anomalies * [[https://codingthecosmos.org/7-Mathematical_electron_magnetic_monopole-quarks.html 7-Monopole-quarks.html]]: Quarks as magnetic monopoles * [[https://codingthecosmos.org/8-Holographic_universe_2D_plus_Compton_wavelength.html 8-Holographic-universe.html]]: Hypersphere surface as 2-D analogue ===Wiki series=== Introductions to principle concepts (for more detailed discussion see General articles) * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_units_(geometrical)]]: Planck units MLTPA as geometrical objects * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Electron_(mathematical)]]: Mathematical electron formula * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Relativity]]: Relativity as a translation between 2 co-ordinate systems * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Planck_unit_scaffolding]]: CMB and a Planck unit universe scaffolding * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/Sqrt_Planck_momentum]]: Link between charge and mass * [[User:Platos_Cave_(physics)/Simulation_Hypothesis/God_(programmer)]]: Introduction to a Planck scale Programmer God Simulation Hypothesis model == External links == * [https://codingthecosmos.com/ Planck scale modelling using geometrical objects] * [https://www.amazon.com/Our-Mathematical-Universe-Ultimate-Reality/dp/0307599809 Our Mathematical Universe: My Quest for the Ultimate Nature of Reality] -Max Tegmark (Book) * [https://link.springer.com/article/10.1134/S0202289308020011/ Dirac-Kerr-Newman black-hole electron] -Alexander Burinskii (article) * [https://plato.stanford.edu/entries/pythagoras/ Pythagoras "all is number"] - Stanford University * [[w:Mathematical universe hypothesis | Mathematical universe hypothesis]] * [[w:Philosophy of mathematics | Philosophy of mathematics]] * [[w:Philosophy of physics | Philosophy of physics]] * [[w:Platonism | Platonism]] ==References== {{Reflist}} __INDEX__ icjijunlkiosuz6809eccu8clljlrtj 0 264910 2835100 2831115 2026-09-30T03:09:24Z Jtneill 10242 /* Book chapter */ Revise and integrate material from Tutorial 8 with assistance of ChatGPT: https://chatgpt.com/share/6abc7d5c-7ccc-83ec-9d73-03d825e24eb0 2835100 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 an 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 [[Motivation and emotion/Assessment/Topic/Feedback|Topic development - General feedback]] and your topic's [[Motivation and emotion/Assessment/Topic|topic development]] marks and feedback. ** Check the [[Motivation and emotion/Assessment/Topic|discussion (talk) page]] for written feedback and [[Motivation and emotion/Assessment/Topic|UCLearn]] for marks. ** Follow up if you do not understand the feedback. * '''Align your topic structure''' ** Ensure the '''title → sub-title → focus questions → headings''' are clearly aligned. ** 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 when relevant empirical research is available. * '''Embed links to related information''' ** Add relevant links 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]] t3uzlpr56uszfpj0wz36wlqzdnowa5t 2835101 2835100 2026-09-30T03:14:34Z Jtneill 10242 /* Topic development feedback */ Revise 2835101 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 an 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]] fzqxuhcyieg3p45ci5zbze00oyr8ym8 0 264914 2835099 2830406 2026-09-30T03:06:42Z Jtneill 10242 /* Topic development feedback */ Move to Tutorial 4 2835099 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/In development}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * topic development feedback and book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === * '''Moment''' (you feel this way right now, that is, at the present moment) * '''Today''' (you have felt this way today) * '''Past few days''' (you have felt this way during the past few days) * '''Week''' (you have felt this way during the past week) * '''Past few weeks''' (you have felt this way during the past few weeks) * '''Year''' (you have felt this way during the past year) * '''General''' (you generally feel this way that is, how you feel on average) === Psychometrics === * Correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlation indicates that when one dimension is higher the other one tends to be lower, but this relationship is very weak (1% to 5% shared variance). So, it is best to consider PA and NA as independent dimensions of affective experience. * Test-retest reliability – how stable is this measure of emotion over time? Based on Watson et al. (1988): ** PA (ranges between .54 (Moment) and .68 (General) ** NA (ranges between .45 (Moment) and .71 (General) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] eeuxjlfshxws8lg7w7v709h7vz2lct1 2835103 2835099 2026-09-30T03:14:55Z Jtneill 10242 2835103 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/In development}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === * '''Moment''' (you feel this way right now, that is, at the present moment) * '''Today''' (you have felt this way today) * '''Past few days''' (you have felt this way during the past few days) * '''Week''' (you have felt this way during the past week) * '''Past few weeks''' (you have felt this way during the past few weeks) * '''Year''' (you have felt this way during the past year) * '''General''' (you generally feel this way that is, how you feel on average) === Psychometrics === * Correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlation indicates that when one dimension is higher the other one tends to be lower, but this relationship is very weak (1% to 5% shared variance). So, it is best to consider PA and NA as independent dimensions of affective experience. * Test-retest reliability – how stable is this measure of emotion over time? Based on Watson et al. (1988): ** PA (ranges between .54 (Moment) and .68 (General) ** NA (ranges between .45 (Moment) and .71 (General) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 0m3jd8opvbeg9iwyy4qd0k3cpx4u7lz 2835104 2835103 2026-09-30T03:15:17Z Jtneill 10242 Update for 2026 2835104 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === * '''Moment''' (you feel this way right now, that is, at the present moment) * '''Today''' (you have felt this way today) * '''Past few days''' (you have felt this way during the past few days) * '''Week''' (you have felt this way during the past week) * '''Past few weeks''' (you have felt this way during the past few weeks) * '''Year''' (you have felt this way during the past year) * '''General''' (you generally feel this way that is, how you feel on average) === Psychometrics === * Correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlation indicates that when one dimension is higher the other one tends to be lower, but this relationship is very weak (1% to 5% shared variance). So, it is best to consider PA and NA as independent dimensions of affective experience. * Test-retest reliability – how stable is this measure of emotion over time? Based on Watson et al. (1988): ** PA (ranges between .54 (Moment) and .68 (General) ** NA (ranges between .45 (Moment) and .71 (General) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 6e873wmx8cet1ddjdr7cmh2tx9o3yvi 2835106 2835104 2026-09-30T03:26:04Z Jtneill 10242 /* Book chapter marking criteria */ 2835106 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === * '''Moment''' (you feel this way right now, that is, at the present moment) * '''Today''' (you have felt this way today) * '''Past few days''' (you have felt this way during the past few days) * '''Week''' (you have felt this way during the past week) * '''Past few weeks''' (you have felt this way during the past few weeks) * '''Year''' (you have felt this way during the past year) * '''General''' (you generally feel this way that is, how you feel on average) === Psychometrics === * Correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlation indicates that when one dimension is higher the other one tends to be lower, but this relationship is very weak (1% to 5% shared variance). So, it is best to consider PA and NA as independent dimensions of affective experience. * Test-retest reliability – how stable is this measure of emotion over time? Based on Watson et al. (1988): ** PA (ranges between .54 (Moment) and .68 (General) ** NA (ranges between .45 (Moment) and .71 (General) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria|marking criteria]] * Check the marking rubric * Compare with top chapters * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] cwrg6t9805qgg45t6u4kjl56nqic9vc 2835109 2835106 2026-09-30T03:28:21Z Jtneill 10242 /* Book chapter tips */ 2835109 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === * '''Moment''' (you feel this way right now, that is, at the present moment) * '''Today''' (you have felt this way today) * '''Past few days''' (you have felt this way during the past few days) * '''Week''' (you have felt this way during the past week) * '''Past few weeks''' (you have felt this way during the past few weeks) * '''Year''' (you have felt this way during the past year) * '''General''' (you generally feel this way that is, how you feel on average) === Psychometrics === * Correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlation indicates that when one dimension is higher the other one tends to be lower, but this relationship is very weak (1% to 5% shared variance). So, it is best to consider PA and NA as independent dimensions of affective experience. * Test-retest reliability – how stable is this measure of emotion over time? Based on Watson et al. (1988): ** PA (ranges between .54 (Moment) and .68 (General) ** NA (ranges between .45 (Moment) and .71 (General) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria|marking criteria]] * Check the marking rubric * Compare with top chapters * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] c2mqbby6s91vzg2ugaoorseda8jwjsg 2835110 2835109 2026-09-30T03:29:44Z Jtneill 10242 /* Book chapter tips */ 2835110 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === * '''Moment''' (you feel this way right now, that is, at the present moment) * '''Today''' (you have felt this way today) * '''Past few days''' (you have felt this way during the past few days) * '''Week''' (you have felt this way during the past week) * '''Past few weeks''' (you have felt this way during the past few weeks) * '''Year''' (you have felt this way during the past year) * '''General''' (you generally feel this way that is, how you feel on average) === Psychometrics === * Correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlation indicates that when one dimension is higher the other one tends to be lower, but this relationship is very weak (1% to 5% shared variance). So, it is best to consider PA and NA as independent dimensions of affective experience. * Test-retest reliability – how stable is this measure of emotion over time? Based on Watson et al. (1988): ** PA (ranges between .54 (Moment) and .68 (General) ** NA (ranges between .45 (Moment) and .71 (General) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] anmzm6jm5wdmr84t2p4yozi9xha2fgf 2835116 2835110 2026-09-30T04:39:02Z Jtneill 10242 /* Temporal framing */ The temporal framing of the PANAS can be customised: 2835116 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: * '''Moment''' (you feel this way right now, that is, at the present moment) * '''Today''' (you have felt this way today) * '''Past few days''' (you have felt this way during the past few days) * '''Week''' (you have felt this way during the past week) * '''Past few weeks''' (you have felt this way during the past few weeks) * '''Year''' (you have felt this way during the past year) * '''General''' (you generally feel this way that is, how you feel on average) === Psychometrics === * Correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlation indicates that when one dimension is higher the other one tends to be lower, but this relationship is very weak (1% to 5% shared variance). So, it is best to consider PA and NA as independent dimensions of affective experience. * Test-retest reliability – how stable is this measure of emotion over time? Based on Watson et al. (1988): ** PA (ranges between .54 (Moment) and .68 (General) ** NA (ranges between .45 (Moment) and .71 (General) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 73ilz543nvr8gdqzo0xgieg6lbclp3j 2835117 2835116 2026-09-30T04:40:59Z Jtneill 10242 /* Temporal framing */ Convert list to table 2835117 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * Correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlation indicates that when one dimension is higher the other one tends to be lower, but this relationship is very weak (1% to 5% shared variance). So, it is best to consider PA and NA as independent dimensions of affective experience. * Test-retest reliability – how stable is this measure of emotion over time? Based on Watson et al. (1988): ** PA (ranges between .54 (Moment) and .68 (General) ** NA (ranges between .45 (Moment) and .71 (General) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] okjli3qgtctmi3i6tiac8d4eaioxjwn 2835118 2835117 2026-09-30T04:46:43Z Jtneill 10242 /* Psychometrics */ 2835118 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, another measurement option is to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] jbun9c1s8ehuagv8lx2ls42e717wavq 2835119 2835118 2026-09-30T04:57:23Z Jtneill 10242 /* How can emotion be measured? */ analysis of written or spoken language 2835119 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Emotion research often induces ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] treil6u6klyk4xxmxxibd2uwwmrnqf6 2835120 2835119 2026-09-30T05:06:59Z Jtneill 10242 /* How can emotion be induced? */ + Table created with assistance of ChatGPT: https://chatgpt.com/share/6abc98ea-fc4c-83ec-866c-9b26d89d52c0 2835120 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagery / scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. [https://doi.org/10.1037/1528-3542.8.3.395 doi:10.1037/1528-3542.8.3.395] |- | '''Pictures / films''' | View emotionally evocative photographs or film clips | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. [https://doi.org/10.3389/fpsyg.2016.00180 doi:10.3389/fpsyg.2016.00180] |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. [https://doi.org/10.1080/02699938808415228 doi:10.1080/02699938808415228] |- | '''Autobiographical recall''' | Recall and vividly re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. [https://doi.org/10.1371/journal.pone.0095837 doi:10.1371/journal.pone.0095837] |- | '''Social / situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. [https://doi.org/10.1016/j.sbspro.2012.11.380 doi:10.1016/j.sbspro.2012.11.380] |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 64r6he9f5fzzmbid6wbd17aaie1pvuc 2835121 2835120 2026-09-30T05:07:47Z Jtneill 10242 /* Overview */ 2835121 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagery / scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. [https://doi.org/10.1037/1528-3542.8.3.395 doi:10.1037/1528-3542.8.3.395] |- | '''Pictures / films''' | View emotionally evocative photographs or film clips | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. [https://doi.org/10.3389/fpsyg.2016.00180 doi:10.3389/fpsyg.2016.00180] |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. [https://doi.org/10.1080/02699938808415228 doi:10.1080/02699938808415228] |- | '''Autobiographical recall''' | Recall and vividly re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. [https://doi.org/10.1371/journal.pone.0095837 doi:10.1371/journal.pone.0095837] |- | '''Social / situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. [https://doi.org/10.1016/j.sbspro.2012.11.380 doi:10.1016/j.sbspro.2012.11.380] |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because its: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 22ex83o7n5yq83yu8f2bj2bk86vh06l 2835122 2835121 2026-09-30T05:08:39Z Jtneill 10242 /* Self-report */ 2835122 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagery / scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. [https://doi.org/10.1037/1528-3542.8.3.395 doi:10.1037/1528-3542.8.3.395] |- | '''Pictures / films''' | View emotionally evocative photographs or film clips | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. [https://doi.org/10.3389/fpsyg.2016.00180 doi:10.3389/fpsyg.2016.00180] |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. [https://doi.org/10.1080/02699938808415228 doi:10.1080/02699938808415228] |- | '''Autobiographical recall''' | Recall and vividly re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. [https://doi.org/10.1371/journal.pone.0095837 doi:10.1371/journal.pone.0095837] |- | '''Social / situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. [https://doi.org/10.1016/j.sbspro.2012.11.380 doi:10.1016/j.sbspro.2012.11.380] |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] hj41cmakm60wkkruwhjyh6busdif0jg 2835124 2835122 2026-09-30T05:12:29Z Jtneill 10242 /* How can emotion be induced? */ Revise table 2835124 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. fMRI is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] q9l8cu2a8e3gp2j1zkukebjwpq6uvng 2835125 2835124 2026-09-30T05:27:19Z Jtneill 10242 /* How can emotion be measured? */ 2835125 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[https://en.wikipedia.org/wiki/Functional_magnetic_resonance_imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] bmstan51khzhdzavw2a4suppna3mg3r 2835126 2835125 2026-09-30T05:28:06Z Jtneill 10242 /* How can emotion be measured? */ 2835126 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2)) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 56luzihwt3blbd3bn6ibtfcpp2om398 2835127 2835126 2026-09-30T05:28:38Z Jtneill 10242 /* How can emotion be measured? */ 2835127 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 265v1s1qddhq37gf7oof5c69o37s0qq 2835128 2835127 2026-09-30T05:29:28Z Jtneill 10242 /* References */ 2835128 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [Tutorial 8] (2026) * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025)<!-- * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] 7pbmjhksblwocr2oi4v9xuyi6n24c6r 2835135 2835128 2026-09-30T08:28:41Z Jtneill 10242 /* Recording */ Update for 2026 2835135 wikitext text/x-wiki {{Motivation and emotion/Tutorials|Tutorial 8: Measuring emotion|eighth}} {{Motivation and emotion/Tutorials/Complete2}} <!-- {{Motivation and emotion/Tutorials/Complete2}} --> <!-- {{Motivation and emotion/Tutorials/In development}} --> ==Overview== This tutorial discusses: * emotion inducement * measurement of emotion * the Positive and Negative Affect Scale * book chapter marking criteria ==How can emotion be induced?== Some emotion research studies induce specific emotions in order to better under them. In ways can human emotion be induced for the purpose of psychological research? {| class="wikitable" ! Method ! Example ! Example study |- | '''Imagined scenarios''' | Imagine a specified emotional situation or vividly imagine an emotionally evocative scenario | Holmes, E. A., Mathews, A., Mackintosh, B., & Dalgleish, T. (2008). The causal effect of mental imagery on emotion assessed using picture-word cues. ''Emotion, 8''(3), 395–409. https://doi.org/10.1037/1528-3542.8.3.395 |- | '''Images, video, VR''' | View emotionally evocative photographs, film clips, or virtual reality | Uhrig, M. K., Trautmann, N., Baumgärtner, U., Treede, R.-D., Henrich, F., Hiller, W., & Marschall, S. (2016). Emotion elicitation: A comparison of pictures and films. ''Frontiers in Psychology, 7'', 180. https://doi.org/10.3389/fpsyg.2016.00180 |- | '''Music''' | Listen to music selected to induce a particular emotional state | Kenealy, P. (1988). Validation of a music mood induction procedure: Some preliminary findings. ''Cognition and Emotion, 2''(1), 41–48. https://doi.org/10.1080/02699938808415228 |- | '''Autobiographical recall''' | Recall and re-experience a personal event associated with the target emotion | Mills, C., & D'Mello, S. (2014). On the validity of the autobiographical emotional memory task for emotion induction. ''PLoS ONE, 9''(4), e95837. https://doi.org/10.1371/journal.pone.0095837 |- | '''Social situational manipulation''' | Interact with another person whose behaviour is deliberately designed to elicit an emotion | Kučera, D., & Haviger, J. (2012). Using mood induction procedures in psychological research. ''Procedia - Social and Behavioral Sciences, 69'', 31–40. https://doi.org/10.1016/j.sbspro.2012.11.380 |} ==How can emotion be measured?== [[File:Eeg registration.jpg|thumb|right|250px|'''Figure 1.''' [[w:Electroencephalography|EEG]] detects electrical activity in different areas of the brain using electrodes attached to the skull.]] Empirical emotion research requires measurement. How can emotion be measured? [[File:El Lehendakari visita la nueva unidad de Resonancia Magnética del HUA (40116421582).jpg|thumb|right|250px|'''Figure 2'''. [[w:Functional magnetic resonance imaging|fMRI]] is an advanced method of neuroimaging which can be used to assess emotion based on blood flow.]] * Behaviour (e.g., body language, eye tracking, key strokes) * Facial expression (e.g. specific combinations of muscle activation) * Neural activity: ** [[w:Electroencephalography|Electroencephalography]] (EEG; see Figure 1) ** [[w:Functional magnetic resonance imaging|functional magnetic resonance imaging]] (fMRI; see Figure 2) * Physiological arousal (e.g., pupil dilation, skin conductance, heart rate, physical activity) Characteristics of these methods: * Resource intensive (especially fMRI) - needs equipment, expertise, software etc. * Based on what is externally [[w:Observation|observable]] or physiologically scannable. But emotion is also fundamentally phenomenological/subjective. So, other measurement options include using analysis of written or spoken language or simple to ask people to [[w:Introspection|introspect]] and self-report. ==Self-report== Emotion can be self-reported qualitatively (open-ended questions with linguistic responses) or quantitatively (close-ended question with rating scales). Open-ended responses can be manually, or increasingly automatically, analysed about their emotional content to identify themes and meanings. Closed-ended self-report approaches to measurement emotion can be: * [[w:Ideogram|Ideographic]] (pictorial) such as the: [https://www.google.com/search?sca_esv=567989033&rlz=1C1GCEA_enAU1011AU1011&sxsrf=AM9HkKlgj5UmDqMh7zkxBlEv3Zwu5eAsvQ:1695553849848&q=self-assessment+manikin Self-Assessment Manikin] (SAM; Bradley & Lang, 1994) ** Valence (happy-sad) ** Arousal (high-low) ** Dominance (small-big) * Discrete/numerical such as: ** [[w:DASS (psychology)|Depression Anxiety and Stress Scale]] (DASS) (Wikipedia) ** [https://www.aci.health.nsw.gov.au/__data/assets/pdf_file/0015/212901/Kessler_10_and_scoring.pdf Kessler 10] (K-10; nsw.gov.au) ** [[w:Profile of mood states|Profile of Mood States]] (POMS) (Wikipedia) ** [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS) (Wikipedia) The DASS and K10 are commonly used as screening tools such as by a general practitioner who is concerned about a patient's psychological distress. So, these tools measure the degree of aversive emotionality. The scores can be compared with norms to help gauge the level of distress. These tools are also sometimes used in research. The POMS and PANAS are commonly used in psychological research about emotion. The PANAS is more popular because it is: * simple * flexible * freely available See also: [[w:Affect measures|Affect measures]] (Wikipedia) ==PANAS== The [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] (PANAS; Watson & Clark, 1999) is the most widely used self-report measure in emotion research. ===Your profile=== {{anchor|Activity}}{{RoundBoxTop|theme=10}} '''Activity: PANAS''' [[File:Antu 67EF addoninstaller.0.svg|right|100px]] # Complete this [https://docs.google.com/forms/d/e/1FAIpQLSdRvz2jh2iTvJmuYXuoiR_1SfOzJ7QtyTnITIgCg36Uh7rtwQ/viewform?usp=sf_link short version of the PANAS] (20-items; Google Form)<!-- # [https://www.psytoolkit.org/c/3.1.0/survey?s=AqxEf Online version] (PsyToolkit) # [https://drive.google.com/open?id=0B2N4zSp4hmN9NV9teWVVVS1uVjA Hard-copy handout] --> # Include a code word if you would like to know your individual results # Discuss PANAS strengths, temporal framing, psychometrics, factor structure, and distributions {{RoundBoxBottom}} ===Strengths=== Strengths of the PANAS include: * Simplicity – based on 1-word emotion descriptors * [[Motivation and emotion/Tutorials/Measuring emotion#Factor structure|Factor structure]] – Short (20-item) and long (60-item) versions * Flexibility ** [[#Temporaral framing|Temporal framing]] – from present state to general ** Domain – General or specific * Availability – Free to use === Temporal framing === The temporal framing of the PANAS can be customised: {| class="wikitable" ! Time frame ! Description |- | '''Moment''' | You feel this way right now, that is, at the present moment. |- | '''Today''' | You have felt this way today. |- | '''Past few days''' | You have felt this way during the past few days. |- | '''Week''' | You have felt this way during the past week. |- | '''Past few weeks''' | You have felt this way during the past few weeks. |- | '''Year''' | You have felt this way during the past year. |- | '''General''' | You generally feel this way, that is, how you feel on average. |} === Psychometrics === * '''Independence of positive and negative affective''': The correlations between PA and NA range between -.12 (Today) and -.23 (Year) (Watson et al., 1988). The negative correlations indicate that when one dimension is higher the other one tends to be lower, but the relationship is very weak (1% to 5% shared variance). Thus, it is best to consider PA and NA as independent dimensions of affective experience. ** In what situations might PA and NA both be high? ** In what situations might PA and NA both be low? * '''Test-retest reliability''': How stable is this measure of emotion over time? Based on an 8-week test-retest period, Watson et al. (1988) found: ** Moment: PA .54 and NA .45 (~25% relability) ** General: PA .68 and NA .71 (~50 relability) === Factor structure === There are short (20-item) and long (60-item) versions of the PANAS. ;Short (20 items; 2 factors; see Table 2) * Positive affect (10 items) * Negative affect (10 items) '''Table 2''' ''PANAS-20 Positive and Negative Affect Items'' {| class="wikitable" style="margin: auto;" |+ !Positive affect !Negative affect |- |Active |Afraid |- |Alert |Ashamed |- |Attentive |Distressed |- |Determined |Guilty |- |Enthusiastic |Hostile |- |Excited |Irritable |- |Inspired |Jittery |- |Interested |Nervous |- |Proud |Scared |- |Strong |Upset |} ;Long (60 items; 11 factors) * '''Basic negative emotions''' ** '''Fear''' (5 items): afraid, frightened, jittery, nervous, scared, shaky ** '''Hostility''' (6 items): angry, disgusted, hostile, irritable, loathing, scornful ** '''Guilt''' (6 items): angry at self, ashamed, blameworthy, disgusted with self, guilty ** '''Sadness''' (5 items): alone, angry, blue, downhearted, sad * '''Basic positivity emotions''' ** '''Joviality''' (8 items): cheerful, delighted, energetic, enthusiastic, excited, happy, joyful, lively ** '''Self-Assurance''' (6 items): bold, confident, daring, fearless, proud, strong ** '''Attentiveness''' (5 items): alert, attentive, concentrating, determined * '''Other affective states''' ** '''Shyness''' (4 items): bashful, sheepish, shy, timid ** '''Fatigue''' (4 items): drowsy, sleepy, sluggish, tired ** '''Serenity''' (3 items): at ease, calm, relaxed ** '''Surprise''' (3 items): amazed, astonished, surprised ===Distributions=== * Examine class distributions for positive affect (PA) and negative affect (NA) * Compare with USA university norms (see Table 1): ** PA = 3 to 3.5 ** NA = 1.5 to 2 '''Table 1''' ''PANAS-20 Positive and Negative Affect Norms'' {| class="wikitable" style="margin: auto;" |+ !Source !N !PA !NA |- |Watson et al. (1988) |660 |2.97 |1.48 |- |Watson & Clark (1994) |3622 |3.57 |1.95 <!-- |- |Motivation & emotion (2000) |34.2 |24.6 --> |} ==Book chapter tips== * Follow the [[Motivation and emotion/Assessment/Chapter|author guidelines]] and [[Motivation and emotion/Assessment/Using generative AI|using genAI guidelines]] * Address the [[Motivation and emotion/Assessment/Chapter#Marking criteria|marking criteria]] * Check the [[Motivation and emotion/Assessment/Chapter#Marking rubric|marking rubric]] * Compare with [[Motivation and emotion/Book|top chapters]] * Get feedback ** Studiosity Writing Feedback+ ** Peer review ** AI review ==Book chapter marking criteria== Familiarse yourself with the [[Motivation and emotion/Assessment/Chapter|book chapter guidelines]] which include the marking criteria: * '''Overview''' (5%) ** Scenario ** Describe problem (1-2 paragraphs) ** Focus questions * '''Theory''' (20%) ** Apply top theories to the problem * '''Research''' (25%) ** Use best research to weigh evidence * '''Integration''' (10%) ** Synthesise theory and research * '''Conclusion''' (5%) ** What are the take-home messages? (i.e., answers to sub-title and/or focus questions) * '''Style''' (20%) ** Professional quality written expression (sentence structure, paragraph structure, spelling, grammar, APA style) (e.g., use Studiosity, [[Motivation and emotion/Assessment/Using generative AI|genAI]], and peer review) * '''Learning features''' (5%) - options: ** Wiki links (to the most relevant Wikipedia page or book chapter) when key words are mentioned for the first time ** Figures and tables ** Scenarios/case studies/examples ** Quizzes ** Feature boxes etc. * '''Social contribution''' (10%) ** Edits ** Comments ** Discussion posts ** Direct links to evidence (see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]) ** Marking based on *** Quantity *** Quality *** Timeliness ==Recording== * [https://au-lti.bbcollab.com/recording/f787e4083a49474785fc57b7631570b9 Tutorial 8] (2026)<!-- * [https://au-lti.bbcollab.com/recording/469acca6d2e747eaab879d60c3ddecd9 Tutorial 8] (2025) * [https://au-lti.bbcollab.com/recording/e20b88bfb3b94251a28834ecd7ee83c8 Tutorial 8] (2024) * [https://au-lti.bbcollab.com/recording/36cc3cf8a7be4d139b2b406d342affc7 Tutorial 8] (2023) * [https://au-lti.bbcollab.com/recording/7f5f45035ebc4de4800cc80731f70f1e Tutorial 8], 2022 * [https://au-lti.bbcollab.com/recording/e4361150e57b4b999a6d002f871be374 Tutorial 8], 2021 --> ==See also== <!-- ;Additional tutorial material --> <!-- ;Book chapters --> ;Wikipedia * [[w:Electroencephalography|Electroencephalography]] * [[w:Functional magnetic resonance imaging|Functional magnetic resonance imaging]] * [[w:Positive and Negative Affect Schedule|Positive and Negative Affect Schedule]] ;Lecture * [[{{#titleparts:{{PAGENAME}}|1}}/Lectures/Aspects of emotion|Aspects of emotion]] ;Tutorials * [[{{#titleparts:{{PAGENAME}}|2}}/Core emotions|Core emotions]] (Previous tutorial) * [[{{#titleparts:{{PAGENAME}}|2}}/20 emotions|20 emotions]] (Next tutorial) <!-- ;Admin * [[/Instructor notes/]] --> ==References== {{Hanging indent|1= <!-- Thompson, E. R. (2007). Development and validation of an internationally reliable short-form of the positive and negative affect sche''dule (PANAS). ''Journal of Cross-cultural Psychology'', ''38''(2), 227–242. https://doi.org/10.1177/0022022106297301 --> Bradley, M. M., & Lang, P. J. (1994). Measuring emotion: The self-assessment manikin and the semantic differential. ''Journal of Behavior Therapy and Experimental Psychiatry'', ''25''(1), 49–59. https://doi.org/10.1016/0005-7916(94)90063-9 Watson, D., & Clark, L. A. (1994). ''[https://doi.org/10.17077/48vt-m4t2 The PANAS-X: Manual for the positive and negative affect schedule-expanded form]''. Watson, D., Clark, L. A., & Tellegen, A. (1988). [https://scienceofbehaviorchange.org/wp-content/uploads/2019/10/PANAS.Watson.1988.pdf Development and validation of brief measures of positive and negative affect: the PANAS scales]. ''Journal of Personality and Social Psychology'', ''54''(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063 }} <noinclude>{{Motivation and emotion/Tutorials/Navigation}}</noinclude> [[Category:Motivation and emotion/Tutorials/Measuring emotion]] lhzj189mqv8lstvholha4xogssn6mv5 0 266023 2835034 2834854 2026-09-29T12:00:07Z ThaniosAkro 2805358 /* Solving M by (M+1) */ 2835034 wikitext text/x-wiki ==Introduction== The word "simultaneous" implies that two or more equations exist in the same context at the same time. For example: <math>3x + 2y - 13 = 0\ \dots\ (1)</math> <math>2x - y - 4 = 0 \ \dots\ (2)</math> Equations <math>(1)</math> and <math>(2)</math> are 2 simultaneous equations. When we see two simultaneous equations, it's natural to ask the question: What are the values of <math>x</math> and <math>y</math> that satisfy both equations <math>(1)</math> and <math>(2)</math>? To calculate <math>(x,y)</math> common to both <math>(1)</math> and <math>(2)</math>: <math>(2)*2\ \dots\ 4x - 2y - 8 = 0 \ \dots\ (3)</math> <math>(3)+(1)\ \dots\ 7x - 21 = 0;\ x = 3.</math> Substitute <math>3</math> for <math>x</math> in <math>(2):\ 2(3) - y - 4 = 0;\ y = 2.</math> The values <math>(x,y)=(3,2)</math> satisfy both equations <math>(1)</math> and <math>(2).</math> In cartesian coordinate geometry of 2 dimensions, point <math>(3,2)</math> is the point of intersection of two lines <math>(1)</math> and <math>(2).</math> See Figure 1 below. If the 2 lines are parallel, there is no point of intersection. See Figure 2 below. The trivial solution <math>(0, 0)</math> is a valid solution. See Figure 3 below. {{RoundBoxTop|theme=2}} <gallery> File:0726_2lines.png|<small>Figure 1. 2 lines that intersect at point (3,2).</small> File:0726_2parallelLines.png|<small>Figure 2. When 2 lines are parallel, there is no point of intersection.</small> File:0729_2lines.png|<small>Figure 3. The trivial solution x=y=0 is a valid solution.</small> </gallery> {{RoundBoxBottom}} The information contained in equations <math>(1)</math> and <math>(2)</math> may constitute a matrix: <pre> [ [3, 2, -13], [2, -1, -4] ] </pre> In fact, in the python programming language, the following statement is valid code: <syntaxhighlight lang=python> data = [ [3, 2, -13], [2, -1, -4] ] </syntaxhighlight> For there to be a point of intersection, <code>data</code> must be valid. Here are examples of invalid data: <syntaxhighlight lang=python> data = [ [3, 2, -13], # Both lines are parallel. [6, 4, -5] # See Figure 2 above. ] </syntaxhighlight> <syntaxhighlight lang=python> data = [ [3, 2, -13], [0, 0, -4] # Empty row, representing equation 0x + 0y - 4 = 0. ] </syntaxhighlight> <syntaxhighlight lang=python> data = [ [3, 0, -13], # Empty column representing 2 parallel lines: [2, 0, -4] # 3x = 13 and 2x = 4. ] </syntaxhighlight> The matrix above with name "data" is described as matrix "2 by 3," meaning that it contains 2 rows with 3 columns or 3 members per row. ==Solving 2 by 3== ===Implementation=== Below is python code containing function <code>solve2by3 (input).</code> The function accepts as input a matrix like <code>data</code> above. After the code are examples of invocation with both good data and bad data. <syntaxhighlight lang=python> import sys import decimal dD = decimal.Decimal def solve2by3 (input_, level=0) : ''' input represents system: a1*x + b1*y + c1 = 0 a2*x + b2*y + c2 = 0 input = ( (a1,b1,c1), (a2,b2,c2), ) To invoke: x,y = solve2by3 (input) Function solve2by3 () may return None. input is not changed by this function. ''' if level : thisName = 'solve2by3 (input_, level = {}) :'.format(level) else : thisName = 'solve2by3 (input_) :' try : error = 0 try : input = [ list(v) for v in input_ ] (a1,b1,c1), (a2,b2,c2) = input except : input = 0 input or {}['input_ not recognized.'] # six_values = a1,b1,c1, a2,b2,c2 for v in six_values : isinstance(v, (int, float, dD)) or {}['Non-numeric value in input.'] set1 = { isinstance(v, dD) for v in six_values } if len(set1) == 2 : # Mix of Decimal and non-Decimal in input. Make all type Decimal. (a1,b1,c1, a2,b2,c2) = [ dD(str(v)) for v in six_values ] # a1 or b1 or {}['Row 1 empty.'] ; a1 or a2 or {}['Column 1 empty.'] a2 or b2 or {}['Row 2 empty.'] ; b1 or b2 or {}['Column 2 empty.'] # if not a1 : # Make a1 non-zero. (a1,b1,c1),(a2,b2,c2) = (a2,b2,c2), (a1,b1,c1) # if a2 : # Make a2 zero. if a2 == a1 : a2,b2,c2 = a1-a2, b1-b2, c1-c2 elif a2 == -a1 : a2,b2,c2 = a1+a2, b1+b2, c1+c2 else : list1 = [ a2*v for v in (a1,b1,c1) ] list2 = [ a1*v for v in (a2,b2,c2) ] a2,b2,c2 = [ (v1-v2) for v1,v2 in zip (list1, list2) ] a2 and {}['Internal error. a2 should be 0.'] b2 or {}['Parallel input.'] # The matrix is: # a1, b1, c1 with a1 non-zero # 0, b2, c2 and b2 non-zero. # 0 x + b2 y + c2 = 0 y = -c2/b2 # a1 x + b1 y + c1 = 0 x = -(b1*y + c1)/a1 # Here is why a1 must be non-zero. output = x,y except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' input of solve2by3() =') print (' ', input[0]) print (' ', input[1]) return None # return output </syntaxhighlight> ====Examples==== Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13], [2, -1, -4] ]) print (output) </syntaxhighlight> <pre> (3.0, 2.0) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13], # Both lines are parallel. [6, 4, -5] # See Figure 2 above. ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('Parallel input.') input of solve2by3() = [3, 2, -13] [6, 4, -5] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13, 7], # Input matrix not exactly 2 by 3. [6, 4, -5] ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('input_ not recognized.') None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 0, 2], [6, 0, 4] ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('Column 2 empty.') input of solve2by3() = [3, 0, 2] [6, 0, 4] None </pre> {{RoundBoxBottom}} ===Reversing the process=== ====Linear Function==== [[File:1212line01.png|thumb|400px|''' Figure 1. Diagram of line defined by 2 points.''' </br> 2 points are: <math>(-5,4), (3,1).</math> </br> Equation of line is: <math>3x + 8y - 17 = 0.</math> ]] Examples above calculate the point of intersection of 2 lines. An example of reversing the process is this task: Given two points <math>(x_1, y_1), (x_2, y_2)</math> calculate equation of line containing these 2 points. Equation of line is of format <math>Ax + By + C = 0,</math> For example: <math>3x + 2y + 10 = 0\ \dots\ (1).</math> Equation <math>(1)</math> can be expressed as <math>6x + 4y + 20 = 0</math> or <math>-9x - 6y - 30 = 0.</math> Also, there appear to be 3 unknowns, but only two sets of values are required to define the line. Assume <math>C = 1</math> and the 2 relevant equations are: <math>Ax_1 + By_1 + 1 = 0</math> <math>Ax_2 + By_2 + 1 = 0</math> To solve for <math>A, B:</math> <math>x_1A + y_1B + 1 = 0</math> <math>x_2A + y_2B + 1 = 0</math> Suppose the line is defined by points <math>(3,1), (-5,4):</math> <syntaxhighlight lang=python> # python code: input = [ [3,1,1], [-5,4,1], ] result = solve2by3 (input) print (result) </syntaxhighlight> <syntaxhighlight> (-0.17647058823529413, -0.47058823529411764) </syntaxhighlight> Desired equation is: <math>-0.17647058823529413\cdot x -0.47058823529411764\cdot y + 1 = 0\ \dots\ (2).</math> To improve appearance of <math>(2):</math> <syntaxhighlight lang=python> # python code: print (A/B) </syntaxhighlight> <syntaxhighlight> 0.37500000000000006 </syntaxhighlight> Let <math>A, B = 3, 8</math> and check: <syntaxhighlight lang=python> # python code A,B = 3,8 p1 = x1,y1 = 3,1 p2 = x2,y2 = -5,4 for v in (p1,p2) : x,y = v C = -(A*x + B*y) s1 = 'C' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> C -17 C -17 </syntaxhighlight> Desired equation <math>(2)</math> becomes <math>3x + 8y - 17 = 0\ \dots\ (3).</math> ====Wrong assumptions==== [[File:1212line02.png|thumb|400px|''' Figure 2. Diagram of line defined by 2 points and passing through origin.''' </br> 2 points are: <math>(3,2), (6,4).</math> </br> Equation of line is: <math>2x - 3y = 0.</math> </br> Non-zero value for coefficient <math>C</math> is impossible. ]] Sometimes you create a matrix that seems correct, but it fails to produce a result. Here is such an example: What is equation of line defined by points <math>(3, 2), (6, 4)?</math> As above assume that <math>C = 1.</math> <syntaxhighlight lang=python> # python code: p1 = x1,y1 = 3,2 p2 = x2,y2 = 6,4 input = [ [x1,y1,1], [x2,y2,1], ] result = solve2by3 (input) print (result) </syntaxhighlight> This assumption failed: <syntaxhighlight> solve2by3() : parallel input. input = [3, 2, 1] [6, 4, 1] None </syntaxhighlight> Assume that <math>A = 1.</math> <syntaxhighlight lang=python> # python code: # 1(x1) + B(y1) + 1(C) = 0 # 1(x2) + B(y2) + 1(c) = 0 # y1(B) + 1(C) + x1 = 0 # y2(B) + 1(C) + x2 = 0 input = [ [y1,1,x1], # Notice that input has been [y2,1,x2], # rotated left by one column. ] result = solve2by3 (input) print (result) </syntaxhighlight> <syntaxhighlight> (-1.5, 0.0) </syntaxhighlight> Equation of line is: <math>1\cdot x + (-1.5)\cdot y + 0 = 0</math> or <math>2x - 3y = 0</math> This line includes the origin. Therefore constant <math>C</math> cannot be non-zero. Generally: * Without rotation, <math>A, B = \text{result}</math> and <math>C = 1.</math> * With rotation left by one column, <math>B, C = \text{result}</math> and <math>A = 1.</math> In this case: <syntaxhighlight lang=python> # python code: >>> B,C = result ; A = 1 >>> A,B,C >>> 1,-1.5,0 </syntaxhighlight> For example of big matrix that failed the first time, but was successful the second time, see [https://en.wikiversity.org/wiki/Solving_simultaneous_equations#Cubic_Resistive_Network cubic resistive network] below. ==Solving 3 by 4== Below is python code containing function <code>solve3by4 (input).</code> The function accepts as input a 3 by 4 matrix like that described in the code comments. In 3d coordinate geometry the equations <code>(1), (2), (3)</code> are the equations of 3 planes and the solution of the system is the point of intersection of the 3 planes. Given 3 random planes, there are 2 conditions that do not produce a unique point of intersection: * If 2 of the planes are parallel. See Figure 1 below. * If the 3 planes form a "tent" or "delta." See Figure 2, 3 or 4 below. A special case of this condition occurs when size of "tent" is zero, in which case all three planes intersect on a common line and there is an infinite number of solutions. See Figure 5 below. The trivial solution <math>(0, 0, 0)</math> is valid. See Figure 6 below. <code></code> <code></code> {{RoundBoxTop|theme=2}} <gallery> File:0726_2parallelPlanes.png|<small>Figure 1. When 2 planes are parallel, there is no point of intersection.</small> File:0730triangularTube.png|<small>Figure 2. Triangular tube, 3 planes that never intersect.</small> File:0726_3planes0.png|<small>Figure 3. 3 planes that form a "tent," view 1. There is no point of intersection.</small> File:0726_3planes1.png|<small>Figure 4. 3 planes that form a "tent," view 2. There is no point of intersection.</small> File:1109_3planes1.png|<small>Figure 5. 3 planes that intersect on a common line. Points <math>(6,6,1),</math> <math>(7,7,4),</math> <math>(8,8,7)</math> are on this line and are common to all 3 planes.</small> File:0729_3planes.png|<small>Figure 6. 3 planes that intersect at origin (0, 0, 0).</small> </gallery> {{RoundBoxBottom}} ===Auxiliary functions=== <syntaxhighlight lang=python> def two_planes_parallel (plane1, plane2) : ''' status = two_planes_parallel (plane1, plane2) status = True if parallel. ''' A1,B1,C1 = plane1[:3] A2,B2,C2 = plane2[:3] A3 = B1*C2 - B2*C1 B3 = C1*A2 - C2*A1 C3 = A1*B2 - A2*B1 return ({ A3,B3,C3 } == {0}) def check_three_rows (input) : ''' result = check_three_rows (input) result is None or string. ''' row0,row1,row2 = input if two_planes_parallel (row0,row1) : return 'Two rows parallel: 0,1' if two_planes_parallel (row0,row2) : return 'Two rows parallel: 0,2' if two_planes_parallel (row1,row2) : return 'Two rows parallel: 1,2' A0,B0,C0 = row0[:3] ; A1,B1,C1 = row1[:3] ; A2,B2,C2 = row2[:3] # Line at intersection of planes 1,2 has direction numbers: A3 = B1*C2 - B2*C1 ; B3 = C1*A2 - C2*A1 ; C3 = A1*B2 - A2*B1 # Line at intersection of planes 0,2 has direction numbers: A4 = B0*C2 - B2*C0 ; B4 = C0*A2 - C2*A0 ; C4 = A0*B2 - A2*B0 # Are 2 lines of intersection parallel? if two_planes_parallel ((A3,B3,C3), (A4,B4,C4)) : return 'Three rows form tent.' return None </syntaxhighlight> ===Implementation=== <syntaxhighlight lang=python> def solve3by4 (input_, level=0) : ''' input_ is : [ [a0,b0,c0,d0], [a1,b1,c1,d1], [a2,b2,c2,d2] ] representing system: a0*x + b0*y + c0*z + d0 = 0 a1*x + b1*y + c1*z + d1 = 0 a2*x + b2*y + c2*z + d2 = 0 x,y,z = solve3by4 (input) Function solve3by4 () may return None. input is not changed by this function. ''' if level : thisName = 'solve3by4 (input_, level = {}) :'.format(level) else : thisName = 'solve3by4 (input_) :' try : error = 0 try : input = [ list(v) for v in input_ ] (a0,b0,c0,d0), (a1,b1,c1,d1), (a2,b2,c2,d2) = input except : input = 0 input or {}['input_ not recognized.'] # twelve_values = a0,b0,c0,d0, a1,b1,c1,d1, a2,b2,c2,d2 for v in twelve_values : isinstance(v, (int, float, dD)) or {}['Non-numeric value in input.'] set1 = { isinstance(v, dD) for v in twelve_values } if len(set1) == 2 : # Mix of Decimal and non-Decimal in input. Make all type Decimal. (a0,b0,c0,d0, a1,b1,c1,d1, a2,b2,c2,d2) = [ dD(str(v)) for v in twelve_values ] # a0 or b0 or c0 or {}['Row 0 empty.'] ; a0 or a1 or a2 or {}['Column 0 empty.'] a1 or b1 or c1 or {}['Row 1 empty.'] ; b0 or b1 or b2 or {}['Column 1 empty.'] a2 or b2 or c2 or {}['Row 2 empty.'] ; c0 or c1 or c2 or {}['Column 2 empty.'] # input = [ [a0,b0,c0,d0], [a1,b1,c1,d1], [a2,b2,c2,d2] ] result = check_three_rows (input) ; result and {}[result] # if not a0 : # Make a0 non-zero. if a1 : input[0],input[1] = input[1],input[0] else : input[0],input[2] = input[2],input[0] # # The matrix is: # a0, b0, c0, d0 with a0 non-zero. # a1, b1, c1, d1 # a2, b2, c2, d2 # Process rows so that a1, a2 become zero. row0 = input[0] ; a0 = row0[0] for p in (1,2) : rowp = input[p] ; ap = rowp[0] if ap : if ap == a0 : input[p] = [ (v1-v2) for (v1,v2) in zip(row0, rowp) ] elif ap == -a0: input[p] = [ (v1+v2) for (v1,v2) in zip(row0, rowp) ] else : input[p] = [ (v0*ap-vp*a0) for (v0,vp) in zip(row0, rowp) ] if input[p][0] : {}['Internal error. input[{}][0] should be 0.'.format(p)] (a0,b0,c0,d0), (a1,b1,c1,d1), (a2,b2,c2,d2) = input # The matrix is: # a0, b0, c0, d0 with a0 non-zero. # 0, b1, c1, d1 # 0, b2, c2, d2 two_rows = (b1,c1,d1), (b2,c2,d2) output = solve2by3 (two_rows, level-1) if output : y,z = output # a0 x + b0 y + c0 z + d0 = 0 x = -(b0*y + c0*z + d0)/a0 # Here is why a0 must be non-zero. output = x,y,z except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' input of solve3by4() =') print (' ', input[0]) print (' ', input[1]) print (' ', input[2]) return None # return output </syntaxhighlight> ====Examples==== Below are examples of invocation with both good data and bad data. Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [2, -1, 3, -17], [1, 3, 2, -25] , [3, 2, -1, -12] , ]) print (output) </syntaxhighlight> <pre> (3.0, 4.0, 5.0) </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [12, -12, -5, -24], [-6, 15, 8, 12] , [ 0, 10, 3, 0] , ]) print (output) </syntaxhighlight> <pre> (2.0, 0.0, -0.0) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [20, 16, 2, 17], [-77, -27, -25, -24], [81, 45, 18, 43] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Three rows form tent.') input of solve3by4() = [20, 16, 2, 17] [-77, -27, -25, -24] [81, 45, 18, 43] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [34, -5, -21, 30], [-54, -33, 63, 62], [18, 11, -21, 38] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Two rows parallel: 1,2') input of solve3by4() = [34, -5, -21, 30] [-54, -33, 63, 62] [18, 11, -21, 38] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [20, 16, 2, 17], [-77, -27, '-25', -24], [81, 45, 18, 43] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Non-numeric value in input.') input of solve3by4() = [20, 16, 2, 17] [-77, -27, '-25', -24] [81, 45, 18, 43] None </pre> {{RoundBoxBottom}} ===Reversing the Process=== ====Quadratic function==== [[File:1212quadratic01.png|thumb|400px|''' Figure 1. Graph of quadratic function defined by 3 points.''' ]] A quadratic function <math>y = f(x) = Ax^2 + Bx + C</math> is defined by 3 points: <math>(-2, 9.0), (5, 4.8), (10, 13.8).</math> What is <math>f(x)?</math> <math>y = Ax^2 + Bx + C</math> <math>A, B, C</math> are 3 unknowns. <math>x^2(A) + x(B) + 1(C) - y = 0</math> <syntaxhighlight lang=python> # python code: x1,y1 = -2, 9 x2,y2 = 5, 4.8 x3,y3 = 10, 13.8 input = [ [x1**2, x1, 1, -y1], [x2**2, x2, 1, -y2], [x3**2, x3, 1, -y3], ] A, B, C = solve3by4 (input) s1 = 'A,B,C' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> A,B,C (0.2, -1.2, 5.8) </syntaxhighlight> <math>y = f(x) = 0.2x^2 - 1.2x + 5.8</math> ====Wrong assumptions==== [[File:1212plane02.png|thumb|400px|''' Figure 2. Graph of plane containing X axis.''' </br> Because plane passes through origin, non-zero value for coefficient <math>D</math> is impossible. </br> Because plane is parallel to <math>X</math> axis, non-zero value for coefficient <math>A</math> is impossible. ]] In 3 dimensions a plane (<math>Ax + By + Cz + D = 0</math>) is defined by 3 points: <math>(5, 3, -2), (-1, 12, -8), (37, 15, -10).</math> What is equation of plane? <math>Ax + By + Cz + D = 0</math> <math>xA + yB + zC + D = 0</math> Assume that <math>D = 1.</math> <math>xA + yB + zC + 1 = 0</math> <syntaxhighlight lang=python> # python code pt1 = x1,y1,z1 = (5, 3, -2) pt2 = x2,y2,z2 = (-1, 12, -8) pt3 = x3,y3,z3 = (37, 15, -10) input = [ [ 5, 3, -2, 1], [-1, 12, -8, 1], [37, 15, -10, 1], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> solve2by3() : parallel input. input = (-63, 42, -6) (36, -24, 32) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = (5, 3, -2, 1) (-1, 12, -8, 1) (37, 15, -10, 1) result None </syntaxhighlight> Input was invalid. Rotate input left and try again. <syntaxhighlight lang=python> # python code. input = [ [ 3, -2, 1, 5], [12, -8, 1, -1], [15, -10, 1, 37], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> solve2by3() : empty column in input. input = (0, 9, 63) (0, 12, -36) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = (3, -2, 1, 5) (12, -8, 1, -1) (15, -10, 1, 37) result None </syntaxhighlight> Input was invalid. Rotate input left and try again. <syntaxhighlight lang=python> input = [ [ -2, 1, 5, 3], [ -8, 1, -1, 12], [-10, 1, 37, 15], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> result (1.5, 0, 0) </syntaxhighlight> Without rotation: <math>A, B, C = \text{result}</math> and <math>D = 1.</math> With rotation left: <math>B, C, D = \text{result}</math> and <math>A = 1.</math> With another rotation left: <math>C, D, A = \text{result}</math> and <math>B = 1.</math> <syntaxhighlight lang=python> # python code: C, D, A = (1.5, 0, 0) ; B = 1 A, B, C, D </syntaxhighlight> <syntaxhighlight> (0, 1, 1.5, 0) </syntaxhighlight> Equation of plane is: <math>0x + 1y + 1.5z + 0 = 0</math> or <math>2y + 3z = 0</math> =====A better method===== {{RoundBoxTop|theme=3}} There are four unknown values: <math>A,B,C,D.</math> Create matrix 4 by 5: <syntaxhighlight lang=python> # python code. pt1 = x1,y1,z1 = (5, 3, -2) pt2 = x2,y2,z2 = (-1, 12, -8) pt3 = x3,y3,z3 = (37, 15, -10) input = [] for (x_,y_,z_) in (pt1,pt2,pt3) : x,y,z = [ dD(v) for v in (x_,y_,z_) ] input += [ [ x,y,z,1,0 ] ] # For valid plane at least one of A,B,C must be non-zero. # For last condition let A + B + C = 5. input += [ [ 1,1,1,0,-5 ] ] A,B,C,D = solveMbyN(input) print (input) print ( '({})x + ({})y + ({})z + ({}) = 0'.format(A,B,C,D) ) </syntaxhighlight> <syntaxhighlight> [[ 5, 3, -2, 1, 0], # 5A + 3B - 2C + 1D + 0 = 0 [-1, 12, -8, 1, 0], # -1A + 12B - 8C + 1D + 0 = 0 [37, 15, -10, 1, 0], # 37A + 15B - 10C + 1D + 0 = 0 [ 1, 1, 1, 0, -5]] # 1A + 1B + 1C + 0D - 5 = 0 (0)x + (2)y + (3)z + (0) = 0 </syntaxhighlight> Equation of plane is: <math>2y + 3z = 0.</math> {{RoundBoxBottom}} ==Solving M by (M+1)== ===Implementation=== Below is python code containing function <code>solveMbyN (input).</code> The function accepts as input a 4 by 5 matrix (or greater) like that described in the code comments. This function is recursive, calling itself with M being reduced by 1 with each recursive invocation until the matrix is size 3 by 4 in which case function solve3by4() is called. <syntaxhighlight lang=python> # python code import decimal Decimal = decimal.Decimal getcontext = decimal.getcontext def reduceRow (row) : ''' This function calculates the max(abs) of all values in row, divides all values by the max(abs) and returns the result. [27, -15, 42] becomes [27/42, -15/42, 42/42]. Very small values are converted to zero. To invoke: output = reduceRow (row) output is list or None ''' if False in [ isinstance(v,Decimal) for v in row ] : print ('reduceRow: non Decimal in input.', { type(v) for v in row }) return None max = sorted([ abs(v) for v in row ])[-1] row = [ v/max for v in row ] almostZero = Decimal('1e-' + str( getcontext().prec )) row = [ (v, Decimal(0))[abs(v) < almostZero] for v in row ] return row enable_reduceRow = 0 def solveMbyN (input) : ''' input represents system: a0*w + b0*x + c0*y + d0*z + e0 = 0 a1*w + b1*x + c1*y + d1*z + e1 = 0 a2*w + b2*x + c2*y + d2*z + e2 = 0 a3*w + b3*x + c3*y + d3*z + e3 = 0 or greater. This solves a matrix of M rows by N columns where N = M+1 and M >= 2 input = [ (a0,b0,c0,d0,e0), (a1,b1,c1,d1,e1), (a2,b2,c2,d2,e2), (a3,b3,c3,d3,e3), ] To invoke: w,x,y,z = solveMbyN (input) Function solveMbyN () may return None. If input is size 15 by 16: v1,v2,v3, .... ,v14,v15 = solveMbyN (input) input is not changed by this function. ''' def solveMbyN_(input) : input = [ list(v) for v in input ] # input is now local, hard copy of original input. # This ensures that original input is not changed by this function. numberOfRows = len(input) numberOfColumns = numberOfRows+1 if numberOfRows < 2 : print ('solveMbyN()! len(input) < 2.') return None if numberOfRows == 2 : return solve2by3(input) if numberOfRows == 3 : return solve3by4(input) for row in range (0, numberOfRows) : if len(input[row]) != numberOfColumns : print ('solveMbyN()! row with bad length.') print (' row number',row,'of',numberOfRows,'rows has length',len(input[row]),'.') return None if True not in [ bool(v) for v in input[row][:-1] ] : print ('solveMbyN()! empty row in input, row number',row,'of',numberOfRows,'rows.') return None for column in range (0, numberOfRows) : sum = 0 for row in range (0, numberOfRows) : sum = bool(input[row][column]) if sum : break if not sum : print ('solveMbyN()! empty column in input. column number',column,'of',numberOfRows,'columns.') return None for column in (numberOfRows,) : sum = 0 for row in range (0, numberOfRows) : sum = bool(input[row][column]) if sum : break if not sum : # Empty column. Trivial solution is valid. return (0,) * numberOfRows if enable_reduceRow : # For matrices greater than 10 by 11 enable this piece of code. for row in range (0, numberOfRows) : data = reduceRow (input[row]) if isinstance(data,list) : input[row] = data # Arrange input if necessary so that a0 is non-zero. if not input[0][0] : for p in range (1, numberOfRows) : if input[p][0] : input[p], input[0] = input[0], input[p] break # The matrix is: # [a0,b0,c0,d0,e0], with a0 non-zero, # [a1,b1,c1,d1,e1], # [a2,b2,c2,d2,e2], # [a3,b3,c3,d3,e3], # Process rows so that a1, a2, a3, .... become zero. a0 = input[0][0] for p in range (1, numberOfRows) : ap = input[p][0] if ap : L0 = [ input[0][q]*ap for q in range (0, numberOfColumns) ] Lp = [ input[p][q]*a0 for q in range (0, numberOfColumns) ] L_ = [ L0[q]-Lp[q] for q in range (0, numberOfColumns) ] if L_[0] : # This should not happen. print ('solveMbyN()! internal error 1.') return None input[p] = L_ # The matrix is: # [a0, b0, c0, d0, e0], with a0 non-zero, # [ 0,b1_,c1_,d1_,e1_], # [ 0,b2_,c2_,d2_,e2_], # [ 0,b3_,c3_,d3_,e3_], data1 = [ input[p][1:] for p in range (1, numberOfRows) ] # data1 = [ # [b1_,c1_,d1_,e1_], # [b2_,c2_,d2_,e2_], # [b3_,c3_,d3_,e3_] ] data2 = solveMbyN(data1) # Here is where function solveMbyN() calls itself. if data2 == None : return None topRow = input[0][1:] # b0, c0, d0, e0 topRow # x, y, z data2 listOfProducts = [ topRow[p]*data2[p] for p in range (0, len(data2)) ] + topRow[-1:] # listOfProducts = [ b0*x, c0*y, d0*z, e0 ] sumOfProducts = [ sum for sum in (0,) for p in listOfProducts for sum in (sum+p,) ][-1] # sumOfProducts = [ b0*x, b0*x+c0*y, b0*x+c0*y+d0*z, b0*x+c0*y+d0*z+e0 ][-1] # sumOfProducts = b0*x + c0*y + d0*z + e0 # a0*w + b0*x + c0*y + d0*z + e0 = 0 # a0*w + sumOfProducts = 0 w = -sumOfProducts/a0 # Here is why a0 must be non-zero. return (w,) + data2 output = error = '' try : output = solveMbyN_(input) except : error = sys.exc_info()[:2] if (output == None) or error : if error : print ('solveMbyN()!') print (' error detected in processing.') print (' ', error) if len(input) >= 4 : print (' input of solveMbyN() with',len(input),'rows =') for row in input : print (' ', row) return None return output </syntaxhighlight> ===Examples=== Below are examples of invocation with both good data and bad data. Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> L1 = [ [Decimal('-870442133162'), Decimal('239132906684'), Decimal('397660499756'), Decimal('788825405004'), Decimal('156830886652'), Decimal('-87096140169')], [Decimal('-112130420352'), Decimal('-93605595828'), Decimal('-185262083472'), Decimal('-93369903383'), Decimal('-497973505065'), Decimal('-766710012513')], [Decimal('-142983492168'), Decimal('619713461197'), Decimal('-608752759383'), Decimal('-448477443042'), Decimal('-281161661751'), Decimal('-799463977245')], [Decimal('572854919541'), Decimal('-148673693908'), Decimal('341291756040'), Decimal('362403188059'), Decimal('-202136092949'), Decimal('-429932229578')], [Decimal('157632861972'), Decimal('330790263276'), Decimal('-836474627955'), Decimal('644295395386'), Decimal('-595590967129'), Decimal('-392835045727')] ] output = solveMbyN(L1) print (output) </syntaxhighlight> The following results were produced with decimal precision set at 50: <pre> ( Decimal('-0.06331410760212760088313271882866553044211194694576'), Decimal('1.0969089506763419155148060427588009931309074487534'), Decimal('1.0837038580207682607126722016017867670831200359767'), Decimal('-0.42989566124678842791674322699930461340596671792215'), Decimal('-2.0541601084281682582146753421426610779297051535362') ) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [-4, -6, 3, -4, -8, -8], [1, 0, 2, 5, 1, 7], [9, -3, -8, 4, 7, -5], [1, -9, 5, -2, 5, -2], [1, -3, -6, -3, -6, 6] ]) print (output) </syntaxhighlight> <pre> # With each step towards solve2by3() the length of each number in digits can theoretically double. solve2by3() : parallel input. input = (-181440, 181440, -101088) (90720, -90720, 406944) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [-756, -1176, 0, -1872] [-324, -744, 240, -936] [-324, -384, -120, -264] input of solveMbyN() with 4 rows = [-6, 11, 16, -4, 20] [-66, -5, -20, -44, -92] [-42, 23, -12, 12, -16] [-18, -21, -16, -32, 16] input of solveMbyN() with 5 rows = [-4, -6, 3, -4, -8, -8] [1, 0, 2, 5, 1, 7] [9, -3, -8, 4, 7, -5] [1, -9, 5, -2, 5, -2] [1, -3, -6, -3, -6, 6] None </pre> Provided that numbers are small, integers, floats and Decimal objects produce the same results: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [-4.0, -6.0, 3.0, -4.0, -8.0, -8.0], [1.0, 0.0, 2.0, 5.0, 1.0, 7.0], [9.0, -3.0, -8.0, 4.0, 7.0, -5.0], [1.0, -9.0, 5.0, -2.0, 5.0, -2.0], [1.0, -3.0, -6.0, -3.0, -6.0, 6.0] ]) print (output) </syntaxhighlight> <pre> solve2by3() : parallel input. input = (-181440.0, 181440.0, -101088.0) (90720.0, -90720.0, 406944.0) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [-756.0, -1176.0, 0.0, -1872.0] [-324.0, -744.0, 240.0, -936.0] [-324.0, -384.0, -120.0, -264.0] input of solveMbyN() with 4 rows = [-6.0, 11.0, 16.0, -4.0, 20.0] [-66.0, -5.0, -20.0, -44.0, -92.0] [-42.0, 23.0, -12.0, 12.0, -16.0] [-18.0, -21.0, -16.0, -32.0, 16.0] input of solveMbyN() with 5 rows = [-4.0, -6.0, 3.0, -4.0, -8.0, -8.0] [1.0, 0.0, 2.0, 5.0, 1.0, 7.0] [9.0, -3.0, -8.0, 4.0, 7.0, -5.0] [1.0, -9.0, 5.0, -2.0, 5.0, -2.0] [1.0, -3.0, -6.0, -3.0, -6.0, 6.0] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [Decimal('-4'), Decimal('-6'), Decimal('3'), Decimal('-4'), Decimal('-8'), Decimal('-8')], [Decimal('1'), Decimal('0'), Decimal('2'), Decimal('5'), Decimal('1'), Decimal('7')], [Decimal('9'), Decimal('-3'), Decimal('-8'), Decimal('4'), Decimal('7'), Decimal('-5')], [Decimal('1'), Decimal('-9'), Decimal('5'), Decimal('-2'), Decimal('5'), Decimal('-2')], [Decimal('1'), Decimal('-3'), Decimal('-6'), Decimal('-3'), Decimal('-6'), Decimal('6')] ]) print (output) </syntaxhighlight> <pre> solve2by3() : parallel input. input = (Decimal('-181440'), Decimal('181440'), Decimal('-101088')) (Decimal('90720'), Decimal('-90720'), Decimal('406944')) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [Decimal('-756'), Decimal('-1176'), Decimal('0'), Decimal('-1872')] [Decimal('-324'), Decimal('-744'), Decimal('240'), Decimal('-936')] [Decimal('-324'), Decimal('-384'), Decimal('-120'), Decimal('-264')] input of solveMbyN() with 4 rows = [Decimal('-6'), Decimal('11'), Decimal('16'), Decimal('-4'), Decimal('20')] [Decimal('-66'), Decimal('-5'), Decimal('-20'), Decimal('-44'), Decimal('-92')] [Decimal('-42'), Decimal('23'), Decimal('-12'), Decimal('12'), Decimal('-16')] [Decimal('-18'), Decimal('-21'), Decimal('-16'), Decimal('-32'), Decimal('16')] input of solveMbyN() with 5 rows = [Decimal('-4'), Decimal('-6'), Decimal('3'), Decimal('-4'), Decimal('-8'), Decimal('-8')] [Decimal('1'), Decimal('0'), Decimal('2'), Decimal('5'), Decimal('1'), Decimal('7')] [Decimal('9'), Decimal('-3'), Decimal('-8'), Decimal('4'), Decimal('7'), Decimal('-5')] [Decimal('1'), Decimal('-9'), Decimal('5'), Decimal('-2'), Decimal('5'), Decimal('-2')] [Decimal('1'), Decimal('-3'), Decimal('-6'), Decimal('-3'), Decimal('-6'), Decimal('6')] None </pre> {{RoundBoxBottom}} {{RoundBoxBottom}} ===Sphere=== In cartesian coordinate geometry of three dimensions a sphere is represented by equation: <math>x^2 + y^2 + z^2 + Ax + By + Cz + D = 0.</math> On the surface of a certain sphere there are 4 known points: <syntaxhighlight lang=python> # python code point1 = (13,7,20) point2 = (13,7,4) point3 = (13,-17,4) point4 = (16,4,4) </syntaxhighlight> What is equation of sphere? Rearrange equation of sphere to prepare for creation of input matrix: <math>(x)A + (y)B + (z)C + (1)D + (x^2 + y^2 + z^2) = 0.</math> Create input matrix of size 4 by 5: <syntaxhighlight lang=python> # python code input = [] for (x,y,z) in (point1, point2, point3, point4) : input += [ ( x, y, z, 1, (x**2 + y**2 + z**2) ) ] print (input) </syntaxhighlight> <syntaxhighlight> [ (13, 7, 20, 1, 618), (13, 7, 4, 1, 234), (13, -17, 4, 1, 474), (16, 4, 4, 1, 288), ] # Matrix containing 4 rows with 5 members per row. </syntaxhighlight> <syntaxhighlight lang=python> # python code result = solveMbyN(input) print (result) </syntaxhighlight> <syntaxhighlight> (-8.0, 10.0, -24.0, -104.0) </syntaxhighlight> Equation of sphere is : <math>x^2 + y^2 + z^2 - 8x + 10y - 24z - 104 = 0</math> ===Quintic function=== [[File:1212quintic01.png|thumb|400px|''' Figure 4. Graph of quintic function defined by 6 points.''' ]] A quintic function <math>y = f(x) = Ax^5 + Bx^4 + Cx^3 + Dx^2 + Ex + F</math> is defined by 6 points: <math>(-8, 0), (-6, 0), (-3, 0), (1,0), (3,0), (5,10).</math> What is <math>f(x)?</math> <math>y = f(x) = Ax^5 + Bx^4 + Cx^3 + Dx^2 + Ex + F</math> <math>A, B, C, D, E, F</math> are 6 unknowns. <math>x^5(A) + x^4(B) + x^3(C) + x^2(D) + x(E) + 1(F) - y = 0</math> <syntaxhighlight lang=python> # python code: pt1 = x1,y1 = -8,0 pt2 = x2,y2 = -6,0 pt3 = x3,y3 = -3,0 pt4 = x4,y4 = 1,0 pt5 = x4,y5 = 3,0 pt6 = x6,y6 = 5,10 input = [] for pt in (pt1,pt2,pt3,pt4,pt5,pt6) : x,y = pt input += [[ x**5, x**4, x**3, x**2, x, 1, -y ]] print (input) </syntaxhighlight> <syntaxhighlight> [[-32768, 4096, -512, 64, -8, 1, 0], [ -7776, 1296, -216, 36, -6, 1, 0], [ -243, 81, -27, 9, -3, 1, 0], [ 1, 1, 1, 1, 1, 1, 0], [ 243, 81, 27, 9, 3, 1, 0], [ 3125, 625, 125, 25, 5, 1, -10]] </syntaxhighlight> <syntaxhighlight> result = solveMbyN (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> result (0.0010926573426573423, 0.014204545454545447, 0.027316433566433533, -0.18028846153846156, -0.3343531468531468, 0.47202797202797203) </syntaxhighlight> From these results the following ratios may be deduced: <math>\frac{1}{A} = 915.2;\ </math> <math>\frac{B}{A} = 13;\ </math> <math>\frac{C}{A} = 25;\ </math> <math>\frac{D}{A} = -165;\ </math> <math>\frac{E}{A} = -306;\ </math> <math>\frac{F}{A} = 432.</math> <math>y = f(x) = \frac{x^5 + 13x^4 + 25x^3 - 165x^2 - 306x + 432}{915.2}</math> ===Resistive network=== {{RoundBoxTop|theme=2}} [[File:1127network01.png|thumb|400px|''' Figure 1. Diagram of resistive network containing 8 resistors.''' ]] A resistive network containing 8 resistors is connected as shown in Figure 1. What is resistance <math>R</math> between points <math>P_1, P_3?</math> {{RoundBoxBottom}} ====Solve for 8 Branch Currents==== {{RoundBoxTop|theme=2}} [[File:1127network02.png|thumb|400px|''' Figure 2. Diagram of resistive network showing all branch currents.''' </br> </br> At any point to which 3 or more conductors are connected, sum of currents = 0. </br> At point <math>P_4</math> currents <math>i_1, i_7</math> flow towards point; current <math>i_4</math> flows away from point. </br> <math>i_1 + i_7 - i_4 = 0.</math> </br> </br> In any closed loop sum of voltages = 0. </br> In loop containing points <math>P_1, P_2</math> voltages <math>e_2, e_8</math> are clockwise; voltage <math>e_3</math> is counter-clockwise. <math></math> </br> <math>e_2 + e_8 - e_3 = 0.</math><math></math><math></math> </br> </br> Direction of flow through <math>r_7, r_8</math> is assumed and is subject to correction. ]] Voltage across <math>r_1:</math> Using <math>E = IR,\ e_1 = i_1\cdot r_1 = r_1\cdot a.</math> Similarly: <math>e_2 = r_2\cdot b.</math> <math>e_3 = r_3\cdot c.</math> <math>\dots\dots</math> <math>e_8 = r_8\cdot h.</math> Build a matrix size 8 by 9 which will be input to function solveMbyN(). <syntaxhighlight lang=python> # Python code: r1,r2,r3,r4,r5,r6,r7,r8 = 10,20,30,40,50,60,70,80 input = [] # e1 = e2 + e7 # 10a = 20b + 70g # 10a - 20b + 0c + 0d + 0e + 0f - 70g + 0h + 0 = 0 input += [[r1, - r2, 0, 0, 0, 0, - r7, 0, 0]] # e3 = e2 + e8 # 30c = 20b + 80h # 0a - 20b + 30c + 0d + 0e + 0f + 0g - 80h + 0 = 0 input += [[0, - r2, r3, 0, 0, 0, 0, - r8, 0]] # e5 = e7 + e4 # 50e = 70g + 40d # 0a + 0b + 0c - 40d + 50e + 0f - 70g + 0h + 0 = 0 input += [[0, 0, 0, - r4, r5, 0, - r7, 0, 0]] # e5 = e8 + e6 # 50e = 80h + 60f # 0a + 0b + 0c + 0d + 50e - 60f + 0g - 80h + 0 = 0 input += [[0, 0, 0, 0, r5, - r6, 0, - r8, 0]] # i7 + i5 + i8 = i2 # g + e + h = b # 0a - 1b + 0c + 0d + 1e + 0f + 1g + 1h + 0 = 0 input += [[0 ,- 1, 0, 0, 1, 0, 1, 1, 0]] # i4 = i1 + i7 # d = a + g # -1a + 0b + 0c + 1d + 0e + 0f - 1g + 0h + 0 = 0 input += [[-1, 0, 0, 1, 0, 0, - 1, 0, 0]] # i6 = i3 + i8 # f = c + h # 0a + 0b - 1c + 0d + 0e + 1f + 0g - 1h + 0 = 0 input += [[0, 0, - 1, 0, 0, 1, 0, - 1, 0]] # Total input current = 1 # a + b + c = 1 # 1a + 1b + 1c + 0d + 0e + 0f + 0g + 0h - 1 = 0 input += [[1, 1, 1, 0, 0, 0, 0, 0, - 1]] </syntaxhighlight> This last entry can contain almost any arbitrary values. For example: <syntaxhighlight lang=python> # Python code: # i7 = 2.3 input += [[0, 0, 0, 0, 0, 0, 1, 0, - 2.3]] # e5 = 1.9 input += [[0, 0, 0, 0, r5, 0, 0, 0, - 1.9]] </syntaxhighlight> Changing this last entry changes all values of <math>e_x, i_x.</math> However, the ratio <math>\frac{e_x}{i_x} = r_x</math> remains constant. {{RoundBoxTop|theme=3}} input is matrix of size 8 by 9: <syntaxhighlight> [ [10, -20, 0, 0, 0, 0, -70, 0, 0], # e1 = e2 + e7, or r1(i1) - r2(i2) - r7(i7) = 0 [ 0, -20, 30, 0, 0, 0, 0, -80, 0], # e3 = e2 + e8, or r3(i3) - r2(i2) - r8(i8) = 0 [ 0, 0, 0, -40, 50, 0, -70, 0, 0], # e5 = e4 + e7, or r5(i5) - r4(i4) - r7(i7) = 0 [ 0, 0, 0, 0, 50, -60, 0, -80, 0], # e5 = e6 + e8, or r5(i5) - r6(i6) - r8(i8) = 0 [ 0, -1, 0, 0, 1, 0, 1, 1, 0], # i2 = i5 + i7 + i8, or 1(i5) + 1(i7) + 1(i8) - 1(i2) = 0 [-1, 0, 0, 1, 0, 0, -1, 0, 0], # i4 = i1 + i7, or 1(i4) - 1(i1) - 1(i7) = 0 [ 0, 0, -1, 0, 0, 1, 0, -1, 0], # i6 = i3 + i8, or 1(i6) - 1(i3) - 1(i8) = 0 [ 1, 1, 1, 0, 0, 0, 0, 0, -1] # i1 + i2 + i3 = 1, or 1(i1) + 1(i2) + 1(i3) - 1 = 0 ] </syntaxhighlight> {{RoundBoxBottom}} <syntaxhighlight lang=python> i1,i2,i3,i4,i5,i6,i7,i8 = values_of_i = solveMbyN (input) s1 = 'values_of_i' ; print(s1,eval(s1)) s1 = 'i1 + i2 + i3' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> values_of_i (0.45727389222364606, 0.3065353746543468, 0.23619073312200717, 0.4350171983543536, 0.31685438726647336, 0.24812841437917316, -0.022256693869292507, 0.011937681257165982) i1 + i2 + i3 1.0 </syntaxhighlight> <math>i_7</math> has negative value. Reverse <math>i_7</math> to make all branch currents positive. {{RoundBoxBottom}} ====Make all Branch Currents positive==== {{RoundBoxTop|theme=2}} [[File:1127network03.png|thumb|400px|''' Figure 3. Diagram of resistive network showing all branch currents positive.''' ]] Make <math>i_7</math> positive and check results. <syntaxhighlight lang=python> # Python code i7 *= -1 values_of_e = e1,e2,e3,e4,e5,e6,e7,e8 = [ eval(s1) for s in '12345678' for s1 in [ 'i' + s + '*r' + s ] ] s1 = 'values_of_e' print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> values_of_e [ 4.572738922236461, 6.130707493086937, 7.085721993660215, 17.400687934174144, 15.842719363323669, 14.88770486275039, 1.5579685708504756, 0.9550145005732785] </syntaxhighlight> <syntaxhighlight lang=python> # python code t1 = ( 'e1+e7-e2', # e1 + e7 should equal e2 'e2+e8-e3', # e2 + e8 should equal e3 'e7+e5-e4', # e7 + e5 should equal e4 'e8+e6-e5', # e8 + e6 should equal e5 'e1+e4-(e2+e5)', # e1 + e4 should equal e2 + e5 'e1+e4-(e3+e6)', # e1 + e4 should equal e3 + e6 'e1+e7+e8-e3', # e1 + e7 + e8 should equal e3 'e7+e8+e6-e4', # e7 + e8 + e6 should equal e4 'i1-i7-i4', # i1 should equal i7 + i4 'i6-i3-i8', # i6 should equal i3 + i8 'i2+i7-(i8+i5)', # i2 + i7 should equal i8 + i5 'i1+i2+i3 - (i4+i5+i6)', # Total input current should # equal total output current. ) for s1 in t1 : print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> e1+e7-e2 -8.881784197001252e-16 e2+e8-e3 0.0 e7+e5-e4 0.0 e8+e6-e5 0.0 e1+e4-(e2+e5) 0.0 e1+e4-(e3+e6) 0.0 e1+e7+e8-e3 -8.881784197001252e-16 e7+e8+e6-e4 0.0 i1-i7-i4 -5.551115123125783e-17 i6-i3-i8 6.938893903907228e-18 i2+i7-(i8+i5) 0.0 i1+i2+i3 - (i4+i5+i6) 0.0 </syntaxhighlight> {{RoundBoxBottom}} ====Compute R==== {{RoundBoxTop|theme=8}} <syntaxhighlight lang=python> # Python code E1 = e3+e6 I1 = i1 + i2 + i3 R1 = E1/I1 s1 = 'R1' ; print(s1,eval(s1)) E2 = e1 + e7 + e5 I2 = i4 + i5 + i6 R2 = E2/I2 s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 21.973426856410605 R2 21.973426856410605 </syntaxhighlight> <math>R = R_1 = R_2</math> {{RoundBoxBottom}} ==Solving big matrices== A big matrix is one of size greater than 10 by 11. With each recursive call of solveMbyN() the size of each value in decimal digits can theoretically double. Python's integer math enjoys infinite precision. If your original matrix is of size 32 by 33, and each value in the matrix is an int of 1 decimal digit, function solve2by3() can be called with ints of size 2**30 (1,073,741,824) decimal digits. Floats can be used instead of ints, but the limited precision of floats may not provide a desirable level of accuracy in the result. Python's decimal objects are a good compromise and function reduceRow() above is an attempt to keep the size of each member manageable. Function reduceRow() works well. However, as with all operations involving python's decimal objects, you need to pay careful attention to precision and accuracy of the results. On my Mac the following python code generates a matrix of size 100 by 101 and calculates the result containing 100 values in about 1.5 seconds, including the time to generate 10,100 random numbers, each containing up to 12 decimal digits with the decimal point in a random position, and including the time to test output over 100 rows to verify that all calculated values of the solution satisfy each row. In function solveMbyN() above find line: <syntaxhighlight lang=python> if 0 : # For matrices greater than 10 by 11 enable this piece of code. </syntaxhighlight> Change it to: <syntaxhighlight lang=python> if 1 : # For matrices greater than 10 by 11 enable this piece of code. </syntaxhighlight> Then: <syntaxhighlight lang=python> from random import getrandbits from decimal import * import sys getcontext().prec=50 # Set precision to 50. numRows=100 def randomNumber(): # 1 invocation in 256 returns 0. if not (getrandbits(10) & 0xFF) : return Decimal(0) return [ w for q in [ getrandbits(10) & 1] for sign in [ (-1,1)[q] ] for numberOfDecimalPlaces in [ getrandbits(10) & 0xF ] for s1 in [ str(getrandbits(50))[-12:] ] for s2 in [ '0'*12+s1 ] for posn in [ len(s2)-numberOfDecimalPlaces ] for w in [ sign*Decimal(s2[:posn]+'.'+s2[posn:]) ] ][0] data = [[ randomNumber() for p in range(numRows+1) ] for p in range (numRows) ] datan = sorted([ v for row in data for v in row if v < 0 ]) datap = sorted([ v for row in data for v in row if v >= 0 ]) print ('A small sample of the random numbers in data:') print ('+ve values:',len(datap), ',', datap[:2],'\n ',datap[-2:]) print ('-ve values:',len(datan), ',', datan[:2],'\n ',datan[-2:]) output = solveMbyN(data) print ('A small sample of the solutions:') print ('output[0] =', output[0]) print ('output[19] =', output[19]) print ('output[59] =', output[59]) print ('output[99] =', output[99]) </syntaxhighlight> <pre> A small sample of the random numbers in data: +ve values: 5021 , [Decimal('1.16871265E-7'), Decimal('1.73721245E-7')] [Decimal('998523464710'), Decimal('999768605679')] -ve values: 5079 , [Decimal('-991079944209'), Decimal('-989786083110')] [Decimal('-4.10272824E-7'), Decimal('-2.38664537E-7')] A small sample of the solutions: output[0] = 0.43689400018920695253771832432651757885163362928745 output[19] = 0.19867480862268284151047885891372314311902973127033 output[59] = 0.46169681824826309421940885550155275946668017604646 output[99] = -0.020598220802233733529683040085023443421113627790464 </pre> ===Testing results=== Data input to function solveMbyN() is an array of 100 rows, each row containing 101 numbers. <pre> [ [v0_0, v0_1, v0_2, ..... v0_98,v0_99,v0_100], ....... [v99_0,v99_1,v99_2, ...... v99_98,v99_99,v99_100],] ] </pre> Data received from function solveMbyN() is an array of 100 numbers. <pre> [ s0,s1,s2, ...... s98,s99 ] </pre> The first row is tested with the solutions by; <pre> L2 = [ v0_0*s0, v0_1*s1, v0_2*s2, ..... v0_98*s98,v0_99*s99,v0_100 ] </pre> sum is the sum of all items in L2. sum is appended to L1 and the process is repeated for all 100 rows. <syntaxhighlight lang=python> L1 = [] for row in data : # a, b, c, d, e, f, g ....... # row # u, v, w, x, y, z # output L2 = [ row[p]*t1[p] for t1 in (output+(1,),) for p in range (0, len(row)) ] # L2 = [a*u , b*v , c*w , d*x , e*y , f*z , g] sum = [ sum for sum in [0] for p in L2 for sum in [sum+p] ][-1] # sum = [a*u, a*u + b*v, a*u + b*v + c*w, a*u + b*v + c*w + d*x, a*u + b*v + c*w + d*x + e*y, # a*u + b*v + c*w + d*x + e*y + f*z, a*u + b*v + c*w + d*x + e*y + f*z + g][-1] # sum = a*u + b*v + c*w + d*x + e*y + f*z + g # sum is the sum of all items in L2 L1 += [abs(sum)] L1a = sorted(L1) print (len(L1a), L1a[0], L1a[-1]) </syntaxhighlight> Ideally sum should be zero. In practice it's extremely unlikely that sum will be zero. My results typically gave values close to <pre> 100 4.1065149609E-38 9.6425614873452398368906E-25 </pre> The worst of the results above was 23 zeroes after the decimal point. Better results can be achieved by increasing precision. ===Cubic Resistive Network=== {{RoundBoxTop|theme=2}} [[File:1129network01.png|thumb|400px|''' Figure 1. Diagram of resistive network containing 12 resistors.''' </br> Blue arrows show assumed direction of current. ]] A resistive network containing 12 resistors is connected as shown in Figure 1. The network is called "cubic" because, in 3 dimensions, each resistor is located on one edge of a cube. What is resistance <math>R</math> between points <math>P_1, P_2?</math> <syntaxhighlight lang=python> # Python code: values_of_r = r1,r2,r3,r4,r5,r6,r7,r8,r9,r10,r11,r12 = 10,20,30,40,50,60,70,80,90,100,110,120 </syntaxhighlight> {{RoundBoxBottom}} ====Solve for 12 Branch Currents==== =====Create matrix 12 by 13===== <syntaxhighlight lang=python> # Python code: input = [ [10, 20, -30, -40, 0, 0, 0, 0, 0, 0, 0, 0, 0], # e1 + e2 = e3 + e4 [ 0, 0, 0, 0, 50, 60, -70, -80, 0, 0, 0, 0, 0], # e5 + e6 = e7 + e8 [ 0, 0, 0, 40, 0, 0, 0, -80, 0, 0, 110, -120, 0], # e11 + e4 = e8 + e12 [10, 0, 0, 0, -50, 0, 0, 0, 90, -100, 0, 0, 0], # e9 + e1 = e5 + e10 [ 0, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0], # i5 = i10 + i6 [ 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, 0, 0], # i7 = i11 + i8 [-1, 0, -1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # i9 = i1 + i3 [ 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0], # i4 = i3 + i11 [-1, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0], # i2 = i1 + i10 [ 0, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 1, 0], # i12 = i6 + i8 [ 0, -1, 0, -1, 1, 0, 1, 0, 1, 0, 0, -1, 0], # i9 + i5 + i7 = i2 + i4 + i12 [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1.6] # i3 = 1.6 ] i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12 = values_of_i = solveMbyN (input) s1 = 'values_of_i' print(s1,eval(s1)) </syntaxhighlight> This matrix failed: <syntaxhighlight> solve2by3() : empty row in input. input = (0, 0, 0) (90533116137774317568000000000000000000000000000000000000000000, -84449318308603494400000000000000000000000000000000000000000000, 1.4228848407261846e+61) checkDirectionNumbers() : 2 rows parallel, 1 and 2. input of solve3by4() = [38760268800000000000000000000, 593753233920000000000000000000, -569385344000000000000000000000, 0] [620164300800000000000000000000000000, 9500051742720000000000000000000000000, -9110165504000000000000000000000000000, 0] [153839206400000000000000000000000, 20882470400000000000000000000000, -81126144000000000000000000000000, -3.67098806272e+32] </syntaxhighlight> =====Try again===== <syntaxhighlight lang=python> # Python code: input = [ [10, 20, -30, -40, 0, 0, 0, 0, 0, 0, 0, 0, 0], # e1 + e2 = e3 + e4 [ 0, 0, 0, 0, 50, 60, -70, -80, 0, 0, 0, 0, 0], # e5 + e6 = e7 + e8 [ 0, 0, 0, 40, 0, 0, 0, -80, 0, 0, 110, -120, 0], # e11 + e4 = e8 + e12 [10, 0, 0, 0, -50, 0, 0, 0, 90, -100, 0, 0, 0], # e9 + e1 = e5 + e10 [ 0, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0], # i5 = i10 + i6 [ 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, 0, 0], # i7 = i11 + i8 [-1, 0, -1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # i9 = i1 + i3 [ 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0], # i4 = i3 + i11 [-1, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0], # i2 = i1 + i10 [ 0, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 1, 0], # i12 = i6 + i8 #[ 0, -1, 0, -1, 1, 0, 1, 0, 1, 0, 0, -1, 0], # i9 + i5 + i7 = i2 + i4 + i12 DELETED. [10, 20, 0, 0, 0, 0, -70, -80, 90, 0, 0, -120, 0], # e9 + e1 + e2 = e7 + e8 + e12 ADDED. [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1.6] # i3 = 1.6 ] import decimal dD = decimal.Decimal dgt = decimal.getcontext() Precision = dgt.prec = 30 Tolerance = dD("1e-" + str(Precision-2)) # Convert all values in input to decimal objects with precision of 30. input = [ [ dD(str(p)) for p in v ] for v in input ] i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12 = values_of_i = solveMbyN (input) </syntaxhighlight> <syntaxhighlight> # values_of_i 5.5027171492204899777282850777 9.3809275973899113038721525414 1.5999999999999999999999999999 # i3 should be 1.6. 4.8661430860000781463681475402 6.12901340210213730316883522816 2.25080295393271597702496776458 4.68526862814050716992927753670 1.41912554214042902356112999643 7.10271714922048997772828507766 3.87821044816942132614386746358 3.26614308600007814636814754027 3.66992849607314500058609776103 </syntaxhighlight> ====Compute R==== {{RoundBoxTop|theme=8}} <syntaxhighlight lang=python> # python code values_of_e = e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12 = [ (i*r) for (i,r) in zip(values_of_i, values_of_r) ] </syntaxhighlight> <syntaxhighlight> values_of_e 55.0271714922048997772828507770 187.618551947798226077443050828 47.9999999999999999999999999970 194.645723440003125854725901608 306.450670105106865158441761408 135.048177235962958621498065875 327.968803969835501895049427569 113.530043371234321884890399714 639.244543429844097995545656989 387.821044816942132614386746358 359.275739460008596100496229430 440.391419528777400070331731324 </syntaxhighlight> <math>e_3</math> should be <math>48,\ i_3*r_3</math> or <math>1.6*30.</math> <syntaxhighlight lang=python> E1 = e5 + e10 + e2 I1 = i9 + i5 + i7 R1 = E1/I1 s1 = 'R1' ; print(s1,eval(s1)) E2 = e7 + e8 - e6 + e10 - e1 + e3 + e4 I2 = i2 + i4 + i12 R2 = E2/I2 s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 49.2208688540148837936367036806 R2 49.2208688540148837936367036803 </syntaxhighlight> Display results with precision of 28: <syntaxhighlight lang=python> dgt.prec = 28 R1 += 0 ; R2 += 0 dgt.prec = Precision s1 = 'R1' ; print(s1,eval(s1)) s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 49.22086885401488379363670368 R2 49.22086885401488379363670368 </syntaxhighlight> <math>R = R_1 = R_2.</math> {{RoundBoxBottom}} ====Review==== In matrix all values <math>i_1, i_2, \dots, i_{11}, i_{12}</math> and <math>e_1, e_2, \dots, e_{11}, e_{12}</math> are included. Testing was done with the following lines substituted for last line of matrix: <syntaxhighlight lang=python> # python code [ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, -3.15] # i7 = 3.15 [ 0, 0, 0, r4, 0, 0, 0, 0, 0, 0, 0, 0, -6 ] # e4 = 6 [ 0, 0, r3, 0, 0, 0, 0, r8, 0, 0, 0, 0, -5 ] # e3 + e8 = 5 </syntaxhighlight> All tests produced a consistent value of <math>R.</math> ====Checking==== =====Examples of current nodes===== {{RoundBoxTop|theme=2}} <gallery> File:0101network01.png|<small><math>i_1 + i_{10} = i_2</math></small> File:0101network02.png|<small><math>i_6 + i_8 = i_{12}</math></small> </gallery> {{RoundBoxBottom}} =====Examples of voltage loops===== {{RoundBoxTop|theme=2}} <gallery> File:0108network00.png|<small>Top and Bottom.<math>e_1 + e_2 - e_4 - e_3 = 0</math><math>e_5 + e_6 - e_8 - e_7 = 0</math></small> File:0108network01.png|<small>Two sides in background.<math>e_5 + e_{10} - e_1 - e_9 = 0</math><math>e_6 + e_{12} - e_2 - e_{10} = 0</math></small> File:0108network02.png|<small>Two sides in foreground.<math>e_7 + e_{11} - e_3 - e_9 = 0</math><math>e_8 + e_{12} - e_4 - e_{11} = 0</math></small> </gallery> {{RoundBoxBottom}} =====Python code===== <syntaxhighlight lang=python> t1 = ( # 3 nodes on top 'i1 + i10 - i2', 'i1 + i3 - i9', 'i3 + i11 - i4', # 3 nodes on bottom 'i10 + i6 - i5', 'i11 + i8 - i7', 'i6 + i8 - i12', # Total input current equals total output current. 'i5 + i7 + i9 - i2 - i4 - i12', # Voltage loops # top 'e1 + e2 - e4 - e3', # bottom 'e5 + e6 - e8 - e7', # 2 sides in background 'e9 + e1 - e10 - e5', 'e10 + e2 - e12 - e6', # 2 sides in foreground 'e9 + e3 - e11 - e7', 'e11 + e4 - e12 - e8', # Some elaborate loops. 'e8 - e6 + e10 + e2 - e4 - e3 - e9 + e7', 'e10 + e2 - e12 - e8 + e11 - e3 - e9 + e5', ) </syntaxhighlight> Result of each of the above calculations should be <math>0.</math> Because of small rounding errors, result may not be exactly <math>0.</math> See values_of_i and values_of_e above. This code verifies that result is close enough to <math>0</math> to be acceptable. For example: <math>\text{result} = e_{10} + e_2 - e_{12} - e_8 + e_{11} - e_3 - e_9 + e_5.</math> <math>\text{v1} = e_{10} + e_2 + e_{11} + e_5,</math> sum of positive values. <math>\text{status = (abs(result)} < \text{(v1}*\text{Tolerance)). status}</math> should be <math>\text{True.}</math> <syntaxhighlight lang=python> # python code import re for str1 in t1 : str2 = re.sub ('\+', ';+', str1) str2 = re.sub ('\-', ';-', str2) L1 = str2.split(';') positives = ''.join([ v for v in L1 if '-' not in v ]) result = eval(str1) v1 = eval( positives ) status = (abs(result) < (v1*Tolerance)) str3 = (str1+(' '*40))[:42] str4 = ((' '*10) + str(result))[-10:] str5 = '{}{} {}'.format(str3,str4,status) print ( str5 ) </syntaxhighlight> {| class="wikitable" |- ! Calculation || Result !! Result Acceptable |- | <math> i_1 + i_{10} - i_2 </math> | <math> -1.2E-28 </math> | <math>\text{True}</math> |- | <math> i_1 + i_3 - i_9 </math> | <math> -6E-29 </math> | <math>\text{True}</math> |- | <math> i_3 + i_{11} - i_4 </math> | <math> -3E-29 </math> | <math>\text{True}</math> |- | <math> i_{10} + i_6 - i_5 </math> | <math> 0E-29 </math> | <math>\text{True}</math> |- | <math> i_{11} + i_8 - i_7 </math> | <math> 0E-29 </math> | <math>\text{True}</math> |- | <math> i_6 + i_8 - i_{12} </math> | <math> -2E-29 </math> | <math>\text{True}</math> |- | <math> i_5 + i_7 + i_9 - i_2 - i_4 - i_{12} </math> | <math> -3E-29 </math> | <math>\text{True}</math> |- | <math> e_1 + e_2 - e_4 - e_3 </math> | <math> 0E-28 </math> | <math>\text{True}</math> |- | <math> e_5 + e_6 - e_8 - e_7 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_9 + e_1 - e_{10} - e_5 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_{10} + e_2 - e_{12} - e_6 </math> | <math> -1.3E-26 </math> | <math>\text{True}</math> |- | <math> e_9 + e_3 - e_{11} - e_7 </math> | <math> -1.3E-26 </math> | <math>\text{True}</math> |- | <math> e_{11} + e_4 - e_{12} - e_8 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_8 - e_6 + e_{10} + e_2 - e_4 - e_3 - e_9 + e_7 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_{10} + e_2 - e_{12} - e_8 + e_{11} - e_3 - e_9 + e_5 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |} ===Big Matrix 64 by 65=== {{RoundBoxTop|theme=2}} [[File:0706matrix64_01.png|thumb|400px|'''Diagram of resistive network containing 64 resistors.''' </br> Positive current flow is assumed to be from bottom to top or from left to right. ]] A network containing 64 resistors is connected as shown in diagram. What is resistance R between points P1, P2? <syntaxhighlight lang=python> # python code values_of_R = ( R10, R11, R12, R13, R14, R15, R16, R17, R18, R19, R20, R21, R22, R23, R24, R25, R26, R27, R28, R29, R30, R31, R32, R33, R34, R35, R36, R37, R38, R39, R40, R41, R42, R43, R44, R45, R46, R47, R48, R49, R50, R51, R52, R53, R54, R55, R56, R57, R58, R59, R60, R61, R62, R63, R64, R65, R66, R67, R68, R69, R70, R71, R72, R73, ) = [ v for v in range (100,731,10) ] </syntaxhighlight> While this resistive circuit may be very theoretical, it lends itself well to the creation of a big matrix, 64 by 65, meaning that there are 64 resistors and 64 simultaneous equations to be solved. {{RoundBoxBottom}} ====Create matrix==== An examination of the circuit produces the following conditions: <syntaxhighlight lang=python> # python code iconditions = [ "+ i10 + i70 - i44" , "+ i11 - i10 - i49" , "+ i12 - i11 - i54", "+ i13 - i12 - i59" , "+ i14 - i13 - i64" , "+ i15 + i44 - i43", "+ i16 + i49 - i15 - i48 - i70" , "+ i17 + i54 - i16 - i53" , "+ i18 + i59 - i17 - i58", "+ i19 + i64 + i71 - i18 - i63" , "+ i69 - i19 - i68" , "+ i20 + i43 - i42", "+ i21 + i48 - i20 - i47" , "+ i22 + i53 - i21 - i52" , "+ i23 + i58 - i22 - i57", "+ i24 + i63 - i23 - i62" , "+ i68 - i24 - i67" , "+ i25 + i42 - i41", "+ i26 + i47 - i25 - i46" , "+ i27 + i52 - i26 - i51" , "+ i28 + i57 - i27 - i56", "+ i29 + i62 - i28 - i61" , "+ i67 - i29 - i66" , "+ i30 + i41 - i40", "+ i31 + i46 - i30 - i45 - i72" , "+ i32 + i51 - i31 - i50" , "+ i33 + i56 - i32 - i55", "+ i34 + i61 + i73 - i33 - i60" , "+ i66 - i34 - i65" , "+ i36 + i45 - i35", "+ i37 + i50 - i36" , "+ i38 + i55 - i37" , "+ i39 + i60 - i38", "+ i65 - i39 - i73" ] sx = 'len(iconditions)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(iconditions) = 34 </syntaxhighlight> <syntaxhighlight lang=python> econditions = [ "+ e40 + e30 - e35 - e45" , "+ e41 + e25 - e30 - e46" , "+ e42 + e20 - e25 - e47", "+ e43 + e15 - e20 - e48" , "+ e44 + e10 - e15 - e49" , "+ e45 + e31 - e36 - e50", "+ e46 + e26 - e31 - e51" , "+ e47 + e21 - e26 - e52" , "+ e48 + e16 - e21 - e53", "+ e49 + e11 - e16 - e54" , "+ e50 + e32 - e37 - e55" , "+ e51 + e27 - e32 - e56", "+ e52 + e22 - e27 - e57" , "+ e53 + e17 - e22 - e58" , "+ e54 + e12 - e17 - e59", "+ e55 + e33 - e38 - e60" , "+ e56 + e28 - e33 - e61" , "+ e57 + e23 - e28 - e62", "+ e58 + e18 - e23 - e63" , "+ e59 + e13 - e18 - e64" , "+ e60 + e34 - e39 - e65", "+ e61 + e29 - e34 - e66" , "+ e62 + e24 - e29 - e67" , "+ e63 + e19 - e24 - e68", "+ e64 + e14 - e19 - e69" , "+ e44 + e70 - e15" , "+ e64 + e14 - e71", "+ e40 + e30 - e72" , "+ e60 + e73 - e39" ] sx = 'len(econditions)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(econditions) = 29 </syntaxhighlight> In iconditions and econditions there are 63 conditions that include all values of i and e. These 63 conditions are used to create matrix. The 64th condition is added manually. The matrix is: <syntaxhighlight lang=python> matrix = [ [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,], [-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], 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[0,0,0,0,140,0,0,0,0,-190,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,640,0,0,0,0,-690,0,0,0,0,0,], [0,0,0,0,0,-150,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,440,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,700,0,0,0,0,], [0,0,0,0,140,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,640,0,0,0,0,0,0,-710,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,300,0,0,0,0,0,0,0,0,0,400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-720,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-390,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,600,0,0,0,0,0,0,0,0,0,0,0,0,730,0,], [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,], ] sx = 'len(matrix)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(matrix) = 64 </syntaxhighlight> Bottom line of matrix is equivalent to: <math>(1)i10 + (-1) = 0</math> or <math>i10 = 1.</math> ====First result==== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", "+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 - e35 - e36 - e37 - e38 - e39 - e65 - e66 - e67 - e68 - e69", "+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 - e35 - e36 - e37 - e38 - e60 - e61 - e62 - e63 - e64 - e14", "+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 - e35 - e36 - e37 - e55 - e56 - e57 - e58 - e59 - e13 - e14", "+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 - e35 - e36 - e50 - e51 - e52 - e53 - e54 - e12 - e13 - e14", "+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 - e35 - e45 - e46 - e47 - e48 - e49 - e11 - e12 - e13 - e14" ] </syntaxhighlight> Produce results: <syntaxhighlight lang=python> if 1 : import decimal dD = decimal.Decimal dgt = decimal.getcontext() Precision = dgt.prec = 60 # Adjust as necessary. Tolerance = dD("1e-" + str(Precision-4)) # Adjust as necessary. import re # Regular expressions. def produce_result (input, flag = 0) : thisName = 'produce_result (input, flag = {}) :'.format(flag) values_of_i = solveMbyN (input) ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = [ (i*R) for (i,R) in zip (values_of_i, values_of_R) ] E1_ = 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14' E1 = eval(E1_) I1 = eval('i40 + i72 + i35') R1 = E1/I1 if not flag : return R1 # Check all conditions. # compiled regular expression plus, compiled regular expression minus crep,crem = [ re.compile(re.escape(v)) for v in '+-' ] # # This code verifies that result of evaluation of condition # is close enough to 0 to be called 0. # for condition in (iconditions + econditions + more_econditions + extra_test_conditions): str2 = crep.sub(';+', condition) str3 = crem.sub(';-', str2) positives = [ v for v in str3.split(';') if ('+' in v) ] pos_sum = eval(''.join(positives)) sum = eval(condition) # pos_sum - neg_sum = sum neg_sum = pos_sum - sum min,max = sorted((neg_sum, pos_sum)) status = (abs(sum) <= (Tolerance*min)) if not status : print (thisName, 'condition failed:') print (' ', condition, sum) return None return R1 # Convert all values in matrix to Decimal objects matrix = [ [ dD(str(eval(str(p)))) for p in v ] for v in matrix ] enable_reduceRow = 1 R = produce_result (matrix,1) sx = 'R' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> R = 723.928575988442547699732563335265663515838075102937503680598 </syntaxhighlight> <math>\text{R}</math> is printed with precision of 60. ====Matrix corrected==== {{RoundBoxTop|theme=2}} [[File:0710matrix64_01.png|thumb|400px|'''Diagram of network containing 64 resistors''' </br> Diagram has been corrected to show positive direction of current through R70, R73. ]] Original assumptions were that currrent flow through 64 resistors would be from bottom to top or from left to right. Examination of results shows that flow through R70, R73 is from right to left. This is reflected in testing below. Corrected diagram conforms to assumption that all current flow is from bottom towards top or from left to right. {{RoundBoxBottom}} <syntaxhighlight lang=python> number_of_columns = 65 output = [] # # Test this matrix 64 times using # i10 = 1 # i11 = 1.1 # i12 = 1.2 # ....... # ....... # i70 = -7 # i71 = 7.1 # i72 = 7.2 # i73 = -7.3 # for I in range(10, 74): new_line = [ dD(0) ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = dD(1) i = dD(I)/10 if I in (70,73) : new_line[-1] = i else : new_line[-1] = -i matrix[-1] = new_line r = produce_result (matrix,1) if r : output += [ r ] sx = 'len(output)' ; print (sx, '=', eval(sx)) # Produce results with slightly reduced precision: dgt.prec -= 4 set2 = { r+0 for r in output } dgt.prec += 4 len2 = len(set2) if len2 == 1 : r, = set2 print ('R =', r) else : print (len2, 'values of R:') for v in set2 : print (' ', v) </syntaxhighlight> <syntaxhighlight> len(output) = 64 R = 723.92857598844254769973256333526566351583807510293750368 </syntaxhighlight> <math>\text{R}</math> is printed with precision of 56. With precision of 56 all 64 results are equal. [[Category:Equations]] c5v9pg14ixaqaboheq7u1y7sdf310ed 2835143 2835034 2026-09-30T09:11:06Z ThaniosAkro 2805358 /* Implementation */ 2835143 wikitext text/x-wiki ==Introduction== The word "simultaneous" implies that two or more equations exist in the same context at the same time. For example: <math>3x + 2y - 13 = 0\ \dots\ (1)</math> <math>2x - y - 4 = 0 \ \dots\ (2)</math> Equations <math>(1)</math> and <math>(2)</math> are 2 simultaneous equations. When we see two simultaneous equations, it's natural to ask the question: What are the values of <math>x</math> and <math>y</math> that satisfy both equations <math>(1)</math> and <math>(2)</math>? To calculate <math>(x,y)</math> common to both <math>(1)</math> and <math>(2)</math>: <math>(2)*2\ \dots\ 4x - 2y - 8 = 0 \ \dots\ (3)</math> <math>(3)+(1)\ \dots\ 7x - 21 = 0;\ x = 3.</math> Substitute <math>3</math> for <math>x</math> in <math>(2):\ 2(3) - y - 4 = 0;\ y = 2.</math> The values <math>(x,y)=(3,2)</math> satisfy both equations <math>(1)</math> and <math>(2).</math> In cartesian coordinate geometry of 2 dimensions, point <math>(3,2)</math> is the point of intersection of two lines <math>(1)</math> and <math>(2).</math> See Figure 1 below. If the 2 lines are parallel, there is no point of intersection. See Figure 2 below. The trivial solution <math>(0, 0)</math> is a valid solution. See Figure 3 below. {{RoundBoxTop|theme=2}} <gallery> File:0726_2lines.png|<small>Figure 1. 2 lines that intersect at point (3,2).</small> File:0726_2parallelLines.png|<small>Figure 2. When 2 lines are parallel, there is no point of intersection.</small> File:0729_2lines.png|<small>Figure 3. The trivial solution x=y=0 is a valid solution.</small> </gallery> {{RoundBoxBottom}} The information contained in equations <math>(1)</math> and <math>(2)</math> may constitute a matrix: <pre> [ [3, 2, -13], [2, -1, -4] ] </pre> In fact, in the python programming language, the following statement is valid code: <syntaxhighlight lang=python> data = [ [3, 2, -13], [2, -1, -4] ] </syntaxhighlight> For there to be a point of intersection, <code>data</code> must be valid. Here are examples of invalid data: <syntaxhighlight lang=python> data = [ [3, 2, -13], # Both lines are parallel. [6, 4, -5] # See Figure 2 above. ] </syntaxhighlight> <syntaxhighlight lang=python> data = [ [3, 2, -13], [0, 0, -4] # Empty row, representing equation 0x + 0y - 4 = 0. ] </syntaxhighlight> <syntaxhighlight lang=python> data = [ [3, 0, -13], # Empty column representing 2 parallel lines: [2, 0, -4] # 3x = 13 and 2x = 4. ] </syntaxhighlight> The matrix above with name "data" is described as matrix "2 by 3," meaning that it contains 2 rows with 3 columns or 3 members per row. ==Solving 2 by 3== ===Implementation=== Below is python code containing function <code>solve2by3 (input).</code> The function accepts as input a matrix like <code>data</code> above. After the code are examples of invocation with both good data and bad data. <syntaxhighlight lang=python> import sys import decimal dD = decimal.Decimal def solve2by3 (input_, level=0) : ''' input represents system: a1*x + b1*y + c1 = 0 a2*x + b2*y + c2 = 0 input = ( (a1,b1,c1), (a2,b2,c2), ) To invoke: x,y = solve2by3 (input) Function solve2by3 () may return None. input is not changed by this function. ''' if level : thisName = 'solve2by3 (input_, level = {}) :'.format(level) else : thisName = 'solve2by3 (input_) :' try : error = 0 try : input = [ list(v) for v in input_ ] (a1,b1,c1), (a2,b2,c2) = input except : input = 0 input or {}['input_ not recognized.'] # six_values = a1,b1,c1, a2,b2,c2 for v in six_values : isinstance(v, (int, float, dD)) or {}['Non-numeric value in input.'] set1 = { isinstance(v, dD) for v in six_values } if len(set1) == 2 : # Mix of Decimal and non-Decimal in input. Make all type Decimal. (a1,b1,c1, a2,b2,c2) = [ dD(str(v)) for v in six_values ] # a1 or b1 or {}['Row 1 empty.'] ; a1 or a2 or {}['Column 1 empty.'] a2 or b2 or {}['Row 2 empty.'] ; b1 or b2 or {}['Column 2 empty.'] # if not a1 : # Make a1 non-zero. (a1,b1,c1),(a2,b2,c2) = (a2,b2,c2), (a1,b1,c1) # if a2 : # Make a2 zero. if a2 == a1 : a2,b2,c2 = a1-a2, b1-b2, c1-c2 elif a2 == -a1 : a2,b2,c2 = a1+a2, b1+b2, c1+c2 else : list1 = [ a2*v for v in (a1,b1,c1) ] list2 = [ a1*v for v in (a2,b2,c2) ] a2,b2,c2 = [ (v1-v2) for v1,v2 in zip (list1, list2) ] a2 and {}['Internal error. a2 should be 0.'] b2 or {}['Parallel input.'] # The matrix is: # a1, b1, c1 with a1 non-zero # 0, b2, c2 and b2 non-zero. # 0 x + b2 y + c2 = 0 y = -c2/b2 # a1 x + b1 y + c1 = 0 x = -(b1*y + c1)/a1 # Here is why a1 must be non-zero. output = x,y except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' input of solve2by3() =') print (' ', input[0]) print (' ', input[1]) return None # return output </syntaxhighlight> ====Examples==== Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13], [2, -1, -4] ]) print (output) </syntaxhighlight> <pre> (3.0, 2.0) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13], # Both lines are parallel. [6, 4, -5] # See Figure 2 above. ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('Parallel input.') input of solve2by3() = [3, 2, -13] [6, 4, -5] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 2, -13, 7], # Input matrix not exactly 2 by 3. [6, 4, -5] ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('input_ not recognized.') None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve2by3([ [3, 0, 2], [6, 0, 4] ]) print (output) </syntaxhighlight> <pre> solve2by3 (input_) : <class 'KeyError'> KeyError('Column 2 empty.') input of solve2by3() = [3, 0, 2] [6, 0, 4] None </pre> {{RoundBoxBottom}} ===Reversing the process=== ====Linear Function==== [[File:1212line01.png|thumb|400px|''' Figure 1. Diagram of line defined by 2 points.''' </br> 2 points are: <math>(-5,4), (3,1).</math> </br> Equation of line is: <math>3x + 8y - 17 = 0.</math> ]] Examples above calculate the point of intersection of 2 lines. An example of reversing the process is this task: Given two points <math>(x_1, y_1), (x_2, y_2)</math> calculate equation of line containing these 2 points. Equation of line is of format <math>Ax + By + C = 0,</math> For example: <math>3x + 2y + 10 = 0\ \dots\ (1).</math> Equation <math>(1)</math> can be expressed as <math>6x + 4y + 20 = 0</math> or <math>-9x - 6y - 30 = 0.</math> Also, there appear to be 3 unknowns, but only two sets of values are required to define the line. Assume <math>C = 1</math> and the 2 relevant equations are: <math>Ax_1 + By_1 + 1 = 0</math> <math>Ax_2 + By_2 + 1 = 0</math> To solve for <math>A, B:</math> <math>x_1A + y_1B + 1 = 0</math> <math>x_2A + y_2B + 1 = 0</math> Suppose the line is defined by points <math>(3,1), (-5,4):</math> <syntaxhighlight lang=python> # python code: input = [ [3,1,1], [-5,4,1], ] result = solve2by3 (input) print (result) </syntaxhighlight> <syntaxhighlight> (-0.17647058823529413, -0.47058823529411764) </syntaxhighlight> Desired equation is: <math>-0.17647058823529413\cdot x -0.47058823529411764\cdot y + 1 = 0\ \dots\ (2).</math> To improve appearance of <math>(2):</math> <syntaxhighlight lang=python> # python code: print (A/B) </syntaxhighlight> <syntaxhighlight> 0.37500000000000006 </syntaxhighlight> Let <math>A, B = 3, 8</math> and check: <syntaxhighlight lang=python> # python code A,B = 3,8 p1 = x1,y1 = 3,1 p2 = x2,y2 = -5,4 for v in (p1,p2) : x,y = v C = -(A*x + B*y) s1 = 'C' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> C -17 C -17 </syntaxhighlight> Desired equation <math>(2)</math> becomes <math>3x + 8y - 17 = 0\ \dots\ (3).</math> ====Wrong assumptions==== [[File:1212line02.png|thumb|400px|''' Figure 2. Diagram of line defined by 2 points and passing through origin.''' </br> 2 points are: <math>(3,2), (6,4).</math> </br> Equation of line is: <math>2x - 3y = 0.</math> </br> Non-zero value for coefficient <math>C</math> is impossible. ]] Sometimes you create a matrix that seems correct, but it fails to produce a result. Here is such an example: What is equation of line defined by points <math>(3, 2), (6, 4)?</math> As above assume that <math>C = 1.</math> <syntaxhighlight lang=python> # python code: p1 = x1,y1 = 3,2 p2 = x2,y2 = 6,4 input = [ [x1,y1,1], [x2,y2,1], ] result = solve2by3 (input) print (result) </syntaxhighlight> This assumption failed: <syntaxhighlight> solve2by3() : parallel input. input = [3, 2, 1] [6, 4, 1] None </syntaxhighlight> Assume that <math>A = 1.</math> <syntaxhighlight lang=python> # python code: # 1(x1) + B(y1) + 1(C) = 0 # 1(x2) + B(y2) + 1(c) = 0 # y1(B) + 1(C) + x1 = 0 # y2(B) + 1(C) + x2 = 0 input = [ [y1,1,x1], # Notice that input has been [y2,1,x2], # rotated left by one column. ] result = solve2by3 (input) print (result) </syntaxhighlight> <syntaxhighlight> (-1.5, 0.0) </syntaxhighlight> Equation of line is: <math>1\cdot x + (-1.5)\cdot y + 0 = 0</math> or <math>2x - 3y = 0</math> This line includes the origin. Therefore constant <math>C</math> cannot be non-zero. Generally: * Without rotation, <math>A, B = \text{result}</math> and <math>C = 1.</math> * With rotation left by one column, <math>B, C = \text{result}</math> and <math>A = 1.</math> In this case: <syntaxhighlight lang=python> # python code: >>> B,C = result ; A = 1 >>> A,B,C >>> 1,-1.5,0 </syntaxhighlight> For example of big matrix that failed the first time, but was successful the second time, see [https://en.wikiversity.org/wiki/Solving_simultaneous_equations#Cubic_Resistive_Network cubic resistive network] below. ==Solving 3 by 4== Below is python code containing function <code>solve3by4 (input).</code> The function accepts as input a 3 by 4 matrix like that described in the code comments. In 3d coordinate geometry the equations <code>(1), (2), (3)</code> are the equations of 3 planes and the solution of the system is the point of intersection of the 3 planes. Given 3 random planes, there are 2 conditions that do not produce a unique point of intersection: * If 2 of the planes are parallel. See Figure 1 below. * If the 3 planes form a "tent" or "delta." See Figure 2, 3 or 4 below. A special case of this condition occurs when size of "tent" is zero, in which case all three planes intersect on a common line and there is an infinite number of solutions. See Figure 5 below. The trivial solution <math>(0, 0, 0)</math> is valid. See Figure 6 below. <code></code> <code></code> {{RoundBoxTop|theme=2}} <gallery> File:0726_2parallelPlanes.png|<small>Figure 1. When 2 planes are parallel, there is no point of intersection.</small> File:0730triangularTube.png|<small>Figure 2. Triangular tube, 3 planes that never intersect.</small> File:0726_3planes0.png|<small>Figure 3. 3 planes that form a "tent," view 1. There is no point of intersection.</small> File:0726_3planes1.png|<small>Figure 4. 3 planes that form a "tent," view 2. There is no point of intersection.</small> File:1109_3planes1.png|<small>Figure 5. 3 planes that intersect on a common line. Points <math>(6,6,1),</math> <math>(7,7,4),</math> <math>(8,8,7)</math> are on this line and are common to all 3 planes.</small> File:0729_3planes.png|<small>Figure 6. 3 planes that intersect at origin (0, 0, 0).</small> </gallery> {{RoundBoxBottom}} ===Auxiliary functions=== <syntaxhighlight lang=python> def two_planes_parallel (plane1, plane2) : ''' status = two_planes_parallel (plane1, plane2) status = True if parallel. ''' A1,B1,C1 = plane1[:3] A2,B2,C2 = plane2[:3] A3 = B1*C2 - B2*C1 B3 = C1*A2 - C2*A1 C3 = A1*B2 - A2*B1 return ({ A3,B3,C3 } == {0}) def check_three_rows (input) : ''' result = check_three_rows (input) result is None or string. ''' row0,row1,row2 = input if two_planes_parallel (row0,row1) : return 'Two rows parallel: 0,1' if two_planes_parallel (row0,row2) : return 'Two rows parallel: 0,2' if two_planes_parallel (row1,row2) : return 'Two rows parallel: 1,2' A0,B0,C0 = row0[:3] ; A1,B1,C1 = row1[:3] ; A2,B2,C2 = row2[:3] # Line at intersection of planes 1,2 has direction numbers: A3 = B1*C2 - B2*C1 ; B3 = C1*A2 - C2*A1 ; C3 = A1*B2 - A2*B1 # Line at intersection of planes 0,2 has direction numbers: A4 = B0*C2 - B2*C0 ; B4 = C0*A2 - C2*A0 ; C4 = A0*B2 - A2*B0 # Are 2 lines of intersection parallel? if two_planes_parallel ((A3,B3,C3), (A4,B4,C4)) : return 'Three rows form tent.' return None </syntaxhighlight> ===Implementation=== <syntaxhighlight lang=python> def solve3by4 (input_, level=0) : ''' input_ is : [ [a0,b0,c0,d0], [a1,b1,c1,d1], [a2,b2,c2,d2] ] representing system: a0*x + b0*y + c0*z + d0 = 0 a1*x + b1*y + c1*z + d1 = 0 a2*x + b2*y + c2*z + d2 = 0 x,y,z = solve3by4 (input) Function solve3by4 () may return None. input is not changed by this function. ''' if level : thisName = 'solve3by4 (input_, level = {}) :'.format(level) else : thisName = 'solve3by4 (input_) :' try : error = 0 try : input = [ list(v) for v in input_ ] (a0,b0,c0,d0), (a1,b1,c1,d1), (a2,b2,c2,d2) = input except : input = 0 input or {}['input_ not recognized.'] # twelve_values = a0,b0,c0,d0, a1,b1,c1,d1, a2,b2,c2,d2 for v in twelve_values : isinstance(v, (int, float, dD)) or {}['Non-numeric value in input.'] set1 = { isinstance(v, dD) for v in twelve_values } if len(set1) == 2 : # Mix of Decimal and non-Decimal in input. Make all type Decimal. (a0,b0,c0,d0, a1,b1,c1,d1, a2,b2,c2,d2) = [ dD(str(v)) for v in twelve_values ] # a0 or b0 or c0 or {}['Row 0 empty.'] ; a0 or a1 or a2 or {}['Column 0 empty.'] a1 or b1 or c1 or {}['Row 1 empty.'] ; b0 or b1 or b2 or {}['Column 1 empty.'] a2 or b2 or c2 or {}['Row 2 empty.'] ; c0 or c1 or c2 or {}['Column 2 empty.'] # input = [ [a0,b0,c0,d0], [a1,b1,c1,d1], [a2,b2,c2,d2] ] result = check_three_rows (input) ; result and {}[result] # if not a0 : # Make a0 non-zero. if a1 : input[0],input[1] = input[1],input[0] else : input[0],input[2] = input[2],input[0] # # The matrix is: # a0, b0, c0, d0 with a0 non-zero. # a1, b1, c1, d1 # a2, b2, c2, d2 # Process rows so that a1, a2 become zero. row0 = input[0] ; a0 = row0[0] for p in (1,2) : rowp = input[p] ; ap = rowp[0] if ap : if ap == a0 : input[p] = [ (v1-v2) for (v1,v2) in zip(row0, rowp) ] elif ap == -a0: input[p] = [ (v1+v2) for (v1,v2) in zip(row0, rowp) ] else : input[p] = [ (v0*ap-vp*a0) for (v0,vp) in zip(row0, rowp) ] if input[p][0] : {}['Internal error. input[{}][0] should be 0.'.format(p)] (a0,b0,c0,d0), (a1,b1,c1,d1), (a2,b2,c2,d2) = input # The matrix is: # a0, b0, c0, d0 with a0 non-zero. # 0, b1, c1, d1 # 0, b2, c2, d2 two_rows = (b1,c1,d1), (b2,c2,d2) output = solve2by3 (two_rows, level-1) if output : y,z = output # a0 x + b0 y + c0 z + d0 = 0 x = -(b0*y + c0*z + d0)/a0 # Here is why a0 must be non-zero. output = x,y,z except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' input of solve3by4() =') print (' ', input[0]) print (' ', input[1]) print (' ', input[2]) return None # return output </syntaxhighlight> ====Examples==== Below are examples of invocation with both good data and bad data. Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [2, -1, 3, -17], [1, 3, 2, -25] , [3, 2, -1, -12] , ]) print (output) </syntaxhighlight> <pre> (3.0, 4.0, 5.0) </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [12, -12, -5, -24], [-6, 15, 8, 12] , [ 0, 10, 3, 0] , ]) print (output) </syntaxhighlight> <pre> (2.0, 0.0, -0.0) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [20, 16, 2, 17], [-77, -27, -25, -24], [81, 45, 18, 43] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Three rows form tent.') input of solve3by4() = [20, 16, 2, 17] [-77, -27, -25, -24] [81, 45, 18, 43] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [34, -5, -21, 30], [-54, -33, 63, 62], [18, 11, -21, 38] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Two rows parallel: 1,2') input of solve3by4() = [34, -5, -21, 30] [-54, -33, 63, 62] [18, 11, -21, 38] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solve3by4([ [20, 16, 2, 17], [-77, -27, '-25', -24], [81, 45, 18, 43] ]) print (output) </syntaxhighlight> <pre> solve3by4 (input_) : <class 'KeyError'> KeyError('Non-numeric value in input.') input of solve3by4() = [20, 16, 2, 17] [-77, -27, '-25', -24] [81, 45, 18, 43] None </pre> {{RoundBoxBottom}} ===Reversing the Process=== ====Quadratic function==== [[File:1212quadratic01.png|thumb|400px|''' Figure 1. Graph of quadratic function defined by 3 points.''' ]] A quadratic function <math>y = f(x) = Ax^2 + Bx + C</math> is defined by 3 points: <math>(-2, 9.0), (5, 4.8), (10, 13.8).</math> What is <math>f(x)?</math> <math>y = Ax^2 + Bx + C</math> <math>A, B, C</math> are 3 unknowns. <math>x^2(A) + x(B) + 1(C) - y = 0</math> <syntaxhighlight lang=python> # python code: x1,y1 = -2, 9 x2,y2 = 5, 4.8 x3,y3 = 10, 13.8 input = [ [x1**2, x1, 1, -y1], [x2**2, x2, 1, -y2], [x3**2, x3, 1, -y3], ] A, B, C = solve3by4 (input) s1 = 'A,B,C' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> A,B,C (0.2, -1.2, 5.8) </syntaxhighlight> <math>y = f(x) = 0.2x^2 - 1.2x + 5.8</math> ====Wrong assumptions==== [[File:1212plane02.png|thumb|400px|''' Figure 2. Graph of plane containing X axis.''' </br> Because plane passes through origin, non-zero value for coefficient <math>D</math> is impossible. </br> Because plane is parallel to <math>X</math> axis, non-zero value for coefficient <math>A</math> is impossible. ]] In 3 dimensions a plane (<math>Ax + By + Cz + D = 0</math>) is defined by 3 points: <math>(5, 3, -2), (-1, 12, -8), (37, 15, -10).</math> What is equation of plane? <math>Ax + By + Cz + D = 0</math> <math>xA + yB + zC + D = 0</math> Assume that <math>D = 1.</math> <math>xA + yB + zC + 1 = 0</math> <syntaxhighlight lang=python> # python code pt1 = x1,y1,z1 = (5, 3, -2) pt2 = x2,y2,z2 = (-1, 12, -8) pt3 = x3,y3,z3 = (37, 15, -10) input = [ [ 5, 3, -2, 1], [-1, 12, -8, 1], [37, 15, -10, 1], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> solve2by3() : parallel input. input = (-63, 42, -6) (36, -24, 32) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = (5, 3, -2, 1) (-1, 12, -8, 1) (37, 15, -10, 1) result None </syntaxhighlight> Input was invalid. Rotate input left and try again. <syntaxhighlight lang=python> # python code. input = [ [ 3, -2, 1, 5], [12, -8, 1, -1], [15, -10, 1, 37], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> solve2by3() : empty column in input. input = (0, 9, 63) (0, 12, -36) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = (3, -2, 1, 5) (12, -8, 1, -1) (15, -10, 1, 37) result None </syntaxhighlight> Input was invalid. Rotate input left and try again. <syntaxhighlight lang=python> input = [ [ -2, 1, 5, 3], [ -8, 1, -1, 12], [-10, 1, 37, 15], ] result = solve3by4 (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> result (1.5, 0, 0) </syntaxhighlight> Without rotation: <math>A, B, C = \text{result}</math> and <math>D = 1.</math> With rotation left: <math>B, C, D = \text{result}</math> and <math>A = 1.</math> With another rotation left: <math>C, D, A = \text{result}</math> and <math>B = 1.</math> <syntaxhighlight lang=python> # python code: C, D, A = (1.5, 0, 0) ; B = 1 A, B, C, D </syntaxhighlight> <syntaxhighlight> (0, 1, 1.5, 0) </syntaxhighlight> Equation of plane is: <math>0x + 1y + 1.5z + 0 = 0</math> or <math>2y + 3z = 0</math> =====A better method===== {{RoundBoxTop|theme=3}} There are four unknown values: <math>A,B,C,D.</math> Create matrix 4 by 5: <syntaxhighlight lang=python> # python code. pt1 = x1,y1,z1 = (5, 3, -2) pt2 = x2,y2,z2 = (-1, 12, -8) pt3 = x3,y3,z3 = (37, 15, -10) input = [] for (x_,y_,z_) in (pt1,pt2,pt3) : x,y,z = [ dD(v) for v in (x_,y_,z_) ] input += [ [ x,y,z,1,0 ] ] # For valid plane at least one of A,B,C must be non-zero. # For last condition let A + B + C = 5. input += [ [ 1,1,1,0,-5 ] ] A,B,C,D = solveMbyN(input) print (input) print ( '({})x + ({})y + ({})z + ({}) = 0'.format(A,B,C,D) ) </syntaxhighlight> <syntaxhighlight> [[ 5, 3, -2, 1, 0], # 5A + 3B - 2C + 1D + 0 = 0 [-1, 12, -8, 1, 0], # -1A + 12B - 8C + 1D + 0 = 0 [37, 15, -10, 1, 0], # 37A + 15B - 10C + 1D + 0 = 0 [ 1, 1, 1, 0, -5]] # 1A + 1B + 1C + 0D - 5 = 0 (0)x + (2)y + (3)z + (0) = 0 </syntaxhighlight> Equation of plane is: <math>2y + 3z = 0.</math> {{RoundBoxBottom}} ==Solving M by (M+1)== ===Implementation=== Below is python code containing function <code>solveMbyN (input).</code> The function accepts as input a 4 by 5 matrix (or greater) like that described in the code comments. This function is recursive, calling itself with M being reduced by 1 with each recursive invocation until the matrix is size 3 by 4 in which case function solve3by4() is called. <syntaxhighlight lang=python> # python code enable_reduceRow = 0 FPE = FloatingPointError # Not used by python. Used here as target of 'goto'. def solveMbyN (input_, level=0) : ''' Input represents system: a0*w + b0*x + c0*y + d0*z + e0 = 0 a1*w + b1*x + c1*y + d1*z + e1 = 0 a2*w + b2*x + c2*y + d2*z + e2 = 0 a3*w + b3*x + c3*y + d3*z + e3 = 0 or greater. This solves a matrix of M rows by N columns where N = M+1 and M >= 2 input = [ (a0,b0,c0,d0,e0), (a1,b1,c1,d1,e1), (a2,b2,c2,d2,e2), (a3,b3,c3,d3,e3), ] To invoke: w,x,y,z = solveMbyN (input [, level]) Function solveMbyN () may return None. If input is size 15 by 16: v1,v2,v3, .... ,v14,v15 = solveMbyN (input) Input is not changed by this function. ''' thisName = 'solveMbyN (input_, level = {}) :'.format(level) try : error = 0 try: input = [ list(v) for v in input_ ] except : input = 0 input or {}['input_ not recognized.'] number_of_rows = len(input) (number_of_rows > 1) or {}['number_of_rows must be > 1.'] if number_of_rows == 2 : output = solve2by3(input, level) raise FPE # Equivalent to goto. if number_of_rows == 3 : output = solve3by4(input, level) raise FPE # Equivalent to goto. number_of_columns = number_of_rows + 1 if level == 0 : dD_count = other_count = 0 for row_number in range (number_of_rows-1,-1,-1) : row = input[row_number] # Check that each row is correct length. if (len(row) != number_of_columns) : error = [ 'row # {} has bad length: {}'.format(row_number, len(row))] error += [ 'Correct length is : {}'.format(number_of_columns)] raise FPE for v in row : # Check that all data is numeric. isinstance(v, (int,float,dD)) or {}['Non-numeric value in input.'] # Record if type dD or not. if isinstance(v, dD) : dD_count += 1 else : other_count += 1 if dD_count and other_count : # Mix of types Decimal and non-Decimal in input. Make all values type Decimal. input = [ [ dD(str(p)) for p in row ] for row in input ] # Each row must not be empty. for row_number in range (number_of_rows-1,-1,-1) : found = 0 for v in input[row_number][:-1]: if v : found = 1 ; break if not found : {}['Empty row in input: # {} of {} rows.'.format(row_number, number_of_rows)] # Arrange input if necessary so that a0 is non-zero. if not input[0][0] : for p in range (1, number_of_rows) : if input[p][0] : input[p], input[0] = input[0], input[p] break # The matrix is: # [a0,b0,c0,d0,e0], with a0 non-zero, # [a1,b1,c1,d1,e1], # [a2,b2,c2,d2,e2], # [a3,b3,c3,d3,e3], # If abs(level) is large, following test can produce error: # OverflowError('int too large to convert to float') # Solution is to convert values in input to type float or Decimal. dD(input[0][0]) ; float(input[0][0]) # Each column must not be empty. for column_number in range (number_of_columns-2,-1,-1) : found = 0 for row in input : if row[column_number] : found = 1 ; break if not found : {}['Empty column in input: # {} of {} columns.'.format(column_number, number_of_columns)] if enable_reduceRow : # global variable # For matrices greater than 10 by 11 enable this piece of code. # This code calculates the max(abs) of all values in row, # divides all values by the max(abs) and updates row with result. # [27, -15, 42] becomes [27/42, -15/42, 42/42]. # Without this code you may see: # solveMbyN (input, level = -52) : # <class 'decimal.Overflow'> # Overflow([<class 'decimal.Overflow'>]) for row in input : max = 0 for v in row : if abs(v) > max : max = abs(v) if max < 1e100 : continue for column_number in range (number_of_columns-1,-1,-1) : if row[column_number] : row[column_number] /= max # Process rows so that a1, a2, a3, .... become zero. row0 = input[0] ; a0 = row0[0] for p in range (1, number_of_rows) : rowp = input[p] ; ap = rowp[0] if ap : if ap == a0 : input[p] = [ (v1-v2) for (v1,v2) in zip(row0, rowp) ] elif ap == -a0: input[p] = [ (v1+v2) for (v1,v2) in zip(row0, rowp) ] else : input[p] = [ (v0*ap-vp*a0) for (v0,vp) in zip(row0, rowp) ] if input[p][0] : try: str1 = str(float(input[p][0])) except : str1 = 'Error' {}['Internal error. input[{}][0] = {}, should be 0.'.format(p,str1)] # The matrix is: # [a0, b0, c0, d0, e0], with a0 non-zero, # [ 0, b1, c1, d1, e1], # [ 0, b2, c2, d2, e2], # [ 0, b3, c3, d3, e3], next_input = [ row[1:] for row in input[1:] ] # next_input is : # [ b1, c1, d1, e1], # [ b2, c2, d2, e2], # [ b3, c3, d3, e3], output = solveMbyN (next_input, level-1) # Here is where function solveMbyN() calls itself. if output : # input[0] = a0, b0, c0, d0, e0 # output = x, y, z (len(input[0][1:-1]) == len(output)) or {}["Internal error. Inputs to zip() don't match."] listOfProducts = [ v1*v2 for v1,v2 in zip(input[0][1:-1], output) ] # listOfProducts = [ b0*x, c0*y, d0*z ] sumOfProducts = input[0][-1] for v in listOfProducts : sumOfProducts += v # sumOfProducts = b0*x + c0*y + d0*z + e0 # a0*w + b0*x + c0*y + d0*z + e0 = 0 # a0*w + sumOfProducts = 0 w = -sumOfProducts/a0 # Here is why a0 must be non-zero. output = (w,) + output except FPE : pass # Target of 'goto'. except : error = str(sys.exc_info())[1:].split(',') ; error[1:] = [ ','.join(error[1:-1]) ] # if error : print (thisName) for v in error : print (' ', v.strip()) if input : print (' Length of input =', len(input)) for p in range (0, len(input)) : if p >= 8 : break try : row = [ float(v) for v in input_[p] ] except : row = 'Error in this row.' print (' input_[{}] ='.format(p), row) return None # return output </syntaxhighlight> ===Examples=== Below are examples of invocation with both good data and bad data. Invocation with good data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> L1 = [ [Decimal('-870442133162'), Decimal('239132906684'), Decimal('397660499756'), Decimal('788825405004'), Decimal('156830886652'), Decimal('-87096140169')], [Decimal('-112130420352'), Decimal('-93605595828'), Decimal('-185262083472'), Decimal('-93369903383'), Decimal('-497973505065'), Decimal('-766710012513')], [Decimal('-142983492168'), Decimal('619713461197'), Decimal('-608752759383'), Decimal('-448477443042'), Decimal('-281161661751'), Decimal('-799463977245')], [Decimal('572854919541'), Decimal('-148673693908'), Decimal('341291756040'), Decimal('362403188059'), Decimal('-202136092949'), Decimal('-429932229578')], [Decimal('157632861972'), Decimal('330790263276'), Decimal('-836474627955'), Decimal('644295395386'), Decimal('-595590967129'), Decimal('-392835045727')] ] output = solveMbyN(L1) print (output) </syntaxhighlight> The following results were produced with decimal precision set at 50: <pre> ( Decimal('-0.06331410760212760088313271882866553044211194694576'), Decimal('1.0969089506763419155148060427588009931309074487534'), Decimal('1.0837038580207682607126722016017867670831200359767'), Decimal('-0.42989566124678842791674322699930461340596671792215'), Decimal('-2.0541601084281682582146753421426610779297051535362') ) </pre> {{RoundBoxBottom}} Invocation with bad or invalid data: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [-4, -6, 3, -4, -8, -8], [1, 0, 2, 5, 1, 7], [9, -3, -8, 4, 7, -5], [1, -9, 5, -2, 5, -2], [1, -3, -6, -3, -6, 6] ]) print (output) </syntaxhighlight> <pre> # With each step towards solve2by3() the length of each number in digits can theoretically double. solve2by3() : parallel input. input = (-181440, 181440, -101088) (90720, -90720, 406944) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [-756, -1176, 0, -1872] [-324, -744, 240, -936] [-324, -384, -120, -264] input of solveMbyN() with 4 rows = [-6, 11, 16, -4, 20] [-66, -5, -20, -44, -92] [-42, 23, -12, 12, -16] [-18, -21, -16, -32, 16] input of solveMbyN() with 5 rows = [-4, -6, 3, -4, -8, -8] [1, 0, 2, 5, 1, 7] [9, -3, -8, 4, 7, -5] [1, -9, 5, -2, 5, -2] [1, -3, -6, -3, -6, 6] None </pre> Provided that numbers are small, integers, floats and Decimal objects produce the same results: {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [-4.0, -6.0, 3.0, -4.0, -8.0, -8.0], [1.0, 0.0, 2.0, 5.0, 1.0, 7.0], [9.0, -3.0, -8.0, 4.0, 7.0, -5.0], [1.0, -9.0, 5.0, -2.0, 5.0, -2.0], [1.0, -3.0, -6.0, -3.0, -6.0, 6.0] ]) print (output) </syntaxhighlight> <pre> solve2by3() : parallel input. input = (-181440.0, 181440.0, -101088.0) (90720.0, -90720.0, 406944.0) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [-756.0, -1176.0, 0.0, -1872.0] [-324.0, -744.0, 240.0, -936.0] [-324.0, -384.0, -120.0, -264.0] input of solveMbyN() with 4 rows = [-6.0, 11.0, 16.0, -4.0, 20.0] [-66.0, -5.0, -20.0, -44.0, -92.0] [-42.0, 23.0, -12.0, 12.0, -16.0] [-18.0, -21.0, -16.0, -32.0, 16.0] input of solveMbyN() with 5 rows = [-4.0, -6.0, 3.0, -4.0, -8.0, -8.0] [1.0, 0.0, 2.0, 5.0, 1.0, 7.0] [9.0, -3.0, -8.0, 4.0, 7.0, -5.0] [1.0, -9.0, 5.0, -2.0, 5.0, -2.0] [1.0, -3.0, -6.0, -3.0, -6.0, 6.0] None </pre> {{RoundBoxBottom}} {{RoundBoxTop|theme=2}} <syntaxhighlight lang=python> output = solveMbyN([ [Decimal('-4'), Decimal('-6'), Decimal('3'), Decimal('-4'), Decimal('-8'), Decimal('-8')], [Decimal('1'), Decimal('0'), Decimal('2'), Decimal('5'), Decimal('1'), Decimal('7')], [Decimal('9'), Decimal('-3'), Decimal('-8'), Decimal('4'), Decimal('7'), Decimal('-5')], [Decimal('1'), Decimal('-9'), Decimal('5'), Decimal('-2'), Decimal('5'), Decimal('-2')], [Decimal('1'), Decimal('-3'), Decimal('-6'), Decimal('-3'), Decimal('-6'), Decimal('6')] ]) print (output) </syntaxhighlight> <pre> solve2by3() : parallel input. input = (Decimal('-181440'), Decimal('181440'), Decimal('-101088')) (Decimal('90720'), Decimal('-90720'), Decimal('406944')) checkDirectionNumbers() : 3 rows form a tent. input of solve3by4() = [Decimal('-756'), Decimal('-1176'), Decimal('0'), Decimal('-1872')] [Decimal('-324'), Decimal('-744'), Decimal('240'), Decimal('-936')] [Decimal('-324'), Decimal('-384'), Decimal('-120'), Decimal('-264')] input of solveMbyN() with 4 rows = [Decimal('-6'), Decimal('11'), Decimal('16'), Decimal('-4'), Decimal('20')] [Decimal('-66'), Decimal('-5'), Decimal('-20'), Decimal('-44'), Decimal('-92')] [Decimal('-42'), Decimal('23'), Decimal('-12'), Decimal('12'), Decimal('-16')] [Decimal('-18'), Decimal('-21'), Decimal('-16'), Decimal('-32'), Decimal('16')] input of solveMbyN() with 5 rows = [Decimal('-4'), Decimal('-6'), Decimal('3'), Decimal('-4'), Decimal('-8'), Decimal('-8')] [Decimal('1'), Decimal('0'), Decimal('2'), Decimal('5'), Decimal('1'), Decimal('7')] [Decimal('9'), Decimal('-3'), Decimal('-8'), Decimal('4'), Decimal('7'), Decimal('-5')] [Decimal('1'), Decimal('-9'), Decimal('5'), Decimal('-2'), Decimal('5'), Decimal('-2')] [Decimal('1'), Decimal('-3'), Decimal('-6'), Decimal('-3'), Decimal('-6'), Decimal('6')] None </pre> {{RoundBoxBottom}} {{RoundBoxBottom}} ===Sphere=== In cartesian coordinate geometry of three dimensions a sphere is represented by equation: <math>x^2 + y^2 + z^2 + Ax + By + Cz + D = 0.</math> On the surface of a certain sphere there are 4 known points: <syntaxhighlight lang=python> # python code point1 = (13,7,20) point2 = (13,7,4) point3 = (13,-17,4) point4 = (16,4,4) </syntaxhighlight> What is equation of sphere? Rearrange equation of sphere to prepare for creation of input matrix: <math>(x)A + (y)B + (z)C + (1)D + (x^2 + y^2 + z^2) = 0.</math> Create input matrix of size 4 by 5: <syntaxhighlight lang=python> # python code input = [] for (x,y,z) in (point1, point2, point3, point4) : input += [ ( x, y, z, 1, (x**2 + y**2 + z**2) ) ] print (input) </syntaxhighlight> <syntaxhighlight> [ (13, 7, 20, 1, 618), (13, 7, 4, 1, 234), (13, -17, 4, 1, 474), (16, 4, 4, 1, 288), ] # Matrix containing 4 rows with 5 members per row. </syntaxhighlight> <syntaxhighlight lang=python> # python code result = solveMbyN(input) print (result) </syntaxhighlight> <syntaxhighlight> (-8.0, 10.0, -24.0, -104.0) </syntaxhighlight> Equation of sphere is : <math>x^2 + y^2 + z^2 - 8x + 10y - 24z - 104 = 0</math> ===Quintic function=== [[File:1212quintic01.png|thumb|400px|''' Figure 4. Graph of quintic function defined by 6 points.''' ]] A quintic function <math>y = f(x) = Ax^5 + Bx^4 + Cx^3 + Dx^2 + Ex + F</math> is defined by 6 points: <math>(-8, 0), (-6, 0), (-3, 0), (1,0), (3,0), (5,10).</math> What is <math>f(x)?</math> <math>y = f(x) = Ax^5 + Bx^4 + Cx^3 + Dx^2 + Ex + F</math> <math>A, B, C, D, E, F</math> are 6 unknowns. <math>x^5(A) + x^4(B) + x^3(C) + x^2(D) + x(E) + 1(F) - y = 0</math> <syntaxhighlight lang=python> # python code: pt1 = x1,y1 = -8,0 pt2 = x2,y2 = -6,0 pt3 = x3,y3 = -3,0 pt4 = x4,y4 = 1,0 pt5 = x4,y5 = 3,0 pt6 = x6,y6 = 5,10 input = [] for pt in (pt1,pt2,pt3,pt4,pt5,pt6) : x,y = pt input += [[ x**5, x**4, x**3, x**2, x, 1, -y ]] print (input) </syntaxhighlight> <syntaxhighlight> [[-32768, 4096, -512, 64, -8, 1, 0], [ -7776, 1296, -216, 36, -6, 1, 0], [ -243, 81, -27, 9, -3, 1, 0], [ 1, 1, 1, 1, 1, 1, 0], [ 243, 81, 27, 9, 3, 1, 0], [ 3125, 625, 125, 25, 5, 1, -10]] </syntaxhighlight> <syntaxhighlight> result = solveMbyN (input) s1 = 'result' print (s1, eval(s1)) </syntaxhighlight> <syntaxhighlight> result (0.0010926573426573423, 0.014204545454545447, 0.027316433566433533, -0.18028846153846156, -0.3343531468531468, 0.47202797202797203) </syntaxhighlight> From these results the following ratios may be deduced: <math>\frac{1}{A} = 915.2;\ </math> <math>\frac{B}{A} = 13;\ </math> <math>\frac{C}{A} = 25;\ </math> <math>\frac{D}{A} = -165;\ </math> <math>\frac{E}{A} = -306;\ </math> <math>\frac{F}{A} = 432.</math> <math>y = f(x) = \frac{x^5 + 13x^4 + 25x^3 - 165x^2 - 306x + 432}{915.2}</math> ===Resistive network=== {{RoundBoxTop|theme=2}} [[File:1127network01.png|thumb|400px|''' Figure 1. Diagram of resistive network containing 8 resistors.''' ]] A resistive network containing 8 resistors is connected as shown in Figure 1. What is resistance <math>R</math> between points <math>P_1, P_3?</math> {{RoundBoxBottom}} ====Solve for 8 Branch Currents==== {{RoundBoxTop|theme=2}} [[File:1127network02.png|thumb|400px|''' Figure 2. Diagram of resistive network showing all branch currents.''' </br> </br> At any point to which 3 or more conductors are connected, sum of currents = 0. </br> At point <math>P_4</math> currents <math>i_1, i_7</math> flow towards point; current <math>i_4</math> flows away from point. </br> <math>i_1 + i_7 - i_4 = 0.</math> </br> </br> In any closed loop sum of voltages = 0. </br> In loop containing points <math>P_1, P_2</math> voltages <math>e_2, e_8</math> are clockwise; voltage <math>e_3</math> is counter-clockwise. <math></math> </br> <math>e_2 + e_8 - e_3 = 0.</math><math></math><math></math> </br> </br> Direction of flow through <math>r_7, r_8</math> is assumed and is subject to correction. ]] Voltage across <math>r_1:</math> Using <math>E = IR,\ e_1 = i_1\cdot r_1 = r_1\cdot a.</math> Similarly: <math>e_2 = r_2\cdot b.</math> <math>e_3 = r_3\cdot c.</math> <math>\dots\dots</math> <math>e_8 = r_8\cdot h.</math> Build a matrix size 8 by 9 which will be input to function solveMbyN(). <syntaxhighlight lang=python> # Python code: r1,r2,r3,r4,r5,r6,r7,r8 = 10,20,30,40,50,60,70,80 input = [] # e1 = e2 + e7 # 10a = 20b + 70g # 10a - 20b + 0c + 0d + 0e + 0f - 70g + 0h + 0 = 0 input += [[r1, - r2, 0, 0, 0, 0, - r7, 0, 0]] # e3 = e2 + e8 # 30c = 20b + 80h # 0a - 20b + 30c + 0d + 0e + 0f + 0g - 80h + 0 = 0 input += [[0, - r2, r3, 0, 0, 0, 0, - r8, 0]] # e5 = e7 + e4 # 50e = 70g + 40d # 0a + 0b + 0c - 40d + 50e + 0f - 70g + 0h + 0 = 0 input += [[0, 0, 0, - r4, r5, 0, - r7, 0, 0]] # e5 = e8 + e6 # 50e = 80h + 60f # 0a + 0b + 0c + 0d + 50e - 60f + 0g - 80h + 0 = 0 input += [[0, 0, 0, 0, r5, - r6, 0, - r8, 0]] # i7 + i5 + i8 = i2 # g + e + h = b # 0a - 1b + 0c + 0d + 1e + 0f + 1g + 1h + 0 = 0 input += [[0 ,- 1, 0, 0, 1, 0, 1, 1, 0]] # i4 = i1 + i7 # d = a + g # -1a + 0b + 0c + 1d + 0e + 0f - 1g + 0h + 0 = 0 input += [[-1, 0, 0, 1, 0, 0, - 1, 0, 0]] # i6 = i3 + i8 # f = c + h # 0a + 0b - 1c + 0d + 0e + 1f + 0g - 1h + 0 = 0 input += [[0, 0, - 1, 0, 0, 1, 0, - 1, 0]] # Total input current = 1 # a + b + c = 1 # 1a + 1b + 1c + 0d + 0e + 0f + 0g + 0h - 1 = 0 input += [[1, 1, 1, 0, 0, 0, 0, 0, - 1]] </syntaxhighlight> This last entry can contain almost any arbitrary values. For example: <syntaxhighlight lang=python> # Python code: # i7 = 2.3 input += [[0, 0, 0, 0, 0, 0, 1, 0, - 2.3]] # e5 = 1.9 input += [[0, 0, 0, 0, r5, 0, 0, 0, - 1.9]] </syntaxhighlight> Changing this last entry changes all values of <math>e_x, i_x.</math> However, the ratio <math>\frac{e_x}{i_x} = r_x</math> remains constant. {{RoundBoxTop|theme=3}} input is matrix of size 8 by 9: <syntaxhighlight> [ [10, -20, 0, 0, 0, 0, -70, 0, 0], # e1 = e2 + e7, or r1(i1) - r2(i2) - r7(i7) = 0 [ 0, -20, 30, 0, 0, 0, 0, -80, 0], # e3 = e2 + e8, or r3(i3) - r2(i2) - r8(i8) = 0 [ 0, 0, 0, -40, 50, 0, -70, 0, 0], # e5 = e4 + e7, or r5(i5) - r4(i4) - r7(i7) = 0 [ 0, 0, 0, 0, 50, -60, 0, -80, 0], # e5 = e6 + e8, or r5(i5) - r6(i6) - r8(i8) = 0 [ 0, -1, 0, 0, 1, 0, 1, 1, 0], # i2 = i5 + i7 + i8, or 1(i5) + 1(i7) + 1(i8) - 1(i2) = 0 [-1, 0, 0, 1, 0, 0, -1, 0, 0], # i4 = i1 + i7, or 1(i4) - 1(i1) - 1(i7) = 0 [ 0, 0, -1, 0, 0, 1, 0, -1, 0], # i6 = i3 + i8, or 1(i6) - 1(i3) - 1(i8) = 0 [ 1, 1, 1, 0, 0, 0, 0, 0, -1] # i1 + i2 + i3 = 1, or 1(i1) + 1(i2) + 1(i3) - 1 = 0 ] </syntaxhighlight> {{RoundBoxBottom}} <syntaxhighlight lang=python> i1,i2,i3,i4,i5,i6,i7,i8 = values_of_i = solveMbyN (input) s1 = 'values_of_i' ; print(s1,eval(s1)) s1 = 'i1 + i2 + i3' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> values_of_i (0.45727389222364606, 0.3065353746543468, 0.23619073312200717, 0.4350171983543536, 0.31685438726647336, 0.24812841437917316, -0.022256693869292507, 0.011937681257165982) i1 + i2 + i3 1.0 </syntaxhighlight> <math>i_7</math> has negative value. Reverse <math>i_7</math> to make all branch currents positive. {{RoundBoxBottom}} ====Make all Branch Currents positive==== {{RoundBoxTop|theme=2}} [[File:1127network03.png|thumb|400px|''' Figure 3. Diagram of resistive network showing all branch currents positive.''' ]] Make <math>i_7</math> positive and check results. <syntaxhighlight lang=python> # Python code i7 *= -1 values_of_e = e1,e2,e3,e4,e5,e6,e7,e8 = [ eval(s1) for s in '12345678' for s1 in [ 'i' + s + '*r' + s ] ] s1 = 'values_of_e' print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> values_of_e [ 4.572738922236461, 6.130707493086937, 7.085721993660215, 17.400687934174144, 15.842719363323669, 14.88770486275039, 1.5579685708504756, 0.9550145005732785] </syntaxhighlight> <syntaxhighlight lang=python> # python code t1 = ( 'e1+e7-e2', # e1 + e7 should equal e2 'e2+e8-e3', # e2 + e8 should equal e3 'e7+e5-e4', # e7 + e5 should equal e4 'e8+e6-e5', # e8 + e6 should equal e5 'e1+e4-(e2+e5)', # e1 + e4 should equal e2 + e5 'e1+e4-(e3+e6)', # e1 + e4 should equal e3 + e6 'e1+e7+e8-e3', # e1 + e7 + e8 should equal e3 'e7+e8+e6-e4', # e7 + e8 + e6 should equal e4 'i1-i7-i4', # i1 should equal i7 + i4 'i6-i3-i8', # i6 should equal i3 + i8 'i2+i7-(i8+i5)', # i2 + i7 should equal i8 + i5 'i1+i2+i3 - (i4+i5+i6)', # Total input current should # equal total output current. ) for s1 in t1 : print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> e1+e7-e2 -8.881784197001252e-16 e2+e8-e3 0.0 e7+e5-e4 0.0 e8+e6-e5 0.0 e1+e4-(e2+e5) 0.0 e1+e4-(e3+e6) 0.0 e1+e7+e8-e3 -8.881784197001252e-16 e7+e8+e6-e4 0.0 i1-i7-i4 -5.551115123125783e-17 i6-i3-i8 6.938893903907228e-18 i2+i7-(i8+i5) 0.0 i1+i2+i3 - (i4+i5+i6) 0.0 </syntaxhighlight> {{RoundBoxBottom}} ====Compute R==== {{RoundBoxTop|theme=8}} <syntaxhighlight lang=python> # Python code E1 = e3+e6 I1 = i1 + i2 + i3 R1 = E1/I1 s1 = 'R1' ; print(s1,eval(s1)) E2 = e1 + e7 + e5 I2 = i4 + i5 + i6 R2 = E2/I2 s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 21.973426856410605 R2 21.973426856410605 </syntaxhighlight> <math>R = R_1 = R_2</math> {{RoundBoxBottom}} ==Solving big matrices== A big matrix is one of size greater than 10 by 11. With each recursive call of solveMbyN() the size of each value in decimal digits can theoretically double. Python's integer math enjoys infinite precision. If your original matrix is of size 32 by 33, and each value in the matrix is an int of 1 decimal digit, function solve2by3() can be called with ints of size 2**30 (1,073,741,824) decimal digits. Floats can be used instead of ints, but the limited precision of floats may not provide a desirable level of accuracy in the result. Python's decimal objects are a good compromise and function reduceRow() above is an attempt to keep the size of each member manageable. Function reduceRow() works well. However, as with all operations involving python's decimal objects, you need to pay careful attention to precision and accuracy of the results. On my Mac the following python code generates a matrix of size 100 by 101 and calculates the result containing 100 values in about 1.5 seconds, including the time to generate 10,100 random numbers, each containing up to 12 decimal digits with the decimal point in a random position, and including the time to test output over 100 rows to verify that all calculated values of the solution satisfy each row. In function solveMbyN() above find line: <syntaxhighlight lang=python> if 0 : # For matrices greater than 10 by 11 enable this piece of code. </syntaxhighlight> Change it to: <syntaxhighlight lang=python> if 1 : # For matrices greater than 10 by 11 enable this piece of code. </syntaxhighlight> Then: <syntaxhighlight lang=python> from random import getrandbits from decimal import * import sys getcontext().prec=50 # Set precision to 50. numRows=100 def randomNumber(): # 1 invocation in 256 returns 0. if not (getrandbits(10) & 0xFF) : return Decimal(0) return [ w for q in [ getrandbits(10) & 1] for sign in [ (-1,1)[q] ] for numberOfDecimalPlaces in [ getrandbits(10) & 0xF ] for s1 in [ str(getrandbits(50))[-12:] ] for s2 in [ '0'*12+s1 ] for posn in [ len(s2)-numberOfDecimalPlaces ] for w in [ sign*Decimal(s2[:posn]+'.'+s2[posn:]) ] ][0] data = [[ randomNumber() for p in range(numRows+1) ] for p in range (numRows) ] datan = sorted([ v for row in data for v in row if v < 0 ]) datap = sorted([ v for row in data for v in row if v >= 0 ]) print ('A small sample of the random numbers in data:') print ('+ve values:',len(datap), ',', datap[:2],'\n ',datap[-2:]) print ('-ve values:',len(datan), ',', datan[:2],'\n ',datan[-2:]) output = solveMbyN(data) print ('A small sample of the solutions:') print ('output[0] =', output[0]) print ('output[19] =', output[19]) print ('output[59] =', output[59]) print ('output[99] =', output[99]) </syntaxhighlight> <pre> A small sample of the random numbers in data: +ve values: 5021 , [Decimal('1.16871265E-7'), Decimal('1.73721245E-7')] [Decimal('998523464710'), Decimal('999768605679')] -ve values: 5079 , [Decimal('-991079944209'), Decimal('-989786083110')] [Decimal('-4.10272824E-7'), Decimal('-2.38664537E-7')] A small sample of the solutions: output[0] = 0.43689400018920695253771832432651757885163362928745 output[19] = 0.19867480862268284151047885891372314311902973127033 output[59] = 0.46169681824826309421940885550155275946668017604646 output[99] = -0.020598220802233733529683040085023443421113627790464 </pre> ===Testing results=== Data input to function solveMbyN() is an array of 100 rows, each row containing 101 numbers. <pre> [ [v0_0, v0_1, v0_2, ..... v0_98,v0_99,v0_100], ....... [v99_0,v99_1,v99_2, ...... v99_98,v99_99,v99_100],] ] </pre> Data received from function solveMbyN() is an array of 100 numbers. <pre> [ s0,s1,s2, ...... s98,s99 ] </pre> The first row is tested with the solutions by; <pre> L2 = [ v0_0*s0, v0_1*s1, v0_2*s2, ..... v0_98*s98,v0_99*s99,v0_100 ] </pre> sum is the sum of all items in L2. sum is appended to L1 and the process is repeated for all 100 rows. <syntaxhighlight lang=python> L1 = [] for row in data : # a, b, c, d, e, f, g ....... # row # u, v, w, x, y, z # output L2 = [ row[p]*t1[p] for t1 in (output+(1,),) for p in range (0, len(row)) ] # L2 = [a*u , b*v , c*w , d*x , e*y , f*z , g] sum = [ sum for sum in [0] for p in L2 for sum in [sum+p] ][-1] # sum = [a*u, a*u + b*v, a*u + b*v + c*w, a*u + b*v + c*w + d*x, a*u + b*v + c*w + d*x + e*y, # a*u + b*v + c*w + d*x + e*y + f*z, a*u + b*v + c*w + d*x + e*y + f*z + g][-1] # sum = a*u + b*v + c*w + d*x + e*y + f*z + g # sum is the sum of all items in L2 L1 += [abs(sum)] L1a = sorted(L1) print (len(L1a), L1a[0], L1a[-1]) </syntaxhighlight> Ideally sum should be zero. In practice it's extremely unlikely that sum will be zero. My results typically gave values close to <pre> 100 4.1065149609E-38 9.6425614873452398368906E-25 </pre> The worst of the results above was 23 zeroes after the decimal point. Better results can be achieved by increasing precision. ===Cubic Resistive Network=== {{RoundBoxTop|theme=2}} [[File:1129network01.png|thumb|400px|''' Figure 1. Diagram of resistive network containing 12 resistors.''' </br> Blue arrows show assumed direction of current. ]] A resistive network containing 12 resistors is connected as shown in Figure 1. The network is called "cubic" because, in 3 dimensions, each resistor is located on one edge of a cube. What is resistance <math>R</math> between points <math>P_1, P_2?</math> <syntaxhighlight lang=python> # Python code: values_of_r = r1,r2,r3,r4,r5,r6,r7,r8,r9,r10,r11,r12 = 10,20,30,40,50,60,70,80,90,100,110,120 </syntaxhighlight> {{RoundBoxBottom}} ====Solve for 12 Branch Currents==== =====Create matrix 12 by 13===== <syntaxhighlight lang=python> # Python code: input = [ [10, 20, -30, -40, 0, 0, 0, 0, 0, 0, 0, 0, 0], # e1 + e2 = e3 + e4 [ 0, 0, 0, 0, 50, 60, -70, -80, 0, 0, 0, 0, 0], # e5 + e6 = e7 + e8 [ 0, 0, 0, 40, 0, 0, 0, -80, 0, 0, 110, -120, 0], # e11 + e4 = e8 + e12 [10, 0, 0, 0, -50, 0, 0, 0, 90, -100, 0, 0, 0], # e9 + e1 = e5 + e10 [ 0, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0], # i5 = i10 + i6 [ 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, 0, 0], # i7 = i11 + i8 [-1, 0, -1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # i9 = i1 + i3 [ 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0], # i4 = i3 + i11 [-1, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0], # i2 = i1 + i10 [ 0, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 1, 0], # i12 = i6 + i8 [ 0, -1, 0, -1, 1, 0, 1, 0, 1, 0, 0, -1, 0], # i9 + i5 + i7 = i2 + i4 + i12 [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1.6] # i3 = 1.6 ] i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12 = values_of_i = solveMbyN (input) s1 = 'values_of_i' print(s1,eval(s1)) </syntaxhighlight> This matrix failed: <syntaxhighlight> solve2by3() : empty row in input. input = (0, 0, 0) (90533116137774317568000000000000000000000000000000000000000000, -84449318308603494400000000000000000000000000000000000000000000, 1.4228848407261846e+61) checkDirectionNumbers() : 2 rows parallel, 1 and 2. input of solve3by4() = [38760268800000000000000000000, 593753233920000000000000000000, -569385344000000000000000000000, 0] [620164300800000000000000000000000000, 9500051742720000000000000000000000000, -9110165504000000000000000000000000000, 0] [153839206400000000000000000000000, 20882470400000000000000000000000, -81126144000000000000000000000000, -3.67098806272e+32] </syntaxhighlight> =====Try again===== <syntaxhighlight lang=python> # Python code: input = [ [10, 20, -30, -40, 0, 0, 0, 0, 0, 0, 0, 0, 0], # e1 + e2 = e3 + e4 [ 0, 0, 0, 0, 50, 60, -70, -80, 0, 0, 0, 0, 0], # e5 + e6 = e7 + e8 [ 0, 0, 0, 40, 0, 0, 0, -80, 0, 0, 110, -120, 0], # e11 + e4 = e8 + e12 [10, 0, 0, 0, -50, 0, 0, 0, 90, -100, 0, 0, 0], # e9 + e1 = e5 + e10 [ 0, 0, 0, 0, 1, -1, 0, 0, 0, -1, 0, 0, 0], # i5 = i10 + i6 [ 0, 0, 0, 0, 0, 0, 1, -1, 0, 0, -1, 0, 0], # i7 = i11 + i8 [-1, 0, -1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # i9 = i1 + i3 [ 0, 0, -1, 1, 0, 0, 0, 0, 0, 0, -1, 0, 0], # i4 = i3 + i11 [-1, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0], # i2 = i1 + i10 [ 0, 0, 0, 0, 0, -1, 0, -1, 0, 0, 0, 1, 0], # i12 = i6 + i8 #[ 0, -1, 0, -1, 1, 0, 1, 0, 1, 0, 0, -1, 0], # i9 + i5 + i7 = i2 + i4 + i12 DELETED. [10, 20, 0, 0, 0, 0, -70, -80, 90, 0, 0, -120, 0], # e9 + e1 + e2 = e7 + e8 + e12 ADDED. [ 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1.6] # i3 = 1.6 ] import decimal dD = decimal.Decimal dgt = decimal.getcontext() Precision = dgt.prec = 30 Tolerance = dD("1e-" + str(Precision-2)) # Convert all values in input to decimal objects with precision of 30. input = [ [ dD(str(p)) for p in v ] for v in input ] i1,i2,i3,i4,i5,i6,i7,i8,i9,i10,i11,i12 = values_of_i = solveMbyN (input) </syntaxhighlight> <syntaxhighlight> # values_of_i 5.5027171492204899777282850777 9.3809275973899113038721525414 1.5999999999999999999999999999 # i3 should be 1.6. 4.8661430860000781463681475402 6.12901340210213730316883522816 2.25080295393271597702496776458 4.68526862814050716992927753670 1.41912554214042902356112999643 7.10271714922048997772828507766 3.87821044816942132614386746358 3.26614308600007814636814754027 3.66992849607314500058609776103 </syntaxhighlight> ====Compute R==== {{RoundBoxTop|theme=8}} <syntaxhighlight lang=python> # python code values_of_e = e1,e2,e3,e4,e5,e6,e7,e8,e9,e10,e11,e12 = [ (i*r) for (i,r) in zip(values_of_i, values_of_r) ] </syntaxhighlight> <syntaxhighlight> values_of_e 55.0271714922048997772828507770 187.618551947798226077443050828 47.9999999999999999999999999970 194.645723440003125854725901608 306.450670105106865158441761408 135.048177235962958621498065875 327.968803969835501895049427569 113.530043371234321884890399714 639.244543429844097995545656989 387.821044816942132614386746358 359.275739460008596100496229430 440.391419528777400070331731324 </syntaxhighlight> <math>e_3</math> should be <math>48,\ i_3*r_3</math> or <math>1.6*30.</math> <syntaxhighlight lang=python> E1 = e5 + e10 + e2 I1 = i9 + i5 + i7 R1 = E1/I1 s1 = 'R1' ; print(s1,eval(s1)) E2 = e7 + e8 - e6 + e10 - e1 + e3 + e4 I2 = i2 + i4 + i12 R2 = E2/I2 s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 49.2208688540148837936367036806 R2 49.2208688540148837936367036803 </syntaxhighlight> Display results with precision of 28: <syntaxhighlight lang=python> dgt.prec = 28 R1 += 0 ; R2 += 0 dgt.prec = Precision s1 = 'R1' ; print(s1,eval(s1)) s1 = 'R2' ; print(s1,eval(s1)) </syntaxhighlight> <syntaxhighlight> R1 49.22086885401488379363670368 R2 49.22086885401488379363670368 </syntaxhighlight> <math>R = R_1 = R_2.</math> {{RoundBoxBottom}} ====Review==== In matrix all values <math>i_1, i_2, \dots, i_{11}, i_{12}</math> and <math>e_1, e_2, \dots, e_{11}, e_{12}</math> are included. Testing was done with the following lines substituted for last line of matrix: <syntaxhighlight lang=python> # python code [ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, -3.15] # i7 = 3.15 [ 0, 0, 0, r4, 0, 0, 0, 0, 0, 0, 0, 0, -6 ] # e4 = 6 [ 0, 0, r3, 0, 0, 0, 0, r8, 0, 0, 0, 0, -5 ] # e3 + e8 = 5 </syntaxhighlight> All tests produced a consistent value of <math>R.</math> ====Checking==== =====Examples of current nodes===== {{RoundBoxTop|theme=2}} <gallery> File:0101network01.png|<small><math>i_1 + i_{10} = i_2</math></small> File:0101network02.png|<small><math>i_6 + i_8 = i_{12}</math></small> </gallery> {{RoundBoxBottom}} =====Examples of voltage loops===== {{RoundBoxTop|theme=2}} <gallery> File:0108network00.png|<small>Top and Bottom.<math>e_1 + e_2 - e_4 - e_3 = 0</math><math>e_5 + e_6 - e_8 - e_7 = 0</math></small> File:0108network01.png|<small>Two sides in background.<math>e_5 + e_{10} - e_1 - e_9 = 0</math><math>e_6 + e_{12} - e_2 - e_{10} = 0</math></small> File:0108network02.png|<small>Two sides in foreground.<math>e_7 + e_{11} - e_3 - e_9 = 0</math><math>e_8 + e_{12} - e_4 - e_{11} = 0</math></small> </gallery> {{RoundBoxBottom}} =====Python code===== <syntaxhighlight lang=python> t1 = ( # 3 nodes on top 'i1 + i10 - i2', 'i1 + i3 - i9', 'i3 + i11 - i4', # 3 nodes on bottom 'i10 + i6 - i5', 'i11 + i8 - i7', 'i6 + i8 - i12', # Total input current equals total output current. 'i5 + i7 + i9 - i2 - i4 - i12', # Voltage loops # top 'e1 + e2 - e4 - e3', # bottom 'e5 + e6 - e8 - e7', # 2 sides in background 'e9 + e1 - e10 - e5', 'e10 + e2 - e12 - e6', # 2 sides in foreground 'e9 + e3 - e11 - e7', 'e11 + e4 - e12 - e8', # Some elaborate loops. 'e8 - e6 + e10 + e2 - e4 - e3 - e9 + e7', 'e10 + e2 - e12 - e8 + e11 - e3 - e9 + e5', ) </syntaxhighlight> Result of each of the above calculations should be <math>0.</math> Because of small rounding errors, result may not be exactly <math>0.</math> See values_of_i and values_of_e above. This code verifies that result is close enough to <math>0</math> to be acceptable. For example: <math>\text{result} = e_{10} + e_2 - e_{12} - e_8 + e_{11} - e_3 - e_9 + e_5.</math> <math>\text{v1} = e_{10} + e_2 + e_{11} + e_5,</math> sum of positive values. <math>\text{status = (abs(result)} < \text{(v1}*\text{Tolerance)). status}</math> should be <math>\text{True.}</math> <syntaxhighlight lang=python> # python code import re for str1 in t1 : str2 = re.sub ('\+', ';+', str1) str2 = re.sub ('\-', ';-', str2) L1 = str2.split(';') positives = ''.join([ v for v in L1 if '-' not in v ]) result = eval(str1) v1 = eval( positives ) status = (abs(result) < (v1*Tolerance)) str3 = (str1+(' '*40))[:42] str4 = ((' '*10) + str(result))[-10:] str5 = '{}{} {}'.format(str3,str4,status) print ( str5 ) </syntaxhighlight> {| class="wikitable" |- ! Calculation || Result !! Result Acceptable |- | <math> i_1 + i_{10} - i_2 </math> | <math> -1.2E-28 </math> | <math>\text{True}</math> |- | <math> i_1 + i_3 - i_9 </math> | <math> -6E-29 </math> | <math>\text{True}</math> |- | <math> i_3 + i_{11} - i_4 </math> | <math> -3E-29 </math> | <math>\text{True}</math> |- | <math> i_{10} + i_6 - i_5 </math> | <math> 0E-29 </math> | <math>\text{True}</math> |- | <math> i_{11} + i_8 - i_7 </math> | <math> 0E-29 </math> | <math>\text{True}</math> |- | <math> i_6 + i_8 - i_{12} </math> | <math> -2E-29 </math> | <math>\text{True}</math> |- | <math> i_5 + i_7 + i_9 - i_2 - i_4 - i_{12} </math> | <math> -3E-29 </math> | <math>\text{True}</math> |- | <math> e_1 + e_2 - e_4 - e_3 </math> | <math> 0E-28 </math> | <math>\text{True}</math> |- | <math> e_5 + e_6 - e_8 - e_7 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_9 + e_1 - e_{10} - e_5 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_{10} + e_2 - e_{12} - e_6 </math> | <math> -1.3E-26 </math> | <math>\text{True}</math> |- | <math> e_9 + e_3 - e_{11} - e_7 </math> | <math> -1.3E-26 </math> | <math>\text{True}</math> |- | <math> e_{11} + e_4 - e_{12} - e_8 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_8 - e_6 + e_{10} + e_2 - e_4 - e_3 - e_9 + e_7 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |- | <math> e_{10} + e_2 - e_{12} - e_8 + e_{11} - e_3 - e_9 + e_5 </math> | <math> 0E-27 </math> | <math>\text{True}</math> |} ===Big Matrix 64 by 65=== {{RoundBoxTop|theme=2}} [[File:0706matrix64_01.png|thumb|400px|'''Diagram of resistive network containing 64 resistors.''' </br> Positive current flow is assumed to be from bottom to top or from left to right. ]] A network containing 64 resistors is connected as shown in diagram. What is resistance R between points P1, P2? <syntaxhighlight lang=python> # python code values_of_R = ( R10, R11, R12, R13, R14, R15, R16, R17, R18, R19, R20, R21, R22, R23, R24, R25, R26, R27, R28, R29, R30, R31, R32, R33, R34, R35, R36, R37, R38, R39, R40, R41, R42, R43, R44, R45, R46, R47, R48, R49, R50, R51, R52, R53, R54, R55, R56, R57, R58, R59, R60, R61, R62, R63, R64, R65, R66, R67, R68, R69, R70, R71, R72, R73, ) = [ v for v in range (100,731,10) ] </syntaxhighlight> While this resistive circuit may be very theoretical, it lends itself well to the creation of a big matrix, 64 by 65, meaning that there are 64 resistors and 64 simultaneous equations to be solved. {{RoundBoxBottom}} ====Create matrix==== An examination of the circuit produces the following conditions: <syntaxhighlight lang=python> # python code iconditions = [ "+ i10 + i70 - i44" , "+ i11 - i10 - i49" , "+ i12 - i11 - i54", "+ i13 - i12 - i59" , "+ i14 - i13 - i64" , "+ i15 + i44 - i43", "+ i16 + i49 - i15 - i48 - i70" , "+ i17 + i54 - i16 - i53" , "+ i18 + i59 - i17 - i58", "+ i19 + i64 + i71 - i18 - i63" , "+ i69 - i19 - i68" , "+ i20 + i43 - i42", "+ i21 + i48 - i20 - i47" , "+ i22 + i53 - i21 - i52" , "+ i23 + i58 - i22 - i57", "+ i24 + i63 - i23 - i62" , "+ i68 - i24 - i67" , "+ i25 + i42 - i41", "+ i26 + i47 - i25 - i46" , "+ i27 + i52 - i26 - i51" , "+ i28 + i57 - i27 - i56", "+ i29 + i62 - i28 - i61" , "+ i67 - i29 - i66" , "+ i30 + i41 - i40", "+ i31 + i46 - i30 - i45 - i72" , "+ i32 + i51 - i31 - i50" , "+ i33 + i56 - i32 - i55", "+ i34 + i61 + i73 - i33 - i60" , "+ i66 - i34 - i65" , "+ i36 + i45 - i35", "+ i37 + i50 - i36" , "+ i38 + i55 - i37" , "+ i39 + i60 - i38", "+ i65 - i39 - i73" ] sx = 'len(iconditions)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(iconditions) = 34 </syntaxhighlight> <syntaxhighlight lang=python> econditions = [ "+ e40 + e30 - e35 - e45" , "+ e41 + e25 - e30 - e46" , "+ e42 + e20 - e25 - e47", "+ e43 + e15 - e20 - e48" , "+ e44 + e10 - e15 - e49" , "+ e45 + e31 - e36 - e50", "+ e46 + e26 - e31 - e51" , "+ e47 + e21 - e26 - e52" , "+ e48 + e16 - e21 - e53", "+ e49 + e11 - e16 - e54" , "+ e50 + e32 - e37 - e55" , "+ e51 + e27 - e32 - e56", "+ e52 + e22 - e27 - e57" , "+ e53 + e17 - e22 - e58" , "+ e54 + e12 - e17 - e59", "+ e55 + e33 - e38 - e60" , "+ e56 + e28 - e33 - e61" , "+ e57 + e23 - e28 - e62", "+ e58 + e18 - e23 - e63" , "+ e59 + e13 - e18 - e64" , "+ e60 + e34 - e39 - e65", "+ e61 + e29 - e34 - e66" , "+ e62 + e24 - e29 - e67" , "+ e63 + e19 - e24 - e68", "+ e64 + e14 - e19 - e69" , "+ e44 + e70 - e15" , "+ e64 + e14 - e71", "+ e40 + e30 - e72" , "+ e60 + e73 - e39" ] sx = 'len(econditions)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(econditions) = 29 </syntaxhighlight> In iconditions and econditions there are 63 conditions that include all values of i and e. These 63 conditions are used to create matrix. The 64th condition is added manually. The matrix is: <syntaxhighlight lang=python> matrix = [ [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,], [-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], [0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,], [0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,], 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[0,0,0,0,140,0,0,0,0,-190,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,640,0,0,0,0,-690,0,0,0,0,0,], [0,0,0,0,0,-150,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,440,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,700,0,0,0,0,], [0,0,0,0,140,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,640,0,0,0,0,0,0,-710,0,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,300,0,0,0,0,0,0,0,0,0,400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-720,0,0,], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-390,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,600,0,0,0,0,0,0,0,0,0,0,0,0,730,0,], [1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,], ] sx = 'len(matrix)' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> len(matrix) = 64 </syntaxhighlight> Bottom line of matrix is equivalent to: <math>(1)i10 + (-1) = 0</math> or <math>i10 = 1.</math> ====First result==== The following conditions are included for testing: <syntaxhighlight lang=python> more_econditions = [ "+ e49 + e70 - e10", "+ e19 + e69 - e71", "+ e35 + e45 - e72", "+ e65 + e73 - e34", ] extra_test_conditions = [ "+ e40 + e41 + e42 + e43 + e44 + e10 - e35 - e45 - e46 - e47 - e48 - e49", "+ e45 + e46 + e47 + e48 + e49 + e11 - e36 - e50 - e51 - e52 - e53 - e54", "+ e50 + e51 + e52 + e53 + e54 + e12 - e37 - e55 - e56 - e57 - e58 - e59", "+ e55 + e56 + e57 + e58 + e59 + e13 - e38 - e60 - e61 - e62 - e63 - e64", "+ e60 + e61 + e62 + e63 + e64 + e14 - e39 - e65 - e66 - e67 - e68 - e69", "+ e44 + e10 + e11 + e12 + e13 + e14 - e69 - e15 - e16 - e17 - e18 - e19", "+ e43 + e15 + e16 + e17 + e18 + e19 - e68 - e20 - e21 - e22 - e23 - e24", "+ e42 + e20 + e21 + e22 + e23 + e24 - e67 - e25 - e26 - e27 - e28 - e29", "+ e41 + e25 + e26 + e27 + e28 + e29 - e66 - e30 - e31 - e32 - e33 - e34", "+ e40 + e30 + e31 + e32 + e33 + e34 - e65 - e35 - e36 - e37 - e38 - e39", "+ i35 + i40 + i72 - i14 - i69 - i71", "+ e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14 - e35 - e36 - e37 - e38 - e39 - e65 - e66 - e67 - e68 - e69", "+ e40 + e41 + e42 + e43 + e15 + e16 + e17 + e18 + e19 + e69 - e35 - e36 - e37 - e38 - e60 - e61 - e62 - e63 - e64 - e14", "+ e40 + e41 + e42 + e20 + e21 + e22 + e23 + e24 + e68 + e69 - e35 - e36 - e37 - e55 - e56 - e57 - e58 - e59 - e13 - e14", "+ e40 + e41 + e25 + e26 + e27 + e28 + e29 + e67 + e68 + e69 - e35 - e36 - e50 - e51 - e52 - e53 - e54 - e12 - e13 - e14", "+ e40 + e30 + e31 + e32 + e33 + e34 + e66 + e67 + e68 + e69 - e35 - e45 - e46 - e47 - e48 - e49 - e11 - e12 - e13 - e14" ] </syntaxhighlight> Produce results: <syntaxhighlight lang=python> if 1 : import decimal dD = decimal.Decimal dgt = decimal.getcontext() Precision = dgt.prec = 60 # Adjust as necessary. Tolerance = dD("1e-" + str(Precision-4)) # Adjust as necessary. import re # Regular expressions. def produce_result (input, flag = 0) : thisName = 'produce_result (input, flag = {}) :'.format(flag) values_of_i = solveMbyN (input) ( i10, i11, i12, i13, i14, i15, i16, i17, i18, i19, i20, i21, i22, i23, i24, i25, i26, i27, i28, i29, i30, i31, i32, i33, i34, i35, i36, i37, i38, i39, i40, i41, i42, i43, i44, i45, i46, i47, i48, i49, i50, i51, i52, i53, i54, i55, i56, i57, i58, i59, i60, i61, i62, i63, i64, i65, i66, i67, i68, i69, i70, i71, i72, i73, ) = values_of_i values_of_e = ( e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46, e47, e48, e49, e50, e51, e52, e53, e54, e55, e56, e57, e58, e59, e60, e61, e62, e63, e64, e65, e66, e67, e68, e69, e70, e71, e72, e73, ) = [ (i*R) for (i,R) in zip (values_of_i, values_of_R) ] E1_ = 'e40 + e41 + e42 + e43 + e44 + e10 + e11 + e12 + e13 + e14' E1 = eval(E1_) I1 = eval('i40 + i72 + i35') R1 = E1/I1 if not flag : return R1 # Check all conditions. # compiled regular expression plus, compiled regular expression minus crep,crem = [ re.compile(re.escape(v)) for v in '+-' ] # # This code verifies that result of evaluation of condition # is close enough to 0 to be called 0. # for condition in (iconditions + econditions + more_econditions + extra_test_conditions): str2 = crep.sub(';+', condition) str3 = crem.sub(';-', str2) positives = [ v for v in str3.split(';') if ('+' in v) ] pos_sum = eval(''.join(positives)) sum = eval(condition) # pos_sum - neg_sum = sum neg_sum = pos_sum - sum min,max = sorted((neg_sum, pos_sum)) status = (abs(sum) <= (Tolerance*min)) if not status : print (thisName, 'condition failed:') print (' ', condition, sum) return None return R1 # Convert all values in matrix to Decimal objects matrix = [ [ dD(str(eval(str(p)))) for p in v ] for v in matrix ] enable_reduceRow = 1 R = produce_result (matrix,1) sx = 'R' ; print (sx, '=', eval(sx)) </syntaxhighlight> <syntaxhighlight> R = 723.928575988442547699732563335265663515838075102937503680598 </syntaxhighlight> <math>\text{R}</math> is printed with precision of 60. ====Matrix corrected==== {{RoundBoxTop|theme=2}} [[File:0710matrix64_01.png|thumb|400px|'''Diagram of network containing 64 resistors''' </br> Diagram has been corrected to show positive direction of current through R70, R73. ]] Original assumptions were that currrent flow through 64 resistors would be from bottom to top or from left to right. Examination of results shows that flow through R70, R73 is from right to left. This is reflected in testing below. Corrected diagram conforms to assumption that all current flow is from bottom towards top or from left to right. {{RoundBoxBottom}} <syntaxhighlight lang=python> number_of_columns = 65 output = [] # # Test this matrix 64 times using # i10 = 1 # i11 = 1.1 # i12 = 1.2 # ....... # ....... # i70 = -7 # i71 = 7.1 # i72 = 7.2 # i73 = -7.3 # for I in range(10, 74): new_line = [ dD(0) ] * number_of_columns place_in_line = I - 10 new_line[place_in_line] = dD(1) i = dD(I)/10 if I in (70,73) : new_line[-1] = i else : new_line[-1] = -i matrix[-1] = new_line r = produce_result (matrix,1) if r : output += [ r ] sx = 'len(output)' ; print (sx, '=', eval(sx)) # Produce results with slightly reduced precision: dgt.prec -= 4 set2 = { r+0 for r in output } dgt.prec += 4 len2 = len(set2) if len2 == 1 : r, = set2 print ('R =', r) else : print (len2, 'values of R:') for v in set2 : print (' ', v) </syntaxhighlight> <syntaxhighlight> len(output) = 64 R = 723.92857598844254769973256333526566351583807510293750368 </syntaxhighlight> <math>\text{R}</math> is printed with precision of 56. With precision of 56 all 64 results are equal. [[Category:Equations]] 3ap222jzst51vji0h5fsva5s4tf0c09 0 322967 2835083 2755846 2026-09-30T00:33:51Z StretchBeyond 3105744 /* Overview */ Grammar improvements made to chapter to improve overall book quality. 2835083 wikitext text/x-wiki {{title|Amygdala and fear motivation:<br>What role does the amygdala play in threat-related motivation responses and avoidance behaviours?}} __TOC__ == Overview == {{RoundBoxTop|theme=11}} [[File:Amygdala.png|thumb|300x300px|'''Figure 1'''. The amygdala's (highlighted in red) position within the brain.]] ;Imagine this ... You are walking home late, the dark street folds to shadow. Air dense with silence. The only sound is the echo of your own steps. As you enter a narrow alleyway, you pause and notice something feels wrong. Your heart begins to race. You see a flicker of movement pulling your attention. Your breath shallows, chest tightens and stomach drops. You do not see a threat but you can feel it. Before you can even rationalise it, your feet have turned away and began sprinting from alley. You did not think, nor plan. You just avoided. {{RoundBoxBottom}} This is not just a story of fear, but a window into the neural processes of motivation, emotion and behaviour. This chapter will explore the functionality of the amygdala and how it orchestrates threat-related motivation and avoidance behaviours. The amygdala is vital to fundamental human survival and decision making. It is among the brain's first responders for detecting and evaluating threats, enabling rapid decisions often before conscious processing occurs. The amygdala provides the biological basis for interpreting motives behind emotion and behaviour, integrating sensory input, personal memories, and context to shape responses. Insight into the function of the amygdala assists researchers and clinicians to build better tools for assessment, intervention, and treatment. Differences in amygdala activation may help explain why individuals differ in their behavioural reactions. This chapter explores the amygdala as a structure and how it drives motivation and emotional behaviour related to threat avoidance. It investigates how the amygdala processes environmental stimuli, to rapidly trigger physiological and emotional responses that influence decisions critical to survival. By integrating psychological theories and current research, it can be understood why people respond differently to threatening situations and how these mechanisms contribute to challenges in mental health. Understanding the amygdala's role highlights pathways for intervention aimed at regulating maladaptive avoidance and improving overall wellbeing. {{RoundBoxTop|theme=11}} ;Focus questions *How does the amygdala contribute to the development and regulation of avoidance behaviours through emotional and physiological responses? *In what ways is the amygdala able to influence human motivation? *How do functional and circuit level connections of the amygdala support both approach and avoidance behaviours? {{RoundBoxBottom}} == Avoidance behaviour and the amygdala == Avoidance behaviour is shaped by the amygdala’s role in learning and evaluating threats. By associating cues with aversive outcomes, the amygdala drives persistent avoidance through emotional memory and appraisal processes, impacting motivation and mental health. === Psychological theories linking to the amygdala === [[wikipedia:Classical_conditioning|Classical conditioning]] provides a foundational perspective to understanding avoidance. The amygdala stores emotional memories by associating neutral cues with aversive outcomes, creating enduring fear responses encouraging avoidance (Fernando et al., 2013). This clarifies how learned emotional responses underlie the development and maintenance of avoidance. To explore how the amygdala regulates, Richard Lazarus' [[Motivation and emotion/Book/2014/Appraisal and emotion|appraisal theory]] provides key insights. The theory suggests that emotions are not merely conditioned responses but arise from cognitive evaluation. The amygdala contributes to primary appraisal by detecting relevance of environmental cues to assess whether threats are present. Secondary appraisal involves assessing an individual's ability to cope with resources, involving prefrontal cortical regions interacting with the amygdala, to decide whether to engage in avoidance behaviours (Yarwood, 2001). According to Lazarus, emotional experience results from interpretation of thoughts, perceived control and memory to shape the final emotion and behavioural response. This dynamic evaluation influences whether avoidance behaviours are engaged, thus addressing the amygdala's role in avoidance regulation. === The amygdala's response to stimuli === The amygdala responds to real and potential stimuli. In events where emotion is heightened, both sides of the amygdala are active (Leitão et al., 2022). This activation reflects its role in emotional processing and motivation for active and passive defence mechanisms (Schlund & Cataldo, 2010). The amygdala integrates feelings with action planning, not just reactive, but also active in determining significance and motivating response. This challenges Paul Ekman's basic emotion theory, proposing that each emotion is associated with specific neural circuits (Coppini et al., 2023). Recent research has shown non-specificity of brain areas, with the amygdala not just acting as a "fear centre" but responding to threatening and rewarding stimuli, motivating responses. Conditioning of the amygdala's response is resistant to change. Studies have shown that the amygdala still activates in response to threat cues despite extinction attempts. This demonstrates that fear memories are encoded robustly. This persistence that can lead to maladaptive avoidance behaviours (Schlund & Cataldo, 2010). Bilateral amygdala activation has been demonstrated in response to threat cues that motivated avoidance and escape, even when aversive outcomes were successfully prevented. This indicates that the amygdala encodes motivational significance of threat beyond simple cue-outcome learning, aligning with two-factor theories of avoidance where threat cues energise avoidance and fear-reduction reinforces it. These results link the amygdala's role in adaptive threat avoidance to the dysfunction in mood and anxiety disorders characterized by excessive and maladaptive avoidance behaviours.{{f}} === The amygdala's response to fear === Individuals engage in avoidance behaviours to reduce distressing experiences and interactions. Avoidance of fear-inducing stimuli activates reward circuits between the amygdala and nucleus accumbens (NAcc), reinforcing avoidance through fear-reduction (Schultz et al., 2019). This contradicts Pavlov's extinction theory, as the amygdala continues to activate to conditioned threat cues despite absence of harm, sustaining avoidance. The amygdala can appraise social threats. Studies have shown that when individuals voluntarily chose to interact with a human rather than a computer, the amygdala showed larger activation during high-risk social decisions. These studies found that individuals who are less inclined to participate in social interaction displayed higher fear responses (Schultz et al., 2019). Individuals who indicated they have a high level of fear around social situations demonstrated a significant increase in functional connectivity between the amygdala and nucleus accumbens during decision making (Schultz et al., 2019). This indicates that those in situations that they fear, are more likely to react based upon emotion and be bias towards avoidance (Rosenberg et al., 2024). {{RoundBoxTop|theme=11}} '''Case study: Amygdala's role in fear motivated behaviours''' Emily, a 23-year-old student, experiences social anxiety and frequently avoids participating in class discussions. functional magnetic resonance imaging (fMRI) scans of her brain during social decision making tasks found increased amygdala activation when she faces high-risk social choices such as talking to a group of students versus having an email conversation. She also demonstrated strong functional connectivity between the amygdala and nucleus accumbens. This indicates that not only was her avoidance fear driven, but rewarded, reinforcing the behaviour further. ;Explanation: Emily's case demonstrates that the amygdala not only influences emotional responses, but also motivates behaviour through learned reward. This is because avoidance reduced emotional discomfort, which is then experienced as rewarding. {{RoundBoxBottom}} == How the amygdala motivates behaviour == The amygdala shapes motivation by integrating emotional and contextual cues, enabling flexible goal-directed behaviour. By processing value and salience, it drives actions toward rewards or avoidance and modulates behaviour via hormonal and learned associations (Fernando et al., 2013; Smith & Torregrossa, 2021). === Goal-directed behaviours === The amygdala guides goal-directed behaviour by processing appetitive and aversive stimuli, steering reward pursuit or avoidance. To influence motivation, the amygdala houses neurons that encode salience, signalling the importance of a stimulus, while others are valence-specific, distinguishing positive from negative cues to shape motivation (Fernando et al., 2013). Through Pavlovian-to-instrument transfer, conditioned stimuli bias instrumental actions according to their learned value, linking emotional learning to flexible goal pursuit{{f}}. {{RoundBoxTop|theme=11}} ;Example of Pavlovian-to-instrument transfer If a person was attempting to restrict their chocolate intake, and then heard the song from a popular chocolate company's advertisement. This conditioned stimulus accompanied with the pleasure from past consumption makes them more likely to walk to the kitchen, an instrumental action, and eat chocolate, even if they were not thinking about it. This demonstrates Pavlovian-to-instrument transfer in humans, with the amygdala influencing emotional cues to encourage goal-motivated behaviours. {{RoundBoxBottom}} === Motivation through hormones === [[File:Dopamine Pathway.png|thumb|360x360px|Figure 2. The neural pathway of dopamine in reference to the amygdala's position.]] [[wikipedia:Corticotropin-releasing_hormone|Corticotropin-releasing hormone]] (CRH) mediates stress responses that influence avoidance-motivated behaviours. CRH is released in response to arousing environmental stimuli, activating the hypothalamic-pituitary-adrenal (HPA) axis and eliciting physical and emotional arousal, including fear-related behaviours (Schlund & Cataldo, 2010). CRH neurons concentrated in the nucleus of the stria terminalis connect with the central amygdala and NAcc through dopaminergic circuits (see Figure 2). This enables CRH to modulate dopamine release, producing a positive affective state (Chang et al., 2022). However, during severe stress responses, CRH loses its capacity to regulate dopamine release due to altered sensitivity of dopamine receptors to CRH, modifying the downstream signalling pathways that are activated by CRH, switching the effect from appetitive to aversive (Tsigos et al., 2020). This shift promotes avoidance-motivated behaviours, explaining why individuals may withdraw from formerly pleasurable activities following stressful events. === Differences between individuals in amygdala activation === Amygdala responses vary between individuals, accounting for differences in approach, avoidance and escape behaviours (Schlund & Cataldo, 2010). Amygdala activation may be low due to learned avoidance. The amygdala responds to threats through active avoidance, but in learnt avoidance the amygdala is less required. Other neurological structures such as the prefrontal cortex are able to influence mediating learnt behaviour, shifting to suppress amygdala activity (Ressler, 2020). This shift predicts safety and reduces emotional arousal, leading to diminished amygdala responses over repeated exposures. Amygdala activation may be high as some people continue to react to threats, even when they consistently avoid harm. This is because some people have stronger emotional and physiological arousal during certain situations. In this case, the original fear association, between conditioned stimulus and unconditioned stimulus may still influence the response of the amygdala (Schlund & Cataldo, 2010). Such sustained activation may underlie maladaptive anxiety and excessive avoidance observed in some clinical populations. {{RoundBoxTop|theme=1}} ;True or false? <quiz display="simple"> {The amygdala influences avoidance behaviours by encoding the salience and emotional value of stimuli, which helps drive goal-directed decisions to approach or avoid certain outcomes.} - False + True {Hormonal mechanisms, such as CRH’s modulation of dopamine release, play a role in shifting motivation from reward-seeking to avoidance behaviour during stress, highlighting the amygdala’s dynamic role in regulating motivation.} - False + True </quiz> {{RoundBoxBottom}} == Functional connectivity of the amygdala == Functional connectivity links the amygdala to emotion and cognition by coordinating activity across cortical and subcortical brain circuits. These networks shape instinctive reactions and flexible, goal-directed behaviours, with development and individual differences affecting avoidance and motivation (Leitão et al., 2022; Rosenberg et al., 2024) === Functional connectivity in a general population === Functional connectivity supports how the amygdala integrates emotional and cognitive inputs to guide behaviour. The amygdala operates within interconnected brain circuits involving cortical and subcortical structures enabling goal-directed decision-making and motivated actions (Leitão et al., 2022). Rapid, reactive behaviours engage the amygdala-caudate (subcortical) circuit, whereas deliberate, value-driven approach behaviours recruit the amygdala-prefrontal (cortical) pathways including orbitofrontal and medial prefrontal cortices (Leitão et al., 2022). This dissociation highlights the amygdala's involvement in both instinctive and higher-order cognitive processes. A limitation with neuroimaging studies is their constrained spatial resolution and the difficulty of isolating specific nuclei (Schlund & Cataldo, 2010). Longitudinal and multi-modal imaging techniques may capture dynamic amygdala functions. In neuroimaging experiments, bilateral amygdala activation occurs in response to cues signaling avoidance, escape, or reward, even when aversive outcomes are successfully avoided (Schlund & Cataldo, 2010). This persistent activation may underlie sustained threat-related motivation and avoidance behaviours observed in the general population, as well as in clinical contexts. These findings underscore the amygdala’s central role in integrating affective and cognitive processes via functional networks to regulate fear-motivated behaviours effectively. === Functional connectivity in adolescence === To understand individual variability in amygdala function and its implications for avoidance behaviours, adolescent neurodevelopment offers crucial insights. Adolescence is marked by neurodevelopmental changes that alter amygdala connectivity and motivational responses to threat. During this period, the amygdala links threat cues to behaviour via the nucleus accumbens, strengthening circuits that promote escape and avoidance (Rosenberg et al., 2024). Adolescents exhibiting elevated internalising symptoms demonstrate increased functional connectivity between the amygdala and nucleus accumbens which impairs safety and threat discrimination, fostering maladaptive avoidance behaviours. This period is also characterised by heightened neural plasticity, enabling dynamic reorganisation of amygdala-related networks in response to environmental demands and facilitating adaptation, but also increasing vulnerability to maladaptive behavioural patterns if adverse experiences occur (Rosenberg et al., 2024). Typically, the dorsolateral prefrontal cortex (dlPFC) downregulates amygdala activity and supports emotion regulation in threat situations. In anxious adolescents, however, [https://www.sciencedirect.com/science/article/abs/pii/S0168010218301706 top-down] control from the dlPFC is weaker, allowing threat-driven amygdala responses to persist and dominate behaviour (Lisk et al., 2020). Maturation of these circuits with age is tied to enhanced motivation and adaptive coping, but their dysregulation increases vulnerability to internalising disorders. The period of adolescence represents a sensitive window where atypical development of amygdala connectivity, especially with reward and regulatory regions, can shape long-term patterns of avoidance and fear-motivated behaviour. Prompt intervention is crucial to prevent persistent maladaptive outcomes. This developmental perspective assists researchers to further understand how neural maturation shapes motivation and behavioural regulation. {{RoundBoxTop|theme=11}} ;Key findings of major reviews Recent meta-analyses and systematic reviews have reinforced the multidimensional role of the amygdala. For instance, Deming and Koenigs (2020) conducted a meta-analysis of {{ic|how many?}} magnetic resonance imaging (MRI) studies, synthesising evidence for altered amygdala connectivity and function in individuals with psychopathy, highlighting its broad involvement in behavioural regulation. Similarly, Schlund and Cataldo (2010) reviewed {{ic}} human avoidance, escape, and approach studies, finding persistent bilateral amygdala activation in response to threat cues, supporting two-factor theories and noting individual differences in avoidance. Dorofeikova et al. (2023) summarised research on genetically distinct central amygdala neurons, providing perspective on how appetitive and aversive responses are modulated within overlapping neural circuits, challenging older single-pathway models. Leitão et al. (2022) integrated neuroimaging findings from multiple studies, illustrating dynamic amygdala connectivity with cortical and striatal regions during approach and avoidance behaviours. These reviews provide evidence that amygdala activation is contextually flexible, persists beyond conscious learning, and is variably expressed across individuals and disorders. These scientific syntheses strengthen clinical and theoretical models of motivation, avoidance, and emotion, and reinforce the importance of targeting amygdala circuits in intervention and future research. {{RoundBoxBottom}} == Amygdala circuits in approach and avoidance behaviours == The amygdala plays a central role in motivating both approach and avoidance behaviours through distinct but overlapping neural circuits. It assigns emotional significance to stimuli, coordinating responses that promote survival by either driving pursuit of rewards or triggering defensive avoidance. Understanding these circuits reveals how the amygdala flexibly integrates appetitive and aversive signals to regulate adaptive behaviour and informs research into related mental health disorders. === Dual role of the amygdala in aversive and appetitive behaviours === The central amygdala sends inhibitory projections to the lateral substantia nigra and other midbrain structures to support [https://pubmed.ncbi.nlm.nih.gov/32294466/ appetitive and aversive learning], encoding the significance of certain events. Acting as a coordinator, the amygdala engages distinct circuits to trigger specific defensive or approach responses (Steinberg et al., 2020). It assigns salience to emotionally arousing stimuli, gauging significance of the situation to drive behaviour accordingly. The amygdala communicates with the midbrain to transform the perceived threat into motivation to power avoidance behaviours. Activating different subcircuits to the midbrain depending on the type of threat, for example, predicting an escapable threat compared to an unavoidable harm, ensures adaptive defensive responses (Steinberg et al., 2020). This is important for efficient detection of stimuli and activation of defence responses to protect individuals from danger by responding in an appropriate way, motivating avoidance of danger or seeking out positive experiences. The amygdala bridges reward and avoidance systems with specific neuronal subsets to encourage appropriate motivational behaviours. Studies {{f}} have found that the central amygdala can activate or inhibit the somatostatin-expressing neurons to influence motivation to reach reward or persistence of reward seeking behaviours. The amygdala coordinates with appetitive and aversive motivation within this behavioural framework, overlapping in circuits (Dorofeikova et al., 2023). This challenges theories of "reward versus fear", instead suggesting disorders stem from imbalances in this dynamic system. This integrated role enables the amygdala to flexibly coordinate motivation and behaviour, ensuring rapid detection and context-appropriate action selection. Disorders of motivation, such as excessive avoidance or impaired reward pursuit, reflect imbalances in these dynamically regulated networks. {| class="wikitable" |+Table 1: Amygdala Subregions and Their Roles in Motivation and Avoidance !Subregion !Associated Behaviour !Motivation/Emotion Role !Supporting Evidence |- |Basolateral amygdala |Approach, reward seeking |Evaluates valence, modulates flexible motivation |Leitão et al. (2022); Fernando et al. (2013) |- |Central amygdala |Avoidance, defensive actions |Triggers rapid fear responses, triggers escape |Dorofeikova et al. (2023); Steinberg et al. (2020) |- |Nucleus accumbens |Reward reinforcement, social motivation |Integrates reward signals, supports approach |Schultz et al. (2019), Chang et al. (2022) |- |Bed nucleus of stria terminalis |Sustained anxiety, avoidance |Maintains long-term motivational states |Smith & Torregrossa (2021) |} === The amygdala's interaction with valence-specific circuits === Valence-specific projections highlight how the amygdala supports threat and reward motivation. The basolateral amygdala (BLA) contains neurons that encode positive or negative emotional value, sending signals along distinct pathways to drive either approach or avoidance (Smith & Torregrossa, 2021). Positive-valence BLA neurons project to the nucleus accumbens and prefrontal cortex, supporting reward-seeking and safety evaluation. Negative-valence BLA neurons target the central amygdala, periaqueductal gray, and bed nucleus of the stria terminalis to trigger defensive and avoidance responses, including sustained anxiety. This circuit organisation allows the amygdala to rapidly sort stimuli and generate context-appropriate behaviours. Such flexibility is crucial for survival and mental wellbeing (Smith & Torregrossa, 2021). When these pathways are dysregulated, it can lead to disorders such as anxiety (excessive avoidance) or addiction (excessive approach), highlighting the importance of understanding amygdala circuits for research and intervention. == Case study and quiz == {{RoundBoxTop|theme=1}} ;Case study Maya, a 22-year-old student, experienced an intense fear response during a fire that occurred during what she thought was a routine drill. Since, Maya exhibits learned avoidance behaviours, including avoiding buildings associated with the fire and anxiety in response to alarm-like sounds. fMRI scans reveal increased functional connectivity between the amygdala and nucleus accumbens, and her therapist is helping her reinterpret her fear through appraisal theory. ;Quiz <quiz display="simple"> {Which best explains how increased functional connectivity between the amygdala and nucleus accumbens may contribute to Maya’s avoidance?} - Enhanced connectivity allows for regulation of stress hormones, which decreases anxiety. + The amygdala signals threat detection, while nucleus accumbens reinforces avoidance behavior by associating it with emotional relief. - Functional connectivity between these regions leads to impaired memory consolidation, causing Maya to forget the event entirely. {''According to appraisal theory, Maya’s emotional response to fire alarms is automatic and independent of her cognitive interpretation of the event.''} + False - True {Which best describes how Maya’s avoidance of specific buildings can be understood through principles of learned behavior and neural mechanisms?} + Maya’s behavior is a form of operant conditioning, where avoidance is negatively reinforced by the reduction of fear. - The amygdala reduces Maya’s sensitivity to fear, making her more likely to explore feared environments. - Classical conditioning does not apply here, as Maya’s fear is entirely rational and context-specific. </quiz> {{RoundBoxBottom}} == Conclusion == The amygdala is central to processing environmental stimuli and motivating appetitive and aversive behaviours. It detects threat, instigating emotional response such as fear and anxiety, working with physiological systems to prepare the body for avoidance actions. By assigning salience to stimuli, the amygdala shapes motivational direction and influences decisions related to reward and threat, supporting approach or avoidance behaviours. Functionally, the amygdala circuits interact with other brain structures to weigh risk against reward, improving adaptive behavioural responses. These connections underlie both deliberate and immediate reactions, reflecting the complex integration of the emotional and cognitive processes. Understanding amygdala mechanisms is essential for appreciating why individuals develop avoidance behaviours and threat-related motivation. This information illuminates the origins of maladaptive responses and mental health disorders and informs future research aiming to develop targeting interventions and treatments to regulate dysfunctional motivational and emotional processes. Deepening awareness of these mechanisms supports personal growth, as understanding one's emotional responses can foster more adaptive self-regulation and resilience. == See also == * [[wikipedia:Amygdala|Amygdala]] (Wikipedia) * [[Motivation and emotion/Book/2014/Amygdala and emotion|Amygdala and emotion]] (Book chapter, 2014) * [[Motivation and emotion/Book/2014/Appraisal and emotion|Appraisal and emotion]] (Book chapter, 2014) * [[Motivation and emotion/Book/2019/Brain circuits and emotion|Brain circuits and emotion]] (Book chapter, 2019) * [[wikipedia:Classical_conditioning|Classical conditioning]] (Wikipedia) * [[wikipedia:Corticotropin-releasing_hormone|Corticotropin-releasing hormone]] (Wikipedia) * [[wikipedia:Empathy|Empathy]] (Wikipedia) * [[wikipedia:Lobes_of_the_brain|Lobes of the brain]] (Wikipedia) * [[wikipedia:Response_modulation_hypothesis|Response modulation hypothesis]] (Wikipedia) == References == {{Hanging indent|1= Blair, R. J. R. (2003). Neurobiological basis of psychopathy. ''British Journal of Psychiatry'', ''182''(1), 5–7. <nowiki>https://doi.org/10.1192/bjp.182.1.5</nowiki> Chang, S., Federica Fermani, Lao, C.-L., Huang, L., Jakovcevski, M., Rossella Di Giaimo, Gagliardi, M., Danusa Menegaz, Alexandru Adrian Hennrich, Ziller, M., Eder, M., Klein, R., Cai, N., & Deussing, J. M. (2022). Tripartite extended amygdala–basal ganglia CRH circuit drives locomotor activation and avoidance behavior. ''Science Advances'', ''8''(46). <nowiki>https://doi.org/10.1126/sciadv.abo1023</nowiki> Deming, P., & Koenigs, M. (2020). Functional neural correlates of psychopathy: a meta-analysis of MRI data. ''Translational Psychiatry'', ''10''(1). <nowiki>https://doi.org/10.1038/s41398-020-0816-8</nowiki> Dorofeikova, M., Stelly, C. E., Duong, A., Basavanhalli, S., Bean, E., Weissmuller, K., Sifnugel, N., Resendez, A., Corey, D. M., Tasker, J. G., & Fadok, J. P. (2023). The Role of Genetically Distinct Central Amygdala Neurons in Appetitive and Aversive Responding Assayed with a Novel Dual Valence Operant Conditioning Paradigm. ''ENeuro'', ''10''(9), ENEURO.0319-22.2023. <nowiki>https://doi.org/10.1523/eneuro.0319-22.2023</nowiki> Fernando, A. B. P., Murray, J. E., & Milton, A. L. (2013). The amygdala: securing pleasure and avoiding pain. ''Frontiers in Behavioral Neuroscience'', ''7'', 190. <nowiki>https://doi.org/10.3389/fnbeh.2013.00190</nowiki> Johnstone , T., Scherer , K., & Schorr, A. (2001). Appraisal Processes in Emotion: Theory, Methods, Research. In ''academic.oup.com''. Oxford University Press. <nowiki>https://academic.oup.com/book/53557</nowiki> Kim, J. J., & Jung, M. W. (2006). Neural circuits and mechanisms involved in Pavlovian fear conditioning: A critical review. ''Neuroscience & Biobehavioral Reviews'', ''30''(2), 188–202. <nowiki>https://doi.org/10.1016/j.neubiorev.2005.06.005</nowiki> Leitão, L., Burckhardt, M., & Vuilleumier, P. (2022). Amygdala in Action: Functional Connectivity during Approach and Avoidance Behaviors. ''Journal of Cognitive Neuroscience'', ''34''(5), 729–747. <nowiki>https://doi.org/10.1162/jocn_a_01800</nowiki> Life Science Databases. (2009). ''Amygdala Structure Highlighted Red''. <nowiki>https://en.wikiversity.org/wiki/File:Amygdala.png</nowiki> Lisk, S., Kadosh, K. C., Zich, C., Haller, S. PW., & Lau, J. YF. (2020). Training negative connectivity patterns between the dorsolateral prefrontal cortex and amygdala through fMRI-based neurofeedback to target adolescent socially-avoidant behaviour. ''Behaviour Research and Therapy'', ''135'', 103760. <nowiki>https://doi.org/10.1016/j.brat.2020.103760</nowiki> Makino, H. (2019). Top-down control: A unified principle of cortical learning. ''Neuroscience Research'', ''141'', 23–28. <nowiki>https://doi.org/10.1016/j.neures.2018.08.004</nowiki> Marsh, A. A., & Cardinale, E. M. (2012). When psychopathy impairs moral judgments: neural responses during judgments about causing fear. ''Social Cognitive and Affective Neuroscience'', ''9''(1), 3–11. <nowiki>https://doi.org/10.1093/scan/nss097</nowiki> Murray, R., Kutlikova, H., Brosch, T., & Sander, D. (2023). The Amygdala and Appraised Concern-Relevance: Initial Evidence That Intrinsic Motivation Modulates Amygdala Response to Otherwise Neutral Stimuli. ''Motivation Science'', ''9''(2). <nowiki>https://web-s-ebscohost-com.ezproxy.canberra.edu.au/ehost/pdfviewer/pdfviewer?vid=0&sid=16dcd072-14b0-4434-9827-fc957d8f7056%40redis</nowiki> Ressler, K. J. (2020). Amygdala activity, fear, and anxiety: Modulation by stress. ''Biological Psychiatry'', ''67''(12), 1117–1119. <nowiki>https://doi.org/10.1016/j.biopsych.2010.04.027</nowiki> Rosenberg, B. M., Moreira, G., Méndez, A. S., Saragosa-Harris, N. M., Gaines, E., Meredith, W. J., Waizman, Y., Ninova, E., & Silvers, J. A. (2024). Functional connectivity between the nucleus accumbens and amygdala underlies avoidance learning during adolescence: Implications for developmental psychopathology. ''Development and Psychopathology'', 1–13. <nowiki>https://doi.org/10.1017/s095457942400141x</nowiki> Schlund, M. W., & Cataldo, M. F. (2010). Amygdala involvement in human avoidance, escape and approach behavior. ''NeuroImage'', ''53''(2), 769–776. <nowiki>https://doi.org/10.1016/j.neuroimage.2010.06.058</nowiki> Schultz, J., Willems, T., Gädeke, M., Chakkour, G., Franke, A., Weber, B., & Hurlemann, R. (2019). A human subcortical network underlying social avoidance revealed by risky economic choices. ''ELife'', ''8''. <nowiki>https://doi.org/10.7554/elife.45249</nowiki> Shane, M. S., & Groat, L. L. (2018). Capacity for upregulation of emotional processing in psychopathy: all you have to do is ask. ''Social Cognitive and Affective Neuroscience'', ''13''(11), 1163–1176. <nowiki>https://doi.org/10.1093/scan/nsy088</nowiki> Smith, D. M., & Torregrossa, M. M. (2021). Valence encoding in the amygdala influences motivated behavior. ''Behavioural Brain Research'', ''411'', 113370. <nowiki>https://doi.org/10.1016/j.bbr.2021.113370</nowiki> Steinberg, E. E., Gore, F., Heifets, B. D., Taylor, M. D., Norville, Z. C., Beier, K. T., Földy, C., Lerner, T. N., Luo, L., Deisseroth, K., & Malenka, R. C. (2020). Amygdala-Midbrain Connections Modulate Appetitive and Aversive Learning. ''Neuron'', ''106''(6), 1026-1043.e9. <nowiki>https://doi.org/10.1016/j.neuron.2020.03.016</nowiki> Tsigos, C., Kyrou, I., Kassi, E., & Chrousos, G. P. (2020). ''Stress, endocrine physiology and pathophysiology''. Nih.gov; MDText.com, Inc. <nowiki>https://www.ncbi.nlm.nih.gov/books/NBK278995/</nowiki> University of Wisconsin-Madison. (2017, November 7). ''Psychopaths’ Brains Show Differences in Structure and Function''. School of Medicine and Public Health. <nowiki>https://www.med.wisc.edu/news/psychopaths-brains-differences-structure-function/</nowiki> Yarwood, M. (2001). Component Process Model (CPM; Scherer, 2001). ''Psu.pb.unizin.org''. <nowiki>https://psu.pb.unizin.org/psych425/chapter/component-process-model-cpm/</nowiki> }} == External links == * [https://elifesciences.org/articles/45249 A human subcortical network underlying social avoidance revealed by risky economic choices] (Schultz et al., 2019) * [[doi:10.1162/jocn_a_01800|Amygdala in action: functional connectivity during approach and avoidance behaviours]] (Leitão et al., 2022) * [https://pmc.ncbi.nlm.nih.gov/articles/PMC3854486/ Amygdala: securing pleasure and avoiding pain] (Fernando et al., 2013) * [https://www.cambridge.org/core/journals/development-and-psychopathology/article/functional-connectivity-between-the-nucleus-accumbens-and-amygdala-underlies-avoidance-learning-during-adolescence-implications-for-developmental-psychopathology/0FEAD5257C212F6EAC7B8AC75F0842A3 Functional connectivity between nucleus accumbens and amygdala] (Rosenberg et al., 2024) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Amygdala]] [[Category:Motivation and emotion/Book/Behaviour]] [[Category:Motivation and emotion/Book/Fear]] boa9hrvfvs0cuvcnf56tc998rdzivp7 0 326060 2835138 2832826 2026-09-30T08:51:26Z Tsaag Valren 130031 /* Use of Wikidata and Wikiversity for research */ 2835138 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 book|url=https://doi.org/10.1007/978-3-030-89460-3_2|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021|publisher=Springer International Publishing|isbn=978-3-030-89460-3|editor-last=Heffron|editor-first=Raphael J.|location=Cham|pages=9–19|language=en|doi=10.1007/978-3-030-89460-3_2}}</ref><ref>{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.sciencedirect.com/science/article/pii/S0301421518302301|journal=Energy Policy|volume=119|pages=1–7|doi=10.1016/j.enpol.2018.04.014|issn=0301-4215}}</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=":15">{{Cite journal|date=2020-03-01|title=Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory|url=https://www.sciencedirect.com/science/article/abs/pii/S0040162518316111|journal=Technological Forecasting and Social Change|language=en-US|volume=152|pages=119894|doi=10.1016/j.techfore.2019.119894|issn=0040-1625}}</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</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 journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </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 journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</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=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</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 journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</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. === 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 journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</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=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</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=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{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>. 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=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{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|doi=10.1016/J.ERSS.2021.102444}}</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="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</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="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, 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=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. 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, and a "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=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</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 journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</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=":25" /><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 journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</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>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</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. 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>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</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. === 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>{{Cite journal|last=West|first=Robert|last2=Godinho|first2=Cristina A.|last3=Bohlen|first3=Lauren Connell|last4=Carey|first4=Rachel N.|last5=Hastings|first5=Janna|last6=Lefevre|first6=Carmen E.|last7=Michie|first7=Susan|date=2019-05|title=Development of a formal system for representing behaviour-change theories|url=https://www.nature.com/articles/s41562-019-0561-2|journal=Nature Human Behaviour|language=en|publisher=Nature Publishing Group|volume=3|issue=5|pages=526–536|doi=10.1038/s41562-019-0561-2|issn=2397-3374}}</ref>,<ref>Hale, J., Hastings, J., West, R., Lefevre, C. E., Direito, A., Connell Bohlen, L., Godinho, C., Anderson, N., Zink, S., Goarke, H., and Michie, S. (2020) An ontology-based modelling system (OBMS) for representing behaviour change theories applied to 76 theories [version 1; peer review: 2 approved]. https://wellcomeopenresearch.org/articles/5-177</ref>. 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=":4" /> 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=":0" />). 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 journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</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, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. 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>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</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 journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</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 statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *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}}). === 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 journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</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 web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</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 journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</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=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|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 journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</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 journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</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 journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</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 journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</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=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. 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=":24" />. 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}} bc6kcmya63cu2mfhp4damazf6f3sjij 2835139 2835138 2026-09-30T09:01:03Z ~2026-52677-87 3111871 /* Use of Wikidata and Wikiversity for research */ 2835139 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 book|url=https://doi.org/10.1007/978-3-030-89460-3_2|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021|publisher=Springer International Publishing|isbn=978-3-030-89460-3|editor-last=Heffron|editor-first=Raphael J.|location=Cham|pages=9–19|language=en|doi=10.1007/978-3-030-89460-3_2}}</ref><ref>{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.sciencedirect.com/science/article/pii/S0301421518302301|journal=Energy Policy|volume=119|pages=1–7|doi=10.1016/j.enpol.2018.04.014|issn=0301-4215}}</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=":15">{{Cite journal|date=2020-03-01|title=Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory|url=https://www.sciencedirect.com/science/article/abs/pii/S0040162518316111|journal=Technological Forecasting and Social Change|language=en-US|volume=152|pages=119894|doi=10.1016/j.techfore.2019.119894|issn=0040-1625}}</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</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 journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </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 journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</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=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</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 journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</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. === 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 journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</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=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</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=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{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>. 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=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{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|doi=10.1016/J.ERSS.2021.102444}}</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="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</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="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, 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=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. 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, and a "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=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</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 journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</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=":25" /><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 journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</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>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</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. 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>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</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. 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. === 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>{{Cite journal|last=West|first=Robert|last2=Godinho|first2=Cristina A.|last3=Bohlen|first3=Lauren Connell|last4=Carey|first4=Rachel N.|last5=Hastings|first5=Janna|last6=Lefevre|first6=Carmen E.|last7=Michie|first7=Susan|date=2019-05|title=Development of a formal system for representing behaviour-change theories|url=https://www.nature.com/articles/s41562-019-0561-2|journal=Nature Human Behaviour|language=en|publisher=Nature Publishing Group|volume=3|issue=5|pages=526–536|doi=10.1038/s41562-019-0561-2|issn=2397-3374}}</ref>,<ref>Hale, J., Hastings, J., West, R., Lefevre, C. E., Direito, A., Connell Bohlen, L., Godinho, C., Anderson, N., Zink, S., Goarke, H., and Michie, S. (2020) An ontology-based modelling system (OBMS) for representing behaviour change theories applied to 76 theories [version 1; peer review: 2 approved]. https://wellcomeopenresearch.org/articles/5-177</ref>. 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=":4" /> 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=":0" />). 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 journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</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, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. 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>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</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 journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</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 statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *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}}). === 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 journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</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 web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</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 journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</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=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|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 journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</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 journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</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 journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</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 journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</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=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. 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=":24" />. 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}} qappue56ykt0ibsr88g2zv745rnjbge 2835142 2835139 2026-09-30T09:03:52Z ~2026-52677-87 3111871 /* Use of Wikidata and Wikiversity for research */ 2835142 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 book|url=https://doi.org/10.1007/978-3-030-89460-3_2|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021|publisher=Springer International Publishing|isbn=978-3-030-89460-3|editor-last=Heffron|editor-first=Raphael J.|location=Cham|pages=9–19|language=en|doi=10.1007/978-3-030-89460-3_2}}</ref><ref>{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.sciencedirect.com/science/article/pii/S0301421518302301|journal=Energy Policy|volume=119|pages=1–7|doi=10.1016/j.enpol.2018.04.014|issn=0301-4215}}</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=":15">{{Cite journal|date=2020-03-01|title=Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory|url=https://www.sciencedirect.com/science/article/abs/pii/S0040162518316111|journal=Technological Forecasting and Social Change|language=en-US|volume=152|pages=119894|doi=10.1016/j.techfore.2019.119894|issn=0040-1625}}</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</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 journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </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 journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</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=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</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 journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</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. === 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 journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</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=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</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=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{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>. 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=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{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|doi=10.1016/J.ERSS.2021.102444}}</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="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</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="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, 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=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. 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, and a "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=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</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 journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</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=":25" /><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 journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</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>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</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. 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>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</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. 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. === 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>{{Cite journal|last=West|first=Robert|last2=Godinho|first2=Cristina A.|last3=Bohlen|first3=Lauren Connell|last4=Carey|first4=Rachel N.|last5=Hastings|first5=Janna|last6=Lefevre|first6=Carmen E.|last7=Michie|first7=Susan|date=2019-05|title=Development of a formal system for representing behaviour-change theories|url=https://www.nature.com/articles/s41562-019-0561-2|journal=Nature Human Behaviour|language=en|publisher=Nature Publishing Group|volume=3|issue=5|pages=526–536|doi=10.1038/s41562-019-0561-2|issn=2397-3374}}</ref>,<ref>Hale, J., Hastings, J., West, R., Lefevre, C. E., Direito, A., Connell Bohlen, L., Godinho, C., Anderson, N., Zink, S., Goarke, H., and Michie, S. (2020) An ontology-based modelling system (OBMS) for representing behaviour change theories applied to 76 theories [version 1; peer review: 2 approved]. https://wellcomeopenresearch.org/articles/5-177</ref>. 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=":4" /> 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=":0" />). 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 journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</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, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. 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>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</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 journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</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 statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *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}}). === 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 journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</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 web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</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 journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</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=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|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 journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</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 journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</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 journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</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 journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</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=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. 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=":24" />. 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}} 78rqyo2c4154xzshdkij4nt3uqtnwre 2835144 2835142 2026-09-30T09:16:02Z Amélie E. Pereira 3042711 /* Use of Wikidata and Wikiversity for research */ 2835144 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 book|url=https://doi.org/10.1007/978-3-030-89460-3_2|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021|publisher=Springer International Publishing|isbn=978-3-030-89460-3|editor-last=Heffron|editor-first=Raphael J.|location=Cham|pages=9–19|language=en|doi=10.1007/978-3-030-89460-3_2}}</ref><ref>{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.sciencedirect.com/science/article/pii/S0301421518302301|journal=Energy Policy|volume=119|pages=1–7|doi=10.1016/j.enpol.2018.04.014|issn=0301-4215}}</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=":15">{{Cite journal|date=2020-03-01|title=Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory|url=https://www.sciencedirect.com/science/article/abs/pii/S0040162518316111|journal=Technological Forecasting and Social Change|language=en-US|volume=152|pages=119894|doi=10.1016/j.techfore.2019.119894|issn=0040-1625}}</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</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 journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </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 journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</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=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</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 journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</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. === 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 journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</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=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</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=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{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>. 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=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{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|doi=10.1016/J.ERSS.2021.102444}}</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="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</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="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, 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=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. 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, and a "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=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</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 journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</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=":25" /><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 journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</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>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</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. 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>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</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. 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. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. 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>{{Cite journal|last=West|first=Robert|last2=Godinho|first2=Cristina A.|last3=Bohlen|first3=Lauren Connell|last4=Carey|first4=Rachel N.|last5=Hastings|first5=Janna|last6=Lefevre|first6=Carmen E.|last7=Michie|first7=Susan|date=2019-05|title=Development of a formal system for representing behaviour-change theories|url=https://www.nature.com/articles/s41562-019-0561-2|journal=Nature Human Behaviour|language=en|publisher=Nature Publishing Group|volume=3|issue=5|pages=526–536|doi=10.1038/s41562-019-0561-2|issn=2397-3374}}</ref>,<ref>Hale, J., Hastings, J., West, R., Lefevre, C. E., Direito, A., Connell Bohlen, L., Godinho, C., Anderson, N., Zink, S., Goarke, H., and Michie, S. (2020) An ontology-based modelling system (OBMS) for representing behaviour change theories applied to 76 theories [version 1; peer review: 2 approved]. https://wellcomeopenresearch.org/articles/5-177</ref>. 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=":4" /> 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=":0" />). 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 journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</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, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. 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>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</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 journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</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 statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *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}}). === 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 journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</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 web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</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 journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</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=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|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 journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</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 journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</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 journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</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 journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</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=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. 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=":24" />. 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}} h6dx3jaepni79rm6vvgjz4g684kweqx 2835146 2835144 2026-09-30T09:44:48Z Amélie E. Pereira 3042711 /* Knowledge graphs for research */ 2835146 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 book|url=https://doi.org/10.1007/978-3-030-89460-3_2|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021|publisher=Springer International Publishing|isbn=978-3-030-89460-3|editor-last=Heffron|editor-first=Raphael J.|location=Cham|pages=9–19|language=en|doi=10.1007/978-3-030-89460-3_2}}</ref><ref>{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.sciencedirect.com/science/article/pii/S0301421518302301|journal=Energy Policy|volume=119|pages=1–7|doi=10.1016/j.enpol.2018.04.014|issn=0301-4215}}</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=":15">{{Cite journal|date=2020-03-01|title=Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory|url=https://www.sciencedirect.com/science/article/abs/pii/S0040162518316111|journal=Technological Forecasting and Social Change|language=en-US|volume=152|pages=119894|doi=10.1016/j.techfore.2019.119894|issn=0040-1625}}</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</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 journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </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 journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</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=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</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 journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</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. === 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 journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</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=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</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=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{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>. 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=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{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|doi=10.1016/J.ERSS.2021.102444}}</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="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</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="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, 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=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. 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, and a "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=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</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 journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</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=":25" /><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 journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</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>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</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. 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>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</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. 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. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. 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>{{Cite journal|last=West|first=Robert|last2=Godinho|first2=Cristina A.|last3=Bohlen|first3=Lauren Connell|last4=Carey|first4=Rachel N.|last5=Hastings|first5=Janna|last6=Lefevre|first6=Carmen E.|last7=Michie|first7=Susan|date=2019-05|title=Development of a formal system for representing behaviour-change theories|url=https://www.nature.com/articles/s41562-019-0561-2|journal=Nature Human Behaviour|language=en|publisher=Nature Publishing Group|volume=3|issue=5|pages=526–536|doi=10.1038/s41562-019-0561-2|issn=2397-3374}}</ref>,<ref>Hale, J., Hastings, J., West, R., Lefevre, C. E., Direito, A., Connell Bohlen, L., Godinho, C., Anderson, N., Zink, S., Goarke, H., and Michie, S. (2020) An ontology-based modelling system (OBMS) for representing behaviour change theories applied to 76 theories [version 1; peer review: 2 approved]. https://wellcomeopenresearch.org/articles/5-177</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. 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=":4" /> 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=":0" />). 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 journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</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, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. 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>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</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 journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</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 statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *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}}). === 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 journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</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 web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</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 journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</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=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|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 journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</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 journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</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 journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</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 journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</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=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. 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=":24" />. 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}} 2sfe4cmvq9vrix52i4kbjw22l0y0688 2835152 2835146 2026-09-30T10:22:38Z Amélie E. Pereira 3042711 /* Knowledge graphs for research */ 2835152 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 book|url=https://doi.org/10.1007/978-3-030-89460-3_2|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021|publisher=Springer International Publishing|isbn=978-3-030-89460-3|editor-last=Heffron|editor-first=Raphael J.|location=Cham|pages=9–19|language=en|doi=10.1007/978-3-030-89460-3_2}}</ref><ref>{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.sciencedirect.com/science/article/pii/S0301421518302301|journal=Energy Policy|volume=119|pages=1–7|doi=10.1016/j.enpol.2018.04.014|issn=0301-4215}}</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=":15">{{Cite journal|date=2020-03-01|title=Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory|url=https://www.sciencedirect.com/science/article/abs/pii/S0040162518316111|journal=Technological Forecasting and Social Change|language=en-US|volume=152|pages=119894|doi=10.1016/j.techfore.2019.119894|issn=0040-1625}}</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</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 journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </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 journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</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=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</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 journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</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. === 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 journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</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=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</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=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{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>. 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=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{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|doi=10.1016/J.ERSS.2021.102444}}</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="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</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="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, 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=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. 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, and a "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=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</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 journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</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=":25" /><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 journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</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>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</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. 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>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</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. 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. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. 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=":4" /> 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=":0" />). 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 journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</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, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. 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>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</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 journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</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 statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *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}}). === 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 journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</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 web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</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 journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</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=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|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 journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</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 journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</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 journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</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 journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</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=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. 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=":24" />. 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}} 81m55caitb9nsahnmxdh8xdfp9mq3qf 2835153 2835152 2026-09-30T10:25:20Z Amélie E. Pereira 3042711 /* Introduction */ mef 2835153 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=":15">{{Cite journal|date=2020-03-01|title=Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory|url=https://www.sciencedirect.com/science/article/abs/pii/S0040162518316111|journal=Technological Forecasting and Social Change|language=en-US|volume=152|pages=119894|doi=10.1016/j.techfore.2019.119894|issn=0040-1625}}</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</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 journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </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 journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</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=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</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 journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</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. === 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 journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</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=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</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=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{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>. 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=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{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|doi=10.1016/J.ERSS.2021.102444}}</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="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</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="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, 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=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. 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, and a "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=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</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 journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</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=":25" /><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 journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</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>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</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. 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>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</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. 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. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. 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=":4" /> 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=":0" />). 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 journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</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, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. 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>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</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 journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</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 statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *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}}). === 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 journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</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 web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</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 journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</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=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|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 journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</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 journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</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 journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</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 journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</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=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. 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=":24" />. 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}} 6psg0syyr43wc3hdlss9nz9ed1ek0nw 2835154 2835153 2026-09-30T10:36:07Z Amélie E. Pereira 3042711 /* Introduction */ 2835154 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=":15">{{Cite journal|date=2020-03-01|title=Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory|url=https://www.sciencedirect.com/science/article/abs/pii/S0040162518316111|journal=Technological Forecasting and Social Change|language=en-US|volume=152|pages=119894|doi=10.1016/j.techfore.2019.119894|issn=0040-1625}}</ref><ref name=":16">{{Cite journal|date=2023-08-01|title=A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration|url=https://www.sciencedirect.com/science/article/pii/S0040162523003244|journal=Technological Forecasting and Social Change|language=en-US|volume=193|pages=122639|doi=10.1016/j.techfore.2023.122639|issn=0040-1625}}</ref><ref name=":17">{{Cite journal|last=Sovacool|first=Benjamin K.|last2=Geels|first2=Frank W.|last3=Andersen|first3=Allan Dahl|last4=Grubb|first4=Michael|last5=Jordan|first5=Andrew J.|last6=Kern|first6=Florian|last7=Kivimaa|first7=Paula|last8=Lockwood|first8=Matthew|last9=Markard|first9=Jochen|date=2025-03-01|title=The acceleration of low-carbon transitions: Insights, concepts, challenges, and new directions for research|url=https://www.sciencedirect.com/science/article/pii/S2214629625000295|journal=Energy Research & Social Science|volume=121|pages=103948|doi=10.1016/j.erss.2025.103948|issn=2214-6296}}</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 journal|last=Kepes|first=Sven|last2=Bennett|first2=Andrew A.|last3=McDaniel|first3=Michael A.|date=2014-09|title=Evidence-Based Management and the Trustworthiness of Our Cumulative Scientific Knowledge: Implications for Teaching, Research, and Practice|url=https://journals.aom.org/doi/10.5465/amle.2013.0193|journal=Academy of Management Learning & Education|volume=13|issue=3|pages=446–466|doi=10.5465/amle.2013.0193|issn=1537-260X}}</ref><ref>Pfeffer, J., & Sutton, R. I. (2006). Evidence-Based Management. Harvard Business Review, 13. </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 journal|last=Bornmann|first=Lutz|last2=Mutz|first2=Rüdiger|date=2015|title=Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.23329|journal=Journal of the Association for Information Science and Technology|language=en|volume=66|issue=11|pages=2215–2222|doi=10.1002/asi.23329|issn=2330-1643}}</ref><ref name=":23">{{Cite journal|last=Hanson|first=Mark A.|last2=Barreiro|first2=Pablo Gómez|last3=Crosetto|first3=Paolo|last4=Brockington|first4=Dan|date=2024-11-01|title=The strain on scientific publishing|url=https://doi.org/10.1162/qss_a_00327|journal=Quantitative Science Studies|volume=5|issue=4|pages=823–843|doi=10.1162/qss_a_00327|issn=2641-3337}}</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=":23" />. This intensification of academic work is being denounced as detrimental to the deep cognitive process needed to actually produce interesting knowledge<ref>{{Cite journal|last=Hartman|first=Yvonne|last2=Darab|first2=Sandy|date=2012-01-01|title=A Call for Slow Scholarship: A Case Study on the Intensification of Academic Life and Its Implications for Pedagogy|url=https://doi.org/10.1080/10714413.2012.643740|journal=Review of Education, Pedagogy, and Cultural Studies|volume=34|issue=1-2|pages=49–60|doi=10.1080/10714413.2012.643740|issn=1071-4413}}</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 journal|last=L.|first=Mobley, David|last2=M.|first2=Zuckerman, Daniel|date=2015-02-03|title=A proposal for regularly updated review/survey articles: "Perpetual Reviews"|url=https://arxiv.org/abs/1502.01329|journal=arXiv.org|language=en|doi=10.48550/arXiv.1502.01329}}</ref> and for shifting from static text format publications to dynamic knowledge mapping<ref name=":11">{{Cite web|url=https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/|title=The death of the literature review and the rise of the dynamic knowledge map - LSE Impact|last=Taster|date=2019-05-14|website=LSE Impact - Understanding impact and practice in academic research|access-date=2026-06-23}}</ref>. This call is being answered through the development of living literature reviews that can be updated dynamically with new knowledge (examples : <ref>{{Cite journal|last=Elliott|first=Julian H.|last2=Synnot|first2=Anneliese|last3=Turner|first3=Tari|last4=Simmonds|first4=Mark|last5=Akl|first5=Elie A.|last6=McDonald|first6=Steve|last7=Salanti|first7=Georgia|last8=Meerpohl|first8=Joerg|last9=MacLehose|first9=Harriet|date=2017-11|title=Living systematic review: 1. Introduction—the why, what, when, and how|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435617306364|journal=Journal of Clinical Epidemiology|volume=91|pages=23–30|doi=10.1016/j.jclinepi.2017.08.010|issn=0895-4356}}</ref>,<ref>{{Cite journal|last=Uttley|first=Lesley|last2=Quintana|first2=Daniel S.|last3=Montgomery|first3=Paul|last4=Carroll|first4=Christopher|last5=Page|first5=Matthew J.|last6=Falzon|first6=Louise|last7=Sutton|first7=Anthea|last8=Moher|first8=David|date=2023-04|title=The problems with systematic reviews: a living systematic review|url=https://linkinghub.elsevier.com/retrieve/pii/S0895435623000112|journal=Journal of Clinical Epidemiology|volume=156|pages=30–41|doi=10.1016/j.jclinepi.2023.01.011|issn=0895-4356}}</ref>,<ref name=":18">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</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. === 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 journal|last=Haley|first=Usha C. V.|date=2023-09-01|title=Triviality and the Search for Scholarly Impact|url=https://doi.org/10.1177/01708406231175292|journal=Organization Studies|language=EN|volume=44|issue=9|pages=1547–1550|doi=10.1177/01708406231175292|issn=0170-8406}}</ref>. Wikipedia is a key knowledge dissemination platform widely used by students<ref>{{Cite journal|last=Sunvy|first=Ahmed Shafkat|last2=Reza|first2=Raiyan Bin|date=2023-04-12|title=Students’ Perception of Wikipedia as an Academic Information Source|url=https://ejournal.undiksha.ac.id/index.php/IJERR/article/view/57572|journal=Indonesian Journal Of Educational Research and Review|volume=6|issue=1|pages=134–147|doi=10.23887/ijerr.v6i1.57572|issn=2621-8984}}</ref> and scientists themselves, as shown by the fact that articles used as sources on Wikipedia are more cited in the literature<ref>{{Cite journal|last=Thompson|first=Neil|last2=Hanley|first2=Douglas|date=2017|title=Science Is Shaped by Wikipedia: Evidence from a Randomized Control Trial|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3039505|journal=SSRN Electronic Journal|doi=10.2139/ssrn.3039505|issn=1556-5068}}</ref> and that some scholars cite directly Wikipedia<ref>{{Cite journal|last=Dooley|first=Patricia L.|date=2010-07-07|title=Wikipedia and the two-faced professoriate|url=https://doi.org/10.1145/1832772.1832803|journal=Proceedings of the 6th International Symposium on Wikis and Open Collaboration|series=WikiSym '10|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=1–2|doi=10.1145/1832772.1832803|isbn=978-1-4503-0056-8}}</ref>. However, scientists do not naturally contribute to wikimedia projects as part of their work because of lack of incentives<ref>{{Cite journal|last=Chen|first=Yan|last2=Farzan|first2=Rosta|last3=Kraut|first3=Robert|last4=YeckehZaare|first4=Iman|last5=Zhang|first5=Ark Fangzhou|date=2024-05|title=Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia|url=https://pubsonline.informs.org/doi/10.1287/mnsc.2023.4852|journal=Management Science|volume=70|issue=5|pages=3264–3280|doi=10.1287/mnsc.2023.4852|issn=0025-1909}}</ref>,<ref>{{Cite journal|last=Kincaid|first=Dustin W.|last2=Beck|first2=Whitney S.|last3=Brandt|first3=Jessica E.|last4=Mars Brisbin|first4=Margaret|last5=Farrell|first5=Kaitlin J.|last6=Hondula|first6=Kelly L.|last7=Larson|first7=Erin I.|last8=Shogren|first8=Arial J.|date=2021|title=Wikipedia can help resolve information inequality in the aquatic sciences|url=https://onlinelibrary.wiley.com/doi/abs/10.1002/lol2.10168|journal=Limnology and Oceanography Letters|language=en|volume=6|issue=1|pages=18–23|doi=10.1002/lol2.10168|issn=2378-2242}}</ref>, but also other factors such as lack of time, lack of recognition and fit with scholarly workflow<ref name=":10">Taraborelli, D., Mietchen, D., Alevizou, P., & Gill, A. (2011, August). Expert participation on Wikipedia: Barriers and opportunities. Wikimania 2011, Haifa, Israel. <nowiki>http://upload.wikimedia.org/wikipedia/commons/4/4f/Expert_Participation_Survey_-_Wikimania_2011.pdf</nowiki> </ref>. In addition, expert participation is not immune to the gender gap<ref name=":10" />. Because of gender segregation in disciplines<ref>{{Cite journal|last=Ceci|first=Stephen J.|last2=Ginther|first2=Donna K.|last3=Kahn|first3=Shulamit|last4=Williams|first4=Wendy M.|date=2014-12-01|title=Women in Academic Science: A Changing Landscape|url=https://doi.org/10.1177/1529100614541236|journal=Psychological Science in the Public Interest|language=EN|volume=15|issue=3|pages=75–141|doi=10.1177/1529100614541236|issn=1529-1006}}</ref>, this may be detrimental to the content coverage on “female” topics<ref>{{Cite journal|last=Lam|first=Shyong (Tony) K.|last2=Uduwage|first2=Anuradha|last3=Dong|first3=Zhenhua|last4=Sen|first4=Shilad|last5=Musicant|first5=David R.|last6=Terveen|first6=Loren|last7=Riedl|first7=John|date=2011-10-03|title=WP:clubhouse?: an exploration of Wikipedia's gender imbalance|url=https://dl.acm.org/doi/10.1145/2038558.2038560|language=en|publisher=ACM|pages=1–10|doi=10.1145/2038558.2038560|isbn=978-1-4503-0909-7}}</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=":0">{{Cite journal|last=McCauley|first=Darren|last2=Heffron|first2=Raphael|date=2018-08-01|title=Just transition: Integrating climate, energy and environmental justice|url=https://www.wikidata.org/wiki/Q129947262|journal=Energy Policy|language=English|volume=119|pages=1–7|doi=10.1016/J.ENPOL.2018.04.014}}</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=":0" />. However, scholars have broadened the use of this term to develop frameworks for analysing issues of fairness in these transitions<ref name=":0" />. The concept of just transition can be used to bridge various bodies of scholarship : climate justice, environmental justiceand energy justice<ref name=":3">{{Cite journal|last=Wang|first=Xinxin|last2=Lo|first2=Kevin|date=2021-12-01|title=Just transition: A conceptual review|url=https://www.wikidata.org/wiki/Q137209041|journal=Energy Research & Social Science|volume=82|pages=102291|doi=10.1016/J.ERSS.2021.102291}}</ref><ref name=":1">{{Cite book|url=https://www.wikidata.org/wiki/Q134545572|title=What is the “Just Transition”?|last=Heffron|first=Raphael J.|date=2021-01-01|pages=9–19|language=English}}</ref> and take into account various aspects of justice including distributional justice, procedural justice, restorative justice, recognition justice<ref name=":0" /><ref name=":3" /><ref name=":1" /><ref name=":4">{{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>. 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=":15" /><ref name=":16" /><ref name=":17" /> and fragmented results coming from various disciplines<ref name=":20">{{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|doi=10.1016/J.ERSS.2021.102444}}</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="Why4">{{Cite journal |last=Akl |first=Elie A. |last2=Meerpohl |first2=Joerg J. |last3=Elliott |first3=Julian |last4=Kahale |first4=Lara A. |last5=Schünemann |first5=Holger J. |last6=Agoritsas |first6=Thomas |last7=Hilton |first7=John |last8=Perron |first8=Caroline |last9=Akl |first9=Elie |last10=Hodder |first10=Rebecca |last11=Pestridge |first11=Charlotte |last12=Albrecht |first12=Lauren |last13=Horsley |first13=Tanya |last14=Platt |first14=Joanne |last15=Armstrong |first15=Rebecca |date=2017-11 |title=Living systematic reviews: 4. Living guideline recommendations |url=https://www.wikidata.org/wiki/Q50084143 |journal=Journal of Clinical Epidemiology |language=en |volume=91 |pages=47–53 |doi=10.1016/j.jclinepi.2017.08.009}}</ref><ref name=":6">{{Citation|title=Living Systematic Reviews|url=https://doi.org/10.1007/978-1-0716-1566-9_7|publisher=Springer US|work=Meta-Research: Methods and Protocols|date=2022|access-date=2026-01-16|place=New York, NY|isbn=978-1-0716-1566-9|pages=121–134|doi=10.1007/978-1-0716-1566-9_7|language=en|first=Mark|last=Simmonds|first2=Julian H.|last2=Elliott|first3=Anneliese|last3=Synnot|first4=Tari|last4=Turner|editor-first=Evangelos|editor-last=Evangelou|editor2-first=Areti Angeliki|editor2-last=Veroniki}}</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="Why4" /><ref name=":6" />. Living systematic reviews exists to address this common problem<ref name="Why1" /><ref name="Why4" /><ref name=":6" /><ref name=":2">https://blogs.lse.ac.uk/impactofsocialsciences/2019/05/14/the-death-of-the-literature-review-and-the-rise-of-the-dynamic-knowledge-map/</ref>. It is therefore particularly useful in rapidly evolving fields of research<ref name="Why1" /><ref name=":6" />, 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=":12">{{Cite journal|last=Krlev|first=Gorgi|last2=Hannigan|first2=Tim|last3=Spicer|first3=André|date=2025-01|title=What Makes a Good Review Article? Empirical Evidence From Management and Organization Research|url=https://journals.aom.org/doi/abs/10.5465/annals.2021.0051|journal=Academy of Management Annals|volume=19|issue=1|pages=376–403|doi=10.5465/annals.2021.0051|issn=1941-6520}}</ref>. Advances in AI could render certain older methodological types of living systematic reviews obsoletes<ref name=":12" />, as IA are useful to extract, filter and classify datas<ref>{{Cite web|url=https://arxiv.org/abs/2504.20276v1|title=Enhancing Systematic Reviews with Large Language Models: Using GPT-4 and Kimi|last=Kaptur|first=Dandan Chen|last2=Huang|first2=Yue|date=2025-04-28|website=arXiv.org|language=en|doi=10.48550/arXiv.2504.20276|access-date=2026-01-21|last3=Ji|first3=Xuejun Ryan|last4=Guo|first4=Yanhui|last5=Kaptur|first5=Bradley}}</ref>. [[Large language models]] (LLM) are "on the rise" (2025), but not yet integrated into tested and validated methodologies<ref name=":13">{{Cite journal |last=Lieberum |first=Judith-Lisa |last2=Toews |first2=Markus |last3=Metzendorf |first3=Maria-Inti |last4=Heilmeyer |first4=Felix |last5=Siemens |first5=Waldemar |last6=Haverkamp |first6=Christian |last7=Böhringer |first7=Daniel |last8=Meerpohl |first8=Joerg J. |last9=Eisele-Metzger |first9=Angelika |date=2025-05 |title=Large language models for conducting systematic reviews: on the rise, but not yet ready for use—a scoping review |url=https://www.wikidata.org/wiki/Q134545593|journal=Journal of Clinical Epidemiology |language=en |volume=181 |pages=111746 |doi=10.1016/j.jclinepi.2025.111746}}</ref>. Human validation stays notably necessary<ref>{{Cite journal|last=Alshami|first=Ahmad|last2=Elsayed|first2=Moustafa|last3=Ali|first3=Eslam|last4=Eltoukhy|first4=Abdelrahman E. E.|last5=Zayed|first5=Tarek|date=2023-07-09|title=Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions|url=https://www.mdpi.com/2079-8954/11/7/351|journal=Systems|language=en|volume=11|issue=7|pages=351|doi=10.3390/systems11070351|issn=2079-8954}}</ref>,<ref name=":13" />. 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, and a "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=":9">{{Cite journal|last=Hogan|first=Aidan|last2=Blomqvist|first2=Eva|last3=Cochez|first3=Michael|last4=D’amato|first4=Claudia|last5=Melo|first5=Gerard De|last6=Gutierrez|first6=Claudio|last7=Kirrane|first7=Sabrina|last8=Gayo|first8=José Emilio Labra|last9=Navigli|first9=Roberto|date=2022-05-31|title=Knowledge Graphs|url=https://dl.acm.org/doi/10.1145/3447772|journal=ACM Computing Surveys|language=en|volume=54|issue=4|pages=1–37|doi=10.1145/3447772|issn=0360-0300}}</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 journal|last=Meijer|first=David|last2=Beniddir|first2=Mehdi A.|last3=Coley|first3=Connor W.|last4=Mejri|first4=Yassine M.|last5=Öztürk|first5=Meltem|last6=Hooft|first6=Justin J. J. van der|last7=Medema|first7=Marnix H.|last8=Skiredj|first8=Adam|date=2025-04-16|title=Empowering natural product science with AI: leveraging multimodal data and knowledge graphs|url=https://pubs.rsc.org/en/content/articlelanding/2025/np/d4np00008k|journal=Natural Product Reports|language=en|volume=42|issue=4|pages=654–662|doi=10.1039/D4NP00008K|issn=1460-4752}}</ref> Such graphs have a strong potential to conduct knowledge synthesis<ref name=":11" /><ref name="Fotopoulou">{{Cite journal|first1=Eleni |last1=Fotopoulou|first2=Ioanna|last2=Mandilara|first3=Anastasios|last3=Zafeiropoulos|first4=Chrysi|last4=Laspidou|first5=Giannis |last5=Adamos|first6=Phoebe|last6=Koundouri|first7=Symeon|last7=Papavassiliou|title=SustainGraph: A knowledge graph for tracking the progress and the interlinking among the sustainable development goals’ targets|journal=Frontiers in environmental science, Frontiers|volume=10|date=2022-10-26|issn=2296-665X|doi=10.3389/FENVS.2022.1003599|url=https://www.wikidata.org/wiki/Q117837999}}.</ref><ref name=":18" />. They are especially usefull to build the ontologies (formal representations of concepts) that are necessary to organize and represent existing knowledge<ref name=":14">{{Cite journal|last=Spadaro|first=Giuliana|last2=Tiddi|first2=Ilaria|last3=Columbus|first3=Simon|last4=Jin|first4=Shuxian|last5=ten Teije|first5=Annette|last6=Balliet|first6=Daniel|date=2022-09-01|title=The Cooperation Databank: Machine-Readable Science Accelerates Research Synthesis|url=https://doi.org/10.1177/17456916211053319|journal=Perspectives on Psychological Science|language=EN|volume=17|issue=5|pages=1472–1489|doi=10.1177/17456916211053319|issn=1745-6916|pmc=9442633|pmid=35580271}}</ref>. Wikidata is a unique project, designed from the outset for multilingual use<ref name=":25">{{Cite journal|first1=Denny|last1=Vrandečić|first2=Markus|last2=Krötzsch|title=Wikidata: a free collaborative knowledgebase|journal=Communications of the ACM|volume=57|issue=10|pages=78–85|publisher=Association for Computing Machinery|date=2014-09-23|issn=0001-0782|doi=10.1145/2629489|url=https://dl.acm.org/doi/10.1145/2629489}}</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=":25" /><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 journal|last=Blaney|first=Jonathan|date=2017-05-07|editor-last=Crymble|editor-first=Adam|others=Terhi Nurmikko-Fuller, Matthew Lincoln|title=Introduction to the Principles of Linked Open Data|url=https://programminghistorian.org/en/lessons/intro-to-linked-data|journal=Programming Historian|language=en|issue=6|doi=10.46430/phen0068|issn=2397-2068}}</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>{{Cite journal|last=Zhao|first=Fudie|date=2023-06-01|title=A systematic review of Wikidata in Digital Humanities projects|url=https://doi.org/10.1093/llc/fqac083|journal=Digital Scholarship in the Humanities|volume=38|issue=2|pages=852–874|doi=10.1093/llc/fqac083|issn=2055-7671}}</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. 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>{{Cite journal|last=Waagmeester|first=Andra|last2=Stupp|first2=Gregory|last3=Burgstaller-Muehlbacher|first3=Sebastian|last4=Good|first4=Benjamin M|last5=Griffith|first5=Malachi|last6=Griffith|first6=Obi L|last7=Hanspers|first7=Kristina|last8=Hermjakob|first8=Henning|last9=Hudson|first9=Toby S|date=2020-03-17|title=Wikidata as a knowledge graph for the life sciences|url=https://elifesciences.org/articles/52614|journal=eLife|language=en|volume=9|doi=10.7554/eLife.52614|issn=2050-084X|pmc=7077981|pmid=32180547}}</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. 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. / Short version / Waagmeester et al. (2020) evaluated Wikidata as a crowdsourced curation platform for the Human Disease Ontology (DO) using a hybrid model that combines community contributions with expert review. 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=":4" /> 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=":0" />). 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 journal|last=Podsakoff|first=Philip M.|last2=MacKenzie|first2=Scott B.|last3=Podsakoff|first3=Nathan P.|date=2016-04|title=Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences|url=https://journals.sagepub.com/doi/10.1177/1094428115624965|journal=Organizational Research Methods|language=en|volume=19|issue=2|pages=159–203|doi=10.1177/1094428115624965|issn=1094-4281}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-12-31|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality|language=en|volume=13|issue=4|pages=1–35|doi=10.1145/3484828|issn=1936-1955}}</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, the discrepancy between the stated goals of this movement and what it actually achieves is precisely what some authors are critiquing<ref name=":20" />. 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>Fleetwood, S. (2004). An ontology for organisation and management studies. ''Critical Realist Applications in Organisation and Management Studies'', 27–53.</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 journal|last=Becker|first=Sören|last2=Naumann|first2=Matthias|date=2017-01-01|title=Energy democracy: Mapping the debate on energy alternatives|url=https://www.wikidata.org/wiki/Q139492906|volume=11|issue=8|doi=10.1111/GEC3.12321}}</ref>"<ref>{{Cite journal|last=Szulecki|first=Kacper|last2=Øverland|first2=Indra|date=2020-11-01|title=Energy democracy as a process, an outcome and a goal: A conceptual review|url=https://www.wikidata.org/wiki/Q136447761|journal=Energy Research & Social Science|language=English|volume=69|pages=101768|doi=10.1016/J.ERSS.2020.101768}}</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 statements using a specitic source in order to map the content of a single academic article. First test here: https://w.wiki/PFqH *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}}). === 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 journal|last=Maryl|first=Maciej|last2=Blaszczyńska|first2=Marta|last3=Zalotyńska|first3=Agnieszka|last4=Taylor|first4=Laurence|last5=Avanço|first5=Karla|last6=Balula|first6=Ana|last7=Buchner|first7=Anna|last8=Caliman|first8=Lorena|last9=Clivaz|first9=Claire|date=2021-01|title=Future of Scholarly Communication|url=https://hal.science/hal-03277615}}</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 web|url=https://eprints.whiterose.ac.uk/id/eprint/226771/|title=CLOUDSENSE Collaborative Review of Wikipedia Cloud Feedback article|last=Finney|first=D.|last2=Huang|first2=X.|date=2025-05-16|website=eprints.whiterose.ac.uk|language=en|doi=10.48785/100/329|access-date=2026-07-28|last3=Hinnie|first3=L.|last4=Sheppard|first4=N.}}</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 journal|last=Pierce|first=Jason R.|date=2025-01|title=Categorizing Concepts and Phenomena in Management Research: A Four-Phase Integrative Review and Recommendations|url=http://journals.aom.org/doi/full/10.5465/annals.2023.0052|journal=Academy of Management Annals|language=en|volume=19|issue=1|page=28|pages=9–37|doi=10.5465/annals.2023.0052|issn=1941-6520}}</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=":9" />. === Quality assessment === <ref>{{Citation|vauthors=((E. Peireira, A.))|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 journal|last=Piscopo|first=Alessandro|last2=Simperl|first2=Elena|date=2019-08-20|title=What we talk about when we talk about wikidata quality: a literature survey|url=https://dl.acm.org/doi/10.1145/3306446.3340822|journal=Proceedings of the 15th International Symposium on Open Collaboration|series=OpenSym '19|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=17|pages=1–11|doi=10.1145/3306446.3340822|isbn=978-1-4503-6319-8}}</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 journal|last=Shenoy|first=Kartik|last2=Ilievski|first2=Filip|last3=Garijo|first3=Daniel|last4=Schwabe|first4=Daniel|last5=Szekely|first5=Pedro|date=2022-04|title=A study of the quality of Wikidata|url=https://linkinghub.elsevier.com/retrieve/pii/S1570826821000536|journal=Journal of Web Semantics|volume=72|pages=100679|doi=10.1016/j.websem.2021.100679|issn=1570-8268}}</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 journal|last=Amaral|first=Gabriel|last2=Piscopo|first2=Alessandro|last3=Kaffee|first3=Lucie-aimée|last4=Rodrigues|first4=Odinaldo|last5=Simperl|first5=Elena|date=2021-10-15|title=Assessing the Quality of Sources in Wikidata Across Languages: A Hybrid Approach|url=https://dl.acm.org/doi/10.1145/3484828|journal=Journal of Data and Information Quality (JDIQ)|location=New York, NY, USA|publisher=Association for Computing Machinery|volume=13|issue=4|pages=23:1–23:35|doi=10.1145/3484828|issn=1936-1955}}</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 journal|last=Hosseini Beghaeiraveri|first=Seyed Amir|last2=Gray|first2=Alasdair|last3=McNeill|first3=Fiona|date=2024-12-01|title=RQSS: Referencing quality scoring system for Wikidata|url=https://journals.sagepub.com/action/showAbstract|journal=Semantic Web|language=EN|publisher=SAGE Publications|volume=15|issue=6|pages=2419–2475|doi=10.3233/SW-243695|issn=1570-0844}}</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 journal|last=Heindorf|first=Stefan|last2=Potthast|first2=Martin|last3=Stein|first3=Benno|last4=Engels|first4=Gregor|date=2016-10-24|title=Vandalism Detection in Wikidata|url=https://dl.acm.org/doi/10.1145/2983323.2983740|journal=Proceedings of the 25th ACM International on Conference on Information and Knowledge Management|series=CIKM '16|location=New York, NY, USA|publisher=Association for Computing Machinery|pages=327–336|doi=10.1145/2983323.2983740|isbn=978-1-4503-4073-1}}</ref><ref>{{Cite journal|last=Sarabadani|first=Amir|last2=Halfaker|first2=Aaron|last3=Taraborelli|first3=Dario|date=2017-04-03|title=Building Automated Vandalism Detection Tools for Wikidata|url=https://dl.acm.org/doi/10.1145/3041021.3053366|journal=Proceedings of the 26th International Conference on World Wide Web Companion|series=WWW '17 Companion|location=Republic and Canton of Geneva, CHE|publisher=International World Wide Web Conferences Steering Committee|pages=1647–1654|doi=10.1145/3041021.3053366|isbn=978-1-4503-4914-7}}</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=":24">{{cite journal|date=June 2015|title=Novices’ Struggles with Conceptual and Theoretical Framing in Writing Dissertations and Papers for Publication|journal=Publications|publisher=Multidisciplinary Digital Publishing Institute|volume=3|issue=2|pages=104–119|doi=10.3390/publications3020104|issn=2304-6775|vauthors=((Casanave, C. P.)), ((Li, Y.))}}</ref>. Conceptualization require to answer the question « what are our data examples of? » <ref name=":24" />. 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=":24" />. 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}} fvo6u53vfnh2ez2tdum1z0vy1m6z1s7 0 330080 2835132 2833122 2026-09-30T08:02:08Z U3254168 3106320 2835132 wikitext text/x-wiki {{title|Cancer screening and emotion:<br>How do emotions such as fear, anxiety, and relief influence cancer screening uptake?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Woman receives mammogram (3).jpg|thumb|right|200px|'''Figure 1'''. A woman undergoing a standard mammogram procedure.]] ;Scenario Megan, 50, discovers a letter in her mailbox inviting her {{missing}} a routine mammogram. She has continuously delayed it for the last four years. Her mother passed as a result of breast cancer, and the mere thought of the appointment makes her stomach knot. A part of her is comfortable with the uncertainty. The letter lays within a draw{{sp}}. In contrast, her friend Stella obtains the same letter a week later. Stella promptly schedules her appointment, Stella's view is synonymous with taking responsibility of her health. The procedure is the same, the same risk is attributed. Consequently, they feel completely differently about it and make opposite decisions. {{RoundBoxBottom}} Cancer screening programs for instance mammography, cervical screening, and bowl screening can significantly reduce mortality through early detection. Conversely, engagement remains below established national targets in Australia and internationally (Australian Institute of Health and Welfare, 2026). Key points this chapter develops: * Recognising these emotional dynamics attributes to screening programs to develop communication strategies that improve uptake. * Individuals{{g}} decision to participate in screening are not soley driven by rational evaluation; anxiety, fear, embarrassment, are all determinants as to whether individuals par take (Consedine et al., 2004) {{RoundBoxTop|theme=2}} '''Focus questions''' * How can emotional determinants be addressed to improve screening participation? * What is the role of relief as an emotional driver in the uptake of screening? * What emotions are experienced in relation to cancer screening? * How does anxiety and fear act as barriers to screening uptake? {{RoundBoxBottom}} == What emotions are involved in cancer screening?== * Emotional responses to screening comprise fear, anxiety, worry, stress, broadly conceptualised as anticipatory anxiety (Goodwin et al., 2023) * Concern around the screening procedure and the cancer itself was reported between 10-50% of participants (Goodwin et al., 2023) * A review of 74 studies identified that diagnostic anxiety tended to promote screening, conversely, procedural fear was almost reliably discouraging it (Goodwin et al., 2023). ==How does anxiety and fear motivate cancer screening?== * Evidence from a systematic review illustrated that anxiety of a possible cancer diagnosis was often linked to greater screening uptake. Conversely, the fear of procedure discouraged participation (Goodwin et al., 2023). * In a large Australian sample, screening engagement increased as an anxiety also increased but when anxiety was severe individuals were less likely to engage in screening (Anderson et al., 2023). * Protection Motivation Theory proposes that individuals are highly probable to screen when they feel at harm and believe screening will benefit (Rogers, 1975). ==How does anxiety and fear act as barriers in cancer screening uptake?== * Fear of receiving screening results can undermine participation, with fear of receiving a positive result as one of the biggest discouragers of cervical screening among Australian women (Nagendiram et al., 2020). * Severe anxiety may mitigate screening participation, with Australian literature illustrating lower bowel cancer screening participation across individuals experiencing severe anxiety (Anderson et al., 2023). * Anticipatory anxiety associated around the screening procedure can attribute to avoidance, with never-screened or under screened Australian's noting psychological distress accompanied by invasive and sometimes discomfort-inducing nature of cervical screening (Creagh et al., 2021). ==Conclusion== * The behavioural impacts of emotional responses on screening uptake, anxiety and fear proficient discouraging and motivating screening participation shaped by their focus and intensity * Developing greater insight into the emotional components shaping screening decisions, guiding he development of strategies to mitigate psychological barriers promoting greater engagement * Anxiety and fear influence screening in multifaceted ways, illustrating that emotional processes collectively shape screening behaviour. ==See also== {{expand}} ==References== {{Hanging indent|1= Anderson, L. E., Ireland, M. J., Myers, L., Avenell, C., Connaughton, T., & Goodwin, B. C. (2023). Psychological distress and bowel cancer screening participation. Psycho-Oncology, 32(2), 229–236. https://doi.org/10.1002/pon.6072 Australian Institute of Health and Welfare. (2026). Cancer screening. Australian Government. https://www.aihw.gov.au/reports/australias-health/cancer-screening-and-treatment Consedine, N. S., Magai, C., Krivoshekova, Y. S., Ryzewicz, L., & Neugut, A. I. (2004). Fear, anxiety, worry, and breast cancer screening behavior: A critical review. Cancer Epidemiology, Biomarkers & Prevention, 13(4), 501–510. https://doi.org/10.1158/1055-9965.501.13.4 Creagh, N. S., Zammit, C., Brotherton, J. M. L., Saville, M., McDermott, T., Nightingale, C., & Kelaher, M. (2021). Self-collection cervical screening in the renewed National Cervical Screening Program: A qualitative study. Medical Journal of Australia, 215(8), 354–358. https://doi.org/10.5694/mja2.51137 Goodwin, B. C., Anderson, L., Collins, K., Sanjida, S., Riba, M., Singh, G. K., Campbell, K. M., Green, H., Ishaque, S., Kwok, A., Opozda, M. J., Pearn, A., Shaw, J., Sansom-Daly, U. M., Tsirgiotis, J. M., Janda, M., & Grech, L. (2023). Anticipatory anxiety and participation in cancer screening: A systematic review. Psycho-Oncology, 32(12), 1773–1786. https://doi.org/10.1002/pon.6238 Nagendiram, A., Bougher, H., Banks, J., Hall, L., & Heal, C. (2020). Australian women's self-perceived barriers to participation in cervical cancer screening: A systematic review. Health Promotion Journal of Australia, 31(3), 343–353. https://doi.org/10.1002/hpja.280 Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. The Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803 }} ==External links== {{expand}} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Behaviour]] [[Category:Motivation and emotion/Book/Emotion]] [[Category:Motivation and emotion/Book/Health]] 9z649pvug2178538nuxspzo3i48t4b8 0 330325 2835062 2834716 2026-09-29T15:12:18Z Mbataw 3084293 Restored revision 2816816 by [[Special:Contributions/Mbataw|Mbataw]] ([[en:w:User:BrandonXLF/Restorer|Restorer]]) 2835062 wikitext text/x-wiki {{Wikipedia|w:Igbo regalia and Headdresses}} {{course}} == Introduction == '''Igbo regalia and headdresses''' comprise the ceremonial headgear, hairstyles, adornments, accessories, clothing and insignia traditionally associated with the Igbo people. These include mainly the ichafu (head ties), aka (beads), helmet and okpu (caps), Other significant headdresses and regalia include: akupe (hand fans), nza (flywhisks), ofo (elephant tusks), nkpara (staffs ), ugo (eagle's feathers), wigs and other symbolic objects used to express cultural identity, social status, title, spiritual significance and ceremonial functions.<ref name=":0">{{Cite book |last=Shaw |first=Thurstan |title=Unearthing Igbo-Ukwu: archaeological discoveries in eastern Nigeria |date=1977 |publisher=Oxford University Press |isbn=978-0-19-575251-9 |location=Ibadan, Nigeria ; New York}}</ref><ref name=":11">{{Cite book |last=Church Missionary Society |url=https://babel.hathitrust.org/cgi/pt?id=ien.35556041684267&seq=160 |title=Dictionary of the Ibo Language: English-Ibo |publisher=Church Missionary Society Bookshop |year=1923 |location=Lagos |pages=160}}</ref><ref name=":16">{{Cite journal |last=Dike |first=P. Chike |date=1987 |title=Art, Symbol and Authority Among the Aro of South-east Nigeria |journal=Nigerian Magazine |volume=55 |pages=30-35}}</ref><ref name=":8">{{Cite book |last=Poynor |first=Robin |url=http://archive.org/details/africanartatharn0000poyn |title=African art at the Harn Museum : spirit eyes, human hands |date=1995 |publisher=Gainesville : University of Florida |others=Internet Archive |isbn=978-0-8130-1325-1 |pages=115}}</ref> Many forms of Igbo regalia are associated with rulers, chiefs, and titled individuals. They are used to mark rank, status, office and authority, and remain an important part of [[Igbo culture|Igbo cultural]] traditions.<ref name=":0" /><ref name=":8" /> Archeological excavations at Igbo-Ukwu by Charles Thurstan Shaw uncovered 9th-century burials containing ceremonial regalia, including beads, Headdresses, crowns, fly-whisks, anklets, and other prestige objects. <ref name=":0" />These discoveries show the long-standing use of adornments and regalia among the Igbo people. == Learning Objectives == Before studying this, you should be able to: * Differentiate between the cultural roles, historical origins, and gender associations of various Igbo headdresses and items of regalia. * Understand the socio-political significance of specific insignia like the Okpu ozo, Okpu agu, and Akupe. * Describe the material culture, artistic elements, and components of traditional Igbo clothing ensembles for both men and women. == Module 1: Women's Headdresses, Coiffures, and Crowns == === Ichafu headdress === [[File:Beauty Queen Bianca.jpg|alt=Bianca Ojukwu wearing Ichafu|thumb|Bianca Odumegwu Ojukwu, an Igbo woman and Nigerian Minister of Foreign Affairs wearing '''Ichafu''' (Ichafo) headdress]] [[File:Igbo woman styled in Igbo Ichafu (headscarf) and Akwete obiakwa. Stunning.jpg|thumb|Igbo woman wearing '''Ichafu''' (Ichafo) headdress boldly and stylishly tied with a damask head-tie fabric]] [[File:Eze Obi Ossai and wives wearing Ichafu with wrappers and elephant tusk Ivory (Odu).jpg|alt=An image of Igbo women in 1841 wearing Ichafu headdress, Odu ukwu, and wrappers and carrying Akupe while the Obi carries mkpara muo.|thumb|Igbo women described by [[William Allen (Royal Navy officer)|William Allen]] in his 1841 book as Eze Obi's wives. The image depicts them wearing headcloths known as Ichafu among the Igbo, and elephant ivory anklets known as ''odu''. They carry ''Akupe'' (handfans) while the Obi carries a staff known as ''nkpara mmuo'']] '''Ichafu''' (also recorded as Ichafo and Icafo in historical sources) is a traditional Igbo women's headdress fashioned from a fabric folded, twisted, and pinned into elaborate shapes like a large flower sitting on the head. It is a prominent part of ceremonial dresses typically worn by Nigerian women with traditional outfits. Chimamanda Ngozi Adichie in a piece republished in Style and Substance: Why What We Wear Matters, edited by Gay Garnet narrated watching her mother arrange Ichafu on her head until it sat on her head like a large flower<ref name=":17">{{Cite book |title=Style and substance: why what we wear matters |date=2023 |publisher=John Murray |isbn=978-1-3998-1246-7 |editor-last=Garnett |editor-first=Bay |location=London}}</ref> <ref>{{Cite book |last=Butticci |first=Annalisa |title=African Pentecostals in Catholic Europe: the politics of presence in the twenty-first century |date=2016 |publisher=Harvard University Press |isbn=978-0-674-73709-9 |location=Cambridge, Massachusetts}}</ref>Likewise, Uzo Aduba in her memoir The road is Good described wearing an elaborate Ichafu on her head in the most gorgeous coral colour.<ref name=":18">{{Cite book |last=Aduba |first=Uzo |title=The road is good: how a mother's strength became a daughter's purpose |date=2024 |publisher=Viking |isbn=978-0-593-29912-8 |location=New York}}</ref> Ichafu has influenced contemporay fashion design beyond [[Nigeria]]. A review in the [[fashion]] section of the British newspaper The Observer of Priya Ahluwalia's Spring/Summer 2026 collection noted that the designer's Jacquard knits drew inspiration from Nigerian Ichafu headwraps alongside Bollywood motifs<ref>{{Cite web |last=Deaman |first=Jo Jones, Helen Seamons, Sam |title=Hometown glory: highlights from London Fashion Week sprin... |url=https://observer.co.uk/style/fashion/article/hometown-glory-highlights-from-london-fashion-week-springsummer-2026 |access-date=2026-06-20 |website=The Observer |language=en}}</ref> Ichafu is also included in an Oxford University Press International Baccalaureate Visual Arts curriculum under the theme "Textiles and cultural signs" alongside Japanese kimonos.<ref>{{Cite book |last=Oxford |url=http://archive.org/details/visual-arts-paterson-poppy-and-vaughn-oxford-2017 |title=Visual Arts Paterson, Poppy And Vaughn Oxford 2017 Textbook |date=2017}}</ref> Headcloths formed an important part of traditional Igbo women's headdresses and attire. Historical and linguistic sources record terms such as Ichafu, Icafo, Ichafo, Ichafu isi in reference to headcloths, head ties, headgears and headdresses worn by Igbo women in both everyday and ceremonial settings. This headdress was associated with markets, meetings, religious observances, weddings, celebrations, and other social occasions.<ref name=":11" /><ref name=":9" /><ref name=":12">{{Cite book |last=Cowen |first=Rhoda |url=https://archive.org/details/goldsilverthread0000cowe |title=The Gold and Silver Threads: A memoir of Life in the Twentieth Century |publisher=Alan Sutton Publishing Ltd |year=1994 |location=Stroud, Gloucestershire, England |publication-date=1994 |pages=67, 84}}</ref><ref name=":13">{{Cite book |last=Green |first=M M |url=https://archive.org/detailsibovillageaffair0000gree/page/218/mode/1up |title=Ibo Village Affairs |date=1947 |publisher=Sidgwick and Jackson |year=1947 |location=Sidgwick London |publication-date=1947 |pages=136, 218, 226}}</ref> Headcloths are part of a long-standing tradition of Igbo women's headdresses and full clothing ensemble. In the ethnographic work of the anthropologist M.M. Green in Igboland, he documented women in 1947 wearing festive headcloths to market and observed that headcloths were commonly worn at meetings and social gatherings as part of their clothing ensemble.<ref name=":13" /> Igbo headtie is worn in a big, bold and stylish manner with flared ends using vibrant fabrics measuring six by three feet in size. Writing about her experiences in Igboland, Rhoda Cowen described Igbo headtie referred to as Ichafo and Icafo as a big brightly colored headdress worn in a bold and stylish manner noting that some were wrapped around the head with projecting ends, while others formed striking elements of women's attire alongside vibrant colored fabrics or textiles and gold jewellery.<ref name=":12" /> Igbo headtie has also been recorded in ethnographic studies of Igbo dress as a headgear fashioned from a decorative piece of cloth worn around the head known as Ichafo. It is fashioned from a piece of cloth approximately six by three feet in size, folded into triangular or rectangular forms and wrapped around the head in an elevated manner that creates a style resembling a tall turban with decorative bow. According to the author, a headgear is distinguished from a head-tie which is smaller and worn flat around the head in the Nigerian context while defining Igbo style of headtie as a headgear.<ref name=":9" /> [[File:Girl on ichafu.jpg|alt=A girl wearing Ịchafú n'isi|thumb|An Igbo girl wearing '''Ichafu''' headdress]] === Helmet coiffures and beaded crowns === Igbo headdresses also include elaborate female head adornments, as well as decorative headgear featuring elaborate coiffures worn by masquerades such as the ''Agbogho Mmuo'' (maiden spirit) during festivals and cultural events. The Headdresses and costumes are intended to depict female figures and their feminine appearance and attributes.<ref>{{Cite book |last=Celenko |first=Theodore |title=A treasury of African art from the Harrison Eiteljorg Collection |last2=Eiteljorg |first2=Harrison |date=1983 |publisher=Indiana University Press |isbn=978-0-253-11057-2 |location=Bloomington}}</ref> [[File:Ancient Igbo helmet Coiffures and headgear (1921).jpg|alt=Helmet Coiffures and Headgears of Ancient Igbo brides|thumb|Ethnographic photos of Igbo brides known as Nkpu brides of prospective chiefs dressed in helmet Coiffures and heagears, necklaces of Leapard teeth and aggry beads 1920.]] Helmet-shaped coiffures were among the elaborate hairstyles historically worn by Igbo women during courtship, marriage festivities, and other ceremonial occasions. Some were built on a foundation of clay, charcoal and palm oil and moulded into a crest resembling the central ridge of a Roman helmet, extending from the forehead to the nape of the neck. The coiffures were often further decorated with beads, small could plaits, cowry shells, mother-of-pearl, brass ornaments, and mirrors sewn into the hair.<ref name=":6">{{Cite book |last=Basden |first=George Thomas |url=https://doi.org/10.5479/sil.115290.39088000476515 |title=Among the Ibos of Nigeria |date=1921 |publisher=Seeley, Service & Co., ltd}}</ref><ref name=":7">{{Cite journal |last=Chudi-Duru |first=Chika C. |date=2024 |title=MMA NWANYI BU EKIKE |url=https://www.journals.ezenwaohaetorc.org/index.php/UJOCC/article/viewFile/3950/4060 |journal=Ohazurume: Unizik Journal of Culture and Civilization (often abbreviated UJOCC) |volume=3 |pages=96-115}}</ref> Other recorded styles include a raised helmet-like ridge formed on a clay foundation and decorated with beads, cowry shells, leopard claws, camwood paste, and other adornments. Such coiffures could signify age, status, wealth or other stages of life and formed part of ceremonial female adornment in parts of Igboland.<ref name=":5" /><ref name=":6" /> [[File:An Igbo bride adorn with the isi agu and the red bead.jpg|alt=An attire featuring Igbo beaded head crown called ngala, aka, and nza|thumb|An Igbo bride adorned with beaded crown called ''ngala'', aka(coral beads) worn around the neck and wrist and worn as earrings and carrying the ''nza'' (flywhisks) regalia.]] While elaborate Helmet-shaped coiffures were a prominent part of historical Igbo women's ceremonial adornment, contemporary ceremonial attire incorporates beaded crowns and bead-based headpieces. Studies of present-day Igbo dress culture depict the brides and her maidens wearing beaded crowns as part of the traditional attire, or decorate their hair with bead accessories during weddings and Cultural celebrations. Beaded crowns, together with corals and other ornamental beads remain a prominent feature of Igbo regalia and are associated with beauty, femininity, cultural identity, fertility, spiritual well-being and marital blessings.<ref name=":7" /><ref name=":6" /> == Module 2: Elite Signifiers, Beads, and Men's Okpu == === Aka === [[File:Igbo Bride during her traditional marriage 20220216.jpg|alt=Igbo bride adorned with beaded accessories and Uli body arts and carrying a Calabash.|thumb|An Igbo bride dressed for ''Igbankwu'' (traditional wedding) adorned in beaded accessories featuring aka attached on the head, ''nkalari'' or ''erulu'' (coral beads) around the neck, wrists ankles and also worn as earrings. She carries the ''nza'' (fly whisk) regalia and a Calabash with her legs designed in Uli body arts.]] Beaded accessories made of glass beads are known as ''aka'' among the Igbo people. They're of various types which consist of coral beads known as ''erulu'' or ''aka'' and waist beads known as ''mgbaji''. The large coral beads are known as ''nkalari''. The ''mgbaji'' is usually a kind of flat circular coral beads worn around the waist. The large coral beads are worn around the neck, and also worn as earrings and on the wrists.<ref name=":9">{{Cite book |last=Melie |first=Edith E. |url=https://books.google.com/books?id=iqZbAAAAMAAJ |title=The Ozo Title of Onitsha: A Study of it's Dress and Insignia |publisher=University of Wisconsin-Madison |year=1977 |location=Madison, Wisconsin, USA |publication-date=1977 |pages=87-140}}</ref><ref name=":19">{{Cite book |url=https://books.google.com/books?id=UAgOAQAAMAAJ |title=Ikenga |date=1985 |publisher=Institute of African Studies, University of Nigeria. |language=en}}</ref> Aka is an important part of both Igbo men's and Women's dress fashion. Among the men, it is also regarded as a status symbol across [[Africa]] and a ceremonial adornment like bridal attire for Igbo women. Gold beads are also incorporated in the dress attire.<ref name=":9" /><ref name=":10" /> [[File:Glass beads from Igbo-Ukwu.jpg|thumb|9th Century carbon-dated Igbo-ukwu glass beads.]] Beads are highly valued in Igboland<ref>{{Cite book |last=Afigbo |first=A. E. |title=The Igbo and their neighbours: inter-group relations in southeastern Nigeria to 1953 |date=1987 |publisher=University Press |isbn=978-0-19-575713-2 |location=Ibadan}}</ref> and have long been an important part of Igbo ceremonial dress and adornment. Excavations at Igbo-ukwu uncovered large quantities of glass and carnelian beads used in necklaces, armlets, wristlets, girdles, and other ornaments. In one royal burial, hundreds of beads were found around the skull, which suggests that the deceased wore a beaded headdress, while strings of beads and a [[copper]] crown was part of the ceremonial regalia. These discoveries dated as early as the 9th century by Thurstan Shaw show that beaded accessories was widely used as a regalia symbol and adornment in ancient Igbo society.<ref name=":0" /> === Okpu === Okpu refers to traditional caps or helmets used by Igbo adult males of various statuses and ranks in the society for symbolic purposes. There are different kinds of Okpu worn by adult males in Igboland. The most prominent are feathered red cap known as ''okpu ozo'' and leopard cap known as ''Okpu agu''.<ref name=":2">{{Cite book |last=Oriji |first=John Nwachimereze |url=http://archive.org/details/ngwahistorystudy0055orij |title=Ngwa history : a study of social and economic changes in Igbo mini-states in time perspective |date=1991 |publisher=New York : P. Lang |others=Internet Archive |isbn=978-0-8204-1411-9}}</ref><ref name=":3">{{Cite book |last=M. Angulu Onwuejeogwu |url=http://archive.org/details/an-igbo-civilization-nri-kingdom-and-hegemony |title=An Igbo Civilization: Nri Kingdom and Hegemony |date=1980}}</ref> ==== Okpu ozo ==== [[File:Red Cap Chiefs at an Igbo Traditional Ceremony.jpg|alt=Ndi Nze na ozo you Okpu ozo ma jidekwa Akupe, ofo, na mkpara|thumb|Titled Igbo men known as Ndi Nze na ozo wearing their traditional regalia featuring Okpu ozo (red caps made of hide with eagle's feathers). Their attire also features other Igbo regalia insignia such as Akupe, ''ofo'', ''nza'', ''nkpara'']] Okpu ozo is described as the feathered red cap worn by titled men known as Ndi Nze na Ozo. As a paraphernalia of office, okpu is regarded as sacred thereby prohibiting ordinary people from touching them.<ref>{{Cite book |last=Oriji |first=J. |url=https://books.google.com/books?id=WZliAQAAQBAJ |title=Political Organization in Nigeria since the Late Stone Age: A History of the Igbo People |date=2011-01-17 |publisher=Springer |isbn=978-0-230-11668-9 |language=en}}</ref><ref name=":2" /><ref name=":10">{{Cite book |url=https://books.google.com/books?id=e-Y6dSeFt_sC |title=Ikenga |date=1980 |publisher=Institute of African Studies, University of Nigeria. |language=en}}</ref>It is a high-crowned red cap made of hide and usually encircled with eight eagle feather plumes called ''ugo''.This is particularly worn by the title holders called ''Nze''. It can also be modest or low-crowned without the feather decorations worn by the ''Ozo'' title holders.<ref name=":1">{{Cite journal |last=Ubani |first=Kenneth |date=2019 |title=Igbo Leadership Through the Visual Arts: Back to the Future |url= |journal=Canadian Social Science |volume=15 |issue=7}}</ref> It is also known as Okpu ''mmee mmee'' which literally translates to colour of the cap and okpu ''mmee'' which signifies true loyalty. Some Igbo regions also refer to it as ''okpu eze''. <ref name=":4">{{Cite book |last=Ifemesia |first=C. C. |url=http://archive.org/details/traditionalhuman00ifem |title=Traditional humane living among the Igbo : an historical perspecitve |date=1979 |publisher=Enugu, Nigeria : Fourth Dimension Publishers |others=Internet Archive |isbn=978-978-156-062-0}}</ref><ref name=":3" /> Okpu ozo is regarded as an insignia that protects the wearer when he was away from his lineage or village as well as other travellers.<ref name=":4" /> The wearers are known as Ndi nze na ozo or red cap chiefs. To obtain the title, a candidate traditionally applied to the red cap chiefs, who supervised the initiation ceremony. During the capping ceremony, the initiate was presented with a red cap and feather as a symbol of his new status and a symbol of authority to enable him perform his duties. This capping stage is also known as ''ikube-okpu''. He also receives other insignia.<ref name=":14">{{Cite book |last=Umeasiegbu |first=Rems N. |title=The way we lived: Ibo customs and stories |date=1981 |publisher=Heinemann |isbn=978-0-435-90061-8 |edition=Repr |series=African writers series |location=London}}</ref> ==== Okpu agu ==== [[File:Igbo kwenu.jpg|alt=Nwoke yi ekike Okpu agu na agba egwu Ohafia|thumb|Ohafia war dance performer wearing Okpu agu]] [[File:Ohafia Igbo Dance Performance Chicago.jpg|alt=Ndi yi Okpu agu agba egwu Ohafia na Chicago|thumb|Ohafia Igbo dance performance in Chicago [[United States]] featuring the Okpu agu Igbo regalia]] Some descriptions of Igbo headdresses highlight that three kinds of helmets were worn: thick ones made of coco-yam stalks, or of the bark of the Achi tree, and fine looking but thin ones made of young palm leaves or raffia hats called ''okpu uturu.''<ref name=":5">{{Cite book |last=Talbot |first=Percy Amaury |title=The People's of Southern Nigeria: A sketch of their History, Ethnology and Languages, with an abstract of 1921 Census. |publisher=Oxford University Press, H Milford. |year=1926 |location=London |publication-date=1926 |pages=413, 839}}</ref> Among these headgears was the okpu agu, a cap associated with Ohafia warrior traditions, known as the leopard cap of bravery. It is round slanting cap made of a knitted wool of black, white and red stripes with a pattern that resemble leopard markings from which the cap derives its name.<ref>{{Cite book |last=McCall |first=John C |url=https://books.google.com/books?id=204eAQAAMAAJ |title=The Ohafia War Dance as Lived Experience |publisher=University of Michigan |year=1992 |location=Ann Arbor, Michigan |pages=37}}</ref> The okpu agu was an important symbol of warrior achievement in Ohafia. According to historical accounts, the red colour of the cap was traditionally reserved for warriors who had taken heads in battle, or returned with the slain body of a strong animal like the leopard and the caps were dyed with the blood of war victims, while the black and white stripe evoked the leopard and it's qualities of strength, agility and martial prowess that were admired in accomplished warriors, as well as the leopard body movement that characterizes the Ohafia War Dance movement.<ref>{{Cite book |last=MacCall |first=John Christensen |title=Dancing histories: heuristic ethnography with the Ohafia Igbo |date=2000 |publisher=University of Michigan Press |isbn=978-0-472-11070-4 |location=Ann Arbor}}</ref> Okpu agu was manufactured locally by process of bending over, tying and sowing. It is also known as ''Okpu-Aji'' by Nkanu Igbo people and ''Okpu Ojji'' by Abajah and ''Okpu oggu'' (fighting war caps)<ref name=":5" /> == Module 3: Ceremonial Utensils, Insignia, and Fly-Whisks == === Akupe (hand fan) === [[File:Akupe handfan.webp|thumb|Igbo man carrying an Akupe with ofo symbol carved on it. The image also features him wearing ''Okpu'' ''Ozo'' and Isiagu flowing shirt and ''aka'' (coral beads) worn around his wrist.]] Akupe is a ceremonial traditional handfan of the Igbo people which forms part of the clothing ensemble of Igbo men and women. However, it isn't merely used as a [[fashion]] complement but functions as both a practical object and insignia or symbol of status within Igbo society. It is mainly made of raw leather but was also made of other materials like straw, palm products and copper historically. As a paraphernalia of office, it is mainly associated with the ''Nze na ozo'' title holders.<ref name=":15">{{Cite book |last=Uzochukwu |first=Sam |title=Traditional funeral poetry of the Igbo |date=2001 |publisher=Lagos University Press |isbn=978-978-017-624-2 |location=Lagos, Nigeria}}</ref><ref name=":0" /><ref name=":8" /> The use of akupe as a ceremonial regalia in Igbo land dates back to Igbo-ukwu archeology where copper hand fan with a handle made of wooden shaft along with other status symbols were unearthed from a royal burial chamber of whom was described by Thurstan Shaw as a high ranking titled man or royalty. These excavations which included the fan was dated 9th century<ref name=":0" /> ==== Akupe as a ceremonial regalia and Fashion among the men ==== The Akupe serves as both a ceremonial insignia and an element of elite male in Igbo Society. It is part of the regalia of titled men like the Ozo title holders, chiefs. and elders. Typically carried at the hand, it complements other symbols of status such as the ''Okpu'', ''nkpara'', ''nza'' or ''odu enyi'' and the traditional flowing shirt known as Isiagu, <ref>{{Cite book |last=Omolade |first=Ajetunmobi |url=https://books.google.com/books?id=9GISAQAAIAAJ |title=Themes in Social Studies Education and Culture: A book of Readings |year=2000 |location=Nigeria |publication-date=2000 |pages=156-166}}</ref>Akwete or Akwa ocha.<ref name=":8" /> Although it is made of various materials, the titled men specifically use raw leather made handfans which is either called Akupe or ''agu''<ref>{{Cite book |last=Ndimele |first=Ozo-mekuri |title=Four Decades in the Study of Languages and Linguistics in Nigeria: A Festschrift for Kay Williamson |year=2003 |publication-date=2003 |pages=435}}</ref> Other names generally used to refer to the ceremonial fan is ''nkuku'' and ''nzuzu'' especially among the ''Agbalanze'' titled group of Onitsha. The Akupe is designed and decorated in various ways but particularly in a thick and heavy pattern for the titled men. Their titles or names are written or carved at the surface of the handfans while their vehicle plate numbers are also designed as such for identification.<ref name=":1" /> The fan is not merely acquired by titled men but bestowed on them during the capping ceremony where candidates are installed as Nze no ozo title holders or red cap chiefs. The final stage of the ceremony involves handing the candidate the ''Okpu nze na ozo'' and the ''Ugo'' feather, a fan and a sword among other insignia.<ref name=":14" /> Akupe also serves as a ritual symbol in the Igbo mmanwu (masquerade) tradition, particularly in the cultural ceremony known as the [[Ijele Masquerade|Ijele]] dance where a significant personality among the dance group is known as Akupe carrier. While he is not a masquerade, he plays the prominent role of leading the ''Ijele'' with it's symbolic powerful Akupe. The disappearance of either the Akupe or it's bearer is believed to place the Ijele at risk. The Akupe bearer determines the movement of the Ijele, which moves or remains stationary according to the bearer's actions<ref>{{Cite journal |last=Ikemerike |first=Ikechukwu John |last2=Efuruhievwe |first2=Margaret Akpevweogene |date=2023 |title=Globalization as a Threat to Cultural Identity: A Case Study of Igba Ijele Dance Group of Awkuzu, Anambra State |url=https://ssjhis.org/wp-content/uploads/2024/02/33.-Globalization-as-a-Threat-to-Cultural-Identity-A-Case-Study-of-Igba-Ijele-Dance-Group-of-Awkuzu-Anambra-State.pdf |journal=South-South Journal of Humanities and International Studies |volume=6 |issue=1 |pages=475-496}}</ref> ==== Akupe as a ceremonial regalia and fashion among the women ==== [[File:Akupe- locally made hand fan.jpg|thumb|Akupe made of decorative woolen textiles often used by women including brides and maids of honour ]] In Igbo society, both large hand fans and artistic hand-held fans have traditionally formed part of women's ceremonial presentation, particularly during weddings, festivals or public celebrations. Historical accounts of Igbo marriage and courtship customs as early as 1921, describe Igbo brides and her maids of honour carrying large fans during the marriage ceremony, particularly the ''Nkpu'' rite to cool and keep the bride refreshed after dancing during the ceremony<ref name=":6" /> In Igbo dances and performance traditions, artistic hand-held fans are used for aesthetics and symbolic purposes where they form part of the ceremonial ensemble<ref>{{Cite journal |last=Obijiaku |first=Chidi |date=2023-02-27 |title=HYBRIDITY IN MODERN NIGERIAN MUSIC: THE CASE OF IGBO CHORAL ART MUSIC |url=https://journal.ru.ac.za/index.php/africanmusic/article/view/2456 |journal=African Music : Journal of the International Library of African Music |volume=11 |issue=4 |pages=25–42 |doi=10.21504/amj.v11i4.2456 |issn=2524-2741}}</ref> === Fly-whisks (''Nza'', ''Odu ebule'') === [[File:Fly whisk (AM 2015.34.53-1).jpg|thumb|Fly-whisk (''Nza'' or ''Odu ebule'')]] Fly-whisks are known as ''Nza'' or ''odu ebule'' among the Igbo people. It is a traditional ceremonial accessory and symbol of distinction in Igbo society. It forms part of the regalia of titled men, chiefs, elders, and other person's of rank also integrated into the attire which includes the akupe, headgear, staff among others. Historical accounts of title taking ceremonies describe newly initiated titled men receiving ceremonial objects as part of their elevation into positions of honour and responsibility within the community such as the ''Ozo'' title.<ref name=":8" /><ref name=":15" /> Archeological evidence from Igbo-ukwu, dating to about the 9th century, shows the antiquity flywhisks within Igbo ceremonial culture. The excavations that uncovered a royal burial furnished with elaborate regalia and the reconstructions of the chamber depicted the high ranking individual holding a ceremonial fly-whisk among other insignia of authority. These regalia have been interpreted in studies as markets of prestige, rank, leadership, royalty, and ritual symbolisms in early Igboland.<ref name=":0" /> Beyond functioning as an insignia among titled men, royalty and chiefs, fly-whisks and related descriptions of the regalia has been recorded as forming part of the attire of Igbo dancers and brides during festivities or ceremonies like dance performances and traditional marriage. According to Basden in 1921, ''Nkpu'' brides during their marriage ceremony carried cow's tail mounted on a leather handle, sometimes accompanied by small mirrors placed in specially carved hand held frames, including large fans which all formed part of their attire in the ceremony.<ref name=":6" /> ''Odu enyi'' is also used in artistic and performance traditions of the Igbi people like the ''nkpokiti'' dance. Studies of Igbo oral poetry includes the fly-whisks among the symbolic paraphernalia carried by performers as emblems of their artistry. The flywhisks were described as part of the ceremonial props employed in dances, processions, and choral performance where they serve both symbolic and aesthetic functions as they express the Igbo culture.<ref name=":15" /> == Module 4: Traditional Dress and Ensembles == === Igbo traditional dress and fashion === Igbo traditional dress and fashion for men typically comprise of loose cotton shirt or robe over an ankle-length wrapper, or loin cloths fashioned from various local Igbo fabrics like the Isiagu, Akwete or Akwaocha complemented with ''okpu'', ''akupe'', ''odu enyi'', ''mkpara'', ''ofo'' and adornments with ''aka'' (coral beads) worn around the neck and wrists. These regalia items proclaim status within the society. Royal robes, royal headdresses, silver sword were used to describe the attire of Igbo royalty like the Obi of Onitsha by Nzimiro and Henderson while the red cap chiefs dressed in their own special attire<ref>{{Cite book |last=Ebuziem |first=Cajetan E. |title=Doing Ministry in the Igbo Context: Towards an Emerging Model and Method for the Church in Africa- Foreword by Theophilus Okere |date=2011 |publisher=Peter Lang Inc., International Academic Publishers |isbn=978-1-4331-1154-9 |edition= |series=Bible and Theology in Africa |location=New York}}</ref><ref name=":20">{{Cite book |last=Nnoromele |first=Salome |url=https://archive.org/details/lifeamongibowome0000nnor |title=Life among the Ibo women of Nigeria |publisher=Lucent books, San Diego |year=1998 |location=San Diego |publication-date=1998}}</ref><ref name=":8" /> <ref name=":16" /> Among the women, the typical tradition of dress consist of a pair of matching wrappers or double wrappers known as ''eregbor'' na ''ntukwasi'', a blouse called ''efe obi'' made of Akwete or George fabrics and Ichafu (also spelt Ichafo and Icafo). In ordinary circumstances according to M.M Green in 1947, the women wore short wrappers folded around the hips and reaching the knee with a headcloth while for ceremonial functions a blouse or tunic was worn together with the waist wrappers and festive headcloth <ref name=":21">{{Cite book |last=Lamb Holmes |first=Venice Judy |title=Nigerian Weaving |publisher=The Roxford Press |year=1981 |pages=247-280}}</ref><ref name=":22">{{Cite journal |last=Kent |first=Kate P. |last2=Eicher |first2=Joanne Bubolz |last3=Dendel |first3=Esther Warner |date=1978 |title=Nigerian Handcrafted Textiles |url=https://doi.org/10.2307/3335408 |journal=African Arts |volume=11 |issue=3 |pages=14 |doi=10.2307/3335408 |issn=0001-9933}}</ref><ref name=":20" /><ref name=":13" /><ref name=":17" /> Igbo women complement their dressing with ''aka'' (beads) and Jewellries especially for festivities or ceremonial occasions like traditional marriage known as ''Igba nkwu''.The beadded accessories include ''aka'' or ''nkalari'' (coral beads) worn around the neck and wrists and used as earrings, ''mgbaji'' (flat circular waist beads) worn around the waist, and ''ola'' (iron bangles) around the ankles.<ref name=":19" /><ref name=":17" /> ==== Layered Identical Double Wrappers (''Eregbor na Ntukwasi''), Blouse (''Efe obi'') and Ichafu ==== Traditionally, Igbo women's textiles like Akwete of all category are woven in pairs of identical design as well as sold in pairs. These pairs are not sewn together but worn together. The two pairs of wrappers are known as ''eregbor na ntukwasi,'' made of multicolored geometric or floral design. The first wrapper is wrapped around the waist and extends down to the ankle. The second wrapper overlaps the first from the waist to the knees, giving the wrappers a layered look. The wrappers are paired with a blouse known as ''efe obi'' which s tucked inside. This combination of wrappers and blouse are paired with head ties described by Chimamanda Adichie as Ichafu. The textiles used are usually Akwete and George.<ref name=":20" /><ref name=":21" /><ref name=":22" /><ref name=":17" /> In recounting her past, Chimamanda Ngozi Adichie describes how she had seen her mother dress up in her double wrappers, blouse and Ichafu.  {{Blockquote|text=She folded and twisted and pinned her Ichafu until it sat on her head like a large flower. She wrapped her George - heavy beaded cloth, alive with embroidery, always in bright shades of red or purple pink - around her waist in two layers, The first, the longer piece, hit her ankles, and the second formed an elegant tier just below her knees. Her sequinned blouse caught the light and glittered. Her shoes and handbag always matched|author=Chimamanda Ngozi Adichie|title=Style and Substance: Why What We Wear Matters}} This attire ensemble of layered double wrappers called ''eregbor na'' ''ntukwasi'' paired with a blouse and Ichafu (Ichafo) head tie is also complemented with jewelleries as described by Chimamanda and Uzo Aduba who had witnessed their mother and aunt dress up.<ref name=":17" /><ref name=":18" /> [[File:Igbo woman wearing Jooji obiakwa(double wrapper) with uweobi and Ichafu.jpg|left|thumb|A full clothing ensemble of the Igbo woman featuring ''Eregbor na ntukwasi'' (Layered identical George wrappers) paired with a puffed sleeved blouse ''(efe elu)'' and an Ichafu (Ichafo) headdress]] [[File:An igbo woman in Ichafu headdress.jpg|thumb|An Igbo woman wearing a fitted blouse (''efe obi'')]] == See also == * [[Igbo culture]] == == [[Category:Igbo culture]] [[Category:Material Culture]] [[Category:Learning Modules]] df88xflor9ts2wv7dysxj9cg4b48u16 0 330494 2835042 2835024 2026-09-29T13:25:53Z JSINST 3110286 2835042 wikitext text/x-wiki The John Snow prediabetes Institute is an international research network focused on prediabetes remission, early risk identification, and metabolic health education. (https://w.wiki/Skm7). '''Background:''' Millions are at increased risk of developing metabolic syndromes with prediabetes, diabetes type 2, high blood pressure and overweight (General Research Draft). <ref> https://www.dropbox.com/scl/fi/gau25oy5y1s57046icjt2/Research-protocol-draft.docx?cloud_editor=word&dl=0&rlkey=wat63e25ritmujwcpss8s4v0s </ref> All can lower their risks by staying physical active and eating well. Early diagnosis and education of prediabetes is a cost-effective preventive strategy that can improve long-term health outcomes. The arteriosclerosis starts in the prediabetes stage. A practical strategy for prediabetes remission in low- and middle-income countries (LMICs) must assume that laboratory capacity, workforce, and financing are constrained. For early identification of the risks we propose to register weight and height (BMI), the fasting blood sugar (glucometer), blood pressure, age, gender in the '''Prevalence studies''' at the schools for seafarers, nurses, medical students and the kids schools followed by giving educational materials.The 16-weeks '''intervention study''' include learnings by short video sequences and self-monitoring of blood sugar with glucometer <ref>https://www.sciencedirect.com/science/article/abs/pii/S1751991825001068 </ref> and self-evaluation of diet and physical activity. Other intervention studies to be tested and developed include Digital lifestyle programs <ref> «Digital Lifestyle Program Cuts Diabetes Risk by 46% in Prediabetics, Study of 130k+ Adults Reveals». News-Medical, 14 de abril de 2025. https://www.news-medical.net/news/20250414/Digital-lifestyle-program-cuts-diabetes-risk-by-4625-in-prediabetics-study-of-130k2b-adults-reveals.aspx.</ref> Educational materials come from the international diabetes organisations e.g the ADA:<ref>https://professional.diabetes.org/diabetes-support-resources</ref> and the Health Promoting Schools.<ref> https://www.dropbox.com/scl/fi/0rm7honrezbjwrcy3h3yk/Health-promoting-schools.docx?cloud_editor=word&dl=0&rlkey=673jyzcmwbfw7k9ui9nmtp0zh </ref>[[File:Lifestyle Medicine Pillars.png|250px|right|<big> Lifestyle Medicine Pillars.png The focus of Lifestyle Medicine is on these 6 pillars</big> ]] ===== <big>'''Prevalence studies''' </big> ===== [[/The Maritime Health database design // |1.1 The Maritime Health database design]] 1.2 Nursing Students Health Database <ref> https://www.dropbox.com/scl/fi/tcznmmd2y3nona5e3h1ro/The-Nursing-students-health-database.docx?cloud_editor=word&dl=0&rlkey=onbjh4o8ko1lzdvgyi8nlrotk </ref> 1.3. Medical student's Health Database <ref>https://www.dropbox.com/scl/fi/f16h9b60u4gxgt56un2jf/The-Medical-students-Health-database.docx?cloud_editor=word&dl=0&rlkey=xyfqen5trdc5lniaovipl548n </ref> 1.4. School childrens` Health database <ref> https://www.dropbox.com/scl/fi/u6u50c8bxwhte9t2t6ck8/The-School-children-s-Health-database.docx?cloud_editor=word&dl=0&rlkey=zlyz5wn673wf7owettq3nx3h5 </ref> 1.5 Excel recoding (pre diabetes, hypertension etc) <ref>https://www.dropbox.com/scl/fi/9qvqeccto2kbuqvx7mdkl?r=ACsntb2AuiFkJbEBLObVdo0HMD67UZBBUGCGl1RPCPy1X5Y3K3e9Lf4s7cG7i7E_iH0IK-WkynXw_FNCDWybHuCgaNl_OM8yche2w2aapJGk5BTHybbsLpLayBU8VKPPqxNa2zDaNslBdQg0MhmKTFSG</ref> '''Personal prevention''' Personal reversal of prediabetes relies on targeted lifestyle changes like eating a healthy diet, exercising regularly, and losing a modest amount of excess weight. (local Diabetes Associations) <span lang="en" dir="ltr"><small>'''Core Institutional Strategies''' Health authorities and organizations implement group-based or digital programs. The workplaces are prompted to make targeted interventions, including nutrition and exercise programs, to safeguard long-term cardiometabolic health in the workforces.</small></span> <small>16 weeks human caused Intervention studies: English <ref>https://www.dropbox.com/scl/fi/oi6cx6tlwwvoko3ed37tn/Invitation-to-the-course-English.docx?cloud_editor=word&dl=0&rlkey=7kzg91tqfgjskxf5aji8khicx </ref> Danish <ref>https://www.dropbox.com/scl/fi/2qahc3q9hmf4skbvk77ab/Invitation-to-the-course-in-Danish.docx?cloud_editor=word&dl=0&rlkey=x63w8oqvarz284zg2btq2johv </ref> Spanish <ref> https://www.dropbox.com/scl/fi/bn71inqeeth4o4mc1fjth/Invitation-to-the-course-Spanish.docx?cloud_editor=word&dl=0&rlkey=popmr1fnodh1v951v9l7k9ezv </ref> and '''AI-Powered Lifestyle Intervention''' in the Diabetes Prevention <ref>Mathioudakis, Nestoras, Benjamin Lalani, Mohammed S. Abusamaan, et al. «An AI-Powered Lifestyle Intervention vs Human Coaching in the Diabetes Prevention Program: A Randomized Clinical Trial». JAMA 334, n.º 23 (2025): 2079-89. https://doi.org/10.1001/jama.2025.19563.</ref> '''Organisation''' - [[/The John Snow Institute bylaws /]] - [[/|Manila conference Oct. 2026]] - General research pr[[Category:Prediabetes ]]otoco[[Category:Prediabetes ]]l draft <ref> https://www.dropbox.com/scl/fi/gau25oy5y1s57046icjt2/Research-protocol-draft.docx?cloud_editor=word&dl=0&rlkey=wat63e25ritmujwcpss8s4v0s </ref> - Health Promoting Schools <ref> https://www.dropbox.com/scl/fi/0rm7honrezbjwrcy3h3yk/Health-promoting-schools.docx?cloud_editor=word&dl=0&rlkey=673jyzcmwbfw7k9ui9nmtp0zh </ref> '''Publications''' <ref name=":0"> https://www.dropbox.com/scl/fi/mw7ft423lkkpjoxywd2bf </ref> '''The John Snow Prediabetes Institute Research Network:''' <small>Prof. Ing. MSc. Nailet Delgado Mujica; Prof. Magda Medir Mb, Spain, Prof. Dr. Olaf Jensen, MD, MPH, PhD; Prof. MSc.Ph.D. Bishal Gyawali SDU; MSc.PhD Vivi Just-Nørregaard; Prof. Dr. Johan Hviid Andersen MD, PhD. Århus University; Prof. MSc. Agnes Flores, UMECIT, Panama; Bruno Nørdam, Randers; Maritime Doctor. Erik Haarløv MD, Assens, Denmark; Dr. Maite Duque MD Venezuela; Dr. Indira Santos Panama MD; Med.Stud. Ashley Lezcano, Panama; Dr. Joseph Abesamis MD Filippines; Dr. Jen Mendoza, MD, Filippines; Dra.Marj Gab Huerte, MD, Filippines:</small> <small>Dr. Andra Ergle MD, Latvia; Prof. MSc. Ingrid Morató, Tarragona and Cadiz, Spain; Dr. Alejandro Martinez, MD, MPH, Costa Rica; Christian Acheampong, MBA, New Jersey US; Dr. Med. Sci Finn Gyntelberg NFA.and Bispebj. Hosp. Denmark: Dr. Solomon Ching MD Filippines: Dr. Marcel Alcaraz MD Filippines;</small> ==References== <references /> <references /> a25q2fhwvhmgaa69miff74cbcead6xc 2835057 2835042 2026-09-29T13:53:56Z JSINST 3110286 2835057 wikitext text/x-wiki The John Snow prediabetes Institute is an international research network focused on prediabetes remission, early risk identification, and metabolic health education. (https://w.wiki/Skm7). '''Background:''' Millions are at increased risk of developing metabolic syndromes with prediabetes, diabetes type 2, high blood pressure and overweight (General Research Draft). <ref> https://www.dropbox.com/scl/fi/gau25oy5y1s57046icjt2/Research-protocol-draft.docx?cloud_editor=word&dl=0&rlkey=wat63e25ritmujwcpss8s4v0s </ref> All can lower their risks by staying physical active and eating well. Early diagnosis and education of prediabetes is a cost-effective preventive strategy that can improve long-term health outcomes. The arteriosclerosis starts in the prediabetes stage. A practical strategy for prediabetes remission in low- and middle-income countries (LMICs) must assume that laboratory capacity, workforce, and financing are constrained. For early identification of the risks we propose to register weight and height (BMI), the fasting blood sugar (glucometer), blood pressure, age, gender in the '''Prevalence studies''' at the schools for seafarers, nurses, medical students and the kids schools followed by giving educational materials.The 16-weeks '''intervention study''' include learnings by short video sequences and self-monitoring of blood sugar with glucometer <ref>https://www.sciencedirect.com/science/article/abs/pii/S1751991825001068 </ref> and self-evaluation of diet and physical activity. Other intervention studies to be tested and developed include Digital lifestyle programs <ref> «Digital Lifestyle Program Cuts Diabetes Risk by 46% in Prediabetics, Study of 130k+ Adults Reveals». News-Medical, 14 de abril de 2025. https://www.news-medical.net/news/20250414/Digital-lifestyle-program-cuts-diabetes-risk-by-4625-in-prediabetics-study-of-130k2b-adults-reveals.aspx.</ref> Educational materials come from the international diabetes organisations e.g the ADA:<ref>https://professional.diabetes.org/diabetes-support-resources</ref> and the Health Promoting Schools.<ref> https://www.dropbox.com/scl/fi/0rm7honrezbjwrcy3h3yk/Health-promoting-schools.docx?cloud_editor=word&dl=0&rlkey=673jyzcmwbfw7k9ui9nmtp0zh </ref>[[File:Lifestyle Medicine Pillars.png|250px|right|<big> Lifestyle Medicine Pillars.png The focus of Lifestyle Medicine is on these 6 pillars</big> ]] ===== <big>'''Prevalence studies''' </big> ===== [[/The Maritime Health database design // |1.1 The Maritime Health database design]] 1.2 Nursing Students Health Database <ref> https://www.dropbox.com/scl/fi/tcznmmd2y3nona5e3h1ro/The-Nursing-students-health-database.docx?cloud_editor=word&dl=0&rlkey=onbjh4o8ko1lzdvgyi8nlrotk </ref> 1.3. Medical student's Health Database <ref>https://www.dropbox.com/scl/fi/f16h9b60u4gxgt56un2jf/The-Medical-students-Health-database.docx?cloud_editor=word&dl=0&rlkey=xyfqen5trdc5lniaovipl548n </ref> 1.4. School childrens` Health database <ref> https://www.dropbox.com/scl/fi/u6u50c8bxwhte9t2t6ck8/The-School-children-s-Health-database.docx?cloud_editor=word&dl=0&rlkey=zlyz5wn673wf7owettq3nx3h5 </ref> 1.5 Excel recoding (pre diabetes, hypertension etc) <ref>https://www.dropbox.com/scl/fi/9qvqeccto2kbuqvx7mdkl?r=ACsntb2AuiFkJbEBLObVdo0HMD67UZBBUGCGl1RPCPy1X5Y3K3e9Lf4s7cG7i7E_iH0IK-WkynXw_FNCDWybHuCgaNl_OM8yche2w2aapJGk5BTHybbsLpLayBU8VKPPqxNa2zDaNslBdQg0MhmKTFSG</ref> '''Personal prevention''' Personal reversal of prediabetes relies on targeted lifestyle changes like eating a healthy diet, exercising regularly, and losing a modest amount of excess weight. (local Diabetes Associations) <span lang="en" dir="ltr"><small>'''Core Institutional Strategies''' Health authorities and organizations implement group-based or digital programs. The workplaces are prompted to make targeted interventions, including nutrition and exercise programs, to safeguard long-term cardiometabolic health in the workforces.</small></span> <small>16 weeks human caused Intervention studies: English <ref>https://www.dropbox.com/scl/fi/oi6cx6tlwwvoko3ed37tn/Invitation-to-the-course-English.docx?cloud_editor=word&dl=0&rlkey=7kzg91tqfgjskxf5aji8khicx </ref> Danish <ref>https://www.dropbox.com/scl/fi/2qahc3q9hmf4skbvk77ab/Invitation-to-the-course-in-Danish.docx?cloud_editor=word&dl=0&rlkey=x63w8oqvarz284zg2btq2johv </ref> Spanish <ref> https://www.dropbox.com/scl/fi/bn71inqeeth4o4mc1fjth/Invitation-to-the-course-Spanish.docx?cloud_editor=word&dl=0&rlkey=popmr1fnodh1v951v9l7k9ezv </ref> and '''AI-Powered Lifestyle Intervention''' in the Diabetes Prevention <ref>Mathioudakis, Nestoras, Benjamin Lalani, Mohammed S. Abusamaan, et al. «An AI-Powered Lifestyle Intervention vs Human Coaching in the Diabetes Prevention Program: A Randomized Clinical Trial». JAMA 334, n.º 23 (2025): 2079-89. https://doi.org/10.1001/jama.2025.19563.</ref> '''Organisation''' - [[/The John Snow Institute bylaws /]] - [[/|Manila conference Oct. 2026]] - General research pr[[Category:Prediabetes ]]otoco[[Category:Prediabetes ]]l draft <ref> https://www.dropbox.com/scl/fi/gau25oy5y1s57046icjt2/Research-protocol-draft.docx?cloud_editor=word&dl=0&rlkey=wat63e25ritmujwcpss8s4v0s </ref> - Health Promoting Schools <ref> https://www.dropbox.com/scl/fi/0rm7honrezbjwrcy3h3yk/Health-promoting-schools.docx?cloud_editor=word&dl=0&rlkey=673jyzcmwbfw7k9ui9nmtp0zh </ref> '''Publications''' <ref name=":0"> https://www.dropbox.com/scl/fi/mw7ft423lkkpjoxywd2bf </ref> '''The John Snow Prediabetes Institute Research Network:''' <small>Prof. Ing. MSc. Nailet Delgado Mujica; Prof. Magda Medir Mb, Spain, Prof. Dr. Olaf Jensen, MD, MPH, PhD; Prof. MSc.Ph.D. Bishal Gyawali SDU; MSc.PhD Vivi Just-Nørregaard; Prof. Dr. Johan Hviid Andersen MD, PhD. Århus University; Prof. MSc. Agnes Flores, UMECIT, Panama; Bruno Nørdam, Randers; Maritime Doctor. Erik Haarløv MD, Assens, Denmark; Dr. Maite Duque MD Venezuela; Dr. Indira Santos Panama MD; Med.Stud. Ashley Lezcano, Panama; Dr. Joseph Abesamis MD Filippines; Dr. Jen Mendoza, MD, Filippines; Dra.Marj Gab Huerte, MD, Filippines:</small> <small>Dr. Andra Ergle MD, Latvia; Prof. MSc. Ingrid Morató, Tarragona and Cadiz, Spain; Dr. Alejandro Martinez, MD, MPH, Costa Rica; Christian Acheampong, MBA, New Jersey US; Dr. Med. Sci Finn Gyntelberg NFA.and Bispebj. Hosp. Denmark: Dr. Solomon Ching MD Filippines: Dr. Marcel Alcaraz MD Filippines;</small> ==References== il53v0efj8eqgmi0s6zn1kqdp9yxbfr 828 331015 2835079 2834933 2026-09-29T23:36:48Z Helpme2222 3106525 2835079 Scribunto text/plain -- My function for teaching grammar local p = {}; local frame = mw.getCurrentFrame() local grammatical_moods = { "Jelen ido", "Mult ido", "Felszolito mod", "Felteteles mod" } local balls = { grammatical_moods } function p.teamfightSource() local frame = mw.getCurrentFrame() local pageContent = mw.html.create(nil) local i = 1 while (frame.args["team"..i.."_ball1"]) do local teamTable = mw.html.create("table") :addClass("wikitable sortable") :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ):node("Participant") ) :node( mw.html.create( 'th' ):node("Contribution") ) :node( mw.html.create( 'th' ):node("Final scaling value") ) :node( mw.html.create( 'th' ):node("Final health") ) ) local j = 1 while (frame.args["team"..i.."_ball"..j]) do teamTable:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j]) ) -- ball also needs to have form and stuff. :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_score"] --[[..]] --[[get contribution type]]) ) -- test: see wordpad comment :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_scaledTo"] --[[..]] --[[get scaling feature]]) ) :node( mw.html.create( 'td' ):node(frame.args["team"..i.."_ball"..j.."_health"]) ) ) end pageContent:node( mw.html.create("h3"):node("Team "..i) ) :node( teamTable ) end pageContent:node( mw.html.create("h2"):node("Outcome") ) local j = 1 while (frame.args["team"..frame.args.winningTeam.."_ball"..j]) do pageContent:node( --[[sprite of ball, linked to team section]] ) end pageContent:node( "Team" ) end local toggleButton = mw.html.create( 'span' ) :css({ float = "right", ["margin-right"] = "0", ["font-weight"] = "normal" }) :addClass("mw-customtoggle-Infobox") :node("[Click to toggle]") function p.subheading( discrim, b_content, content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node((discrim) and b_content or content) :node((discrim) and toggleButton) ) end function p.s_subheading( s_content ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible mw-collapsed" ) :node( mw.html.create( 'th' ) :attr( "colspan", "2" ) :css( "text-align","left" ) :node(s_content) :node(toggleButton) ) end function p.row( discrim, name, data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( (discrim) and "mw-collapsible" ) :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(name) ) :node( mw.html.create( 'td' ) :node(data) ) end function p.s_row( s_name, s_data ) return mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass("mw-collapsible mw-collapsed") :node( mw.html.create( 'td' ) :css( "font-weight","bold" ) :node(s_name) ) :node( mw.html.create( 'td' ) :node(s_data) ) end function p.var(symbol) return frame:expandTemplate{ title = "Template:Var", args = {symbol} } end function p.iseq() return table.concat({ frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args[1] .. ( (frame.args[1] == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.iseqNamed() return table.concat({ frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/'") and " is equal to User:Helpme2222/Sandbox/'" or " is not equal to User:Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "User:Helpme2222/Sandbox/&#039;") and " is equal to User:Helpme2222/Sandbox/&#039;" or " is not equal to User:Helpme2222/Sandbox/&#039;"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/'") and " is equal to Helpme2222/Sandbox/'" or " is not equal to Helpme2222/Sandbox/'"), frame.args.arg .. ( (frame.args.arg == "Helpme2222/Sandbox/&#039;") and " is equal to Helpme2222/Sandbox/&#039;" or " is not equal to Helpme2222/Sandbox/&#039;"), }, "<br>") end function p.infoboxWBB() -- Passing expressions of conditional value: https://www.lua.org/pil/3.3.html --[[ https://www.mediawiki.org/wiki/LUAREF#mw.html:node Thankfully, these operations interpret passed nils as no-ops (I'm technically using false though. Somehow that works anyways?)]] local frame = mw.getCurrentFrame() local ballname = frame.args["Title"] or tostring(mw.title.getCurrentTitle()) local Entities = p -- require("Module:Entities") local featureCount = tonumber(frame.args["Feature count"]) or 1 local s_featureCount = tonumber(frame.args["SUPER Feature count"]) or featureCount local matchCount = { total = mw.site.stats.pagesInCategory( ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local matchWinCount = { standard = mw.site.stats.pagesInCategory( ballname.."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local s_matchCount = { total = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History", "pages" ), standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard", "pages" ), } local s_matchWinCount = { standard = mw.site.stats.pagesInCategory( "Super " .. ballname .."'s Match History/Weapon Ball Battles/Standard/Won", "pages" ), } local isSuper = frame.args["SUPER Feature count"] or frame.args["SUPER Type"] or frame.args["SUPER Debuted"] or (s_matchCount.total > 0) or nil -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. The extra "or nil" had to be added since this is used in :addClass calls. -- TITLE local infobox = mw.html.create( 'table' ) :addClass("wikitable") :css({ float = "right"; ["margin-left"] = "10px" }) :node( mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass((isSuper) and "mw-collapsible" or nil) :node("<big>" .. ballname .. "</big>") ) ) :node((isSuper) and mw.html.create( 'tr' ) :node( mw.html.create( 'th' ) :attr({ colspan = "2", id = "mw-customcollapsible-Infobox" }) :addClass("mw-collapsible mw-collapsed") :node("<big>" .. (frame.args["SUPER Title"] or ("Super " .. ballname)) .. "</big>") ) ) -- SECTION: Identification -- Section Heading :node( p.subheading( (frame.args["SUPER Type"]), "Base Identification", "Basic Info" ) ) :node( (frame.args["SUPER Type"]) and p.s_subheading( "Super Identification" ) ) -- Type :node( p.row( (frame.args["SUPER Type"]), "Type", frame.args["Type"] ) ) :node( (frame.args["SUPER Type"]) and p.s_row( "Type", frame.args["SUPER Type"] ) ) -- Color local color = frame.args["Color"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "color" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Color") ) :node( mw.html.create( 'td' ) :node( (color ~= "") and frame:expandTemplate{ title = "Color", args = {color} } or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add color...</i>]]" ) ) ) -- Emoji local emoji = frame.args["Emoji"] or Entities.getBallAttribute( "Entities/Weapon Ball Battles/Balls/Data", ballname, "emoji" ) infobox:node( mw.html.create( 'tr' ) :node( mw.html.create( 'td' ) :css("font-weight", "bold") :node("Emoji") ) :node( mw.html.create( 'td' ) :node( (emoji ~= "") and ( emoji .. " <code>" .. p.emojiCodepointInternal(emoji) .. "</code>") or "[[Module:Entities/Weapon Ball Battles/Balls/Data|<i>Add emoji...</i>]]" ) ) ) -- SECTION: Scaling Characteristics --[[ Some data will be collected first. ]] -- (Base) Behavior local features = {} local starts = {} local scalings = {} if (featureCount > 1) then for i = 1, featureCount do table.insert(features, { frame.args["Feature "..i], " (" .. p.var(frame.args["Var "..i]) .. ")" }) table.insert(starts, { p.var( frame.args["Var0 "..i] or (frame.args["Var "..i].."₀") ) .. ": ", frame.args["Starting value "..i] }) table.insert(scalings, { p.var( "Δ"..(frame.args["Var "..i]) ) .. ": ", frame.args["Scaling "..i] }) end else -- These weird ass tables are meant to be compatible with the clone-and-overwrite operation the supers may undergo if the SUPER feature count, unlike the hypothetical base feature count, is greater than 1 features[1] = {frame.args["Feature"],""} starts[1] = {"",frame.args["Starting value"]} scalings[1] = {"",frame.args["Scaling"]} end -- Super Behavior local s_features local s_starts local s_scalings -- for some reason, html:node interprets false-valued parameters as no-op signals, while html:addClass does not. These booleans below are therefore left undefined (nil) as default. local has_s_features; local has_s_starts; local has_s_scalings; if (frame.args["SUPER Feature count"]) then if s_featureCount > 1 then -- Deep copy base characteristics, i.e. use them as default, overwrite what is explicitly specified as new super data s_features = mw.clone(features) s_starts = mw.clone(starts) s_scalings = mw.clone(scalings) -- If # of super features != # of base features, trim or expand the deep-copied tables accordingly. Avoid index errors. if s_featureCount > featureCount then for i = featureCount + 1, s_featureCount do table.insert( s_features, {"",""} ) table.insert( s_starts, {"",""} ) table.insert( s_scalings, {"",""} ) end elseif s_featureCount < featureCount then for i = s_featureCount + 1, featureCount do s_features[i] = nil s_starts[i] = nil s_scalings[i] = nil end end -- Parse super data, set the has_s_... flags if triggered for i = 1,s_featureCount do if frame.args["SUPER Feature "..i] then s_features[i][1] = frame.args["SUPER Feature "..i] if (not has_s_features) then has_s_features = true end end if frame.args["SUPER Starting value "..i] then s_starts[i][2] = frame.args["SUPER Starting value "..i] if (not has_s_starts) then has_s_starts = true end end if frame.args["SUPER Scaling "..i] then s_scalings[i][2] = frame.args["SUPER Scaling "..i] if (not has_s_scalings) then has_s_scalings = true end end if frame.args["SUPER Var "..i] then s_features[i][2] = " (" .. p.var(frame.args["SUPER Var "..i]) .. ")" s_starts[i][1] = p.var( frame.args["SUPER Var0 "..i] or (frame.args["SUPER Var "..i].."₀") ) .. ": " s_scalings[i][1] = p.var( '<span style="font-style:normal">Δ</span>'..(frame.args["SUPER Var "..i]) ) .. ": " if (not has_s_features) then has_s_features = true end if (not has_s_starts) then has_s_starts = true end if (not has_s_scalings) then has_s_scalings = true end end s_features[i] = table.concat(s_features[i]) s_starts[i] = table.concat(s_starts[i]) s_scalings[i] = table.concat(s_scalings[i]) end s_features = table.concat(s_features,"<br>") s_starts = table.concat(s_starts,"<br>") s_scalings = table.concat(s_scalings,"<br>") else -- # of super features = 1? just write directly to the variable if frame.args["SUPER Var"] or frame.args["SUPER Feature"] then has_s_features = true s_features = frame.args["SUPER Feature"] end if frame.args["SUPER Var0"] or frame.args["SUPER Var"] or frame.args["SUPER Starting value"] then has_s_starts = true s_starts = frame.args["SUPER Starting value"] end if frame.args["SUPER Scaling"] then has_s_scalings = true s_scalings = frame.args["SUPER Scaling"] end end end -- finalize base data as strings now that work is otherwise complete if (featureCount > 1) then for i = 1, featureCount do features[i] = table.concat(features[i]) starts[i] = table.concat(starts[i]) scalings[i] = table.concat(scalings[i]) end features = table.concat(features,"<br>") starts = table.concat(starts,"<br>") scalings = table.concat(scalings,"<br>") else features = features[1][1] starts = starts[1][2] scalings = scalings[1][2] end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (frame.args["SUPER Feature count"]), "Base Scaling Characteristics", "Scaling Characteristics" ) ) :node( (frame.args["SUPER Feature count"]) and p.s_subheading( "Super Scaling Characteristics" ) ) -- Features :node( p.row( (has_s_features), (featureCount > 1) and "Features" or ( (frame.args["Var"]) and ("Feature (" .. p.var(frame.args["Var"]) .. ")") or "Feature" ), features ) ) :node( (has_s_features) and p.s_row( (s_featureCount > 1) and "Features" or ( (frame.args["SUPER Var"]) and ("Feature (" .. p.var(frame.args["SUPER Var"]) .. ")") or "Feature" ), s_features ) ) -- Starting values :node( p.row( (has_s_starts), (featureCount > 1) and "Starting values" or ( (frame.args["Var"]) and ("Starting value (" .. ( p.var(frame.args["Var0"] or (frame.args["Var"].."₀") ) ) .. ")") or "Starting value" ), starts ) ) :node( (has_s_starts) and p.s_row( (s_featureCount > 1) and "Starting values" or ( (frame.args["SUPER Var"]) and ("Starting value (" .. ( p.var(frame.args["SUPER Var0"] or (frame.args["SUPER Var"].."₀") ) ) .. ")") or "Starting value" ), s_starts ) ) -- Scaling :node( p.row( (has_s_scalings), "Scaling", scalings) ) :node( (has_s_scalings) and p.s_row("Scaling", s_scalings) ) -- SECTION: Career --[[ Some data will be collected first. ]] -- (Base) Games played local gamesPlayedText = {} if matchCount.total > 0 then table.insert(gamesPlayedText, matchCount.total .. " (total)") if matchCount.standard > 0 then table.insert(gamesPlayedText, matchCount.standard .. " (standard)") end end -- (Base) Winrate local winrateText = {} if matchCount.total > 0 then if matchCount.standard > 0 then table.insert(winrateText, p.roundedPct(matchWinCount.standard,matchCount.standard) .. "% (standard)" ) end end -- Super Games played local s_gamesPlayedText = {} if s_matchCount.total > 0 then table.insert(s_gamesPlayedText, s_matchCount.total .. " (total)") if s_matchCount.standard > 0 then table.insert(s_gamesPlayedText, s_matchCount.standard .. " (standard)") end end -- Super Winrate local s_winrateText = {} if s_matchCount.total > 0 then if s_matchCount.standard > 0 then table.insert(s_winrateText, p.roundedPct(s_matchWinCount.standard,s_matchCount.standard) .. "% (standard)" ) end end --[[ Begin rendering ]] -- Section Heading infobox:node( p.subheading( (isSuper), "Base Career", "Career ") ) :node( (isSuper) and p.s_subheading( "Super Career") ) -- Debuted :node( p.row( (isSuper), "Debut", frame.args["Debut"] ) ) :node( (isSuper) and p.s_row("Debut", frame.args["SUPER Debut"]) ) -- Games played :node( p.row( (isSuper), "Games played", (#gamesPlayedText > 0) and table.concat(gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Games played", (#s_gamesPlayedText > 0) and table.concat(s_gamesPlayedText, "<br>") or "<i>Not enough data...</i>" ) ) -- Winrate :node( p.row( (isSuper), "Winrate", (#winrateText > 0) and table.concat(winrateText, "<br>") or "<i>Not enough data...</i>" ) ) :node( (isSuper) and p.s_row( "Winrate", (#s_winrateText > 0) and table.concat(s_winrateText, "<br>") or "<i>Not enough data...</i>" ) ) return tostring(infobox) end function p.referenceTest() local element = mw.html.create( 'tr' ) :attr( "id","mw-customcollapsible-Infobox" ) :addClass( "mw-collapsible" ) :css( "text-align","left" ) local bigElement = mw.html.create( "div" ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface") ) :node( mw.clone(element) :attr( "colspan", "2" ) :node( "shitface2") ) return tostring(element) .. "\n" .. tostring(bigElement) .. "\n" end function p.roundedPct(num, den) return (num/den % 0.01 < 0.005) and math.floor(num/den * 100) or math.ceil(num/den * 100) end function p.title() --[[local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA" } } local cases2 = "ba" local cases3 = "ba" -- if grammatical_cases.inessive[frame:getParent():getTitle()] then cases2 = "true" else cases2 = "false" end -- if "ANCOVA" == frame:getParent():getTitle() then cases3 = "true" else cases3 = "false" end local detected = false detected = detected or true]] return mw.title.getCurrentTitle() end function p.ifexist() return tonumber(frame:expandTemplate{ title = "User:Helpme2222/Sandbox", args = {frame.args[1]} }) end function p.performance() for i = 1,5000000 do p.tableMake() end return end function p.performance1() local var = "" for i = 1,100000000 do if var[1] then end end return end function p.performance2() local var = "" for i = 1,100000000 do if type(var) == "table" then end end return end p.counter = 0 function p.tableBake() p.counter = p.counter + 1 return p.counter end function p.tableMake() p.counter = 0 local var = { keyword = {p.tableBake()}, kljuczslovo = {p.tableBake()}, yaoshiwenzi = {p.tableBake()}, llavepalabra = {p.tableBake()}, } return var end function p.expand() return frame:expandTemplate{ title = "User:Helpme2222/Sandbox" } end function p.title3() return mw.title.getCurrentTitle().fullText end function p.getBallAttribute() return p.getBallAttributeInternal(frame.args[1], frame.args[2], frame.args[3], frame.args[4]) end function p.getBallAttributeInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local _, ballData = pcall( p.getBallAttributeInternalInternal, arg1_table, arg2_ball, arg3_att, arg4_iteration ) if _ then return mw.text.nowiki(ballData) else return "" end end function p.getBallAttributeInternalInternal(arg1_table, arg2_ball, arg3_att, arg4_iteration) local ballData = mw.loadData(arg1_table)[arg2_ball][arg3_att] if ballData[1] then return ballData[tonumber(arg4_iteration) or p.listCountInternal(ballData)] end return ballData end function p.emojiCodepointInternal( emoji ) emoji = mw.text.trim( emoji ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.emojiCodepoint() local emoji = mw.text.trim( mw.getCurrentFrame().args[1] ) local i,v = mw.ustring.codepoint( emoji, 1, mw.ustring.len(emoji) ) if v then return "U+" .. string.format("%X", i ) .. " U+" .. string.format("%X", v ) else return "U+" .. string.format("%X", i ) end end function p.title2() local grammatical_cases = { ablative = 1, inessive = { ANCOVA = "ANCOVA", ["Module:Sandbox/22"] = "Module:Sandbox/22" } } local concepts = { grammatical_cases, } local PAGENAME = tostring(mw.title.getCurrentTitle()) -- local detected = false local out = {} local debugger = {} for i, group in ipairs(concepts) do if group.inessive[PAGENAME] then table.insert(debugger,"Okay, managed TRUE on "..i..":"..group.ablative) -- detected = detected or true local formattedGroup = {} for memberKey, memberRendervalue in pairs(group.inessive) do table.insert(formattedGroup, "<li>" .. memberRendervalue .. "</li>") end table.insert(out, "<h3>" .. group.ablative .. "</h3><ul>" .. table.concat( formattedGroup ) .. "</ul>" ) table.insert(out, "this sucks ass") return "this sucks ass" else table.insert(debugger,"Managed FALSE on "..i..":"..group.ablative..". Comparator: "..PAGENAME..", ") end end return debugger --[[ if detected then return tostring(detected) .. table.concat(out) end return --]] end function p.sanitizeChar(capture) -- If the set of likely illegal characters to appear in title expands, a rewrite of this as a table is merited if capture == "?" then return "" elseif capture == "#" then return "No. " end end function p.sanitizeTitle() local title = frame.args[1] return mw.ustring.gsub( title, "(?:\\?|\\#)", p.sanitizeChar) end function p.sanitizeTitletest2() return mw.ustring.gsub( "Ki vagy? (🌡️🌾⭐🗡️ VS 🪐 🪨 💣 🧿)", "(?:\\?|\\#)", p.sanitizeChar()) end function p.safetyTest() if string.len(frame.args[1]) < 500 then return frame.args[1] else return "" end end --[[ function array_iter(t) local i = 0 return function () i = i + 1 return t[i] end end --]] function p.listInline() --[[ This function is a godsend! https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#mw.text.listToText --]] local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return mw.text.listToText( spritedTable , ", ", ", and " ) end function p.listNavbox() -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.concat local spritedTable = {} for i,entry in ipairs(balls[tonumber(frame.args[1])]) do spritedTable[i] = "{{Sprite|named=1|linked=1|"..entry.."}}" end return table.concat( spritedTable , " • ") end function p.listCountInternal(table) local count = 0 for index,value in ipairs( table ) do count = count + 1 end return count end function p.listCount() return table.maxn(balls[tonumber(frame.args[1])]) end -- https://www.mediawiki.org/wiki/Extension:Scribunto/Lua_reference_manual#table.maxn function p.tableTest() return balls[1][1] end function p.todaysBall() --[[ https://www.lua.org/pil/3.6.html The use of explicit indexing here is not strictly semantic; it's just to emphasize the rotation order. ]] local unixDay = math.floor(os.time()/86400) local ballTotalCount = 0 local ballCounts = {} for whichTable,subtable in ipairs(balls) do ballCounts[whichTable] = #subtable ballTotalCount = ballTotalCount + ballCounts[whichTable] end local cycleDayIndex, cycleStartingBall = unixDay % ballTotalCount, math.floor(unixDay/ballTotalCount) % ballTotalCount local cycleTodaysBall if ballTotalCount % 7 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*7) % ballTotalCount elseif ballTotalCount % 11 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*11) % ballTotalCount elseif ballTotalCount % 13 ~= 0 then cycleTodaysBall = (cycleStartingBall + cycleDayIndex*13) % ballTotalCount else cycleTodaysBall = (cycleStartingBall + cycleDayIndex*(ballTotalCount - 1)) % ballTotalCount end --[[ debug return cycleTodaysBall .. " " .. ballTotalCount .. " " .. os.time() .. " " .. math.floor(os.time()/86400) .. " " .. cycleDayIndex .. " " .. cycleStartingBall ]] for whichTable = 1, #balls do if ballCounts[whichTable] > cycleTodaysBall then return balls[whichTable][cycleTodaysBall + 1] else cycleTodaysBall = cycleTodaysBall - ballCounts[whichTable] end end --]] end return p; dxxo3xcla843c17abrypka7gjxd3yon 0 331021 2835085 2834786 2026-09-30T00:46:38Z StretchBeyond 3105744 /* Overview */ 2835085 wikitext text/x-wiki {{title|Immersive therapy for PTSD treatment:<br>How does it work and what are the effects?}} __TOC__ == Overview == {{RoundBoxTop|theme=2}} '''Scenario: Immersive PTSD therapies''' Andriy, a soldier, harnessed to a treadmill, walks towards an image he spent months avoiding, his clinical therapist beside him. This is multi-modular motion assisted memory desensitisation and reconsolidation (3MDR), one of a new generation of immersive therapies for post-traumatic stress disorder. [[File:Andriy 3MDR enhanced.gif|center|600x600px]] '''Figure 1.''' Andriy moves through his 3MDR treatment. Learn about immersive therapy and Andriy’s* experience below (*Andriy: a fictional name). {{RoundBoxBottom}} [[File:Post-traumatic_stress_disorder_world_map_-_DALY_-_WHO2004.svg|alt=|thumb|271x271px|'''Figure 2:''' The World Health Organisation (2024) estimated that [https://www.who.int/news-room/fact-sheets/detail/post-traumatic-stress-disorder 3.9% of the world's population had PTSD] at some stage.]] [[w:Post-traumatic_stress_disorder|Post-traumatic stress disorder]] (PTSD) develops after severe or life-threatening trauma and carries a substantial personal and societal cost (Figure 2), with military personnel disproportionately represented (Boska et al., 2025). See costs and limitations below (Davis et al., 2022; Montgomery-Marks et al., 2025). PTSD's emotional impact is shaped by [[w:Emotional_dysregulation|emotional dysregulation]] - difficulty managing intense feelings such as guilt, fear or shame (Westphal et al., 2017). This commonly triggers [[Cognitive psychology|cognitive]] and behavioural avoidance that offers short-term relief but prevents traumatic memory from being adaptively processed, trapping individuals in cycles of avoidance and chronic hyper-arousal (de Haart et al., 2026; van Gelderen et al., 2018). Immersive interventions, including [[w:Virtual_reality_therapy|virtual reality exposure therapy]] (VRET) and 3MDR, aim to break this avoidance cycle by creating controlled environments in which trauma cues can be safely approached rather than avoided (van Gelderen et al., 2018; Wiederhold & Wiederhold, 2025). This chapter explains the psychological theory behind these approaches, reviews the research evidence for their effects and considers their limitations. {{RoundBoxTop|theme=2}} '''Focus questions'''[[File:Crystal Clear app ktip.svg|left|20px|]] * Why is emotional processing important in PTSD? * How can immersive therapies influence the emotional processes underlying PTSD? * What does the research evidence show? * What are the costs and limitations of immersive therapies? {{RoundBoxBottom}} == Why is emotional processing important in PTSD? == [[File:PTSD.png|thumb|'''Figure 3.''' PTSD can deeply affect our emotions.]]PTSD is formally diagnosed according to [[w:DSM-5|DSM-5]] criteria and is characterised by disrupted executive and emotional processing systems, heightened threat perception, hyper-vigilance and persistent negative emotional states as depicted in Figure 3 (Kukharuk et al., 2025; López-Ojeda & Hurley, 2022; Osman et al., 2016). Emotional processing theory provides the primary framework for understanding this disruption, supported by emotion regulation theory and inhibitory learning models introduced later in the chapter. {{RoundBoxTop|theme=3}}[[Image:Crystal Clear app help index.svg|left|50px]] ;Predict the outcome A soldier with PTSD encounters a trauma-related image expecting: '''TRAUMA CUE → DANGER → DISTRESS → AVOID''' However, during immersive treatment, the expected danger does not occur. What is the most likely consequence?<quiz display=simple> { |type="()"} - Fear increases permanently. - Memory cannot change. + Prediction error creates opportunities for new learning. - Emotional processing stops.  } </quiz> <div style="text-align:right; color:red; font-weight:bold;"> Click "show" below to understand more⤵ </div> {{Hidden begin|title=Please consider the answer before opening this section}}The answer is '''C'''. <div style="text-align:left; color:black; font-weight:regular;"> Mismatches between expected and actual danger create a '''prediction error'''. This may contribute to fear extinction, emotion regulation, and memory reconsolidation. '''Think about it:''' If approaching rather than avoiding trauma can create new learning, what role might emotion regulation, fear extinction, prediction error and memory reconsolidation play? </div>   {{Hidden end}} <div style="text-align:left; color:black; font-weight:regular;"> </div>{{RoundBoxBottom}} === Understanding PTSD and emotions === Emotional processing theory suggests recovery requires the trauma memory to be reactivated and updated with corrective information. In PTSD, this process is blocked and to manage distress, many individuals adopt cognitive and behavioural avoidance mechanisms (López-Ojeda & Hurley, 2022). Avoidance offers short-term relief, but prevents the traumatic memory from being reactivated, so it cannot be updated. Trauma reminders such as flashbacks continue to trigger extreme distress, trapping the individual in a maladaptive, self-reinforcing avoidance cycle (Figure 4) (Vermetten, Burback, et al., 2025b). At a neural level, Westphal et al. (2017) linked this to [[wikipedia:Transdiagnostic_process|transdiagnostic]] [[w:Emotional_dysregulation|emotion dysregulation]], in which the traumatic memory network remains isolated from the brain's [[w:Salience_network|salience]] and central executive networks. Effective treatment requires reactivating this network so the memory can be integrated (Vermetten, Burback, et al., 2025b; Westphal et al., 2017). This is empirically supported: A 2025 study of Danish military veterans (''n''=142) found emotional regulation difficulties explained an additional 28% of the variance in PTSD symptoms; combined with [[w:Comorbidity|comorbid]] symptoms, these factors accounted for 52% of the variance in severity (''F''(13, 92) = 9.58, ''p'' <0.001) (Elklit & Dahl, 2025).[[File:Avoidance and Processing Cycles.png|500x500px|thumb|'''Figure 4'''. Avoidance cycles and the anticipated positive responses associated with immersive therapies. Based on: Lopez-Ojeda et al. (2022), Felemban et al. (2026), and Vermetten et. al. (2025b).|center]] === Why treatment can be difficult === Trauma-focused psychotherapies such as [[w:Prolonged_exposure_therapy|prolonged exposure]] (PE) and [[w:Cognitive_processing_therapy|cognitive processing therapy]] (CPT) ask patients to actively engage with distressing memories to generate fear extinction, precisely what avoidance prevents (van Toorenburg et al., 2020). Many patients cannot tolerate the emotional exposure these therapies require (Lopes et al., 2025; van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b). Because the trigger is never confronted, the brain cannot experience a prediction error needed to learn the threat has passed, so symptoms persist (de Haart et al., 2026; López-Ojeda & Hurley, 2022). This is reflected in outcomes where an estimated 39.2% of patients fail to respond to standard trauma-focused therapy, and dropout rates range from 16-48% (de Haart et al., 2026; Vermetten, Burback, et al., 2025b). Among military veterans, younger patients show heightened severity when trauma is central to their identity, while others turn to poor diet or substance abuse, further eroding emotional regulation (Efremov, 2025; Niles et al., 2023). [[w:Emotional_dysregulation|Emotional dysregulation]] was historically viewed as a fixed barrier requiring lengthy stabilisation before treatment could begin (van Toorenburg et al., 2020). More recent evidence suggests otherwise, although emotional regulation contributes to PTSD symptoms, it is also being increasingly viewed as a modifiable process with dynamic capacity, one able to improve as a natural consequence of successful memory processing (van Toorenburg et al., 2020). This reframes the clinical challenge as helping an individual safely approach and process the traumatic memory, not correcting a fixed deficit. [[File:UC PhD VR study.png|right|thumb|'''Figure 5.''' PhD work by Selvakumaran (University of Canberra) examining cultural adaptation using the US-''Bravemind'' system.]]Cultural context adds another layer of difficulty. Doctoral research at the [[University of Canberra]] is integrating exposure therapy with gamified, posture-adaptive cognitive rehabilitation to support physical and emotional recovery (Figure 5). Selvakumaran (2025), is examining how existing protocols such as used in the US-centric ''[https://medvr.ict.usc.edu/projects/bravemind.html Bravemind]'' system need cultural adaptation for Australian veterans and first responders, because their operational context and backgrounds differ from their US counterparts (Selvakumaran, 2025). These treatment gaps carry a substantial economic and personal cost, part of the motivation for developing alternatives such as immersive therapies.    == How can immersive therapies influence emotional processes? == Immersive PTSD treatments mark a shift from passive, sedentary therapy towards active, embodied, interactive approaches (van Gelderen et al., 2018). Immersive therapy uses three psychological mechanisms and their interaction: multisensory presence, embodied cognition, and divergent thinking (López-Ojeda & Hurley, 2022; van Gelderen et al., 2018). Embodied cognition is how physical states of the body can directly modify states of the mind (van Gelderen et al., 2018). Immersion therapy goes beyond simple visual replication of a trauma memory; instead, capturing the participant’s visceral and cognitive focus by limiting distractions (Macey et al., 2026). === What is immersive therapy? === [[w:Immersion_therapy|Immersive therapies]] use [[w:Extended_reality|extended reality]] (XR) platforms, encompassing [[virtual reality]] (VR), [[Augmented Reality|augmented reality]] (AR), and [[w:Mixed_reality_game|mixed reality]] (MR), to create customisable, controlled, and standardised therapeutic environments (López-Ojeda & Hurley, 2022; Wiederhold & Wiederhold, 2025). This ecosystem is depicted in Figure 6. This chapter focuses on two applications: VRET where therapists reconstruct traumatic scenarios in safe, graded environments, and 3MDR, which extends this by having the patient move on a treadmill beside their therapist, rather than in a stationary, face-to-face session (de Haart et al., 2026; Felemban et al., 2026).[[File:XR and Human Senses.png|thumb|'''Figure 6.''' The Extended Reality environment. |center|750x750px]] === Presence and embodied cognition === Immersive therapy’s distinguishing feature is its ability to generate presence, or the psychological illusion of being ‘''there’''. The illusion is amplified by integrating synchronised audio, visual, [[w:Olfactory|olfactory]], [[wikipedia:Haptic_perception|haptic]], and movement stimuli (Lopes et al., 2025; López-Ojeda & Hurley, 2022). This increases engagement with the trauma memory and supports emotional processing (van Gelderen et al., 2018). In 3MDR, presence combines with cognition. The working principle is that physical states of the body can directly shape states of the mind (van Gelderen et al., 2018). Walking towards a virtual trauma reminder functions as a fear antagonistic action and rather than retreating in avoidance, the patient approaches, converting passive helplessness into active, empowered participation and disrupting the rigid and repetitive trauma narratives common in PTSD (de Haart et al., 2026; Osman et al., 2016; van Gelderen et al., 2018). Notably, extinction learning normally requires moderate-to-high-intensity activity to stimulate [[w:Brain-derived_neurotrophic_factor|brain-derived neurotrophic factor]] (BDNF), but 3MDR's walking pace (< 4 km/h) is too slow to generate meaningful BDNF secretion, making a major exercise induced BDNF mechanism unlikely, although physiological factors cannot be ruled out. The approach action and the cognitive restructuring it enables may be more important psychological drivers (de Haart et al., 2026). === Prediction error and inhibitory learning === Immersive therapy builds on the inhibitory learning model of exposure therapy, in which a new, safe association competes with and suppresses the original fear response. Walking towards a trauma cue and encountering safety instead of the expected catastrophe creates a prediction error between the anticipated, life-threatening event and actual reality. This may destabilise the traumatic memory, potentially creating conditions for memory reconsolidation to occur (van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b; Wiederhold & Wiederhold, 2025). === Memory reconsolidation === According to [[w:Memory_consolidation|memory reconsolidation]] theory, traumatic memories retrieved in a safe immersive context can become [[w:Malleability_of_intelligence|malleable]], allowing new, safe information to reconsolidate the memory in a non-threatening form (van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b). To prevent the patient from becoming overwhelmed, 3MDR uses dual-attention tasks such as tracking an oscillating ball (Figure 1), which tax working memory resources and reduce the vividness and emotional intensity of the memory (Vermetten, Burback, et al., 2025b). Emerging linguistic research suggests this processing is reflected in patients' language. Across successive 3MDR sessions, [[w:Affect_labeling|affective labelling]] of feelings such as guilt shifted from past-tense to present-tense narration, consistent with a renewed ability to integrate traumatic memories into present-moment awareness (Vermetten, Barcaro, et al., 2025a). == What does the research evidence show? == Addressing these barriers is important for any PTSD population, but especially critical for military populations with high treatment failure and dropout rates (van Gelderen et al., 2018). Immersive therapies as outlined in Table 1, can tailor patient-selected trauma cues to improve access to traumatic memory networks (Vermetten, Burback, et al., 2025b). === Virtual reality exposure therapy === [[w:Virtual_reality_therapy|VRET]] reconstructs traumatic events in a structured context (Felemban et al., 2026; López-Ojeda & Hurley, 2022). This may help bypass imagination challenges such as emotional numbing or amnesia that can prevent patients from engaging with traditional therapy (Macey et al., 2026). A meta-analysis of VRET for PTSD found substantial symptom reductions, averaging a 33.73-point decrease in the 0-80 point [[w:Clinician_Administered_PTSD_Scale|Clinician-Administered PTSD Scale]] and a 20.96-point decrease in the 0-80 point [https://www.ptsd.va.gov/professional/assessment/adult-sr/ptsd-checklist.asp PTSD Checklist PCL-5) scale] (Felemban et al., 2026). Because changes of 10-20 points on these scales are considered clinically significant, this could mean the difference between severe functional impairment and mild or subclinical symptoms (Boska et al., 2025; de Haart et al., 2026; Felemban et al., 2026). Comparative effects against other active PTSD treatments remain modest, but VRET appears to be a more engaging alternative to conventional treatment (Felemban et al., 2026). === 3MDR === 3MDR takes the same multisensory effect in VRET and adds an activating context. Rather than a sedentary, face-to-face session, the patient and the therapist face the virtual display together (van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b). It follows a three-phase protocol: pre-platform preparation, platform treadmill exposure, and post-platform re-consolidation (Vermetten, Burback, et al., 2025b). In a trial involving treatment-resistant PTSD; 3MDR showed large effect sizes from pre-treatment to six-months (''n'' = 134, ''d'' = 1.0) and high-acceptability, with 7-20% dropout rates (de Haart et al., 2026; van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b). Substantially lower than the 16-48% typical trauma-focused therapy in military populations (Lewis et al., 2020). Improvements are not limited to PTSD symptoms. A trial of 62 adults with severe PTSD, including childhood sexual trauma, found intensive trauma-focused treatment improved emotion-regulation abilities regardless of PTSD outcome (van Toorenburg et al., 2020). Some researchers link this improvement to positive psychology [[w:Broaden-and-build|broaden-and-build theory]]. Theorising that as patients regain a sense of safety and control, this may support a positive spiral of emotional flexibility that reinforces recovery (Fredrickson, 2001; Niles et al., 2023; Westphal et al., 2017). Critically, the exact causation remains unknown. Given the recent innovations in immersive therapies and small study samples, it remains unclear whether they work through exposure-based extinction, enhanced emotional engagement, physiological factors, embodiment or positive cognitive restructuring. These questions are relevant to both basic and applied research and have not yet been adequately addressed by current trial designs. '''Table 1''' ''Treatment Effects and Psychological Mechanisms'' {| class="wikitable mw-collapsible" | valign="top" |'''Clinical Dimension''' | valign="top" |'''Traditional''' | valign="top" |'''Immersive''' | valign="top" |'''Psychological Mechanisms''' |- | valign="top" |'''Context''' | valign="top" |'''''Sedentary'''''. Face-to-face, verbally describes trauma. | valign="top" |'''''Activating.''''' Dynamic, multi-sensory environment. | valign="top" |'''''Fear Antagonistic Action.''''' '''''Approach behaviours.''''' '''''Prediction Errors.''''' |- | valign="top" |'''Trauma cue delivery''' | valign="top" |'''''Imaginary Retrieval''''' Patient capacity | valign="top" |'''''Multisensory Immersion''''' Highly tailored | valign="top" |'''''External Scaffolding.''''' Bypasses internal barriers to activate memory networks. |- | valign="top" |'''Processing''' | valign="top" |'''''Convergent processing.''''' Repeated narration and fear habituation. | valign="top" |'''''Active Narrative Processing.''''' Interactive, real-time affective labelling and dual attention tasks. | valign="top" |'''''Working Memory.''''' Memory taxation reduces vividness and emotional intensity. |- | valign="top" |'''Engagement''' | valign="top" |'''''Attrition.''''' Dropout rates 16-48%. | valign="top" |'''''Acceptability.''''' Attractive. Dropout rates 7-20%. | valign="top" |'''''Sustained Motivation.''''' Presence and safety in immersive environment. |} === Applied example: 3MDR treatment in Ukraine === {{RoundBoxTop|theme=2}} '''Scenario: Ukraine War: an applied 3MDR example''' Andriy*, a Ukrainian Armed Forces volunteer, is struggling with hyper-vigilance, anxiety, and depression (Kukharuk et al., 2025). Traditional ‘talk’ therapy feels impossible; his mind remains in a constant state of combat readiness, even in quiet rooms. In the pre-platform phase, Andriy identifies ‘hotspot’ memories in photographs. On the treadmill, harnessed and walking, he faces a panoramic screen as personalised warm-up music plays, selected to keep him connected to his traumatic memory network (Vermetten et al., 2025b). As his hotspot image fills the screen, his therapist asks three questions (Vermetten et al., 2025b): 1. What do you '''SEE''' ? 2. What does it '''TELL''' you? 3. What do you '''FEEL''' in your body NOW? When Andriy identifies a surge of shame, the word '''GUILT''' is displayed as an affective label, and a dual-attention task begins. He tracks an oscillating, numbered ball while he stays with the emotion, taxing his working memory and reducing the intensity of the recalled trauma. [[File:Andriy 3MDR enhanced.gif|center|600x600px]] '''Figure 7.''' Andriy's 3MDR treatment. By the end of the session, Andriy had walked toward what he used to avoid, creating a mismatch between his expectation of threat and his safety and turning a rigid, stuck memory into a manageable narrative. *''Andriy, a fictional name given to one of 69 Ukrainian veterans, participating in a 2023 randomised controlled trial. Many demobilised after one year because of mental or neurological injuries'' (Kukharuk et al., 2025). {{RoundBoxBottom}} == What are the costs and limitations of immersive therapies? == PTSD carries a substantial economic burden. An estimated US$232 billion in excess costs in the United States in 2018 and over £40 billion, in the United Kingdom in 2020-21, 92.4% of which were indirect rather than direct clinical costs (Davis et al., 2022; Montgomery-Marks et al., 2025). In Australia, the annual cost of PTSD per military veteran was estimated at $112,172 in 2025 (Magnusson & Dey, 2025). In addition, individual healthcare costs surge by 142% in the year following a PTSD diagnosis, with comorbidities tripling this effect (Bothe et al., 2020). These figures span several countries and years and should be read as an indication of scale rather than as directly comparable totals. Immersive therapy’s ability to move from small trials into mainstream PTSD treatment remains limited by methodological [[w:Homogeneity_and_heterogeneity|heterogeneity]], small sample sizes, and a lack of long-term data (Felemban et al., 2026). Many trials rely on military-heavy, treatment-resistant samples with few active comparison conditions, which limits the generalisation of findings to civilian or initial treatment populations. Practical issues such as [[w:Virtual_reality_sickness|cyber sickness]] or motion sickness can disrupt participation (Kukharuk et al., 2025). Structural barriers include workforce training and equipment costs. Basic VR systems cost around US$3,500 per provider headset annually, with advanced simulation environments costing up to US$200,000 (Garrett et al., 2018). Despite this, adoption of immersive therapy is scaling. The [[w:United_States_Department_of_Veterans_Affairs|United States Veterans Affairs]] have expanded VR use from five medical centres in 2017 to over 154 centres and 2,300 staff, with applications now including over 40 documented clinical interventions such as chronic pain and suicide intervention (Bailey et al., 2024). Reflecting this potential growth trend, some market analysts estimate the global PTSD-focused VR therapy market was worth US$1.59 billion in 2025, forecasted to reach US$5.94 billion by 2032, driven largely by growing mental health awareness and the absence of standard clinical protocols (Stratistics MRC, 2025, an industry market report). These limitations do not undermine the case for immersive therapy, but they show its evidence base and infrastructure are still maturing. Demonstrating rigorously why these therapies work, rather than assuming their novelty accounts for their effects is essential to avoid misallocating resources to unproven interventions and may support an emerging shift towards greater emphasis on post-traumatic growth and renewed optimism (Trejo et al., 2015; Vermetten, Burback, et al., 2025b; Wiederhold & Wiederhold, 2025). {{Robelbox|theme=2|title=Quiz}} <quiz display=simple> {Which of the following is an expected outcome of immersive therapy ? |type="()"} - Patients are at risk because of an uncontrolled environment. - The environments represent traditional face-to-face treatments. - Failure and dropout rates are higher than traditional PTSD treatment. + Patients often broaden and build an upward spiral of emotion and optimism. </quiz> {{Robelbox/close}} == Conclusion == PTSD traps people in a self-reinforcing cycle of avoidance that blocks the adaptive processing necessary for traumatic memories to be resolved (see: ''[[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment#Understanding PTSD and emotions|Understanding PTSD and emotions]]''). Standard trauma-focused therapies require patients to confront exactly what this cycle causes them to avoid, which contributes to high non-response and dropout rates (see ''[[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment#Why treatment can be difficult|Why treatment can be difficult]]''). Immersive therapies such as VRET and 3MDR address this by using presence, embodied cognition, prediction error and memory reconsolidation to help patients safely approach trauma cues rather than avoid them (see: ''[[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment#What does the research evidence show?|What does the research evidence show]]''). The technology itself is only a delivery mechanism that enables the processes, the positive benefits appear to arise from the psychological mechanisms that immersive therapies facilitate, rather than the novelty of technology alone. The evidence to date shows meaningful reductions in PTSD symptoms and comparatively low drop-out rates, alongside broader gains in emotional regulation. However, small samples, methodological variation, and a lack of long-term data mean the evidence base is still developing, and cost and infrastructure barriers remain significant (see: [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment#What are the costs and limitations of immersive therapies?|costs and limitations]]'').{{RoundBoxTop|theme=11}} [[File:Nuvola apps kuser.svg|Nuvola apps kuser|left|20px]] ''' Take-home message:''' Immersive therapies do not heal PTSD trauma through technological novelty or digital feedback. Instead, they create a safe, dynamic space that lets individuals confront trauma and reprocess memories into something they can live with. In doing so, people’s lives may once again shift toward value, optimism, and wellness.{{RoundBoxBottom}} == See also == '''Wikiversity''' * [[Motivation and emotion/Textbook/Emotion/Anxiety|Anxiety]] (Book chapter, 2010) * [[/Non-invasive brain stimulation techniques/]] (Sub-page) * [[Evidence-based assessment/Posttraumatic stress disorder (disorder portfolio)|Evidence-based PTSD assessment]] * [[Motivation and emotion/Book/2024/Sense hacking|Sense hacking]] (Book chapter, 2024) '''Wikipedia''' * [[w:Affect_labeling|Affective labelling]] * [[Augmented Reality|Augmented reality]] * [[w:Brain-derived_neurotrophic_factor|Brain-derived neurotrophic factor]] * [[w:Broaden-and-build|Broaden-and-build theory]] * [[w:Cognitive_processing_therapy|Cognitive processing therapy]] * [[w:Virtual_reality_sickness|Cyber sickness]] * [[w:DSM-5|DSM-5]] * [[w:Emotional_dysregulation|Emotional dysregulation]] * [[w:Extended_reality|Extended reality]] * [[w:Malleability_of_intelligence|Malleability of intelligence]] * [[w:Memory_consolidation|Memory reconsolidation]] * [[w:Mixed_reality_game|Mixed reality]] * [[w:Post-traumatic_stress_disorder|Post-traumatic stress disorder]] * [[w:Prolonged_exposure_therapy|Prolonged exposure therapy]] * [[wikipedia:Virtual_reality_therapy|Virtual reality exposure therapy]] == References == {{Hanging indent|Bailey, A. L., Kirsh, S., Rawlins, C., Persky, S., & Clancy, C. (2024). Early scaling of immersive technology within the Veterans Health Administration. ''NEJM Catalyst Innovations in Care Delivery'', 5(4). https://doi.org/10.1056/cat.23.0356 Boska, R. L., Bishop, T. M., Capron, D. W., Paxton Willing, M. M., & Ashrafioun, L. (2025). Difficulties with emotion regulation within PTSD clusters and moral injury subtypes. ''Military Psychology'', 37(2), 159-167. https://doi.org/10.1080/08995605.2024.2322904 de Haart, R., Daniels, J. K., Timmerman, M. E., Cath, D. C., & Lommen, M. J. J. (2026). Augmenting virtual reality exposure for PTSD with physical activity: Study protocol of a randomised controlled trial. ''European'' ''Journal of Psychotraumatology'', 17(1), 2605803. https://doi.org/10.1080/20008066.2025.2605803 Efremov, A. (2025). Age-specific mental health profiles of combat veterans: Post-traumatic stress disorder and related disorders. ''Journal of Rational-Emotive & Cognitive-Behavior Therapy'', 44(4), 1-15. https://doi.org/10.1007/s10942-025-00637-7 Elklit, A., & Dahl, N. H. (2025). Emotion regulation difficulties, aggression, and PTSD symptoms in Danish treatment-seeking veterans. ''Scandinavian Journal of Military Studies'', 8(1), 308-326. https://doi.org/10.31374/sjms.264 Felemban, R. G., Alzahrani, R. R., Alrefaei, N. F., Alharbi, N. M., Alghamdi, A. S., & Alqadi, S. (2026). Efficacy of virtual reality-based exposure therapy for post-traumatic stress disorder in military veterans: A systematic review and meta-analysis. ''Frontiers in Psychiatry'', 17, 1857109. https://doi.org/10.3389/fpsyt.2026.1857109 Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build theory of positive emotions. ''American Psychologist'', 56(3), 218-226. https://doi.org/10.1037/0003-066X.56.3.218 Garrett, B., Taverner, T., Gromala, D., Tao, G., Cordingley, E., & Sun, C. (2018). Virtual reality clinical research: Promises and challenges. ''JMIR Serious Games'', 6(4), e10839. https://doi.org/10.2196/10839 Kukharuk, O., Tkalich, K., Kamash, N., & Georgiou, O. (2025). Effectiveness of immersive VR therapy in reducing stress-associated symptoms in Ukraine. ''European Journal of Psychotraumatology'', 16(1), 2488097. https://doi.org/10.1080/20008066.2025.2488097 Lewis, C., Roberts, N. P., Andrew, M., Starling, E., & Bisson, J. I. (2020). Psychological therapies for post-traumatic stress disorder in adults: Systematic review and meta-analysis. ''European Journal of Psychotraumatology'', 11(1), 1729633. https://doi.org/10.1080/20008198.2020.1729633 Lopes, M. K. S., Perreault, L., de Jesus, B. Jr., Roberge, M. C., & Falk, T. H. (2025). Subjective and objective evaluation of the benefits of multisensory virtual nature immersion for patients with post-traumatic stress disorder. In ''Proceedings of the 17th International Conference on Quality of Multimedia Experience'' (QoMEX) (pp.1-5). IEEE. https://doi.org/10.1109/QoMEX65720.2025.11219945 López-Ojeda, W., & Hurley, R. A. (2022). Extended reality technologies: Expanding therapeutic approaches for PTSD. ''The Journal of Neuropsychiatry and Clinical Neurosciences'', 34(1), 1-5. https://doi.org/10.1176/appi.neuropsych.21100244 Macey, A.-L., Macey, J., & Hamari, J. (2026). Emotion regulation in immersive virtual reality environments: A scoping review. ''Interacting with Computers'', 29, 1-20. https://doi.org/10.1093/iwc/iwag029 Niles, B., Lang, A., & Olff, M. (2023). Complementary and integrative interventions for PTSD. ''European Journal of Psychotraumatology'', 14(2), 2247888. https://doi.org/10.1080/20008066.2023.2247888 Osman, A., Paczynski, M., & Jha, A. P. (2016). Affective expectations influence neural responses to stressful images in soldiers. ''Military Psychology'', 29(1), 41-57. https://doi.org/10.1037/mil0000128 Selvakumaran, R. V. (2025). Developing virtual reality (VR) simulations with embedded user analytics for cognitive rehabilitation in PTSD veterans. In ''Proceedings of the 27th International Conference on Multimodal Interaction'' (pp. 740-744). ACM. https://doi.org/10.1145/3716553.3750826 Trejo, B. C., Richard, E. M., van Driel, M., & McDonald, D. P. (2015). Cross-cultural competence: The role of emotion regulation ability and optimism. ''Military Psychology'', 27(5), 276-286. https://doi.org/10.1037/mil0000081 van Gelderen, M. J., Nijdam, M. J., & Vermetten, E. (2018). An innovative framework for delivering psychotherapy to patients with treatment-resistant posttraumatic stress disorder: Rationale for interactive motion-assisted therapy. ''Frontiers in Psychiatry'', 9, 176. https://doi.org/10.3389/fpsyt.2018.00176 van Toorenburg, M. M., Sanches, S. A., Linders, B., Rozendaal, L., Voorendonk, E. M., Van Minnen, A., & De Jongh, A. (2020). Do emotion regulation difficulties affect outcome of intensive trauma-focused treatment of patients with severe PTSD? ''European Journal of Psychotraumatology'', 11(1), 1724417. https://doi.org/10.1080/20008198.2020.1724417 Vermetten, E., Barcaro, S., Espejo, E., Bellini, P., Roy, M. J., & Bremault-Phillips, S. (2025a). Linguistic analysis of patients’ labels during 3MDR psychotherapy. ''Psychiatry and Clinical Psychopharmacology'', 35(Suppl. 1), S29. https://doi.org/10.5152/pcp.2025.241024 Vermetten, E., Burback, L., Sevigny, P. R., Nijdam, M. J., Winkler, O., Espejo, E., Sessoms, P., Bright, K., Roy, M. J., & Brémault-Phillips, S. (2025b). Brief manual for multi-modal motion-assisted memory desensitization and reconsolidation therapy for the treatment of post-traumatic stress disorder. ''Psychiatry and Clinical Psychopharmacology'', 35(Suppl. 1), S122. https://doi.org/10.5152/pcp.2025.241028 Westphal, M., Aldao, A., & Jackson, C. (2017). Emotion dysregulation in comorbid posttraumatic stress disorder and substance use disorders: A narrative review. ''Military Psychology'', 29(3), 216-233. https://doi.org/10.1037/mil0000157 Wiederhold, B. K., & Wiederhold, M. D. (2025). Virtual reality therapy combined with physiological monitoring provides effective treatment, with objective metrics, for post-traumatic stress disorder. ''Expert Review of Medical Devices'', 22(2), 117-119. https://doi.org/10.1080/17434440.2025.2454930 }} == External links == * '''Web:''' [https://www.healthdirect.gov.au/post-traumatic-stress-disorder-ptsd Post traumatic stress disorder] (Australian Government) * '''Web:''' [https://www.ptsd.va.gov/index.asp National Center for PTSD information home page] (US Government) * '''Web:''' [https://www.innovation.va.gov/hil/views/immersive/immersive-programs.html US Veterans Affairs Immersive Programs Innov]<nowiki/>[https://www.innovation.va.gov/hil/views/immersive/immersive-programs.html ation] (US Government) * '''Web:''' [https://defenceveteransuicide.royalcommission.gov.au/publications/final-report Australian Royal Commission into Defence and Veteran Suicide - Final Repor]<nowiki/>[https://defenceveteransuicide.royalcommission.gov.au/publications/final-report t] (Australian Government) * '''Web:''' [https://www.strategymrc.com/report/virtual-reality-therapy-for-ptsd-market Virtual reality therapy for PTSD market forecasts to 2032:] (Stratistics MR<nowiki/>C, a 2025 industry market report). * '''Podcast:''' [https://shows.acast.com/5c3353e484e2e79370e1d135/5c3353ef84e2e79370e1d13c PTSD Podcast] (Peace of Mind: Mental Health and Psychiatry, ACAST, 43 min) * '''Video:''' [https://www.youtube.com/watch?v=bD43R_oa6qo 3MDR: Virtual reality treatment for veterans] (National Centre for Mental Health,Youtube, 2:46 min) * '''Video:''' [https://www.youtube.com/watch?v=jL2bKmniMTc VR exposure for combat PTSD] (PsyTech VR, Youtube, 2:20 min) * '''Final Report:''' [https://www.ncmh.info/wp-content/uploads/2020/05/Cardiff-3MDR-Study-Final-Report-with-cover-21.5.20.pdf 3MDR randomised control trial - Final-Report] (Cardiff University) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Psychotherapy]] [[Category:Motivation and emotion/Book/Trauma]] <references /> mgjrbojr5qwjwhrsjx63s1prgywp2zg 2835086 2835085 2026-09-30T00:58:17Z StretchBeyond 3105744 2835086 wikitext text/x-wiki {{title|Immersive therapy for PTSD treatment:<br>How does it work and what are the effects?}} __TOC__ == Overview == {{RoundBoxTop|theme=2}} '''Scenario: Immersive PTSD therapies''' Andriy, a soldier, harnessed to a treadmill, walks towards an image he spent months avoiding, his clinical therapist beside him. This is multi-modular motion assisted memory desensitisation and reconsolidation (3MDR), one of a new generation of immersive therapies for post-traumatic stress disorder. [[File:Andriy 3MDR enhanced.gif|center|600x600px]] '''Figure 1.''' Andriy moves through his 3MDR treatment. Learn about immersive therapy and Andriy’s* experience below (*Andriy: a fictional name). {{RoundBoxBottom}} [[File:Post-traumatic_stress_disorder_world_map_-_DALY_-_WHO2004.svg|alt=|thumb|271x271px|'''Figure 2:''' The World Health Organisation (2024) estimated that [https://www.who.int/news-room/fact-sheets/detail/post-traumatic-stress-disorder 3.9% of the world's population had PTSD] at some stage.]] [[w:Post-traumatic_stress_disorder|Post-traumatic stress disorder]] (PTSD) develops after severe or life-threatening trauma and carries a substantial personal and societal cost (Figure 2), with military personnel disproportionately represented (Boska et al., 2025). See costs and limitations below (Davis et al., 2022; Montgomery-Marks et al., 2025). PTSD's emotional impact is shaped by [[w:Emotional_dysregulation|emotional dysregulation]], a difficulty in managing intense feelings such as guilt, fear or shame (Westphal et al., 2017). This commonly triggers [[Cognitive psychology|cognitive]] and behavioural avoidance that offers short-term relief but prevents traumatic memory from being adaptively processed, trapping individuals in cycles of avoidance and chronic hyper-arousal (de Haart et al., 2026; van Gelderen et al., 2018). Immersive interventions, including [[w:Virtual_reality_therapy|virtual reality exposure therapy]] (VRET) and 3MDR, aim to break this avoidance cycle by creating controlled environments in which trauma cues can be safely approached rather than avoided (van Gelderen et al., 2018; Wiederhold & Wiederhold, 2025). This chapter explains the psychological theory behind these approaches, reviews the research evidence for their effects and considers their limitations. {{RoundBoxTop|theme=2}} '''Focus questions'''[[File:Crystal Clear app ktip.svg|left|20px|]] * Why is emotional processing important in PTSD? * How can immersive therapies influence the emotional processes underlying PTSD? * What does the research evidence show? * What are the costs and limitations of immersive therapies? {{RoundBoxBottom}} == Why is emotional processing important in PTSD? == [[File:PTSD.png|thumb|'''Figure 3.''' PTSD can deeply affect our emotions.]]PTSD is formally diagnosed according to [[w:DSM-5|DSM-5]] criteria and is characterised by disrupted executive and emotional processing systems, heightened threat perception, hyper-vigilance and persistent negative emotional states as depicted in Figure 3 (Kukharuk et al., 2025; López-Ojeda & Hurley, 2022; Osman et al., 2016). Emotional processing theory provides the primary framework for understanding this disruption, supported by emotion regulation theory and inhibitory learning models introduced later in the chapter. {{RoundBoxTop|theme=3}}[[Image:Crystal Clear app help index.svg|left|50px]] ;Predict the outcome A soldier with PTSD encounters a trauma-related image expecting: '''TRAUMA CUE → DANGER → DISTRESS → AVOID''' However, during immersive treatment, the expected danger does not occur. What is the most likely consequence?<quiz display=simple> { |type="()"} - Fear increases permanently. - Memory cannot change. + Prediction error creates opportunities for new learning. - Emotional processing stops.  } </quiz> <div style="text-align:right; color:red; font-weight:bold;"> Click "show" below to understand more⤵ </div> {{Hidden begin|title=Please consider the answer before opening this section}}The answer is '''C'''. <div style="text-align:left; color:black; font-weight:regular;"> Mismatches between expected and actual danger create a '''prediction error'''. This may contribute to fear extinction, emotion regulation, and memory reconsolidation. '''Think about it:''' If approaching rather than avoiding trauma can create new learning, what role might emotion regulation, fear extinction, prediction error and memory reconsolidation play? </div>   {{Hidden end}} <div style="text-align:left; color:black; font-weight:regular;"> </div>{{RoundBoxBottom}} === Understanding PTSD and emotions === Emotional processing theory suggests recovery requires the trauma memory to be reactivated and updated with corrective information. In PTSD, this process is blocked and to manage distress, many individuals adopt cognitive and behavioural avoidance mechanisms (López-Ojeda & Hurley, 2022). Avoidance offers short-term relief, but prevents the traumatic memory from being reactivated, so it cannot be updated. Trauma reminders such as flashbacks continue to trigger extreme distress, trapping the individual in a maladaptive, self-reinforcing avoidance cycle (Figure 4) (Vermetten, Burback, et al., 2025b). At a neural level, Westphal et al. (2017) linked this to [[wikipedia:Transdiagnostic_process|transdiagnostic]] [[w:Emotional_dysregulation|emotion dysregulation]], in which the traumatic memory network remains isolated from the brain's [[w:Salience_network|salience]] and central executive networks. Effective treatment requires reactivating this network so the memory can be integrated (Vermetten, Burback, et al., 2025b; Westphal et al., 2017). This is empirically supported: A 2025 study of Danish military veterans (''n''=142) found emotional regulation difficulties explained an additional 28% of the variance in PTSD symptoms; combined with [[w:Comorbidity|comorbid]] symptoms, these factors accounted for 52% of the variance in severity (''F''(13, 92) = 9.58, ''p'' <0.001) (Elklit & Dahl, 2025).[[File:Avoidance and Processing Cycles.png|500x500px|thumb|'''Figure 4'''. Avoidance cycles and the anticipated positive responses associated with immersive therapies. Based on: Lopez-Ojeda et al. (2022), Felemban et al. (2026), and Vermetten et. al. (2025b).|center]] === Why treatment can be difficult === Trauma-focused psychotherapies such as [[w:Prolonged_exposure_therapy|prolonged exposure]] (PE) and [[w:Cognitive_processing_therapy|cognitive processing therapy]] (CPT) ask patients to actively engage with distressing memories to generate fear extinction, precisely what avoidance prevents (van Toorenburg et al., 2020). Many patients cannot tolerate the emotional exposure these therapies require (Lopes et al., 2025; van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b). Because the trigger is never confronted, the brain cannot experience a prediction error needed to learn the threat has passed, so symptoms persist (de Haart et al., 2026; López-Ojeda & Hurley, 2022). This is reflected in outcomes where an estimated 39.2% of patients fail to respond to standard trauma-focused therapy, and dropout rates range from 16-48% (de Haart et al., 2026; Vermetten, Burback, et al., 2025b). Among military veterans, younger patients show heightened severity when trauma is central to their identity, while others turn to poor diet or substance abuse, further eroding emotional regulation (Efremov, 2025; Niles et al., 2023). [[w:Emotional_dysregulation|Emotional dysregulation]] was historically viewed as a fixed barrier requiring lengthy stabilisation before treatment could begin (van Toorenburg et al., 2020). More recent evidence suggests otherwise, although emotional regulation contributes to PTSD symptoms, it is also being increasingly viewed as a modifiable process with dynamic capacity, one able to improve as a natural consequence of successful memory processing (van Toorenburg et al., 2020). This reframes the clinical challenge as helping an individual safely approach and process the traumatic memory, not correcting a fixed deficit. [[File:UC PhD VR study.png|right|thumb|'''Figure 5.''' PhD work by Selvakumaran (University of Canberra) examining cultural adaptation using the US-''Bravemind'' system.]]Cultural context adds another layer of difficulty. Doctoral research at the [[University of Canberra]] is integrating exposure therapy with gamified, posture-adaptive cognitive rehabilitation to support physical and emotional recovery (Figure 5). Selvakumaran (2025), is examining how existing protocols such as used in the US-centric ''[https://medvr.ict.usc.edu/projects/bravemind.html Bravemind]'' system need cultural adaptation for Australian veterans and first responders, because their operational context and backgrounds differ from their US counterparts (Selvakumaran, 2025). These treatment gaps carry a substantial economic and personal cost, part of the motivation for developing alternatives such as immersive therapies.    == How can immersive therapies influence emotional processes? == Immersive PTSD treatments mark a shift from passive, sedentary therapy towards active, embodied, interactive approaches (van Gelderen et al., 2018). Immersive therapy uses three psychological mechanisms and their interaction: multisensory presence, embodied cognition, and divergent thinking (López-Ojeda & Hurley, 2022; van Gelderen et al., 2018). Embodied cognition is how physical states of the body can directly modify states of the mind (van Gelderen et al., 2018). Immersion therapy goes beyond simple visual replication of a trauma memory; instead, it captures the participant’s visceral and cognitive focus by limiting distractions (Macey et al., 2026). === What is immersive therapy? === [[w:Immersion_therapy|Immersive therapies]] use [[w:Extended_reality|extended reality]] (XR) platforms, encompassing [[virtual reality]] (VR), [[Augmented Reality|augmented reality]] (AR), and [[w:Mixed_reality_game|mixed reality]] (MR), to create customisable, controlled, and standardised therapeutic environments (López-Ojeda & Hurley, 2022; Wiederhold & Wiederhold, 2025). This ecosystem is depicted in Figure 6. This chapter focuses on two applications: VRET where therapists reconstruct traumatic scenarios in safe, graded environments, and 3MDR, which extends this by having the patient move on a treadmill beside their therapist, rather than in a stationary, face-to-face session (de Haart et al., 2026; Felemban et al., 2026).[[File:XR and Human Senses.png|thumb|'''Figure 6.''' The Extended Reality environment. |center|750x750px]] === Presence and embodied cognition === Immersive therapy’s distinguishing feature is its ability to generate presence, or the psychological illusion of being ‘''there’''. The illusion is amplified by integrating synchronised audio, visual, [[w:Olfactory|olfactory]], [[wikipedia:Haptic_perception|haptic]], and movement stimuli (Lopes et al., 2025; López-Ojeda & Hurley, 2022). This increases engagement with the trauma memory and supports emotional processing (van Gelderen et al., 2018). In 3MDR, presence combines with cognition. The working principle is that physical states of the body can directly shape states of the mind (van Gelderen et al., 2018). Walking towards a virtual trauma reminder functions as a fear antagonistic action and rather than retreating in avoidance, the patient approaches, converting passive helplessness into active, empowered participation and disrupting the rigid and repetitive trauma narratives common in PTSD (de Haart et al., 2026; Osman et al., 2016; van Gelderen et al., 2018). Notably, extinction learning normally requires moderate-to-high-intensity activity to stimulate [[w:Brain-derived_neurotrophic_factor|brain-derived neurotrophic factor]] (BDNF), but 3MDR's walking pace (< 4 km/h) is too slow to generate meaningful BDNF secretion, making a major exercise-induced BDNF mechanism unlikely, although physiological factors cannot be ruled out. The approach action and the cognitive restructuring it enables may be more important psychological drivers (de Haart et al., 2026). === Prediction error and inhibitory learning === Immersive therapy builds on the inhibitory learning model of exposure therapy, in which a new, safe association competes with and suppresses the original fear response. Walking towards a trauma cue and encountering safety instead of the expected catastrophe creates a prediction error between the anticipated, life-threatening event and actual reality. This may destabilise the traumatic memory, potentially creating conditions for memory reconsolidation to occur (van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b; Wiederhold & Wiederhold, 2025). === Memory reconsolidation === According to [[w:Memory_consolidation|memory reconsolidation]] theory, traumatic memories retrieved in a safe immersive context can become [[w:Malleability_of_intelligence|malleable]], allowing new, safe information to reconsolidate the memory in a non-threatening form (van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b). To prevent the patient from becoming overwhelmed, 3MDR uses dual-attention tasks such as tracking an oscillating ball (Figure 1), which tax working memory resources and reduce the vividness and emotional intensity of the memory (Vermetten, Burback, et al., 2025b). Emerging linguistic research suggests this processing is reflected in patients' language. Across successive 3MDR sessions, [[w:Affect_labeling|affective labelling]] of feelings such as guilt shifted from past-tense to present-tense narration, consistent with a renewed ability to integrate traumatic memories into present-moment awareness (Vermetten, Barcaro, et al., 2025a). == What does the research evidence show? == Addressing these barriers is important for any PTSD population, but especially critical for military populations with high treatment failure and dropout rates (van Gelderen et al., 2018). Immersive therapies, as outlined in Table 1, can tailor patient-selected trauma cues to improve access to traumatic memory networks (Vermetten, Burback, et al., 2025b). === Virtual reality exposure therapy === [[w:Virtual_reality_therapy|VRET]] reconstructs traumatic events in a structured context (Felemban et al., 2026; López-Ojeda & Hurley, 2022). This may help bypass imagination challenges such as emotional numbing or amnesia that can prevent patients from engaging with traditional therapy (Macey et al., 2026). A meta-analysis of VRET for PTSD found substantial symptom reductions, averaging a 33.73-point decrease in the 0-80 point [[w:Clinician_Administered_PTSD_Scale|Clinician-Administered PTSD Scale]] and a 20.96-point decrease in the 0-80 point [https://www.ptsd.va.gov/professional/assessment/adult-sr/ptsd-checklist.asp PTSD Checklist PCL-5) scale] (Felemban et al., 2026). Because changes of 10-20 points on these scales are considered clinically significant, this could mean the difference between severe functional impairment and mild or subclinical symptoms (Boska et al., 2025; de Haart et al., 2026; Felemban et al., 2026). Comparative effects against other active PTSD treatments remain modest, but VRET appears to be a more engaging alternative to conventional treatment (Felemban et al., 2026). === 3MDR === 3MDR takes the same multisensory effect in VRET and adds an activating context. Rather than a sedentary, face-to-face session, the patient and the therapist face the virtual display together (van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b). It follows a three-phase protocol: pre-platform preparation, platform treadmill exposure, and post-platform re-consolidation (Vermetten, Burback, et al., 2025b). In a trial involving treatment-resistant PTSD; 3MDR showed large effect sizes from pre-treatment to six-months (''n'' = 134, ''d'' = 1.0) and high-acceptability, with 7-20% dropout rates (de Haart et al., 2026; van Gelderen et al., 2018; Vermetten, Burback, et al., 2025b). Substantially lower than the 16-48% typical trauma-focused therapy in military populations (Lewis et al., 2020). Improvements are not limited to PTSD symptoms. A trial of 62 adults with severe PTSD, including childhood sexual trauma, found intensive trauma-focused treatment improved emotion-regulation abilities regardless of PTSD outcome (van Toorenburg et al., 2020). Some researchers link this improvement to positive psychology [[w:Broaden-and-build|broaden-and-build theory]]. Theorising that as patients regain a sense of safety and control, this may support a positive spiral of emotional flexibility that reinforces recovery (Fredrickson, 2001; Niles et al., 2023; Westphal et al., 2017). Critically, the exact causation remains unknown. Given the recent innovations in immersive therapies and small study samples, it remains unclear whether they work through exposure-based extinction, enhanced emotional engagement, physiological factors, embodiment or positive cognitive restructuring. These questions are relevant to both basic and applied research and have not yet been adequately addressed by current trial designs. '''Table 1''' ''Treatment Effects and Psychological Mechanisms'' {| class="wikitable mw-collapsible" | valign="top" |'''Clinical Dimension''' | valign="top" |'''Traditional''' | valign="top" |'''Immersive''' | valign="top" |'''Psychological Mechanisms''' |- | valign="top" |'''Context''' | valign="top" |'''''Sedentary'''''. Face-to-face, verbally describes trauma. | valign="top" |'''''Activating.''''' Dynamic, multi-sensory environment. | valign="top" |'''''Fear Antagonistic Action.''''' '''''Approach behaviours.''''' '''''Prediction Errors.''''' |- | valign="top" |'''Trauma cue delivery''' | valign="top" |'''''Imaginary Retrieval''''' Patient capacity | valign="top" |'''''Multisensory Immersion''''' Highly tailored | valign="top" |'''''External Scaffolding.''''' Bypasses internal barriers to activate memory networks. |- | valign="top" |'''Processing''' | valign="top" |'''''Convergent processing.''''' Repeated narration and fear habituation. | valign="top" |'''''Active Narrative Processing.''''' Interactive, real-time affective labelling and dual-attention tasks. | valign="top" |'''''Working Memory.''''' Memory taxation reduces vividness and emotional intensity. |- | valign="top" |'''Engagement''' | valign="top" |'''''Attrition.''''' Dropout rates 16-48%. | valign="top" |'''''Acceptability.''''' Attractive. Dropout rates 7-20%. | valign="top" |'''''Sustained Motivation.''''' Presence and safety in immersive environment. |} === Applied example: 3MDR treatment in Ukraine === {{RoundBoxTop|theme=2}} '''Scenario: Ukraine War: an applied 3MDR example''' Andriy*, a Ukrainian Armed Forces volunteer, is struggling with hyper-vigilance, anxiety, and depression (Kukharuk et al., 2025). Traditional ‘talk’ therapy feels impossible; his mind remains in a constant state of combat readiness, even in quiet rooms. In the pre-platform phase, Andriy identifies ‘hotspot’ memories in photographs. On the treadmill, harnessed and walking, he faces a panoramic screen as personalised warm-up music plays, selected to keep him connected to his traumatic memory network (Vermetten et al., 2025b). As his hotspot image fills the screen, his therapist asks three questions (Vermetten et al., 2025b): 1. What do you '''SEE''' ? 2. What does it '''TELL''' you? 3. What do you '''FEEL''' in your body NOW? When Andriy identifies a surge of shame, the word '''GUILT''' is displayed as an affective label, and a dual-attention task begins. He tracks an oscillating, numbered ball while he stays with the emotion, taxing his working memory and reducing the intensity of the recalled trauma. [[File:Andriy 3MDR enhanced.gif|center|600x600px]] '''Figure 7.''' Andriy's 3MDR treatment. By the end of the session, Andriy had walked toward what he used to avoid, creating a mismatch between his expectation of threat and his safety and turning a rigid, stuck memory into a manageable narrative. *''Andriy, a fictional name given to one of 69 Ukrainian veterans, participating in a 2023 randomised controlled trial. Many demobilised after one year because of mental or neurological injuries'' (Kukharuk et al., 2025). {{RoundBoxBottom}} == What are the costs and limitations of immersive therapies? == PTSD carries a substantial economic burden. PTSD was associated with an estimated US$232 billion in excess costs in the United States in 2018 and over £40 billion in the United Kingdom in 2020-21, 92.4% of which were indirect rather than direct clinical costs (Davis et al., 2022; Montgomery-Marks et al., 2025). In Australia, the annual cost of PTSD per military veteran was estimated at $112,172 in 2025 (Magnusson & Dey, 2025). In addition, individual healthcare costs surge by 142% in the year following a PTSD diagnosis, with comorbidities tripling this effect (Bothe et al., 2020). These figures span several countries and years and should be read as an indication of scale rather than as directly comparable totals. Immersive therapy’s ability to move from small trials into mainstream PTSD treatment remains limited by methodological [[w:Homogeneity_and_heterogeneity|heterogeneity]], small sample sizes, and a lack of long-term data (Felemban et al., 2026). Many trials rely on military-heavy, treatment-resistant samples with few active comparison conditions, which limits the generalisation of findings to civilian or initial treatment populations. Practical issues such as [[w:Virtual_reality_sickness|cyber sickness]] or motion sickness can disrupt participation (Kukharuk et al., 2025). Structural barriers include workforce training and equipment costs. Basic VR systems cost around US$3,500 per provider headset annually, with advanced simulation environments costing up to US$200,000 (Garrett et al., 2018). Despite this, adoption of immersive therapy is scaling. The [[w:United_States_Department_of_Veterans_Affairs|United States Veterans Affairs]] have expanded VR use from five medical centres in 2017 to over 154 centres and 2,300 staff, with applications now including over 40 documented clinical interventions such as chronic pain and suicide intervention (Bailey et al., 2024). Reflecting this potential growth trend, some market analysts estimate the global PTSD-focused VR therapy market was worth US$1.59 billion in 2025, forecasted to reach US$5.94 billion by 2032, driven largely by growing mental health awareness and the absence of standard clinical protocols (Stratistics MRC, 2025, an industry market report). These limitations do not undermine the case for immersive therapy, but they show its evidence base and infrastructure are still maturing. Demonstrating rigorously why these therapies work, rather than assuming their novelty accounts for their effects is essential to avoid misallocating resources to unproven interventions and may support an emerging shift towards greater emphasis on post-traumatic growth and renewed optimism (Trejo et al., 2015; Vermetten, Burback, et al., 2025b; Wiederhold & Wiederhold, 2025). {{Robelbox|theme=2|title=Quiz}} <quiz display=simple> {Which of the following is an expected outcome of immersive therapy ? |type="()"} - Patients are at risk because of an uncontrolled environment. - The environments represent traditional face-to-face treatments. - Failure and dropout rates are higher than traditional PTSD treatment. + Patients often broaden and build an upward spiral of emotion and optimism. </quiz> {{Robelbox/close}} == Conclusion == PTSD traps people in a self-reinforcing cycle of avoidance that blocks the adaptive processing necessary for traumatic memories to be resolved (see: ''[[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment#Understanding PTSD and emotions|Understanding PTSD and emotions]]''). Standard trauma-focused therapies require patients to confront exactly what this cycle causes them to avoid, which contributes to high non-response and dropout rates (see ''[[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment#Why treatment can be difficult|Why treatment can be difficult]]''). Immersive therapies such as VRET and 3MDR address this by using presence, embodied cognition, prediction error and memory reconsolidation to help patients safely approach trauma cues rather than avoid them (see: ''[[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment#What does the research evidence show?|What does the research evidence show]]''). The technology itself is only a delivery mechanism that enables the processes, the positive benefits appear to arise from the psychological mechanisms that immersive therapies facilitate, rather than the novelty of technology alone. The evidence to date shows meaningful reductions in PTSD symptoms and comparatively low drop-out rates, alongside broader gains in emotional regulation. However, small samples, methodological variation, and a lack of long-term data mean the evidence base is still developing, and cost and infrastructure barriers remain significant (see: [[Motivation and emotion/Book/2026/Immersive therapy for PTSD treatment#What are the costs and limitations of immersive therapies?|costs and limitations]]'').{{RoundBoxTop|theme=11}} [[File:Nuvola apps kuser.svg|Nuvola apps kuser|left|20px]] ''' Take-home message:''' Immersive therapies do not heal PTSD trauma through technological novelty or digital feedback. Instead, they create a safe, dynamic space that lets individuals confront trauma and reprocess memories into something they can live with. In doing so, people’s lives may once again shift toward value, optimism, and wellness.{{RoundBoxBottom}} == See also == '''Wikiversity''' * [[Motivation and emotion/Textbook/Emotion/Anxiety|Anxiety]] (Book chapter, 2010) * [[/Non-invasive brain stimulation techniques/]] (Sub-page) * [[Evidence-based assessment/Posttraumatic stress disorder (disorder portfolio)|Evidence-based PTSD assessment]] * [[Motivation and emotion/Book/2024/Sense hacking|Sense hacking]] (Book chapter, 2024) '''Wikipedia''' * [[w:Affect_labeling|Affective labelling]] * [[Augmented Reality|Augmented reality]] * [[w:Brain-derived_neurotrophic_factor|Brain-derived neurotrophic factor]] * [[w:Broaden-and-build|Broaden-and-build theory]] * [[w:Cognitive_processing_therapy|Cognitive processing therapy]] * [[w:Virtual_reality_sickness|Cyber sickness]] * [[w:DSM-5|DSM-5]] * [[w:Emotional_dysregulation|Emotional dysregulation]] * [[w:Extended_reality|Extended reality]] * [[w:Malleability_of_intelligence|Malleability of intelligence]] * [[w:Memory_consolidation|Memory reconsolidation]] * [[w:Mixed_reality_game|Mixed reality]] * [[w:Post-traumatic_stress_disorder|Post-traumatic stress disorder]] * [[w:Prolonged_exposure_therapy|Prolonged exposure therapy]] * [[wikipedia:Virtual_reality_therapy|Virtual reality exposure therapy]] == References == {{Hanging indent|Bailey, A. 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M., Van Minnen, A., & De Jongh, A. (2020). Do emotion regulation difficulties affect outcome of intensive trauma-focused treatment of patients with severe PTSD? ''European Journal of Psychotraumatology'', 11(1), 1724417. https://doi.org/10.1080/20008198.2020.1724417 Vermetten, E., Barcaro, S., Espejo, E., Bellini, P., Roy, M. J., & Bremault-Phillips, S. (2025a). Linguistic analysis of patients’ labels during 3MDR psychotherapy. ''Psychiatry and Clinical Psychopharmacology'', 35(Suppl. 1), S29. https://doi.org/10.5152/pcp.2025.241024 Vermetten, E., Burback, L., Sevigny, P. R., Nijdam, M. J., Winkler, O., Espejo, E., Sessoms, P., Bright, K., Roy, M. J., & Brémault-Phillips, S. (2025b). Brief manual for multi-modal motion-assisted memory desensitization and reconsolidation therapy for the treatment of post-traumatic stress disorder. ''Psychiatry and Clinical Psychopharmacology'', 35(Suppl. 1), S122. https://doi.org/10.5152/pcp.2025.241028 Westphal, M., Aldao, A., & Jackson, C. (2017). Emotion dysregulation in comorbid posttraumatic stress disorder and substance use disorders: A narrative review. ''Military Psychology'', 29(3), 216-233. https://doi.org/10.1037/mil0000157 Wiederhold, B. K., & Wiederhold, M. D. (2025). Virtual reality therapy combined with physiological monitoring provides effective treatment, with objective metrics, for post-traumatic stress disorder. ''Expert Review of Medical Devices'', 22(2), 117-119. https://doi.org/10.1080/17434440.2025.2454930 }} == External links == * '''Web:''' [https://www.healthdirect.gov.au/post-traumatic-stress-disorder-ptsd Post traumatic stress disorder] (Australian Government) * '''Web:''' [https://www.ptsd.va.gov/index.asp National Center for PTSD information home page] (US Government) * '''Web:''' [https://www.innovation.va.gov/hil/views/immersive/immersive-programs.html US Veterans Affairs Immersive Programs Innov]<nowiki/>[https://www.innovation.va.gov/hil/views/immersive/immersive-programs.html ation] (US Government) * '''Web:''' [https://defenceveteransuicide.royalcommission.gov.au/publications/final-report Australian Royal Commission into Defence and Veteran Suicide - Final Repor]<nowiki/>[https://defenceveteransuicide.royalcommission.gov.au/publications/final-report t] (Australian Government) * '''Web:''' [https://www.strategymrc.com/report/virtual-reality-therapy-for-ptsd-market Virtual reality therapy for PTSD market forecasts to 2032:] (Stratistics MR<nowiki/>C, a 2025 industry market report). * '''Podcast:''' [https://shows.acast.com/5c3353e484e2e79370e1d135/5c3353ef84e2e79370e1d13c PTSD Podcast] (Peace of Mind: Mental Health and Psychiatry, ACAST, 43 min) * '''Video:''' [https://www.youtube.com/watch?v=bD43R_oa6qo 3MDR: Virtual reality treatment for veterans] (National Centre for Mental Health,Youtube, 2:46 min) * '''Video:''' [https://www.youtube.com/watch?v=jL2bKmniMTc VR exposure for combat PTSD] (PsyTech VR, Youtube, 2:20 min) * '''Final Report:''' [https://www.ncmh.info/wp-content/uploads/2020/05/Cardiff-3MDR-Study-Final-Report-with-cover-21.5.20.pdf 3MDR randomised control trial - Final-Report] (Cardiff University) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Psychotherapy]] [[Category:Motivation and emotion/Book/Trauma]] <references /> q8iek0h82fpzwpz5a08dr5d85ehcmay 0 331034 2835102 2832501 2026-09-30T03:14:41Z U3254168 3106320 Inserted clarification comments throughout 2835102 wikitext text/x-wiki {{title|Perfectionism and procrastination:<br>What is the role of perfectionism in procrastination and what can be done about it?}} <div align=center>Edit the title and sub-title to match the wording (and casing) in the [[Motivation and emotion/Book/2025|2026 list of topics]].<br>[[Motivation and emotion/About/Staff|Seek approval]] for any changes.<br>Do not include your name (authorship is as per [[Special:History/{{PAGENAME}}|the page history]]).</div> __TOC__ ==Overview== {{RoundBoxTop|theme=9}} [[File:The procrastinating student - panoramio.jpg|right|thumb|150px|'''Figure 1'''. Waiting for the perfect moment]] '''Scenario''' Brian has been trying for several days to start preparing an important presentation for an upcoming meeting. He is convinced that he must deliver a flawless presentation - think everything through and execute everything perfectly. He’s long had a clear picture in his mind of what the presentation should be like, but some kind of inner resistance keeps making him put off getting started. He glances through the materials, then switches to other tasks, as if waiting for the moment when he’ll finally feel completely ready. But that moment never comes. {{RoundBoxBottom}} In a world where success and high achievement are highly valued, it is paradoxical that individuals who attach great importance to these goals may nonetheless refrain from action or engage in task avoidance {{citation needed}}. The interplay of these motives can result in two psychological constructs: [[wikipedia:Perfectionism_(psychology)|perfectionism]] and [[wikipedia:Procrastination|procrastination]] {{citation needed}}. Although they do not necessarily co-occur, empirical research indicates that some links exist between them {{citation needed}}. Understanding which possible mechanisms underlie the relationship between perfectionism and procrastination may help identify ways to overcome procrastination and achieve intended goals {{citation needed}}. Key resources: * [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 02]] explains about how to edit * [[Motivation and emotion/Assessment/Topic|Topic development guidelines]] * [[Motivation and emotion/Assessment/Chapter|Book chapter guidelines]] {{RoundBoxTop|theme=3}} '''Focus questions''' [[File:Crystal Clear app ktip.svg|left|20px|]] * What is the nature{{vague}} of perfectionism and procrastination? * What is the relationship between perfectionism and procrastination? * What dimensions of perfectionism predict (contribute to) procrastination? * How can we reduce procrastination and the negative effects of perfectionism? {{RoundBoxBottom}} == Perfectionism and Procrastination == '''Perfectionism and procrastination''' are complex psychological constructs that may be closely related but differ in their nature and manifestations. Perfectionism primarily refers to personality traits and attitudes, whereas procrastination manifests itself primarily as a pattern of behaviour (Akpur & Yurtseven, 2019, Husain et al., 2025) '''Perfectionism''': definition and key characteristics (Stoeber et al., 2018) '''Perfectionism''' is the pursuit of perfection or flawlessness, the setting of high standards, and a critical attitude toward one's own mistakes (imperfections) (Sirois, 2017). According to a multidimensional model main dimensions: perfectionistic strivings (setting high standards, striving for excellence; It is often considered an adaptive trait, as it can help achieve goals ) and perfectionictics concerns (fear of making a mistake, fear of criticism, excessive self-criticism, inability to take joy in success;is classified as maladaptive because it leads to negative consequences and is associated with failure of self-regulation (Gäde et al., 2017, Sirois, 2017) {{grammar}}. '''Procrastination''': definition and key characteristics (Sirois, 2017, Steel, 2007) '''Procrastination''' is a ''behaviour'' in which a person voluntarily postpones important planned tasks, knowing that the negative consequences of such an action are inevitable; '''criteria''': * '''Consciousness and''' '''voluntariness''': the delay is not due to objective external circumstances but is a conscious choice made by the individual. * '''Irrationality''': a person, clearly aware of the negative consequences, still continues to avoid performing the activity. * '''Failure of self‑regulation''': Failure to the delay in activity is related to the individual’s inability to sufficiently control their behavior and emotions at the present moment (Sirois, 2017). '''Domains of procrastination''': academic, work, everyday life, health, interpersonal (Kurtovic at al., 2019)<gallery> </gallery> '''Table 1.''' Types of procrastination and their characteristics{{fact}} {| class="wikitable" |+ !'''Type''' !'''Description''' |- |Academic procrastination |Delaying academic assignments, exam preparation, and writing academic papers. |- |Workplace procrastination |Postponing important work tasks, meetings, reports, and phone calls. |- |Health procrastination |Postponing medical appointments, health check-ups, treatment, or health-promoting behaviours |- |Decision procrastination |Postponing or avoiding important decisions. |} {{Robelbox|left|alt=|theme=6|title=Learning Checkpoint |icon=Emblem-question-yellow.svg|iconwidth=48px}}<div style="{{Robelbox/pad}}"> <quiz display=simple> {Imagine this situation: you have a deadline for a report, but your boss has asked you to take on some of the work of a colleague who is sick. Do you think it’s considered procrastination if you put off your report to deal your boss’s request? } -Yes +No </quiz> </div> {{Robelbox/close}} == How perfectionism relates to procrastination == '''Perfectionistic concerns''': their contribution to procrastination - is an attempt to avoid the negative feelings associated with a potentially less than ideal outcomes; an individual’s choice to delay in order to avoid confronting negative thoughts and feelings {{fact}} '''Underlying mechanisms:''' high standards and the inability to meet them lead to a breakdown in self-regulation, which in turn leads to avoidance behavior (Sirois, 2017)'''.''' '''Mediating factors''' ( fear of failure as a mediator (Yosopov et al., 2024), perceived discrepancy between standards and performance (Kurtovic at al., 2019), concern over mistakes, self-critical evaluation) == A motivational perspective on perfectionism and procrastination == Relevant motiventional theories (Stoeber et al., 2018) '''Self-Determination Theory''' According to Self-Determination Theory, motivation depends on the fulfillment of basic needs for autonomy, competence, and relatedness {{fact}}. A person successfully achieves only those goals that they consider valuable and important {{fact}}. If a task is imposed from the outside and these needs are not met, a natural internal resistance arises {{fact}}. Within this framework, these basic needs for autonomy, competence, and relatedness can be met in various ways, which can be divided into internal and external {{fact}}. Internal approaches are linked to internal values and aspirations, while external approaches depend on external factors such as pressure, rewards, and punishments {{fact}}. In the case of perfectionism, when needs are formed more autonomously, adaptive perfectionism may develop, whereas with the external approach, maladaptive perfectionism may develop (Stoeber et al., 2018). '''Motivational mechanism''': Lack of autonomy and competence creates internal resistance, triggering a desire to delay non-autonomous tasks which ultimately leads to procrastination (Grund & Fries, 2018). == Approaches to adressing perfectionism-related procrastination == '''Evidence for effectivness''' Psychological interventions (2018 meta-analysis on the effectiveness of psychological interventions for combating procrastination. Psychotherapeutic methods generally have a small but statistically significant effect (g = 0.34).The most effective method is cognitive-behavioral therapy (CDT) (Rosental et al., 2018). Self-help strategies (Self-monitoring/Time tracking; Goal-setting;Self-control training;Time management) produce inconsistent results; they address external symptoms but ignore the underlying psychological causes (perfectionism, emotional dysregulation ...) (Rosental et al., 2018 ==Conclusion== * Perfectionism and procrastination may be interrelated (Akpur & Yurtseven, 2019, Husain et al., 2025) . * Not all perfectionism leads to procrastination; procrastination is associated with perfectionist concerns {{fact}}. * Perfectionist concerns may contribute to procrastination by leading individuals to avoid negative thoughts and feelings, as well as the fear of failing to meet high standards {{fact}}. * From a motivational perspective, extrinsic motivation may be linked to maladaptive perfectionism, which in certain cases leads to procrastination {{fact}}. * According to self-determination theory, a lack of autonomy can reduce motivation and lead to procrastination (Stoeber et al., 2018) . * One of the most effective psychotherapeutic method for overcoming procrastination is cognitive-behavioral therapy (CBT)(Rosental et al., 2018) . ==See also== * [[Motivation and emotion/Book/2022/Perfectionism|Perfectionism]] (Book chapter,2022) * [[Motivation and emotion/Book/2015/Procrastination, moods, and emotion|Procrastination, moods, and emotion]] (Book chapter,2015) ==References == {{Hanging indent|1= Akpur, U., & Yurtseven, N. (2019). Structural Relationships between Academic Motivation, Procrastination and Perfectionism: A Modelling Study. ''Cumhuriyet International Journal of Education''. https://doi.org/10.30703/cije.452633 Ferrari, J. R. (1992). Procrastinators and perfect behavior: An exploratory factor analysis of self-presentation, self-awareness, and self-handicapping components. ''Journal of Research in Personality'', ''26''(1), 75–84. https://doi.org/10.1016/0092-6566(92)90060-h Frost, R. O., Marten, P., Lahart, C., & Rosenblate, R. (1990). The dimensions of perfectionism. ''Cognitive Therapy and Research'', 14(5), 449–468. https://doi.org/10.1007/BF01172967 Gäde, J. C., Schermelleh-Engel, K., & Klein, A. G. (2017). Disentangling the Common Variance of Perfectionistic Strivings and Perfectionistic Concerns: A Bifactor Model of Perfectionism. ''Frontiers in Psychology'', ''8''(160). https://doi.org/10.3389/fpsyg.2017.00160 Grund, A., & Fries, S. (2018). Understanding procrastination: A motivational approach. ''Personality and Individual Differences'', ''121'', 120–130. https://doi.org/10.1016/j.paid.2017.09.035 Husain, W., Trabelsi, K., Ammar, A., Saif, Z., & Jahrami, H. (2025). The development and validation of a one-off scale to measure procrastination and precrastination traits in young adults. BMC Psychology, 13(1). https://doi.org/10.1186/s40359-025-03072-6 Kurtovic, A., Vrdoljak, G., & Idzanovic, A. (2019). Predicting procrastination: The role of academic achievement, self-efficacy and perfectionism. International Journal of Educational Psychology, 8(1), 1–26. https://doi.org/10.17583/ijep.2019.2993 Rozental, A., Bennett, S., Forsström, D., Ebert, D. D., Shafran, R., Andersson, G., & Carlbring, P. (2018). Targeting Procrastination Using Psychological Treatments: A Systematic Review and Meta-Analysis. Frontiers in Psychology, 9. https://doi.org/10.3389/fpsyg.2018.01588 Ryan, R. M., & Deci, E. L. (2000). Self-determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-being. ''American Psychologist'', ''55''(1), 68–78. https://selfdeterminationtheory.org/SDT/documents/2000_RyanDeci_SDT.pdf Sirois, F. M., Molnar, D. S., & Hirsch, J. K. (2017). A Meta-analytic and Conceptual Update on the Associations Between Procrastination and Multidimensional Perfectionism. ''European Journal of Personality'', ''31''(2), 137–159. https://doi.org/10.1002/per.2098         Steel, P. (2007). The nature of procrastination: A meta-analytic and theoretical review of quintessential self-regulatory failure. ''Psychological Bulletin'', ''133''(1), 65–94. https://doi.org/10.1037/0033-2909.133.1.65 Stoeber, J., Damian, L. E., & Madigan, D. J. (2018). Perfectionism: A motivational perspective. In J. Stoeber (Ed.), The psychology of perfectionism: Theory, research, applications (pp. 19–43). Routledge/Taylor & Francis Group.https://www.researchgate.net/publication/311970309_Perfectionism_A_motivational_perspective Xie, Y., Yang, J., & Chen, F. (2018). Procrastination and multidimensional perfectionism: A meta-analysis of main, mediating, and moderating effects. Social Behavior and Personality: An International Journal, 46(3), 395–408. https://doi.org/10.2224/sbp.6680 Yosopov, L., Saklofske, D. H., Smith, M. M., Flett, G. L., & Hewitt, P. L. (2024). Failure Sensitivity in Perfectionism and Procrastination: Fear of Failure and Overgeneralization of Failure as Mediators of Traits and Cognitions. Journal of Psychoeducational Assessment, 42(6). https://doi.org/10.1177/07342829241249784 }} This section lists the cited references in [[w:APA style|APA style]] (7th ed.) or [[w:Wikipedia:Citing sources|wiki style]]. 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== {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} [https://www.oneyoufeed.net/procrastinator/ Being a Procrastinator with Tim Pychyl] [https://www.youtube.com/watch?v=lFG1b1-EsW8 Our dangerous obsession with perfectionism is getting worse | Thomas Curran] [https://www.apa.org/gradpsych/2010/01/procrastination Procrastination or 'intentional delay'?] {{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/Perfectionism]] [[Category:Motivation and emotion/Book/Procrastination]] nwxe3awjgcl4fpidqdyujg86sn7pg1p 0 331038 2835087 2833545 2026-09-30T01:34:36Z ChelsSchofield 3106760 edited figures 2835087 wikitext text/x-wiki {{title|Technology-based pain management:<br>How can technology-based tools alter pain perception and pain management?}} __TOC__ ==Overview== [[File:Headache touching forehead.jpg|thumb|Figure 1: Headache ]] [[File:Pain cycle.jpg|thumb|326x326px|'''Figure 2 :'''The avoidance pain [https://pmc.ncbi.nlm.nih.gov/articles/PMC3820295/ cycle]]] *Technology-based pain interventions are receiving increasing research attention across healthcare settings, including postoperative care, rehabilitation, and labour wards (Musters et al., 2023; Yang et al., 2023).The pain technology market is projected to increase by '''USD $70.2 billion''' over the 10 years ( online forcast ask in next session). Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems help individuals regulate physiological arousal.Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems can help individuals regulate physiological arousal. Wearables, mobile applications, and telehealth platforms are also becoming more widely used, giving people accessible ways to track pain patterns and engage in self-management (Green & Chakravarthy, 2025; Li et al., 2024). Technology has therefore become increasingly influential in how pain is monitored, interpreted and managed across healthcare. For people with chronic pain, catastrophic thoughts and fear of further pain or injury may lead to avoidance of movement and meaningful activities, contributing to reduced functioning and increased distress (Gatchel, 2016; Vlaeyen & Linton, 2000). This chapter explores how technology-based interventions may interrupt this cycle by influencing pain signals, attention, emotions, thoughts, motivation and perceived control. {{RoundBoxTop|theme=2}} '''Focus questions''' {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} •How does technology alter the way people perceive and respond to pain? •How do psychological processes such as attention, emotion and cognitive appraisal contribute to technology-based pain management? •How do different technologies influence people's sense of control, engagement and motivation when managing pain? {{RoundBoxBottom}} == Understanding pain perception and management == Pain is not determined solely by physical injury. It is a personal sensory and emotional experience influenced by biological, psychological and social factors (Raja et al., 2020). Understanding the distinction between pain and nociception helps explain why technology can change a person’s pain experience even when it does not remove the original injury or health condition. Pain perception is shaped by how the brain interprets nociceptive signals alongside attention, emotions, memories, beliefs, expectations and the surrounding context (Bushnell et al., 2013; Tracey & Mantyh, 2007). Technology can alter this interpretation by redirecting attention, regulating physiological arousal, modifying pain-signal transmission or changing catastrophic thoughts about pain. It may also influence how a person responds by encouraging movement, coping and active self-management rather than fear and avoidance. Technology can therefore reduce the intensity, unpleasantness or perceived threat of pain while supporting greater confidence and control over pain-management behaviour. === Pain and nociception === * [[w:Pain|Pain]] is an unpleasant sensory and emotional experience associated with, or resembling an experience associated with, actual or potential tissue damage (Raja,2020). * Pain is personal and can be influenced by biological, psychological and social factors. * Nociception as the nervous system’s detection and processing of potentially harmful stimuli. * Pain and nociception are related but are not identical. * Nociception can occur without a conscious experience of pain and that pain may sometimes continue without clear evidence of current tissue damage (Basbaum ,2009; Raja ,2020). * Relate this distinction to technology by explaining that a tool may change a person’s pain experience without removing the original injury or condition. === Physiology of pain and pain perception === * Nociceptors detect potentially harmful mechanical, chemical or temperature-related stimuli and convert them into electrical signals. * Refer to these signals travelling through peripheral nerves to the spinal cord and then through ascending pathways to the brain (Basbaum,2009). * The brain interprets nociceptive information alongside attention, emotions, memories, beliefs, expectations and context. * The sensory dimension identifying the location and intensity of pain, while emotional, cognitive and motivational processes influence its unpleasantness, meaning and the person’s response. * Descending pathways from the brain can increase or reduce pain-signal transmission (Tracey & Mantyh, 2007). * Pain is not a direct measurement of tissue damage. Therefore, the same stimulus may be experienced differently by different people or by the same person in different situations (Bushnell,2013). * Relate this process to technology by introducing TENS as a tool that may modulate pain-signal transmission and VR as a tool that may change attention and the brain’s interpretation of pain. === Chronic pain and avoidance === * Chronic pain is pain that persists or recurs for longer than three months. * Chronic pain may affect attention, memory, mood, sleep, motivation, relationships and participation in daily activities. * Refer to increased attention towards bodily sensations and possible signs of pain. * Pain catastrophising as an exaggerated negative interpretation in which a person believes pain will be unbearable, uncontrollable or a sign of serious harm. * Fear-avoidance model. * Catastrophic interpretations can produce fear of pain, movement or reinjury. * Fear may lead the person to avoid physical activity, work, social activities and other meaningful experiences. * Avoidance can provide short-term relief from fear but may contribute to reduced activity, lower confidence, disability and emotional distress over time (Gatchel,2016; Vlaeyen & Linton, 2000). * '''See figure:''' One The Avoidance Pain Cyle === Understanding pain management === * Pain management as strategies used to reduce pain, distress and interference with daily life. * Chronic pain management may improve coping, functioning and participation without completely eliminating pain. * Refer to the biopsychosocial approach, which considers biological, psychological and social influences on pain (Raja, 2020). * Technology may support pain management through symptom monitoring, coping strategies and improved access to care (Li,2024). == How does technology alter pain perception? == {{ic|Include an introductory paragraph before branching into sub-sections}} === VR and attention modulation === * Refer to VR immerse user effecting attention - Limited capacity theory of attention (de Araujo, Zeferino, & Galas, 2026) === Biofeedback and autonomic regulation === *How biofeedback provides information about physiological pain responses, enabling users to practise regulating these responses and develop greater control over their pain experience. Related to self-regulation theory (Arsenault,2013). === Cognitive Digital CBT and ACT tools === * How CBT can modify unhelpful pain-related thoughts and behaviours, while ACT can increase pain acceptance and engagement in valued activities. These processes may reduce distress and improve functioning even when pain is not eliminated. Related - to cognitive appraisal theory and the psychological flexibility mode'''l''' (Hysing,2017; Neblett,2016).- Beneficial for catastrophic thinking, === Wearable sensors === * Wearable systems that collect pain ratings, adherence information and physiological data to personalise treatment and help users identify patterns in their pain. Related to self-regulation theory, particularly monitoring, feedback and behavioural adjustment (Green & Chakravarthy, 2025). === TENS === * Low-voltage electrical stimulation activating non-painful sensory fibres and reducing the transmission of pain signals. Relate this to gate control theory and endogenous pain inhibition (Blincoe,2007; Green & Chakravarthy,2025). === Telehealth and remote monitoring === * Clinicians monitoring pain ratings, treatment use and progress from a distance. Feedback and support may improve confidence, access and treatment adjustment. Relate this to self-efficacy and self-regulation (Green & Chakravarthy,2025). === Mobile applications === * Apps recording pain ratings, showing patterns, providing education or coping activities, and reminding users to practise pain-management strategies. Relate this to self-regulation theory. A dedicated mobile pain-application study is still required. == Psychological theories behind technology‑based pain management == * '''Psychological theories behind technology‑based pain management:'''Technology‑based pain interventions draw on established psychological theories explaining how cognition, emotion, attention and behaviour shape pain perception. These mechanisms help explain how tools such as VR, wearables and AI‑guided apps influence pain experience (Gatchel et al., 2007; Eccleston & Crombez, 1999). * '''Biopsychosocial model of pain:'''The biopsychosocial model proposes that pain arises from interactions between biological processes, psychological factors and social context. Technology‑based interventions align with this model by targeting multiple domains simultaneously, such as emotional regulation, behavioural change and physiological monitoring (Gatchel et al., 2007; Williams & Craig, 2016). * '''Limited‑capacity theory of attention:'''Pain captures limited attentional resources, increasing perceived intensity. VR and immersive technologies reduce pain by redirecting attention away from nociceptive input, supporting the theory’s predictions (Eccleston & Crombez, 1999; Malloy & Milling, 2010). * '''Gate control theory of pain:'''Gate control theory suggests that cognitive and emotional factors modulate nociceptive signals at the spinal level. Technologies such as TENS, VR and biofeedback influence these gates by altering attention and emotional state (Melzack & Wall, 1965; Moayedi & Davis, 2013). * '''Neuromodulation and neuroplasticity:'''Pain perception is shaped by dynamic neural networks that reorganise with experience. VR, neurofeedback and AI‑guided training promote adaptive neuroplasticity by reducing maladaptive signalling and strengthening regulatory pathways (Apkarian et al., 2009; Kutch & Apkarian, 2018). * '''Self‑regulation theory:'''Self‑regulation theory emphasises managing thoughts, emotions and behaviours to achieve desired outcomes. Technology‑based pain tools enhance self‑regulation through real‑time feedback, guided breathing and emotional tracking (Karoly, 1993; Jensen et al., 2014). * '''Operant conditioning:'''Pain behaviours can be reinforced by environmental responses. Technology‑based interventions apply operant principles by rewarding adaptive behaviours such as movement, pacing and relaxation (Fordyce, 1976; Vlaeyen & Linton, 2000). * '''Fear‑avoidance model of pain:'''Fear of pain leads to avoidance, deconditioning and increased disability. Graded VR exposure and movement‑tracking apps reduce fear by providing safe exposure and positive reinforcement (Vlaeyen & Linton, 2000; Crombez et al., 2012). * '''Cognitive appraisal and reframing:'''Pain intensity is influenced by how individuals interpret symptoms. Digital CBT tools help reframe catastrophic thoughts, reduce threat appraisal and promote adaptive interpretations of pain (Lazarus & Folkman, 1984; Turk & Wilson, 2010). * '''Psychological flexibility model:'''Psychological flexibility involves adapting behaviour in alignment with values despite discomfort. ACT‑based digital interventions enhance flexibility through acceptance, present‑moment awareness and committed action (Hayes et al., 2012; Trompetter et al., 2016). * '''Social cognitive theory and self‑efficacy:'''Self‑efficacy predicts pain coping and functional outcomes. Technology‑based interventions increase self‑efficacy through mastery experiences, modelling and feedback (Bandura, 1997; Jackson et al., 2014). * '''Affective‑motivational modulation of pain:'''Pain is shaped by emotional and motivational states such as fear, anxiety and goal orientation. Negative affect amplifies pain through enhanced salience and descending facilitation, while positive affect reduces pain via prefrontal‑limbic modulation. Technologies such as VR, AI‑guided relaxation and biofeedback apps modulate affective‑motivational systems by reducing threat cues and enhancing emotional regulation (Modernell et al., 2026; Vervoort & Trost, 2018; Garcia‑Larrea & Fauchon, 2023; ''Current Opinion in Psychology'', 2025). == Applications and tools == [[File:Pain pathway diagram showing transduction, transmission, modulation, and perception.png|thumb|293x293px|Figure 2: Brain Pain Pathways ]] * VR * TENS * Mobile apps * Wearables * Gamification * Telehealth == Future Applications and Emerging Technologies == * List Of Various Cutting edge * Emerging technologies * futuristics applications == Limitations and ethical considerations == * Effectiveness differs between users, technologies and pain conditions. * Refer to barriers including cost, access, digital skills and user engagement (Li,2024). * Possible side effects, privacy concerns and increased attention to symptoms. ==Learning features== '''Table 1''' See The Summary Table below : {{ic|Provide a more descriptive caption}} {| class="wikitable" style="margin: auto; |- ! Technology !! How it alters pain perception !! Theory / Model |- | VR || Redirects attention || Limited-capacity attention |- | TENS || Modulates pain signals || Gate control theory |- |Biofeedback |Support regulation of arousal |Self-regulation, conditioning |- |CBT/ACT tools |Changes to coping, appraisal and avoidance |Fear avoidance, flexibility |- |Wearables/apps |Records patterns and provides feedback |Self-regulation |- |Telehealth |Remote support, health access and treatment |Self-efficacy |} ;Quizzes * Why might VR reduce the amount of attention given to pain? See: * Which theory best explains how TENS may reduce pain-signal transmission? * How can feedback from a wearable device support self-regulation? * How might catastrophic thinking contribute to the fear-avoidance cycle? <quiz display="simple"> {Virtual reality (VR) can reduce pain by redirecting a person’s attention away from painful stimuli?: |type="()"} + True - False {TENS devices work by increasing the intensity of pain signals sent to the brain. Answer?: |type="()"} - True + False </quiz> ==Conclusion== * Pain is interpreted by the brain and is influenced by attention, emotion, appraisal, behaviour and social support, not only by signals from the body. * Different technologies alter pain perception through different pathways: VR redirects attention, TENS modulates signals, and feedback or cognitive tools influence arousal, appraisal and control. * Technology is most useful as part of individualised, biopsychosocial pain management rather than as a replacement for all existing care (Hysing,2017; Li,2024). * Effectiveness depends on the user, pain condition, technology, level of support and quality of available evidence. {{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== [[wikipedia:Virtual_reality_therapy|Virtual reality therapy]] (Wikipedia) [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * https://en.wikipedia.org/wiki/Pain {{ic|Create internal link}} * https://en.wikipedia.org/wiki/Virtual_reality {{ic|Create internal link}} * [[Motivation and emotion/Book/2021/Self-regulation|Self-regulation]] (Book chapter, 2021) * [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * [[wikipedia:Cognitive_behavioral_therapy|Cognitive behavioral therapy]] (Wikipedia) * [[wikipedia:Biopsychosocial_model|Biopsychosocial model]] (Wikipedia) * [[wikipedia:Gate_control_theory|Gate control theory]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== This section lists the cited references in [[w:APA style|APA style]] (7th ed.) or [[w:Wikipedia:Citing sources|wiki style]]. {{Hanging indent|1= }} * Musters, A., Vandevenne, A. S., Franx, A., & Wassen, M. M. L. H. (2023). Virtual Reality Experience during Labour (VIREL): A qualitative study. ''BMC Pregnancy and Childbirth, 23'', Article 283. <nowiki>https://doi.org/10.1186/s12884-023-05633-0</nowiki> * Yang, X., Zhong, S., Yang, S., He, M., Xu, X., He, S., Fan, G., & Liu, L. (2023). Global scientific trends in virtual reality for pain treatment from 2000 to 2022: Bibliometric analysis. ''JMIR Serious Games, 11'', Article e48354. <nowiki>https://doi.org/10.2196/48354</nowiki> * Green, M., & Chakravarthy, K. (2025). Artificial intelligence-enhanced pain management: The NXTSTIM EcoAI platform. ''Pain Management, 15''(8), 467–475. * Li, L. W., Yi, T. H., & Khaing, N. E. E. (2024). Chronic pain healthcare workers’ challenges in pain management and receptiveness towards VR as an adjunct management tool: A qualitative study. ''BMC Digital Health, 2'', Article 26. * Gatchel, R. J., Neblett, R., Kishino, N., & Ray, C. T. (2016). Fear-avoidance beliefs and chronic pain. ''Journal of Orthopaedic & Sports Physical Therapy, 46''(2), 38–43. <nowiki>https://doi.org/10.2519/jospt.2016.0601</nowiki> * Vlaeyen, J. W. S., & Linton, S. J. (2000). Fear-avoidance and its consequences in chronic musculoskeletal pain: A state of the art. ''Pain, 85''(3), 317–332. <nowiki>https://doi.org/10.1016/S0304-3959(99)00242-0</nowiki> * Raja, S. N., Carr, D. B., Cohen, M., Finnerup, N. B., Flor, H., Gibson, S., Keefe, F. J., Mogil, J. S., Ringkamp, M., Sluka, K. A., Song, X.-J., Stevens, B., Sullivan, M. D., Tutelman, P. R., Ushida, T., & Vader, K. (2020). The revised International Association for the Study of Pain definition of pain: Concepts, challenges, and compromises. ''Pain, 161''(9), 1976–1982. <nowiki>https://doi.org/10.1097/j.pain.0000000000001939</nowiki> * Bushnell, M. C., Čeko, M., & Low, L. A. (2013). Cognitive and emotional control of pain and its disruption in chronic pain. ''Nature Reviews Neuroscience, 14''(7), 502–511. <nowiki>https://doi.org/10.1038/nrn3516</nowiki> * Tracey, I., & Mantyh, P. W. (2007). The cerebral signature for pain perception and its modulation. ''Neuron, 55''(3), 377–391. <nowiki>https://doi.org/10.1016/j.neuron.2007.07.012</nowiki> * Basbaum, A. I., Bautista, D. M., Scherrer, G., & Julius, D. (2009). Cellular and molecular mechanisms of pain. ''Cell, 139''(2), 267–284. <nowiki>https://doi.org/10.1016/j.cell.2009.09.028</nowiki> * de Araujo, D. D., Zeferino, S. P., & Galas, F. R. B. G. (2026). Virtual reality for opioid reduction in postoperative cardiac and thoracic surgery: A randomized controlled trial protocol. ''MethodsX, 17'', Article 104029. * Arsenault, M., Piché, M., Duncan, G. H., & Rainville, P. (2013). Self-regulation of acute experimental pain with and without biofeedback using spinal nociceptive responses. ''Neuroscience, 231'', 102–110. <nowiki>https://doi.org/10.1016/j.neuroscience.2012.11.039</nowiki> * Hysing, E.-B., Smith, L., Thulin, M., Karlsten, R., & Gordh, T. (2017). Detection of systemic inflammation in severely impaired chronic pain patients, and effects of a CBT-ACT-based multi-modal pain rehabilitation program. ''Scandinavian Journal of Pain, 16'', 175. <nowiki>https://doi.org/10.1016/j.sjpain.2017.04.033</nowiki> * Neblett, R., Mayer, T. G., Hartzell, M. M., Williams, M. J., & Gatchel, R. J. (2016). The Fear-Avoidance Components Scale (FACS): Development and psychometric evaluation of a new measure of pain-related fear avoidance. ''Pain Practice, 16''(4), 435–450. <nowiki>https://doi.org/10.1111/papr.12333</nowiki> * Blincoe, A. J. (2007). TENS machines and their use in managing labour pain. ''British Journal of Midwifery, 15''(8), 516–519. * Gatchel, R. J., Peng, Y. B., Peters, M. L., Fuchs, P. N., & Turk, D. C. (2007). The biopsychosocial approach to chronic pain: Scientific advances and future directions. ''Psychological Bulletin, 133''(4), 581–624. <nowiki>https://doi.org/10.1037/0033-2909.133.4.581</nowiki> * Eccleston, C., & Crombez, G. (1999). Pain demands attention: A cognitive-affective model of the interruptive function of pain. ''Psychological Bulletin, 125''(3), 356–366. <nowiki>https://doi.org/10.1037/0033-2909.125.3.356</nowiki> * Williams, A. C. de C., & Craig, K. D. (2016). Updating the definition of pain. ''Pain, 157''(11), 2420–2423. <nowiki>https://doi.org/10.1097/j.pain.0000000000000613</nowiki> * Malloy, K. M., & Milling, L. S. (2010). The effectiveness of virtual reality distraction for pain reduction: A systematic review. ''Clinical Psychology Review, 30''(8), 1011–1018. <nowiki>https://doi.org/10.1016/j.cpr.2010.07.001</nowiki> * Melzack, R., & Wall, P. D. (1965). Pain mechanisms: A new theory. ''Science, 150''(3699), 971–979. <nowiki>https://doi.org/10.1126/science.150.3699.971</nowiki> * Moayedi, M., & Davis, K. D. (2013). Theories of pain: From specificity to gate control. ''Journal of Neurophysiology, 109''(1), 5–12. <nowiki>https://doi.org/10.1152/jn.00457.2012</nowiki> * Apkarian, A. V., Baliki, M. N., & Geha, P. Y. (2009). Towards a theory of chronic pain. ''Progress in Neurobiology, 87''(2), 81–97. <nowiki>https://doi.org/10.1016/j.pneurobio.2008.09.018</nowiki> * Kutch, J. J., & Apkarian, A. V. (2018). Potential mechanisms underlying centralized pain and emerging therapeutic interventions. ''Frontiers in Cellular Neuroscience, 12'', Article 35. <nowiki>https://doi.org/10.3389/fncel.2018.00035</nowiki> * Karoly, P. (1993). Mechanisms of self-regulation: A systems view. ''Annual Review of Psychology, 44'', 23–52. <nowiki>https://doi.org/10.1146/annurev.ps.44.020193.000323</nowiki> * Hamilton, N. A., Karoly, P., & Kitzman, H. (2004). Self-regulation and chronic pain: The role of emotion. ''Cognitive Therapy and Research, 28''(5), 559–576. <nowiki>https://doi.org/10.1023/B:COTR.0000045565.88145.76</nowiki> * Fordyce, W. E. (1976). ''Behavioral methods for chronic pain and illness''. Mosby. * Crombez, G., Eccleston, C., Van Damme, S., Vlaeyen, J. W. S., & Karoly, P. (2012). Fear-avoidance model of chronic pain: The next generation. ''Clinical Journal of Pain, 28''(6), 475–483. <nowiki>https://doi.org/10.1097/AJP.0b013e3182385392</nowiki> * Lazarus, R. S., & Folkman, S. (1984). ''Stress, appraisal, and coping''. Springer. * Turk, D. C., & Wilson, H. D. (2010). Fear of pain as a prognostic factor in chronic pain: Conceptual models, assessment, and treatment implications. ''Current Pain and Headache Reports, 14''(2), 88–95. <nowiki>https://doi.org/10.1007/s11916-010-0094-x</nowiki> * Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). ''Acceptance and commitment therapy: The process and practice of mindful change'' (2nd ed.). Guilford Press. * Veehof, M. M., Trompetter, H. R., Bohlmeijer, E. T., & Schreurs, K. M. G. (2016). Acceptance- and mindfulness-based interventions for the treatment of chronic pain: A meta-analytic review. ''Cognitive Behaviour Therapy, 45''(1), 5–31. <nowiki>https://doi.org/10.1080/16506073.2015.1098724</nowiki> * Bandura, A. (1997). ''Self-efficacy: The exercise of control''. W. H. Freeman. * Jackson, T., Wang, Y., Wang, Y., & Fan, H. (2014). Self-efficacy and chronic pain outcomes: A meta-analytic review. ''The Journal of Pain, 15''(8), 800–814. <nowiki>https://doi.org/10.1016/j.jpain.2014.05.002</nowiki> * Modernell, L. M., Faillenot, I., Garcia-Larrea, L., & Fauchon, C. (2026). The multifaceted neural architecture of pain modulation by emotion and cognition: A systematic review and meta-analysis. ''British Journal of Anaesthesia, 136''(6), 1894–1909. <nowiki>https://doi.org/10.1016/j.bja.2026.03.015</nowiki> * Vervoort, T., & Trost, Z. (2018). An affective-motivational account of interpersonal dynamics in pain. In T. Vervoort, K. Karos, Z. Trost, & K. M. Prkachin (Eds.), ''Social and interpersonal dynamics in pain: We don’t suffer alone'' (pp. 57–75). Springer. <nowiki>https://doi.org/10.1007/978-3-319-78340-6_4</nowiki> * Boersma, K., & Flink, I. K. (2025). Key aspects concerning the role of emotion in the chronic pain experience. ''Current Opinion in Psychology, 62'', Article 102000. <nowiki>https://doi.org/10.1016/j.copsyc.2025.102000</nowiki> {{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== * https://www.iasp-pain.org/resources/terminology/ * https://www.qld.gov.au/health/services/specialists/persistent-pain/understanding-pain/managing-your-pain * https://aci.health.nsw.gov.au/chronic-pain/painbytes/pain-and-mind-body-connection {{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/Pain]] [[Category:Motivation and emotion/Book/Technology]] d4kuv74z27j32coxdcmhc87fjsifi74 2835088 2835087 2026-09-30T01:36:34Z ChelsSchofield 3106760 /* Chronic pain and avoidance */ edit figure reference 2835088 wikitext text/x-wiki {{title|Technology-based pain management:<br>How can technology-based tools alter pain perception and pain management?}} __TOC__ ==Overview== [[File:Headache touching forehead.jpg|thumb|Figure 1: Headache ]] [[File:Pain cycle.jpg|thumb|326x326px|'''Figure 2 :'''The avoidance pain [https://pmc.ncbi.nlm.nih.gov/articles/PMC3820295/ cycle]]] *Technology-based pain interventions are receiving increasing research attention across healthcare settings, including postoperative care, rehabilitation, and labour wards (Musters et al., 2023; Yang et al., 2023).The pain technology market is projected to increase by '''USD $70.2 billion''' over the 10 years ( online forcast ask in next session). Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems help individuals regulate physiological arousal.Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems can help individuals regulate physiological arousal. Wearables, mobile applications, and telehealth platforms are also becoming more widely used, giving people accessible ways to track pain patterns and engage in self-management (Green & Chakravarthy, 2025; Li et al., 2024). Technology has therefore become increasingly influential in how pain is monitored, interpreted and managed across healthcare. For people with chronic pain, catastrophic thoughts and fear of further pain or injury may lead to avoidance of movement and meaningful activities, contributing to reduced functioning and increased distress (Gatchel, 2016; Vlaeyen & Linton, 2000). This chapter explores how technology-based interventions may interrupt this cycle by influencing pain signals, attention, emotions, thoughts, motivation and perceived control. {{RoundBoxTop|theme=2}} '''Focus questions''' {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} •How does technology alter the way people perceive and respond to pain? •How do psychological processes such as attention, emotion and cognitive appraisal contribute to technology-based pain management? •How do different technologies influence people's sense of control, engagement and motivation when managing pain? {{RoundBoxBottom}} == Understanding pain perception and management == Pain is not determined solely by physical injury. It is a personal sensory and emotional experience influenced by biological, psychological and social factors (Raja et al., 2020). Understanding the distinction between pain and nociception helps explain why technology can change a person’s pain experience even when it does not remove the original injury or health condition. Pain perception is shaped by how the brain interprets nociceptive signals alongside attention, emotions, memories, beliefs, expectations and the surrounding context (Bushnell et al., 2013; Tracey & Mantyh, 2007). Technology can alter this interpretation by redirecting attention, regulating physiological arousal, modifying pain-signal transmission or changing catastrophic thoughts about pain. It may also influence how a person responds by encouraging movement, coping and active self-management rather than fear and avoidance. Technology can therefore reduce the intensity, unpleasantness or perceived threat of pain while supporting greater confidence and control over pain-management behaviour. === Pain and nociception === * [[w:Pain|Pain]] is an unpleasant sensory and emotional experience associated with, or resembling an experience associated with, actual or potential tissue damage (Raja,2020). * Pain is personal and can be influenced by biological, psychological and social factors. * Nociception as the nervous system’s detection and processing of potentially harmful stimuli. * Pain and nociception are related but are not identical. * Nociception can occur without a conscious experience of pain and that pain may sometimes continue without clear evidence of current tissue damage (Basbaum ,2009; Raja ,2020). * Relate this distinction to technology by explaining that a tool may change a person’s pain experience without removing the original injury or condition. === Physiology of pain and pain perception === * Nociceptors detect potentially harmful mechanical, chemical or temperature-related stimuli and convert them into electrical signals. * Refer to these signals travelling through peripheral nerves to the spinal cord and then through ascending pathways to the brain (Basbaum,2009). * The brain interprets nociceptive information alongside attention, emotions, memories, beliefs, expectations and context. * The sensory dimension identifying the location and intensity of pain, while emotional, cognitive and motivational processes influence its unpleasantness, meaning and the person’s response. * Descending pathways from the brain can increase or reduce pain-signal transmission (Tracey & Mantyh, 2007). * Pain is not a direct measurement of tissue damage. Therefore, the same stimulus may be experienced differently by different people or by the same person in different situations (Bushnell,2013). * Relate this process to technology by introducing TENS as a tool that may modulate pain-signal transmission and VR as a tool that may change attention and the brain’s interpretation of pain. === Chronic pain and avoidance === * Chronic pain is pain that persists or recurs for longer than three months. * Chronic pain may affect attention, memory, mood, sleep, motivation, relationships and participation in daily activities. * Refer to increased attention towards bodily sensations and possible signs of pain. * Pain catastrophising as an exaggerated negative interpretation in which a person believes pain will be unbearable, uncontrollable or a sign of serious harm. * Fear-avoidance model. * Catastrophic interpretations can produce fear of pain, movement or reinjury. * Fear may lead the person to avoid physical activity, work, social activities and other meaningful experiences. * Avoidance can provide short-term relief from fear but may contribute to reduced activity, lower confidence, disability and emotional distress over time (Gatchel,2016; Vlaeyen & Linton, 2000). * '''See figure 2:''' One The Avoidance Pain Cyle === Understanding pain management === * Pain management as strategies used to reduce pain, distress and interference with daily life. * Chronic pain management may improve coping, functioning and participation without completely eliminating pain. * Refer to the biopsychosocial approach, which considers biological, psychological and social influences on pain (Raja, 2020). * Technology may support pain management through symptom monitoring, coping strategies and improved access to care (Li,2024). == How does technology alter pain perception? == {{ic|Include an introductory paragraph before branching into sub-sections}} === VR and attention modulation === * Refer to VR immerse user effecting attention - Limited capacity theory of attention (de Araujo, Zeferino, & Galas, 2026) === Biofeedback and autonomic regulation === *How biofeedback provides information about physiological pain responses, enabling users to practise regulating these responses and develop greater control over their pain experience. Related to self-regulation theory (Arsenault,2013). === Cognitive Digital CBT and ACT tools === * How CBT can modify unhelpful pain-related thoughts and behaviours, while ACT can increase pain acceptance and engagement in valued activities. These processes may reduce distress and improve functioning even when pain is not eliminated. Related - to cognitive appraisal theory and the psychological flexibility mode'''l''' (Hysing,2017; Neblett,2016).- Beneficial for catastrophic thinking, === Wearable sensors === * Wearable systems that collect pain ratings, adherence information and physiological data to personalise treatment and help users identify patterns in their pain. Related to self-regulation theory, particularly monitoring, feedback and behavioural adjustment (Green & Chakravarthy, 2025). === TENS === * Low-voltage electrical stimulation activating non-painful sensory fibres and reducing the transmission of pain signals. Relate this to gate control theory and endogenous pain inhibition (Blincoe,2007; Green & Chakravarthy,2025). === Telehealth and remote monitoring === * Clinicians monitoring pain ratings, treatment use and progress from a distance. Feedback and support may improve confidence, access and treatment adjustment. Relate this to self-efficacy and self-regulation (Green & Chakravarthy,2025). === Mobile applications === * Apps recording pain ratings, showing patterns, providing education or coping activities, and reminding users to practise pain-management strategies. Relate this to self-regulation theory. A dedicated mobile pain-application study is still required. == Psychological theories behind technology‑based pain management == * '''Psychological theories behind technology‑based pain management:'''Technology‑based pain interventions draw on established psychological theories explaining how cognition, emotion, attention and behaviour shape pain perception. These mechanisms help explain how tools such as VR, wearables and AI‑guided apps influence pain experience (Gatchel et al., 2007; Eccleston & Crombez, 1999). * '''Biopsychosocial model of pain:'''The biopsychosocial model proposes that pain arises from interactions between biological processes, psychological factors and social context. Technology‑based interventions align with this model by targeting multiple domains simultaneously, such as emotional regulation, behavioural change and physiological monitoring (Gatchel et al., 2007; Williams & Craig, 2016). * '''Limited‑capacity theory of attention:'''Pain captures limited attentional resources, increasing perceived intensity. VR and immersive technologies reduce pain by redirecting attention away from nociceptive input, supporting the theory’s predictions (Eccleston & Crombez, 1999; Malloy & Milling, 2010). * '''Gate control theory of pain:'''Gate control theory suggests that cognitive and emotional factors modulate nociceptive signals at the spinal level. Technologies such as TENS, VR and biofeedback influence these gates by altering attention and emotional state (Melzack & Wall, 1965; Moayedi & Davis, 2013). * '''Neuromodulation and neuroplasticity:'''Pain perception is shaped by dynamic neural networks that reorganise with experience. VR, neurofeedback and AI‑guided training promote adaptive neuroplasticity by reducing maladaptive signalling and strengthening regulatory pathways (Apkarian et al., 2009; Kutch & Apkarian, 2018). * '''Self‑regulation theory:'''Self‑regulation theory emphasises managing thoughts, emotions and behaviours to achieve desired outcomes. Technology‑based pain tools enhance self‑regulation through real‑time feedback, guided breathing and emotional tracking (Karoly, 1993; Jensen et al., 2014). * '''Operant conditioning:'''Pain behaviours can be reinforced by environmental responses. Technology‑based interventions apply operant principles by rewarding adaptive behaviours such as movement, pacing and relaxation (Fordyce, 1976; Vlaeyen & Linton, 2000). * '''Fear‑avoidance model of pain:'''Fear of pain leads to avoidance, deconditioning and increased disability. Graded VR exposure and movement‑tracking apps reduce fear by providing safe exposure and positive reinforcement (Vlaeyen & Linton, 2000; Crombez et al., 2012). * '''Cognitive appraisal and reframing:'''Pain intensity is influenced by how individuals interpret symptoms. Digital CBT tools help reframe catastrophic thoughts, reduce threat appraisal and promote adaptive interpretations of pain (Lazarus & Folkman, 1984; Turk & Wilson, 2010). * '''Psychological flexibility model:'''Psychological flexibility involves adapting behaviour in alignment with values despite discomfort. ACT‑based digital interventions enhance flexibility through acceptance, present‑moment awareness and committed action (Hayes et al., 2012; Trompetter et al., 2016). * '''Social cognitive theory and self‑efficacy:'''Self‑efficacy predicts pain coping and functional outcomes. Technology‑based interventions increase self‑efficacy through mastery experiences, modelling and feedback (Bandura, 1997; Jackson et al., 2014). * '''Affective‑motivational modulation of pain:'''Pain is shaped by emotional and motivational states such as fear, anxiety and goal orientation. Negative affect amplifies pain through enhanced salience and descending facilitation, while positive affect reduces pain via prefrontal‑limbic modulation. Technologies such as VR, AI‑guided relaxation and biofeedback apps modulate affective‑motivational systems by reducing threat cues and enhancing emotional regulation (Modernell et al., 2026; Vervoort & Trost, 2018; Garcia‑Larrea & Fauchon, 2023; ''Current Opinion in Psychology'', 2025). == Applications and tools == [[File:Pain pathway diagram showing transduction, transmission, modulation, and perception.png|thumb|293x293px|Figure 2: Brain Pain Pathways ]] * VR * TENS * Mobile apps * Wearables * Gamification * Telehealth == Future Applications and Emerging Technologies == * List Of Various Cutting edge * Emerging technologies * futuristics applications == Limitations and ethical considerations == * Effectiveness differs between users, technologies and pain conditions. * Refer to barriers including cost, access, digital skills and user engagement (Li,2024). * Possible side effects, privacy concerns and increased attention to symptoms. ==Learning features== '''Table 1''' See The Summary Table below : {{ic|Provide a more descriptive caption}} {| class="wikitable" style="margin: auto; |- ! Technology !! How it alters pain perception !! Theory / Model |- | VR || Redirects attention || Limited-capacity attention |- | TENS || Modulates pain signals || Gate control theory |- |Biofeedback |Support regulation of arousal |Self-regulation, conditioning |- |CBT/ACT tools |Changes to coping, appraisal and avoidance |Fear avoidance, flexibility |- |Wearables/apps |Records patterns and provides feedback |Self-regulation |- |Telehealth |Remote support, health access and treatment |Self-efficacy |} ;Quizzes * Why might VR reduce the amount of attention given to pain? See: * Which theory best explains how TENS may reduce pain-signal transmission? * How can feedback from a wearable device support self-regulation? * How might catastrophic thinking contribute to the fear-avoidance cycle? <quiz display="simple"> {Virtual reality (VR) can reduce pain by redirecting a person’s attention away from painful stimuli?: |type="()"} + True - False {TENS devices work by increasing the intensity of pain signals sent to the brain. Answer?: |type="()"} - True + False </quiz> ==Conclusion== * Pain is interpreted by the brain and is influenced by attention, emotion, appraisal, behaviour and social support, not only by signals from the body. * Different technologies alter pain perception through different pathways: VR redirects attention, TENS modulates signals, and feedback or cognitive tools influence arousal, appraisal and control. * Technology is most useful as part of individualised, biopsychosocial pain management rather than as a replacement for all existing care (Hysing,2017; Li,2024). * Effectiveness depends on the user, pain condition, technology, level of support and quality of available evidence. {{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== [[wikipedia:Virtual_reality_therapy|Virtual reality therapy]] (Wikipedia) [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * https://en.wikipedia.org/wiki/Pain {{ic|Create internal link}} * https://en.wikipedia.org/wiki/Virtual_reality {{ic|Create internal link}} * [[Motivation and emotion/Book/2021/Self-regulation|Self-regulation]] (Book chapter, 2021) * [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * [[wikipedia:Cognitive_behavioral_therapy|Cognitive behavioral therapy]] (Wikipedia) * [[wikipedia:Biopsychosocial_model|Biopsychosocial model]] (Wikipedia) * [[wikipedia:Gate_control_theory|Gate control theory]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== This section lists the cited references in [[w:APA style|APA style]] (7th ed.) or [[w:Wikipedia:Citing sources|wiki style]]. {{Hanging indent|1= }} * Musters, A., Vandevenne, A. S., Franx, A., & Wassen, M. M. L. H. (2023). Virtual Reality Experience during Labour (VIREL): A qualitative study. ''BMC Pregnancy and Childbirth, 23'', Article 283. <nowiki>https://doi.org/10.1186/s12884-023-05633-0</nowiki> * Yang, X., Zhong, S., Yang, S., He, M., Xu, X., He, S., Fan, G., & Liu, L. (2023). Global scientific trends in virtual reality for pain treatment from 2000 to 2022: Bibliometric analysis. ''JMIR Serious Games, 11'', Article e48354. <nowiki>https://doi.org/10.2196/48354</nowiki> * Green, M., & Chakravarthy, K. (2025). Artificial intelligence-enhanced pain management: The NXTSTIM EcoAI platform. ''Pain Management, 15''(8), 467–475. * Li, L. W., Yi, T. H., & Khaing, N. E. E. (2024). Chronic pain healthcare workers’ challenges in pain management and receptiveness towards VR as an adjunct management tool: A qualitative study. ''BMC Digital Health, 2'', Article 26. * Gatchel, R. J., Neblett, R., Kishino, N., & Ray, C. T. (2016). Fear-avoidance beliefs and chronic pain. ''Journal of Orthopaedic & Sports Physical Therapy, 46''(2), 38–43. <nowiki>https://doi.org/10.2519/jospt.2016.0601</nowiki> * Vlaeyen, J. W. S., & Linton, S. J. (2000). Fear-avoidance and its consequences in chronic musculoskeletal pain: A state of the art. ''Pain, 85''(3), 317–332. <nowiki>https://doi.org/10.1016/S0304-3959(99)00242-0</nowiki> * Raja, S. N., Carr, D. B., Cohen, M., Finnerup, N. B., Flor, H., Gibson, S., Keefe, F. J., Mogil, J. S., Ringkamp, M., Sluka, K. A., Song, X.-J., Stevens, B., Sullivan, M. D., Tutelman, P. R., Ushida, T., & Vader, K. (2020). The revised International Association for the Study of Pain definition of pain: Concepts, challenges, and compromises. ''Pain, 161''(9), 1976–1982. <nowiki>https://doi.org/10.1097/j.pain.0000000000001939</nowiki> * Bushnell, M. C., Čeko, M., & Low, L. A. (2013). Cognitive and emotional control of pain and its disruption in chronic pain. ''Nature Reviews Neuroscience, 14''(7), 502–511. <nowiki>https://doi.org/10.1038/nrn3516</nowiki> * Tracey, I., & Mantyh, P. W. (2007). The cerebral signature for pain perception and its modulation. ''Neuron, 55''(3), 377–391. <nowiki>https://doi.org/10.1016/j.neuron.2007.07.012</nowiki> * Basbaum, A. I., Bautista, D. M., Scherrer, G., & Julius, D. (2009). Cellular and molecular mechanisms of pain. ''Cell, 139''(2), 267–284. <nowiki>https://doi.org/10.1016/j.cell.2009.09.028</nowiki> * de Araujo, D. D., Zeferino, S. P., & Galas, F. R. B. G. (2026). Virtual reality for opioid reduction in postoperative cardiac and thoracic surgery: A randomized controlled trial protocol. ''MethodsX, 17'', Article 104029. * Arsenault, M., Piché, M., Duncan, G. H., & Rainville, P. (2013). Self-regulation of acute experimental pain with and without biofeedback using spinal nociceptive responses. ''Neuroscience, 231'', 102–110. <nowiki>https://doi.org/10.1016/j.neuroscience.2012.11.039</nowiki> * Hysing, E.-B., Smith, L., Thulin, M., Karlsten, R., & Gordh, T. (2017). Detection of systemic inflammation in severely impaired chronic pain patients, and effects of a CBT-ACT-based multi-modal pain rehabilitation program. ''Scandinavian Journal of Pain, 16'', 175. <nowiki>https://doi.org/10.1016/j.sjpain.2017.04.033</nowiki> * Neblett, R., Mayer, T. G., Hartzell, M. M., Williams, M. J., & Gatchel, R. J. (2016). The Fear-Avoidance Components Scale (FACS): Development and psychometric evaluation of a new measure of pain-related fear avoidance. ''Pain Practice, 16''(4), 435–450. <nowiki>https://doi.org/10.1111/papr.12333</nowiki> * Blincoe, A. J. (2007). TENS machines and their use in managing labour pain. ''British Journal of Midwifery, 15''(8), 516–519. * Gatchel, R. J., Peng, Y. B., Peters, M. L., Fuchs, P. N., & Turk, D. C. (2007). The biopsychosocial approach to chronic pain: Scientific advances and future directions. ''Psychological Bulletin, 133''(4), 581–624. <nowiki>https://doi.org/10.1037/0033-2909.133.4.581</nowiki> * Eccleston, C., & Crombez, G. (1999). Pain demands attention: A cognitive-affective model of the interruptive function of pain. ''Psychological Bulletin, 125''(3), 356–366. <nowiki>https://doi.org/10.1037/0033-2909.125.3.356</nowiki> * Williams, A. C. de C., & Craig, K. D. (2016). Updating the definition of pain. ''Pain, 157''(11), 2420–2423. <nowiki>https://doi.org/10.1097/j.pain.0000000000000613</nowiki> * Malloy, K. M., & Milling, L. S. (2010). The effectiveness of virtual reality distraction for pain reduction: A systematic review. ''Clinical Psychology Review, 30''(8), 1011–1018. <nowiki>https://doi.org/10.1016/j.cpr.2010.07.001</nowiki> * Melzack, R., & Wall, P. D. (1965). Pain mechanisms: A new theory. ''Science, 150''(3699), 971–979. <nowiki>https://doi.org/10.1126/science.150.3699.971</nowiki> * Moayedi, M., & Davis, K. D. (2013). Theories of pain: From specificity to gate control. ''Journal of Neurophysiology, 109''(1), 5–12. <nowiki>https://doi.org/10.1152/jn.00457.2012</nowiki> * Apkarian, A. V., Baliki, M. N., & Geha, P. Y. (2009). Towards a theory of chronic pain. ''Progress in Neurobiology, 87''(2), 81–97. <nowiki>https://doi.org/10.1016/j.pneurobio.2008.09.018</nowiki> * Kutch, J. J., & Apkarian, A. V. (2018). Potential mechanisms underlying centralized pain and emerging therapeutic interventions. ''Frontiers in Cellular Neuroscience, 12'', Article 35. <nowiki>https://doi.org/10.3389/fncel.2018.00035</nowiki> * Karoly, P. (1993). Mechanisms of self-regulation: A systems view. ''Annual Review of Psychology, 44'', 23–52. <nowiki>https://doi.org/10.1146/annurev.ps.44.020193.000323</nowiki> * Hamilton, N. A., Karoly, P., & Kitzman, H. (2004). Self-regulation and chronic pain: The role of emotion. ''Cognitive Therapy and Research, 28''(5), 559–576. <nowiki>https://doi.org/10.1023/B:COTR.0000045565.88145.76</nowiki> * Fordyce, W. E. (1976). ''Behavioral methods for chronic pain and illness''. Mosby. * Crombez, G., Eccleston, C., Van Damme, S., Vlaeyen, J. W. S., & Karoly, P. (2012). Fear-avoidance model of chronic pain: The next generation. ''Clinical Journal of Pain, 28''(6), 475–483. <nowiki>https://doi.org/10.1097/AJP.0b013e3182385392</nowiki> * Lazarus, R. S., & Folkman, S. (1984). ''Stress, appraisal, and coping''. Springer. * Turk, D. C., & Wilson, H. D. (2010). Fear of pain as a prognostic factor in chronic pain: Conceptual models, assessment, and treatment implications. ''Current Pain and Headache Reports, 14''(2), 88–95. <nowiki>https://doi.org/10.1007/s11916-010-0094-x</nowiki> * Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). ''Acceptance and commitment therapy: The process and practice of mindful change'' (2nd ed.). Guilford Press. * Veehof, M. M., Trompetter, H. R., Bohlmeijer, E. T., & Schreurs, K. M. G. (2016). Acceptance- and mindfulness-based interventions for the treatment of chronic pain: A meta-analytic review. ''Cognitive Behaviour Therapy, 45''(1), 5–31. <nowiki>https://doi.org/10.1080/16506073.2015.1098724</nowiki> * Bandura, A. (1997). ''Self-efficacy: The exercise of control''. W. H. Freeman. * Jackson, T., Wang, Y., Wang, Y., & Fan, H. (2014). Self-efficacy and chronic pain outcomes: A meta-analytic review. ''The Journal of Pain, 15''(8), 800–814. <nowiki>https://doi.org/10.1016/j.jpain.2014.05.002</nowiki> * Modernell, L. M., Faillenot, I., Garcia-Larrea, L., & Fauchon, C. (2026). The multifaceted neural architecture of pain modulation by emotion and cognition: A systematic review and meta-analysis. 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''Current Opinion in Psychology, 62'', Article 102000. <nowiki>https://doi.org/10.1016/j.copsyc.2025.102000</nowiki> {{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== * https://www.iasp-pain.org/resources/terminology/ * https://www.qld.gov.au/health/services/specialists/persistent-pain/understanding-pain/managing-your-pain * https://aci.health.nsw.gov.au/chronic-pain/painbytes/pain-and-mind-body-connection {{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/Pain]] [[Category:Motivation and emotion/Book/Technology]] 76o1ssj37jlviuuyuo0d3zmo7pf54fm 2835093 2835088 2026-09-30T02:45:20Z ChelsSchofield 3106760 /* Learning features */ changed explanation of table 2835093 wikitext text/x-wiki {{title|Technology-based pain management:<br>How can technology-based tools alter pain perception and pain management?}} __TOC__ ==Overview== [[File:Headache touching forehead.jpg|thumb|Figure 1: Headache ]] [[File:Pain cycle.jpg|thumb|326x326px|'''Figure 2 :'''The avoidance pain [https://pmc.ncbi.nlm.nih.gov/articles/PMC3820295/ cycle]]] *Technology-based pain interventions are receiving increasing research attention across healthcare settings, including postoperative care, rehabilitation, and labour wards (Musters et al., 2023; Yang et al., 2023).The pain technology market is projected to increase by '''USD $70.2 billion''' over the 10 years ( online forcast ask in next session). Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems help individuals regulate physiological arousal.Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems can help individuals regulate physiological arousal. Wearables, mobile applications, and telehealth platforms are also becoming more widely used, giving people accessible ways to track pain patterns and engage in self-management (Green & Chakravarthy, 2025; Li et al., 2024). Technology has therefore become increasingly influential in how pain is monitored, interpreted and managed across healthcare. For people with chronic pain, catastrophic thoughts and fear of further pain or injury may lead to avoidance of movement and meaningful activities, contributing to reduced functioning and increased distress (Gatchel, 2016; Vlaeyen & Linton, 2000). This chapter explores how technology-based interventions may interrupt this cycle by influencing pain signals, attention, emotions, thoughts, motivation and perceived control. {{RoundBoxTop|theme=2}} '''Focus questions''' {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} •How does technology alter the way people perceive and respond to pain? •How do psychological processes such as attention, emotion and cognitive appraisal contribute to technology-based pain management? •How do different technologies influence people's sense of control, engagement and motivation when managing pain? {{RoundBoxBottom}} == Understanding pain perception and management == Pain is not determined solely by physical injury. It is a personal sensory and emotional experience influenced by biological, psychological and social factors (Raja et al., 2020). Understanding the distinction between pain and nociception helps explain why technology can change a person’s pain experience even when it does not remove the original injury or health condition. Pain perception is shaped by how the brain interprets nociceptive signals alongside attention, emotions, memories, beliefs, expectations and the surrounding context (Bushnell et al., 2013; Tracey & Mantyh, 2007). Technology can alter this interpretation by redirecting attention, regulating physiological arousal, modifying pain-signal transmission or changing catastrophic thoughts about pain. It may also influence how a person responds by encouraging movement, coping and active self-management rather than fear and avoidance. Technology can therefore reduce the intensity, unpleasantness or perceived threat of pain while supporting greater confidence and control over pain-management behaviour. === Pain and nociception === * [[w:Pain|Pain]] is an unpleasant sensory and emotional experience associated with, or resembling an experience associated with, actual or potential tissue damage (Raja,2020). * Pain is personal and can be influenced by biological, psychological and social factors. * Nociception as the nervous system’s detection and processing of potentially harmful stimuli. * Pain and nociception are related but are not identical. * Nociception can occur without a conscious experience of pain and that pain may sometimes continue without clear evidence of current tissue damage (Basbaum ,2009; Raja ,2020). * Relate this distinction to technology by explaining that a tool may change a person’s pain experience without removing the original injury or condition. === Physiology of pain and pain perception === * Nociceptors detect potentially harmful mechanical, chemical or temperature-related stimuli and convert them into electrical signals. * Refer to these signals travelling through peripheral nerves to the spinal cord and then through ascending pathways to the brain (Basbaum,2009). * The brain interprets nociceptive information alongside attention, emotions, memories, beliefs, expectations and context. * The sensory dimension identifying the location and intensity of pain, while emotional, cognitive and motivational processes influence its unpleasantness, meaning and the person’s response. * Descending pathways from the brain can increase or reduce pain-signal transmission (Tracey & Mantyh, 2007). * Pain is not a direct measurement of tissue damage. Therefore, the same stimulus may be experienced differently by different people or by the same person in different situations (Bushnell,2013). * Relate this process to technology by introducing TENS as a tool that may modulate pain-signal transmission and VR as a tool that may change attention and the brain’s interpretation of pain. === Chronic pain and avoidance === * Chronic pain is pain that persists or recurs for longer than three months. * Chronic pain may affect attention, memory, mood, sleep, motivation, relationships and participation in daily activities. * Refer to increased attention towards bodily sensations and possible signs of pain. * Pain catastrophising as an exaggerated negative interpretation in which a person believes pain will be unbearable, uncontrollable or a sign of serious harm. * Fear-avoidance model. * Catastrophic interpretations can produce fear of pain, movement or reinjury. * Fear may lead the person to avoid physical activity, work, social activities and other meaningful experiences. * Avoidance can provide short-term relief from fear but may contribute to reduced activity, lower confidence, disability and emotional distress over time (Gatchel,2016; Vlaeyen & Linton, 2000). * '''See figure 2:''' One The Avoidance Pain Cyle === Understanding pain management === * Pain management as strategies used to reduce pain, distress and interference with daily life. * Chronic pain management may improve coping, functioning and participation without completely eliminating pain. * Refer to the biopsychosocial approach, which considers biological, psychological and social influences on pain (Raja, 2020). * Technology may support pain management through symptom monitoring, coping strategies and improved access to care (Li,2024). == How does technology alter pain perception? == {{ic|Include an introductory paragraph before branching into sub-sections}} === VR and attention modulation === * Refer to VR immerse user effecting attention - Limited capacity theory of attention (de Araujo, Zeferino, & Galas, 2026) === Biofeedback and autonomic regulation === *How biofeedback provides information about physiological pain responses, enabling users to practise regulating these responses and develop greater control over their pain experience. Related to self-regulation theory (Arsenault,2013). === Cognitive Digital CBT and ACT tools === * How CBT can modify unhelpful pain-related thoughts and behaviours, while ACT can increase pain acceptance and engagement in valued activities. These processes may reduce distress and improve functioning even when pain is not eliminated. Related - to cognitive appraisal theory and the psychological flexibility mode'''l''' (Hysing,2017; Neblett,2016).- Beneficial for catastrophic thinking, === Wearable sensors === * Wearable systems that collect pain ratings, adherence information and physiological data to personalise treatment and help users identify patterns in their pain. Related to self-regulation theory, particularly monitoring, feedback and behavioural adjustment (Green & Chakravarthy, 2025). === TENS === * Low-voltage electrical stimulation activating non-painful sensory fibres and reducing the transmission of pain signals. Relate this to gate control theory and endogenous pain inhibition (Blincoe,2007; Green & Chakravarthy,2025). === Telehealth and remote monitoring === * Clinicians monitoring pain ratings, treatment use and progress from a distance. Feedback and support may improve confidence, access and treatment adjustment. Relate this to self-efficacy and self-regulation (Green & Chakravarthy,2025). === Mobile applications === * Apps recording pain ratings, showing patterns, providing education or coping activities, and reminding users to practise pain-management strategies. Relate this to self-regulation theory. A dedicated mobile pain-application study is still required. == Psychological theories behind technology‑based pain management == * '''Psychological theories behind technology‑based pain management:'''Technology‑based pain interventions draw on established psychological theories explaining how cognition, emotion, attention and behaviour shape pain perception. These mechanisms help explain how tools such as VR, wearables and AI‑guided apps influence pain experience (Gatchel et al., 2007; Eccleston & Crombez, 1999). * '''Biopsychosocial model of pain:'''The biopsychosocial model proposes that pain arises from interactions between biological processes, psychological factors and social context. Technology‑based interventions align with this model by targeting multiple domains simultaneously, such as emotional regulation, behavioural change and physiological monitoring (Gatchel et al., 2007; Williams & Craig, 2016). * '''Limited‑capacity theory of attention:'''Pain captures limited attentional resources, increasing perceived intensity. VR and immersive technologies reduce pain by redirecting attention away from nociceptive input, supporting the theory’s predictions (Eccleston & Crombez, 1999; Malloy & Milling, 2010). * '''Gate control theory of pain:'''Gate control theory suggests that cognitive and emotional factors modulate nociceptive signals at the spinal level. Technologies such as TENS, VR and biofeedback influence these gates by altering attention and emotional state (Melzack & Wall, 1965; Moayedi & Davis, 2013). * '''Neuromodulation and neuroplasticity:'''Pain perception is shaped by dynamic neural networks that reorganise with experience. VR, neurofeedback and AI‑guided training promote adaptive neuroplasticity by reducing maladaptive signalling and strengthening regulatory pathways (Apkarian et al., 2009; Kutch & Apkarian, 2018). * '''Self‑regulation theory:'''Self‑regulation theory emphasises managing thoughts, emotions and behaviours to achieve desired outcomes. Technology‑based pain tools enhance self‑regulation through real‑time feedback, guided breathing and emotional tracking (Karoly, 1993; Jensen et al., 2014). * '''Operant conditioning:'''Pain behaviours can be reinforced by environmental responses. Technology‑based interventions apply operant principles by rewarding adaptive behaviours such as movement, pacing and relaxation (Fordyce, 1976; Vlaeyen & Linton, 2000). * '''Fear‑avoidance model of pain:'''Fear of pain leads to avoidance, deconditioning and increased disability. Graded VR exposure and movement‑tracking apps reduce fear by providing safe exposure and positive reinforcement (Vlaeyen & Linton, 2000; Crombez et al., 2012). * '''Cognitive appraisal and reframing:'''Pain intensity is influenced by how individuals interpret symptoms. Digital CBT tools help reframe catastrophic thoughts, reduce threat appraisal and promote adaptive interpretations of pain (Lazarus & Folkman, 1984; Turk & Wilson, 2010). * '''Psychological flexibility model:'''Psychological flexibility involves adapting behaviour in alignment with values despite discomfort. ACT‑based digital interventions enhance flexibility through acceptance, present‑moment awareness and committed action (Hayes et al., 2012; Trompetter et al., 2016). * '''Social cognitive theory and self‑efficacy:'''Self‑efficacy predicts pain coping and functional outcomes. Technology‑based interventions increase self‑efficacy through mastery experiences, modelling and feedback (Bandura, 1997; Jackson et al., 2014). * '''Affective‑motivational modulation of pain:'''Pain is shaped by emotional and motivational states such as fear, anxiety and goal orientation. Negative affect amplifies pain through enhanced salience and descending facilitation, while positive affect reduces pain via prefrontal‑limbic modulation. Technologies such as VR, AI‑guided relaxation and biofeedback apps modulate affective‑motivational systems by reducing threat cues and enhancing emotional regulation (Modernell et al., 2026; Vervoort & Trost, 2018; Garcia‑Larrea & Fauchon, 2023; ''Current Opinion in Psychology'', 2025). == Applications and tools == [[File:Pain pathway diagram showing transduction, transmission, modulation, and perception.png|thumb|293x293px|Figure 2: Brain Pain Pathways ]] * VR * TENS * Mobile apps * Wearables * Gamification * Telehealth == Future Applications and Emerging Technologies == * List Of Various Cutting edge * Emerging technologies * futuristics applications == Limitations and ethical considerations == * Effectiveness differs between users, technologies and pain conditions. * Refer to barriers including cost, access, digital skills and user engagement (Li,2024). * Possible side effects, privacy concerns and increased attention to symptoms. ==Learning features== '''Table 1''' See The Summary Table below : Technology-based pain management approaches, their effects on pain perception, emotion and motivation, and the psychological theories that help explain these effects {| class="wikitable" style="margin: auto; |- ! Technology !! How it alters pain perception !! Theory / Model |- | VR || Redirects attention || Limited-capacity attention |- | TENS || Modulates pain signals || Gate control theory |- |Biofeedback |Support regulation of arousal |Self-regulation, conditioning |- |CBT/ACT tools |Changes to coping, appraisal and avoidance |Fear avoidance, flexibility |- |Wearables/apps |Records patterns and provides feedback |Self-regulation |- |Telehealth |Remote support, health access and treatment |Self-efficacy |} ;Quizzes * Why might VR reduce the amount of attention given to pain? See: * Which theory best explains how TENS may reduce pain-signal transmission? * How can feedback from a wearable device support self-regulation? * How might catastrophic thinking contribute to the fear-avoidance cycle? <quiz display="simple"> {Virtual reality (VR) can reduce pain by redirecting a person’s attention away from painful stimuli?: |type="()"} + True - False {TENS devices work by increasing the intensity of pain signals sent to the brain. Answer?: |type="()"} - True + False </quiz> ==Conclusion== * Pain is interpreted by the brain and is influenced by attention, emotion, appraisal, behaviour and social support, not only by signals from the body. * Different technologies alter pain perception through different pathways: VR redirects attention, TENS modulates signals, and feedback or cognitive tools influence arousal, appraisal and control. * Technology is most useful as part of individualised, biopsychosocial pain management rather than as a replacement for all existing care (Hysing,2017; Li,2024). * Effectiveness depends on the user, pain condition, technology, level of support and quality of available evidence. {{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== [[wikipedia:Virtual_reality_therapy|Virtual reality therapy]] (Wikipedia) [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * https://en.wikipedia.org/wiki/Pain {{ic|Create internal link}} * https://en.wikipedia.org/wiki/Virtual_reality {{ic|Create internal link}} * [[Motivation and emotion/Book/2021/Self-regulation|Self-regulation]] (Book chapter, 2021) * [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * [[wikipedia:Cognitive_behavioral_therapy|Cognitive behavioral therapy]] (Wikipedia) * [[wikipedia:Biopsychosocial_model|Biopsychosocial model]] (Wikipedia) * [[wikipedia:Gate_control_theory|Gate control theory]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== This section lists the cited references in [[w:APA style|APA style]] (7th ed.) or [[w:Wikipedia:Citing sources|wiki style]]. {{Hanging indent|1= }} * Musters, A., Vandevenne, A. S., Franx, A., & Wassen, M. M. L. H. (2023). Virtual Reality Experience during Labour (VIREL): A qualitative study. ''BMC Pregnancy and Childbirth, 23'', Article 283. <nowiki>https://doi.org/10.1186/s12884-023-05633-0</nowiki> * Yang, X., Zhong, S., Yang, S., He, M., Xu, X., He, S., Fan, G., & Liu, L. (2023). Global scientific trends in virtual reality for pain treatment from 2000 to 2022: Bibliometric analysis. ''JMIR Serious Games, 11'', Article e48354. <nowiki>https://doi.org/10.2196/48354</nowiki> * Green, M., & Chakravarthy, K. (2025). Artificial intelligence-enhanced pain management: The NXTSTIM EcoAI platform. ''Pain Management, 15''(8), 467–475. * Li, L. W., Yi, T. H., & Khaing, N. E. E. (2024). Chronic pain healthcare workers’ challenges in pain management and receptiveness towards VR as an adjunct management tool: A qualitative study. ''BMC Digital Health, 2'', Article 26. * Gatchel, R. J., Neblett, R., Kishino, N., & Ray, C. T. (2016). Fear-avoidance beliefs and chronic pain. ''Journal of Orthopaedic & Sports Physical Therapy, 46''(2), 38–43. <nowiki>https://doi.org/10.2519/jospt.2016.0601</nowiki> * Vlaeyen, J. W. S., & Linton, S. J. (2000). Fear-avoidance and its consequences in chronic musculoskeletal pain: A state of the art. ''Pain, 85''(3), 317–332. <nowiki>https://doi.org/10.1016/S0304-3959(99)00242-0</nowiki> * Raja, S. N., Carr, D. B., Cohen, M., Finnerup, N. B., Flor, H., Gibson, S., Keefe, F. J., Mogil, J. S., Ringkamp, M., Sluka, K. A., Song, X.-J., Stevens, B., Sullivan, M. D., Tutelman, P. R., Ushida, T., & Vader, K. (2020). The revised International Association for the Study of Pain definition of pain: Concepts, challenges, and compromises. ''Pain, 161''(9), 1976–1982. <nowiki>https://doi.org/10.1097/j.pain.0000000000001939</nowiki> * Bushnell, M. C., Čeko, M., & Low, L. A. (2013). Cognitive and emotional control of pain and its disruption in chronic pain. ''Nature Reviews Neuroscience, 14''(7), 502–511. <nowiki>https://doi.org/10.1038/nrn3516</nowiki> * Tracey, I., & Mantyh, P. W. (2007). The cerebral signature for pain perception and its modulation. ''Neuron, 55''(3), 377–391. <nowiki>https://doi.org/10.1016/j.neuron.2007.07.012</nowiki> * Basbaum, A. I., Bautista, D. M., Scherrer, G., & Julius, D. (2009). Cellular and molecular mechanisms of pain. ''Cell, 139''(2), 267–284. <nowiki>https://doi.org/10.1016/j.cell.2009.09.028</nowiki> * de Araujo, D. D., Zeferino, S. P., & Galas, F. R. B. G. (2026). Virtual reality for opioid reduction in postoperative cardiac and thoracic surgery: A randomized controlled trial protocol. ''MethodsX, 17'', Article 104029. * Arsenault, M., Piché, M., Duncan, G. H., & Rainville, P. (2013). Self-regulation of acute experimental pain with and without biofeedback using spinal nociceptive responses. ''Neuroscience, 231'', 102–110. <nowiki>https://doi.org/10.1016/j.neuroscience.2012.11.039</nowiki> * Hysing, E.-B., Smith, L., Thulin, M., Karlsten, R., & Gordh, T. (2017). Detection of systemic inflammation in severely impaired chronic pain patients, and effects of a CBT-ACT-based multi-modal pain rehabilitation program. ''Scandinavian Journal of Pain, 16'', 175. <nowiki>https://doi.org/10.1016/j.sjpain.2017.04.033</nowiki> * Neblett, R., Mayer, T. G., Hartzell, M. M., Williams, M. J., & Gatchel, R. J. (2016). The Fear-Avoidance Components Scale (FACS): Development and psychometric evaluation of a new measure of pain-related fear avoidance. ''Pain Practice, 16''(4), 435–450. <nowiki>https://doi.org/10.1111/papr.12333</nowiki> * Blincoe, A. J. (2007). TENS machines and their use in managing labour pain. ''British Journal of Midwifery, 15''(8), 516–519. * Gatchel, R. J., Peng, Y. B., Peters, M. L., Fuchs, P. N., & Turk, D. C. (2007). The biopsychosocial approach to chronic pain: Scientific advances and future directions. ''Psychological Bulletin, 133''(4), 581–624. <nowiki>https://doi.org/10.1037/0033-2909.133.4.581</nowiki> * Eccleston, C., & Crombez, G. (1999). Pain demands attention: A cognitive-affective model of the interruptive function of pain. ''Psychological Bulletin, 125''(3), 356–366. <nowiki>https://doi.org/10.1037/0033-2909.125.3.356</nowiki> * Williams, A. C. de C., & Craig, K. D. (2016). Updating the definition of pain. ''Pain, 157''(11), 2420–2423. <nowiki>https://doi.org/10.1097/j.pain.0000000000000613</nowiki> * Malloy, K. M., & Milling, L. S. (2010). The effectiveness of virtual reality distraction for pain reduction: A systematic review. ''Clinical Psychology Review, 30''(8), 1011–1018. <nowiki>https://doi.org/10.1016/j.cpr.2010.07.001</nowiki> * Melzack, R., & Wall, P. D. (1965). Pain mechanisms: A new theory. ''Science, 150''(3699), 971–979. <nowiki>https://doi.org/10.1126/science.150.3699.971</nowiki> * Moayedi, M., & Davis, K. D. (2013). Theories of pain: From specificity to gate control. ''Journal of Neurophysiology, 109''(1), 5–12. <nowiki>https://doi.org/10.1152/jn.00457.2012</nowiki> * Apkarian, A. V., Baliki, M. N., & Geha, P. Y. (2009). Towards a theory of chronic pain. ''Progress in Neurobiology, 87''(2), 81–97. <nowiki>https://doi.org/10.1016/j.pneurobio.2008.09.018</nowiki> * Kutch, J. J., & Apkarian, A. V. (2018). Potential mechanisms underlying centralized pain and emerging therapeutic interventions. ''Frontiers in Cellular Neuroscience, 12'', Article 35. <nowiki>https://doi.org/10.3389/fncel.2018.00035</nowiki> * Karoly, P. (1993). Mechanisms of self-regulation: A systems view. ''Annual Review of Psychology, 44'', 23–52. <nowiki>https://doi.org/10.1146/annurev.ps.44.020193.000323</nowiki> * Hamilton, N. A., Karoly, P., & Kitzman, H. (2004). Self-regulation and chronic pain: The role of emotion. ''Cognitive Therapy and Research, 28''(5), 559–576. <nowiki>https://doi.org/10.1023/B:COTR.0000045565.88145.76</nowiki> * Fordyce, W. E. (1976). ''Behavioral methods for chronic pain and illness''. Mosby. * Crombez, G., Eccleston, C., Van Damme, S., Vlaeyen, J. W. S., & Karoly, P. (2012). Fear-avoidance model of chronic pain: The next generation. ''Clinical Journal of Pain, 28''(6), 475–483. <nowiki>https://doi.org/10.1097/AJP.0b013e3182385392</nowiki> * Lazarus, R. S., & Folkman, S. (1984). ''Stress, appraisal, and coping''. Springer. * Turk, D. C., & Wilson, H. D. (2010). Fear of pain as a prognostic factor in chronic pain: Conceptual models, assessment, and treatment implications. ''Current Pain and Headache Reports, 14''(2), 88–95. <nowiki>https://doi.org/10.1007/s11916-010-0094-x</nowiki> * Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). ''Acceptance and commitment therapy: The process and practice of mindful change'' (2nd ed.). Guilford Press. * Veehof, M. M., Trompetter, H. R., Bohlmeijer, E. T., & Schreurs, K. M. G. (2016). Acceptance- and mindfulness-based interventions for the treatment of chronic pain: A meta-analytic review. ''Cognitive Behaviour Therapy, 45''(1), 5–31. <nowiki>https://doi.org/10.1080/16506073.2015.1098724</nowiki> * Bandura, A. (1997). ''Self-efficacy: The exercise of control''. W. H. Freeman. * Jackson, T., Wang, Y., Wang, Y., & Fan, H. (2014). Self-efficacy and chronic pain outcomes: A meta-analytic review. ''The Journal of Pain, 15''(8), 800–814. <nowiki>https://doi.org/10.1016/j.jpain.2014.05.002</nowiki> * Modernell, L. M., Faillenot, I., Garcia-Larrea, L., & Fauchon, C. (2026). The multifaceted neural architecture of pain modulation by emotion and cognition: A systematic review and meta-analysis. 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''Current Opinion in Psychology, 62'', Article 102000. <nowiki>https://doi.org/10.1016/j.copsyc.2025.102000</nowiki> {{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== * https://www.iasp-pain.org/resources/terminology/ * https://www.qld.gov.au/health/services/specialists/persistent-pain/understanding-pain/managing-your-pain * https://aci.health.nsw.gov.au/chronic-pain/painbytes/pain-and-mind-body-connection {{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/Pain]] [[Category:Motivation and emotion/Book/Technology]] jrzavl8wkd3kx1yrz3pumvsmkocqz1s 2835113 2835093 2026-09-30T04:20:53Z Jtneill 10242 Reinstate scenario 2835113 wikitext text/x-wiki {{title|Technology-based pain management:<br>How can technology-based tools alter pain perception and pain management?}} __TOC__ ==Overview== {{RoundBoxTop|theme=2}} [[File:Pain cycle.jpg|thumb|326x326px|'''Figure 2 :'''The avoidance pain [https://pmc.ncbi.nlm.nih.gov/articles/PMC3820295/ cycle]] '''Case study: Elena's shift in pain perception''' Elena is a 35-year-old graphic designer living with chronic neuropathic pain following a viral infection. For years, her pain felt unpredictable and overwhelming, some days she could work normally, while other days even holding a pencil felt impossible. What frightened her most wasn’t the pain itself, but the random timing and the belief that she had no control over it. Her pain specialist introduced her to a set of perception altering technologies: VR program designed to redirect attention and reduce pain intensity through immersive environments a wearable sensor that tracked muscle tension and autonomic arousal a mobile app that visualised her pain patterns using predictive coding algorithms Within two weeks, Elena noticed something she didn’t expect: her pain felt less threatening. The VR sessions helped her shift attention away from the pain, reducing the “alarm” response in her brain. The wearable showed spikes in tension before flare ups, helping her intervene early. The app revealed consistent patterns stress, poor sleep, and long work sessions transforming what once felt random into something understandable and predictable. As Elena’s understanding changed, her perception changed. Pain episodes felt less catastrophic, shorter, and easier to manage. Technology didn’t eliminate her pain it altered the way her brain interpreted it, giving her a sense of agency she hadn’t felt in years. {{RoundBoxBottom}} [[File:Pain cycle.jpg|thumb|326x326px|'''Figure 1'''. The avoidance pain [https://pmc.ncbi.nlm.nih.gov/articles/PMC3820295/ cycle]]] *Technology-based pain interventions are receiving increasing research attention across healthcare settings, including postoperative care, rehabilitation, and labour wards (Musters et al., 2023; Yang et al., 2023).The pain technology market is projected to increase by '''USD $70.2 billion''' over the 10 years ( online forcast ask in next session). Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems help individuals regulate physiological arousal.Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems can help individuals regulate physiological arousal. Wearables, mobile applications, and telehealth platforms are also becoming more widely used, giving people accessible ways to track pain patterns and engage in self-management (Green & Chakravarthy, 2025; Li et al., 2024). Technology has therefore become increasingly influential in how pain is monitored, interpreted and managed across healthcare. For people with chronic pain, catastrophic thoughts and fear of further pain or injury may lead to avoidance of movement and meaningful activities, contributing to reduced functioning and increased distress (Gatchel, 2016; Vlaeyen & Linton, 2000). This chapter explores how technology-based interventions may interrupt this cycle by influencing pain signals, attention, emotions, thoughts, motivation and perceived control. {{RoundBoxTop|theme=2}} '''Focus questions''' {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} •How does technology alter the way people perceive and respond to pain? •How do psychological processes such as attention, emotion and cognitive appraisal contribute to technology-based pain management? •How do different technologies influence people's sense of control, engagement and motivation when managing pain? {{RoundBoxBottom}} == Understanding pain perception and management == Pain is not determined solely by physical injury. It is a personal sensory and emotional experience influenced by biological, psychological and social factors (Raja et al., 2020). Understanding the distinction between pain and nociception helps explain why technology can change a person’s pain experience even when it does not remove the original injury or health condition. Pain perception is shaped by how the brain interprets nociceptive signals alongside attention, emotions, memories, beliefs, expectations and the surrounding context (Bushnell et al., 2013; Tracey & Mantyh, 2007). Technology can alter this interpretation by redirecting attention, regulating physiological arousal, modifying pain-signal transmission or changing catastrophic thoughts about pain. It may also influence how a person responds by encouraging movement, coping and active self-management rather than fear and avoidance. Technology can therefore reduce the intensity, unpleasantness or perceived threat of pain while supporting greater confidence and control over pain-management behaviour. === Pain and nociception === * [[w:Pain|Pain]] is an unpleasant sensory and emotional experience associated with, or resembling an experience associated with, actual or potential tissue damage (Raja,2020). * Pain is personal and can be influenced by biological, psychological and social factors. * Nociception as the nervous system’s detection and processing of potentially harmful stimuli. * Pain and nociception are related but are not identical. * Nociception can occur without a conscious experience of pain and that pain may sometimes continue without clear evidence of current tissue damage (Basbaum ,2009; Raja ,2020). * Relate this distinction to technology by explaining that a tool may change a person’s pain experience without removing the original injury or condition. === Physiology of pain and pain perception === * Nociceptors detect potentially harmful mechanical, chemical or temperature-related stimuli and convert them into electrical signals. * Refer to these signals travelling through peripheral nerves to the spinal cord and then through ascending pathways to the brain (Basbaum,2009). * The brain interprets nociceptive information alongside attention, emotions, memories, beliefs, expectations and context. * The sensory dimension identifying the location and intensity of pain, while emotional, cognitive and motivational processes influence its unpleasantness, meaning and the person’s response. * Descending pathways from the brain can increase or reduce pain-signal transmission (Tracey & Mantyh, 2007). * Pain is not a direct measurement of tissue damage. Therefore, the same stimulus may be experienced differently by different people or by the same person in different situations (Bushnell,2013). * Relate this process to technology by introducing TENS as a tool that may modulate pain-signal transmission and VR as a tool that may change attention and the brain’s interpretation of pain. === Chronic pain and avoidance === * Chronic pain is pain that persists or recurs for longer than three months. * Chronic pain may affect attention, memory, mood, sleep, motivation, relationships and participation in daily activities. * Refer to increased attention towards bodily sensations and possible signs of pain. * Pain catastrophising as an exaggerated negative interpretation in which a person believes pain will be unbearable, uncontrollable or a sign of serious harm. * Fear-avoidance model. * Catastrophic interpretations can produce fear of pain, movement or reinjury. * Fear may lead the person to avoid physical activity, work, social activities and other meaningful experiences. * Avoidance can provide short-term relief from fear but may contribute to reduced activity, lower confidence, disability and emotional distress over time (Gatchel,2016; Vlaeyen & Linton, 2000). * '''See figure:''' One The Avoidance Pain Cyle === Understanding pain management === * Pain management as strategies used to reduce pain, distress and interference with daily life. * Chronic pain management may improve coping, functioning and participation without completely eliminating pain. * Refer to the biopsychosocial approach, which considers biological, psychological and social influences on pain (Raja, 2020). * Technology may support pain management through symptom monitoring, coping strategies and improved access to care (Li,2024). == How does technology alter pain perception? == {{ic|Include an introductory paragraph before branching into sub-sections}} === VR and attention modulation === * Refer to VR immerse user effecting attention - Limited capacity theory of attention (de Araujo, Zeferino, & Galas, 2026) === Biofeedback and autonomic regulation === *How biofeedback provides information about physiological pain responses, enabling users to practise regulating these responses and develop greater control over their pain experience. Related to self-regulation theory (Arsenault,2013). === Cognitive Digital CBT and ACT tools === * How CBT can modify unhelpful pain-related thoughts and behaviours, while ACT can increase pain acceptance and engagement in valued activities. These processes may reduce distress and improve functioning even when pain is not eliminated. Related - to cognitive appraisal theory and the psychological flexibility mode'''l''' (Hysing,2017; Neblett,2016).- Beneficial for catastrophic thinking, === Wearable sensors === * Wearable systems that collect pain ratings, adherence information and physiological data to personalise treatment and help users identify patterns in their pain. Related to self-regulation theory, particularly monitoring, feedback and behavioural adjustment (Green & Chakravarthy, 2025). === TENS === * Low-voltage electrical stimulation activating non-painful sensory fibres and reducing the transmission of pain signals. Relate this to gate control theory and endogenous pain inhibition (Blincoe,2007; Green & Chakravarthy,2025). === Telehealth and remote monitoring === * Clinicians monitoring pain ratings, treatment use and progress from a distance. Feedback and support may improve confidence, access and treatment adjustment. Relate this to self-efficacy and self-regulation (Green & Chakravarthy,2025). === Mobile applications === * Apps recording pain ratings, showing patterns, providing education or coping activities, and reminding users to practise pain-management strategies. Relate this to self-regulation theory. A dedicated mobile pain-application study is still required. == Psychological theories behind technology‑based pain management == * '''Psychological theories behind technology‑based pain management:'''Technology‑based pain interventions draw on established psychological theories explaining how cognition, emotion, attention and behaviour shape pain perception. These mechanisms help explain how tools such as VR, wearables and AI‑guided apps influence pain experience (Gatchel et al., 2007; Eccleston & Crombez, 1999). * '''Biopsychosocial model of pain:'''The biopsychosocial model proposes that pain arises from interactions between biological processes, psychological factors and social context. Technology‑based interventions align with this model by targeting multiple domains simultaneously, such as emotional regulation, behavioural change and physiological monitoring (Gatchel et al., 2007; Williams & Craig, 2016). * '''Limited‑capacity theory of attention:'''Pain captures limited attentional resources, increasing perceived intensity. VR and immersive technologies reduce pain by redirecting attention away from nociceptive input, supporting the theory’s predictions (Eccleston & Crombez, 1999; Malloy & Milling, 2010). * '''Gate control theory of pain:'''Gate control theory suggests that cognitive and emotional factors modulate nociceptive signals at the spinal level. Technologies such as TENS, VR and biofeedback influence these gates by altering attention and emotional state (Melzack & Wall, 1965; Moayedi & Davis, 2013). * '''Neuromodulation and neuroplasticity:'''Pain perception is shaped by dynamic neural networks that reorganise with experience. VR, neurofeedback and AI‑guided training promote adaptive neuroplasticity by reducing maladaptive signalling and strengthening regulatory pathways (Apkarian et al., 2009; Kutch & Apkarian, 2018). * '''Self‑regulation theory:'''Self‑regulation theory emphasises managing thoughts, emotions and behaviours to achieve desired outcomes. Technology‑based pain tools enhance self‑regulation through real‑time feedback, guided breathing and emotional tracking (Karoly, 1993; Jensen et al., 2014). * '''Operant conditioning:'''Pain behaviours can be reinforced by environmental responses. Technology‑based interventions apply operant principles by rewarding adaptive behaviours such as movement, pacing and relaxation (Fordyce, 1976; Vlaeyen & Linton, 2000). * '''Fear‑avoidance model of pain:'''Fear of pain leads to avoidance, deconditioning and increased disability. Graded VR exposure and movement‑tracking apps reduce fear by providing safe exposure and positive reinforcement (Vlaeyen & Linton, 2000; Crombez et al., 2012). * '''Cognitive appraisal and reframing:'''Pain intensity is influenced by how individuals interpret symptoms. Digital CBT tools help reframe catastrophic thoughts, reduce threat appraisal and promote adaptive interpretations of pain (Lazarus & Folkman, 1984; Turk & Wilson, 2010). * '''Psychological flexibility model:'''Psychological flexibility involves adapting behaviour in alignment with values despite discomfort. ACT‑based digital interventions enhance flexibility through acceptance, present‑moment awareness and committed action (Hayes et al., 2012; Trompetter et al., 2016). * '''Social cognitive theory and self‑efficacy:'''Self‑efficacy predicts pain coping and functional outcomes. Technology‑based interventions increase self‑efficacy through mastery experiences, modelling and feedback (Bandura, 1997; Jackson et al., 2014). * '''Affective‑motivational modulation of pain:'''Pain is shaped by emotional and motivational states such as fear, anxiety and goal orientation. Negative affect amplifies pain through enhanced salience and descending facilitation, while positive affect reduces pain via prefrontal‑limbic modulation. Technologies such as VR, AI‑guided relaxation and biofeedback apps modulate affective‑motivational systems by reducing threat cues and enhancing emotional regulation (Modernell et al., 2026; Vervoort & Trost, 2018; Garcia‑Larrea & Fauchon, 2023; ''Current Opinion in Psychology'', 2025). == Applications and tools == [[File:Pain pathway diagram showing transduction, transmission, modulation, and perception.png|thumb|293x293px|Figure 2: Brain Pain Pathways ]] * VR * TENS * Mobile apps * Wearables * Gamification * Telehealth == Future Applications and Emerging Technologies == * List Of Various Cutting edge * Emerging technologies * futuristics applications == Limitations and ethical considerations == * Effectiveness differs between users, technologies and pain conditions. * Refer to barriers including cost, access, digital skills and user engagement (Li,2024). * Possible side effects, privacy concerns and increased attention to symptoms. ==Learning features== '''Table 1''' See The Summary Table below : {{ic|Provide a more descriptive caption}} {| class="wikitable" style="margin: auto; |- ! Technology !! How it alters pain perception !! Theory / Model |- | VR || Redirects attention || Limited-capacity attention |- | TENS || Modulates pain signals || Gate control theory |- |Biofeedback |Support regulation of arousal |Self-regulation, conditioning |- |CBT/ACT tools |Changes to coping, appraisal and avoidance |Fear avoidance, flexibility |- |Wearables/apps |Records patterns and provides feedback |Self-regulation |- |Telehealth |Remote support, health access and treatment |Self-efficacy |} ;Quizzes * Why might VR reduce the amount of attention given to pain? See: * Which theory best explains how TENS may reduce pain-signal transmission? * How can feedback from a wearable device support self-regulation? * How might catastrophic thinking contribute to the fear-avoidance cycle? <quiz display="simple"> {Virtual reality (VR) can reduce pain by redirecting a person’s attention away from painful stimuli?: |type="()"} + True - False {TENS devices work by increasing the intensity of pain signals sent to the brain. Answer?: |type="()"} - True + False </quiz> ==Conclusion== * Pain is interpreted by the brain and is influenced by attention, emotion, appraisal, behaviour and social support, not only by signals from the body. * Different technologies alter pain perception through different pathways: VR redirects attention, TENS modulates signals, and feedback or cognitive tools influence arousal, appraisal and control. * Technology is most useful as part of individualised, biopsychosocial pain management rather than as a replacement for all existing care (Hysing,2017; Li,2024). * Effectiveness depends on the user, pain condition, technology, level of support and quality of available evidence. {{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== [[wikipedia:Virtual_reality_therapy|Virtual reality therapy]] (Wikipedia) [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * https://en.wikipedia.org/wiki/Pain {{ic|Create internal link}} * https://en.wikipedia.org/wiki/Virtual_reality {{ic|Create internal link}} * [[Motivation and emotion/Book/2021/Self-regulation|Self-regulation]] (Book chapter, 2021) * [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * [[wikipedia:Cognitive_behavioral_therapy|Cognitive behavioral therapy]] (Wikipedia) * [[wikipedia:Biopsychosocial_model|Biopsychosocial model]] (Wikipedia) * [[wikipedia:Gate_control_theory|Gate control theory]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== This section lists the cited references in [[w:APA style|APA style]] (7th ed.) or [[w:Wikipedia:Citing sources|wiki style]]. {{Hanging indent|1= }} * Musters, A., Vandevenne, A. S., Franx, A., & Wassen, M. M. L. H. (2023). Virtual Reality Experience during Labour (VIREL): A qualitative study. ''BMC Pregnancy and Childbirth, 23'', Article 283. <nowiki>https://doi.org/10.1186/s12884-023-05633-0</nowiki> * Yang, X., Zhong, S., Yang, S., He, M., Xu, X., He, S., Fan, G., & Liu, L. (2023). Global scientific trends in virtual reality for pain treatment from 2000 to 2022: Bibliometric analysis. ''JMIR Serious Games, 11'', Article e48354. <nowiki>https://doi.org/10.2196/48354</nowiki> * Green, M., & Chakravarthy, K. (2025). Artificial intelligence-enhanced pain management: The NXTSTIM EcoAI platform. ''Pain Management, 15''(8), 467–475. * Li, L. W., Yi, T. H., & Khaing, N. E. E. (2024). Chronic pain healthcare workers’ challenges in pain management and receptiveness towards VR as an adjunct management tool: A qualitative study. ''BMC Digital Health, 2'', Article 26. * Gatchel, R. J., Neblett, R., Kishino, N., & Ray, C. T. (2016). 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''Nature Reviews Neuroscience, 14''(7), 502–511. <nowiki>https://doi.org/10.1038/nrn3516</nowiki> * Tracey, I., & Mantyh, P. W. (2007). The cerebral signature for pain perception and its modulation. ''Neuron, 55''(3), 377–391. <nowiki>https://doi.org/10.1016/j.neuron.2007.07.012</nowiki> * Basbaum, A. I., Bautista, D. M., Scherrer, G., & Julius, D. (2009). Cellular and molecular mechanisms of pain. ''Cell, 139''(2), 267–284. <nowiki>https://doi.org/10.1016/j.cell.2009.09.028</nowiki> * de Araujo, D. D., Zeferino, S. P., & Galas, F. R. B. G. (2026). Virtual reality for opioid reduction in postoperative cardiac and thoracic surgery: A randomized controlled trial protocol. ''MethodsX, 17'', Article 104029. * Arsenault, M., Piché, M., Duncan, G. H., & Rainville, P. (2013). Self-regulation of acute experimental pain with and without biofeedback using spinal nociceptive responses. ''Neuroscience, 231'', 102–110. <nowiki>https://doi.org/10.1016/j.neuroscience.2012.11.039</nowiki> * Hysing, E.-B., Smith, L., Thulin, M., Karlsten, R., & Gordh, T. (2017). Detection of systemic inflammation in severely impaired chronic pain patients, and effects of a CBT-ACT-based multi-modal pain rehabilitation program. ''Scandinavian Journal of Pain, 16'', 175. <nowiki>https://doi.org/10.1016/j.sjpain.2017.04.033</nowiki> * Neblett, R., Mayer, T. G., Hartzell, M. M., Williams, M. J., & Gatchel, R. J. (2016). The Fear-Avoidance Components Scale (FACS): Development and psychometric evaluation of a new measure of pain-related fear avoidance. ''Pain Practice, 16''(4), 435–450. <nowiki>https://doi.org/10.1111/papr.12333</nowiki> * Blincoe, A. J. (2007). TENS machines and their use in managing labour pain. ''British Journal of Midwifery, 15''(8), 516–519. * Gatchel, R. J., Peng, Y. B., Peters, M. L., Fuchs, P. N., & Turk, D. C. (2007). The biopsychosocial approach to chronic pain: Scientific advances and future directions. ''Psychological Bulletin, 133''(4), 581–624. <nowiki>https://doi.org/10.1037/0033-2909.133.4.581</nowiki> * Eccleston, C., & Crombez, G. (1999). Pain demands attention: A cognitive-affective model of the interruptive function of pain. ''Psychological Bulletin, 125''(3), 356–366. <nowiki>https://doi.org/10.1037/0033-2909.125.3.356</nowiki> * Williams, A. C. de C., & Craig, K. D. (2016). Updating the definition of pain. ''Pain, 157''(11), 2420–2423. <nowiki>https://doi.org/10.1097/j.pain.0000000000000613</nowiki> * Malloy, K. M., & Milling, L. S. (2010). The effectiveness of virtual reality distraction for pain reduction: A systematic review. ''Clinical Psychology Review, 30''(8), 1011–1018. <nowiki>https://doi.org/10.1016/j.cpr.2010.07.001</nowiki> * Melzack, R., & Wall, P. D. (1965). Pain mechanisms: A new theory. ''Science, 150''(3699), 971–979. <nowiki>https://doi.org/10.1126/science.150.3699.971</nowiki> * Moayedi, M., & Davis, K. D. (2013). Theories of pain: From specificity to gate control. ''Journal of Neurophysiology, 109''(1), 5–12. <nowiki>https://doi.org/10.1152/jn.00457.2012</nowiki> * Apkarian, A. V., Baliki, M. N., & Geha, P. Y. (2009). Towards a theory of chronic pain. ''Progress in Neurobiology, 87''(2), 81–97. <nowiki>https://doi.org/10.1016/j.pneurobio.2008.09.018</nowiki> * Kutch, J. J., & Apkarian, A. V. (2018). Potential mechanisms underlying centralized pain and emerging therapeutic interventions. ''Frontiers in Cellular Neuroscience, 12'', Article 35. <nowiki>https://doi.org/10.3389/fncel.2018.00035</nowiki> * Karoly, P. (1993). Mechanisms of self-regulation: A systems view. ''Annual Review of Psychology, 44'', 23–52. <nowiki>https://doi.org/10.1146/annurev.ps.44.020193.000323</nowiki> * Hamilton, N. A., Karoly, P., & Kitzman, H. (2004). Self-regulation and chronic pain: The role of emotion. ''Cognitive Therapy and Research, 28''(5), 559–576. <nowiki>https://doi.org/10.1023/B:COTR.0000045565.88145.76</nowiki> * Fordyce, W. E. (1976). ''Behavioral methods for chronic pain and illness''. Mosby. * Crombez, G., Eccleston, C., Van Damme, S., Vlaeyen, J. W. S., & Karoly, P. (2012). Fear-avoidance model of chronic pain: The next generation. ''Clinical Journal of Pain, 28''(6), 475–483. <nowiki>https://doi.org/10.1097/AJP.0b013e3182385392</nowiki> * Lazarus, R. S., & Folkman, S. (1984). ''Stress, appraisal, and coping''. Springer. * Turk, D. C., & Wilson, H. D. (2010). Fear of pain as a prognostic factor in chronic pain: Conceptual models, assessment, and treatment implications. ''Current Pain and Headache Reports, 14''(2), 88–95. <nowiki>https://doi.org/10.1007/s11916-010-0094-x</nowiki> * Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). ''Acceptance and commitment therapy: The process and practice of mindful change'' (2nd ed.). Guilford Press. * Veehof, M. M., Trompetter, H. R., Bohlmeijer, E. T., & Schreurs, K. M. G. (2016). Acceptance- and mindfulness-based interventions for the treatment of chronic pain: A meta-analytic review. ''Cognitive Behaviour Therapy, 45''(1), 5–31. <nowiki>https://doi.org/10.1080/16506073.2015.1098724</nowiki> * Bandura, A. (1997). ''Self-efficacy: The exercise of control''. W. H. Freeman. * Jackson, T., Wang, Y., Wang, Y., & Fan, H. (2014). Self-efficacy and chronic pain outcomes: A meta-analytic review. ''The Journal of Pain, 15''(8), 800–814. <nowiki>https://doi.org/10.1016/j.jpain.2014.05.002</nowiki> * Modernell, L. M., Faillenot, I., Garcia-Larrea, L., & Fauchon, C. (2026). The multifaceted neural architecture of pain modulation by emotion and cognition: A systematic review and meta-analysis. ''British Journal of Anaesthesia, 136''(6), 1894–1909. <nowiki>https://doi.org/10.1016/j.bja.2026.03.015</nowiki> * Vervoort, T., & Trost, Z. (2018). An affective-motivational account of interpersonal dynamics in pain. In T. Vervoort, K. Karos, Z. Trost, & K. M. Prkachin (Eds.), ''Social and interpersonal dynamics in pain: We don’t suffer alone'' (pp. 57–75). Springer. <nowiki>https://doi.org/10.1007/978-3-319-78340-6_4</nowiki> * Boersma, K., & Flink, I. K. (2025). Key aspects concerning the role of emotion in the chronic pain experience. ''Current Opinion in Psychology, 62'', Article 102000. <nowiki>https://doi.org/10.1016/j.copsyc.2025.102000</nowiki> {{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== * https://www.iasp-pain.org/resources/terminology/ * https://www.qld.gov.au/health/services/specialists/persistent-pain/understanding-pain/managing-your-pain * https://aci.health.nsw.gov.au/chronic-pain/painbytes/pain-and-mind-body-connection {{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/Pain]] [[Category:Motivation and emotion/Book/Technology]] 7podp60c412hpanvi8i03ojyvvdpkvw 2835114 2835113 2026-09-30T04:23:51Z Jtneill 10242 Move figures 2835114 wikitext text/x-wiki {{title|Technology-based pain management:<br>How can technology-based tools alter pain perception and pain management?}} __TOC__ ==Overview== {{RoundBoxTop|theme=2}} [[File:Headache touching forehead.jpg|thumb|326x326px|'''Figure 1'''. Headache]] '''Case study: Elena's shift in pain perception''' Elena is a 35-year-old graphic designer living with chronic neuropathic pain following a viral infection. For years, her pain felt unpredictable and overwhelming, some days she could work normally, while other days even holding a pencil felt impossible. What frightened her most wasn’t the pain itself, but the random timing and the belief that she had no control over it. Her pain specialist introduced her to a set of perception altering technologies: VR program designed to redirect attention and reduce pain intensity through immersive environments a wearable sensor that tracked muscle tension and autonomic arousal a mobile app that visualised her pain patterns using predictive coding algorithms Within two weeks, Elena noticed something she didn’t expect: her pain felt less threatening. The VR sessions helped her shift attention away from the pain, reducing the “alarm” response in her brain. The wearable showed spikes in tension before flare ups, helping her intervene early. The app revealed consistent patterns stress, poor sleep, and long work sessions transforming what once felt random into something understandable and predictable. As Elena’s understanding changed, her perception changed. Pain episodes felt less catastrophic, shorter, and easier to manage. Technology didn’t eliminate her pain it altered the way her brain interpreted it, giving her a sense of agency she hadn’t felt in years. {{RoundBoxBottom}} *Technology-based pain interventions are receiving increasing research attention across healthcare settings, including postoperative care, rehabilitation, and labour wards (Musters et al., 2023; Yang et al., 2023).The pain technology market is projected to increase by '''USD $70.2 billion''' over the 10 years ( online forcast ask in next session). Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems help individuals regulate physiological arousal.Virtual reality can redirect attention away from pain, TENS devices can modulate pain-signal transmission, and biofeedback systems can help individuals regulate physiological arousal. Wearables, mobile applications, and telehealth platforms are also becoming more widely used, giving people accessible ways to track pain patterns and engage in self-management (Green & Chakravarthy, 2025; Li et al., 2024). Technology has therefore become increasingly influential in how pain is monitored, interpreted and managed across healthcare. For people with chronic pain, catastrophic thoughts and fear of further pain or injury may lead to avoidance of movement and meaningful activities, contributing to reduced functioning and increased distress (Gatchel, 2016; Vlaeyen & Linton, 2000). This chapter explores how technology-based interventions may interrupt this cycle by influencing pain signals, attention, emotions, thoughts, motivation and perceived control. {{RoundBoxTop|theme=2}} '''Focus questions''' {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} •How does technology alter the way people perceive and respond to pain? •How do psychological processes such as attention, emotion and cognitive appraisal contribute to technology-based pain management? •How do different technologies influence people's sense of control, engagement and motivation when managing pain? {{RoundBoxBottom}} == Understanding pain perception and management == Pain is not determined solely by physical injury. It is a personal sensory and emotional experience influenced by biological, psychological and social factors (Raja et al., 2020). Understanding the distinction between pain and nociception helps explain why technology can change a person’s pain experience even when it does not remove the original injury or health condition. Pain perception is shaped by how the brain interprets nociceptive signals alongside attention, emotions, memories, beliefs, expectations and the surrounding context (Bushnell et al., 2013; Tracey & Mantyh, 2007). Technology can alter this interpretation by redirecting attention, regulating physiological arousal, modifying pain-signal transmission or changing catastrophic thoughts about pain. It may also influence how a person responds by encouraging movement, coping and active self-management rather than fear and avoidance. Technology can therefore reduce the intensity, unpleasantness or perceived threat of pain while supporting greater confidence and control over pain-management behaviour. === Pain and nociception === * [[w:Pain|Pain]] is an unpleasant sensory and emotional experience associated with, or resembling an experience associated with, actual or potential tissue damage (Raja,2020). * Pain is personal and can be influenced by biological, psychological and social factors. * Nociception as the nervous system’s detection and processing of potentially harmful stimuli. * Pain and nociception are related but are not identical. * Nociception can occur without a conscious experience of pain and that pain may sometimes continue without clear evidence of current tissue damage (Basbaum ,2009; Raja ,2020). * Relate this distinction to technology by explaining that a tool may change a person’s pain experience without removing the original injury or condition. === Physiology of pain and pain perception === * Nociceptors detect potentially harmful mechanical, chemical or temperature-related stimuli and convert them into electrical signals. * Refer to these signals travelling through peripheral nerves to the spinal cord and then through ascending pathways to the brain (Basbaum,2009). * The brain interprets nociceptive information alongside attention, emotions, memories, beliefs, expectations and context. * The sensory dimension identifying the location and intensity of pain, while emotional, cognitive and motivational processes influence its unpleasantness, meaning and the person’s response. * Descending pathways from the brain can increase or reduce pain-signal transmission (Tracey & Mantyh, 2007). * Pain is not a direct measurement of tissue damage. Therefore, the same stimulus may be experienced differently by different people or by the same person in different situations (Bushnell,2013). * Relate this process to technology by introducing TENS as a tool that may modulate pain-signal transmission and VR as a tool that may change attention and the brain’s interpretation of pain. === Chronic pain and avoidance === [[File:Pain cycle.jpg|thumb|326x326px|'''Figure 2'''. The avoidance pain [https://pmc.ncbi.nlm.nih.gov/articles/PMC3820295/ cycle]]] * Chronic pain is pain that persists or recurs for longer than three months. * Chronic pain may affect attention, memory, mood, sleep, motivation, relationships and participation in daily activities. * Refer to increased attention towards bodily sensations and possible signs of pain. * Pain catastrophising as an exaggerated negative interpretation in which a person believes pain will be unbearable, uncontrollable or a sign of serious harm. * Fear-avoidance model. * Catastrophic interpretations can produce fear of pain, movement or reinjury. * Fear may lead the person to avoid physical activity, work, social activities and other meaningful experiences. * Avoidance can provide short-term relief from fear but may contribute to reduced activity, lower confidence, disability and emotional distress over time (Gatchel,2016; Vlaeyen & Linton, 2000). * '''See Figure 2''' One The Avoidance Pain Cyle === Understanding pain management === * Pain management as strategies used to reduce pain, distress and interference with daily life. * Chronic pain management may improve coping, functioning and participation without completely eliminating pain. * Refer to the biopsychosocial approach, which considers biological, psychological and social influences on pain (Raja, 2020). * Technology may support pain management through symptom monitoring, coping strategies and improved access to care (Li,2024). == How does technology alter pain perception? == {{ic|Include an introductory paragraph before branching into sub-sections}} === VR and attention modulation === * Refer to VR immerse user effecting attention - Limited capacity theory of attention (de Araujo, Zeferino, & Galas, 2026) === Biofeedback and autonomic regulation === *How biofeedback provides information about physiological pain responses, enabling users to practise regulating these responses and develop greater control over their pain experience. Related to self-regulation theory (Arsenault,2013). === Cognitive Digital CBT and ACT tools === * How CBT can modify unhelpful pain-related thoughts and behaviours, while ACT can increase pain acceptance and engagement in valued activities. These processes may reduce distress and improve functioning even when pain is not eliminated. Related - to cognitive appraisal theory and the psychological flexibility mode'''l''' (Hysing,2017; Neblett,2016).- Beneficial for catastrophic thinking, === Wearable sensors === * Wearable systems that collect pain ratings, adherence information and physiological data to personalise treatment and help users identify patterns in their pain. Related to self-regulation theory, particularly monitoring, feedback and behavioural adjustment (Green & Chakravarthy, 2025). === TENS === * Low-voltage electrical stimulation activating non-painful sensory fibres and reducing the transmission of pain signals. Relate this to gate control theory and endogenous pain inhibition (Blincoe,2007; Green & Chakravarthy,2025). === Telehealth and remote monitoring === * Clinicians monitoring pain ratings, treatment use and progress from a distance. Feedback and support may improve confidence, access and treatment adjustment. Relate this to self-efficacy and self-regulation (Green & Chakravarthy,2025). === Mobile applications === * Apps recording pain ratings, showing patterns, providing education or coping activities, and reminding users to practise pain-management strategies. Relate this to self-regulation theory. A dedicated mobile pain-application study is still required. == Psychological theories behind technology‑based pain management == * '''Psychological theories behind technology‑based pain management:'''Technology‑based pain interventions draw on established psychological theories explaining how cognition, emotion, attention and behaviour shape pain perception. These mechanisms help explain how tools such as VR, wearables and AI‑guided apps influence pain experience (Gatchel et al., 2007; Eccleston & Crombez, 1999). * '''Biopsychosocial model of pain:'''The biopsychosocial model proposes that pain arises from interactions between biological processes, psychological factors and social context. Technology‑based interventions align with this model by targeting multiple domains simultaneously, such as emotional regulation, behavioural change and physiological monitoring (Gatchel et al., 2007; Williams & Craig, 2016). * '''Limited‑capacity theory of attention:'''Pain captures limited attentional resources, increasing perceived intensity. VR and immersive technologies reduce pain by redirecting attention away from nociceptive input, supporting the theory’s predictions (Eccleston & Crombez, 1999; Malloy & Milling, 2010). * '''Gate control theory of pain:'''Gate control theory suggests that cognitive and emotional factors modulate nociceptive signals at the spinal level. Technologies such as TENS, VR and biofeedback influence these gates by altering attention and emotional state (Melzack & Wall, 1965; Moayedi & Davis, 2013). * '''Neuromodulation and neuroplasticity:'''Pain perception is shaped by dynamic neural networks that reorganise with experience. VR, neurofeedback and AI‑guided training promote adaptive neuroplasticity by reducing maladaptive signalling and strengthening regulatory pathways (Apkarian et al., 2009; Kutch & Apkarian, 2018). * '''Self‑regulation theory:'''Self‑regulation theory emphasises managing thoughts, emotions and behaviours to achieve desired outcomes. Technology‑based pain tools enhance self‑regulation through real‑time feedback, guided breathing and emotional tracking (Karoly, 1993; Jensen et al., 2014). * '''Operant conditioning:'''Pain behaviours can be reinforced by environmental responses. Technology‑based interventions apply operant principles by rewarding adaptive behaviours such as movement, pacing and relaxation (Fordyce, 1976; Vlaeyen & Linton, 2000). * '''Fear‑avoidance model of pain:'''Fear of pain leads to avoidance, deconditioning and increased disability. Graded VR exposure and movement‑tracking apps reduce fear by providing safe exposure and positive reinforcement (Vlaeyen & Linton, 2000; Crombez et al., 2012). * '''Cognitive appraisal and reframing:'''Pain intensity is influenced by how individuals interpret symptoms. Digital CBT tools help reframe catastrophic thoughts, reduce threat appraisal and promote adaptive interpretations of pain (Lazarus & Folkman, 1984; Turk & Wilson, 2010). * '''Psychological flexibility model:'''Psychological flexibility involves adapting behaviour in alignment with values despite discomfort. ACT‑based digital interventions enhance flexibility through acceptance, present‑moment awareness and committed action (Hayes et al., 2012; Trompetter et al., 2016). * '''Social cognitive theory and self‑efficacy:'''Self‑efficacy predicts pain coping and functional outcomes. Technology‑based interventions increase self‑efficacy through mastery experiences, modelling and feedback (Bandura, 1997; Jackson et al., 2014). * '''Affective‑motivational modulation of pain:'''Pain is shaped by emotional and motivational states such as fear, anxiety and goal orientation. Negative affect amplifies pain through enhanced salience and descending facilitation, while positive affect reduces pain via prefrontal‑limbic modulation. Technologies such as VR, AI‑guided relaxation and biofeedback apps modulate affective‑motivational systems by reducing threat cues and enhancing emotional regulation (Modernell et al., 2026; Vervoort & Trost, 2018; Garcia‑Larrea & Fauchon, 2023; ''Current Opinion in Psychology'', 2025). == Applications and tools == [[File:Pain pathway diagram showing transduction, transmission, modulation, and perception.png|thumb|293x293px|Figure 2: Brain Pain Pathways ]] * VR * TENS * Mobile apps * Wearables * Gamification * Telehealth == Future Applications and Emerging Technologies == * List Of Various Cutting edge * Emerging technologies * futuristics applications == Limitations and ethical considerations == * Effectiveness differs between users, technologies and pain conditions. * Refer to barriers including cost, access, digital skills and user engagement (Li,2024). * Possible side effects, privacy concerns and increased attention to symptoms. ==Learning features== '''Table 1''' See The Summary Table below : {{ic|Provide a more descriptive caption}} {| class="wikitable" style="margin: auto; |- ! Technology !! How it alters pain perception !! Theory / Model |- | VR || Redirects attention || Limited-capacity attention |- | TENS || Modulates pain signals || Gate control theory |- |Biofeedback |Support regulation of arousal |Self-regulation, conditioning |- |CBT/ACT tools |Changes to coping, appraisal and avoidance |Fear avoidance, flexibility |- |Wearables/apps |Records patterns and provides feedback |Self-regulation |- |Telehealth |Remote support, health access and treatment |Self-efficacy |} ;Quizzes * Why might VR reduce the amount of attention given to pain? See: * Which theory best explains how TENS may reduce pain-signal transmission? * How can feedback from a wearable device support self-regulation? * How might catastrophic thinking contribute to the fear-avoidance cycle? <quiz display="simple"> {Virtual reality (VR) can reduce pain by redirecting a person’s attention away from painful stimuli?: |type="()"} + True - False {TENS devices work by increasing the intensity of pain signals sent to the brain. Answer?: |type="()"} - True + False </quiz> ==Conclusion== * Pain is interpreted by the brain and is influenced by attention, emotion, appraisal, behaviour and social support, not only by signals from the body. * Different technologies alter pain perception through different pathways: VR redirects attention, TENS modulates signals, and feedback or cognitive tools influence arousal, appraisal and control. * Technology is most useful as part of individualised, biopsychosocial pain management rather than as a replacement for all existing care (Hysing,2017; Li,2024). * Effectiveness depends on the user, pain condition, technology, level of support and quality of available evidence. {{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== [[wikipedia:Virtual_reality_therapy|Virtual reality therapy]] (Wikipedia) [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * https://en.wikipedia.org/wiki/Pain {{ic|Create internal link}} * https://en.wikipedia.org/wiki/Virtual_reality {{ic|Create internal link}} * [[Motivation and emotion/Book/2021/Self-regulation|Self-regulation]] (Book chapter, 2021) * [[wikipedia:Transcutaneous_electrical_nerve_stimulation|Transcutaneous electrical nerve stimulation]] (Wikipedia) * [[wikipedia:Cognitive_behavioral_therapy|Cognitive behavioral therapy]] (Wikipedia) * [[wikipedia:Biopsychosocial_model|Biopsychosocial model]] (Wikipedia) * [[wikipedia:Gate_control_theory|Gate control theory]] (Wikipedia) {{tip|Suggestions for this section: * Only select links to major internal resources about the topic * Include the source in parentheses }} ==References== This section lists the cited references in [[w:APA style|APA style]] (7th ed.) or [[w:Wikipedia:Citing sources|wiki style]]. {{Hanging indent|1= }} * Musters, A., Vandevenne, A. 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''Neuroscience, 231'', 102–110. <nowiki>https://doi.org/10.1016/j.neuroscience.2012.11.039</nowiki> * Hysing, E.-B., Smith, L., Thulin, M., Karlsten, R., & Gordh, T. (2017). Detection of systemic inflammation in severely impaired chronic pain patients, and effects of a CBT-ACT-based multi-modal pain rehabilitation program. ''Scandinavian Journal of Pain, 16'', 175. <nowiki>https://doi.org/10.1016/j.sjpain.2017.04.033</nowiki> * Neblett, R., Mayer, T. G., Hartzell, M. M., Williams, M. J., & Gatchel, R. J. (2016). The Fear-Avoidance Components Scale (FACS): Development and psychometric evaluation of a new measure of pain-related fear avoidance. ''Pain Practice, 16''(4), 435–450. <nowiki>https://doi.org/10.1111/papr.12333</nowiki> * Blincoe, A. J. (2007). TENS machines and their use in managing labour pain. ''British Journal of Midwifery, 15''(8), 516–519. * Gatchel, R. J., Peng, Y. B., Peters, M. L., Fuchs, P. N., & Turk, D. C. (2007). The biopsychosocial approach to chronic pain: Scientific advances and future directions. ''Psychological Bulletin, 133''(4), 581–624. <nowiki>https://doi.org/10.1037/0033-2909.133.4.581</nowiki> * Eccleston, C., & Crombez, G. (1999). Pain demands attention: A cognitive-affective model of the interruptive function of pain. ''Psychological Bulletin, 125''(3), 356–366. <nowiki>https://doi.org/10.1037/0033-2909.125.3.356</nowiki> * Williams, A. C. de C., & Craig, K. D. (2016). Updating the definition of pain. ''Pain, 157''(11), 2420–2423. <nowiki>https://doi.org/10.1097/j.pain.0000000000000613</nowiki> * Malloy, K. M., & Milling, L. S. (2010). The effectiveness of virtual reality distraction for pain reduction: A systematic review. ''Clinical Psychology Review, 30''(8), 1011–1018. <nowiki>https://doi.org/10.1016/j.cpr.2010.07.001</nowiki> * Melzack, R., & Wall, P. D. (1965). Pain mechanisms: A new theory. ''Science, 150''(3699), 971–979. <nowiki>https://doi.org/10.1126/science.150.3699.971</nowiki> * Moayedi, M., & Davis, K. D. (2013). Theories of pain: From specificity to gate control. ''Journal of Neurophysiology, 109''(1), 5–12. <nowiki>https://doi.org/10.1152/jn.00457.2012</nowiki> * Apkarian, A. V., Baliki, M. N., & Geha, P. Y. (2009). Towards a theory of chronic pain. ''Progress in Neurobiology, 87''(2), 81–97. <nowiki>https://doi.org/10.1016/j.pneurobio.2008.09.018</nowiki> * Kutch, J. J., & Apkarian, A. V. (2018). Potential mechanisms underlying centralized pain and emerging therapeutic interventions. ''Frontiers in Cellular Neuroscience, 12'', Article 35. <nowiki>https://doi.org/10.3389/fncel.2018.00035</nowiki> * Karoly, P. (1993). Mechanisms of self-regulation: A systems view. ''Annual Review of Psychology, 44'', 23–52. <nowiki>https://doi.org/10.1146/annurev.ps.44.020193.000323</nowiki> * Hamilton, N. A., Karoly, P., & Kitzman, H. (2004). Self-regulation and chronic pain: The role of emotion. ''Cognitive Therapy and Research, 28''(5), 559–576. <nowiki>https://doi.org/10.1023/B:COTR.0000045565.88145.76</nowiki> * Fordyce, W. E. (1976). ''Behavioral methods for chronic pain and illness''. Mosby. * Crombez, G., Eccleston, C., Van Damme, S., Vlaeyen, J. W. S., & Karoly, P. (2012). Fear-avoidance model of chronic pain: The next generation. ''Clinical Journal of Pain, 28''(6), 475–483. <nowiki>https://doi.org/10.1097/AJP.0b013e3182385392</nowiki> * Lazarus, R. S., & Folkman, S. (1984). ''Stress, appraisal, and coping''. Springer. * Turk, D. C., & Wilson, H. D. (2010). Fear of pain as a prognostic factor in chronic pain: Conceptual models, assessment, and treatment implications. ''Current Pain and Headache Reports, 14''(2), 88–95. <nowiki>https://doi.org/10.1007/s11916-010-0094-x</nowiki> * Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). ''Acceptance and commitment therapy: The process and practice of mindful change'' (2nd ed.). Guilford Press. * Veehof, M. M., Trompetter, H. R., Bohlmeijer, E. T., & Schreurs, K. M. G. (2016). Acceptance- and mindfulness-based interventions for the treatment of chronic pain: A meta-analytic review. ''Cognitive Behaviour Therapy, 45''(1), 5–31. <nowiki>https://doi.org/10.1080/16506073.2015.1098724</nowiki> * Bandura, A. (1997). ''Self-efficacy: The exercise of control''. W. H. Freeman. * Jackson, T., Wang, Y., Wang, Y., & Fan, H. (2014). Self-efficacy and chronic pain outcomes: A meta-analytic review. ''The Journal of Pain, 15''(8), 800–814. <nowiki>https://doi.org/10.1016/j.jpain.2014.05.002</nowiki> * Modernell, L. M., Faillenot, I., Garcia-Larrea, L., & Fauchon, C. (2026). The multifaceted neural architecture of pain modulation by emotion and cognition: A systematic review and meta-analysis. ''British Journal of Anaesthesia, 136''(6), 1894–1909. <nowiki>https://doi.org/10.1016/j.bja.2026.03.015</nowiki> * Vervoort, T., & Trost, Z. (2018). An affective-motivational account of interpersonal dynamics in pain. In T. Vervoort, K. Karos, Z. Trost, & K. M. Prkachin (Eds.), ''Social and interpersonal dynamics in pain: We don’t suffer alone'' (pp. 57–75). Springer. <nowiki>https://doi.org/10.1007/978-3-319-78340-6_4</nowiki> * Boersma, K., & Flink, I. K. (2025). Key aspects concerning the role of emotion in the chronic pain experience. ''Current Opinion in Psychology, 62'', Article 102000. <nowiki>https://doi.org/10.1016/j.copsyc.2025.102000</nowiki> {{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== * https://www.iasp-pain.org/resources/terminology/ * https://www.qld.gov.au/health/services/specialists/persistent-pain/understanding-pain/managing-your-pain * https://aci.health.nsw.gov.au/chronic-pain/painbytes/pain-and-mind-body-connection {{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/Pain]] [[Category:Motivation and emotion/Book/Technology]] b317tizo2meqaale6ll9t8uzvmbajiu 0 331110 2835133 2833365 2026-09-30T08:12:02Z U3254168 3106320 made suggestions for inserting references throughout 2835133 wikitext text/x-wiki {{title|Moral disgust and jury decision-making: How does moral disgust impact jurors' judgements of guilt, blame, and punishment?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} [[File:Trial by Jury - Chaos in the Courtroom.png | thumb | right | 250px |'''Figure 1'''. A jury is a group of sworn individuals who determine a defendant's guilt. ]] Consider sitting on a jury. The defendant appears composed, well-dressed, and speaks clearly. Someone like this couldn't have done anything bad — that's your instinct. Then you hear the charge: embezzlement. Over three years, they quietly transferred company funds to a personal account. Thousands of dollars were spent, and real people were harmed. You are angry. It's wrong. However, it does not make you feel sick. Consider the same composed defendant in the same courtroom, but this time the charge is posing as a charity volunteer to gain the trust of dying hospice patients before stealing the donations intended for their care. The financial loss is the same as the embezzlement case. Same amount, same number of victims. But something else arises in you. Not just anger, but more of a revulsion, as if something was contaminated. This doesn't simply feel like a crime. It has an unclean feeling to it. The same defendant. Same harm. So, why does one case make you feel cold and angry, while the other makes your skin crawl? And, aside from the actual harm done, could that visceral reaction be influencing how harshly you believe they should be punished? {{RoundBoxBottom}} It is the law that [https://www.monash.edu/law/news-and-events/news/2020/juries-why-do-we-actually-need-them-and-can-they-get-it-wrong jurors] {{ic|The law varies by jurisdiction; write for an international audience; Australians represent ~.3% of the world human population}} {{ic|Move external links to the External links section}} must base their verdicts on the facts of a case {{citation needed}}. But moral disgust, an emotional gut reaction, seems to influence how jurors assess guilt, blame and punishment, regardless of the strength of the evidence presented {{citation needed}}. A disgusted juror might unconsciously become more certain of guilt, assign more blame and suggest harsher punishment, regardless of what the facts actually establish. If disgust always biases judgements and sentences in one direction or the other, no matter how strong a case is, the implications are profound: wrongful convictions, disproportionate sentencing, and differences in the punishment of similar crimes depending on how “disgusting” the evidence seems, rather than the true seriousness of the crime {{long}}. It also raises questions for current legal practices: courts commonly admit gruesome evidence under the assumption that its evidentiary value outweighs its emotional impact, an assumption this body of research directly undermines {{citation needed}}. Psychological science provides the legal system with something it cannot produce itself: controlled empirical evidence about the nature and causes of this bias {{citation needed}}. It shows not only that jurors appear to be affected by emotion but also the processes (appraisal patterns, purity vs. harm, violations, and individual differences such as private body consciousness) that determine when and for whom the effect is strongest {{citation needed}}. This template provides key headings, examples, and tips for each section. Gradually remove this generic information as the chapter develops. It is OK to retain some of the template material for the topic development, but it should all be removed for the final book chapter. Key resources: * [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 02]] explains about how to edit * [[Motivation and emotion/Assessment/Topic|Topic development guidelines]] * [[Motivation and emotion/Assessment/Chapter|Book chapter guidelines]] {{RoundBoxTop|theme=3}} '''Focus questions''' *If disgust can make moral judgements more severe, even when it’s incidental to the act being judged, what does that say about the reliability of human moral reasoning? *Can moral disgust be used by the legal system? {{ic|Use open-ended questions}} *How might a juror's own sensitivity to physiological sensations of disgust impact how vulnerable they are to disgust-driven bias? *How can psychological theories be used to mitigate risks of bias in the legal system? {{RoundBoxBottom}} == What is Moral Disgust? == {{ic|Include at least an introductory paragraph before branching into sub-headings}} === Disgust === [[w:Disgust|Disgust]] is one of the six universal emotions that humans experience and can be visually recognised on a person's face {{citation needed}}. The emotion of disgust is theorised to have originated from a biological protective mechanism to protect an organism from harm that may be brought on by food or poison {{citation needed}}. Disgust has evolved to become an emotion/behaviour directed at anything that may potentially cause harm or disease. For example, * body products * animals * hygiene * body violations, death or disease {{citation needed}} Paul Ekman proposed six basic emotions in his literature based on the theories that these emotions, across research all over the world, concluded in agreement on six emotions: happiness, surprise, fear, anger, sadness and disgust. Therefore, he proposed that the universality of these findings and the facial expression alone could conclude that there are 6 basic emotions (Ekman, 1992). === Moral Disgust === Moral disgust refers to the emotional response a person feels when their social or cultural norms are transgressed, therefore resulting in a reaction {{citation needed}}. Moral disgust is complex, and there is varying evidence for and against its genuine purpose as an emotion. Researchers argue that moral disgust is a metaphorical extension of physical disgust; shared facial expression, language, etc {{citation needed}}. Other researchers argue that it's functionally unique to traditional, physical disgust {{citation needed}}. It does not reliably trigger the same physiological processes: facial muscle activation, nausea, etc. (Chapman et al., 2012). Moral disgust is triggered by acts that are supposedly a violation of an individual's perceived purity or dignity {{citation needed}}. For example, betraying someone's trust (cheating on a partner) or exploiting a vulnerable person (as mentioned in the scenario at the start). Rozin et al. (1999) proposed a theory that moral disgust specifically clusters around violations of a person's divinity or purity. This is different from anger, which generally clusters around autonomy violations, also opposed to contempt, which clusters around community violations. This distinction is vital when discussing emotion for jurors. If moral disgust behaves differently from physical disgust, it may influence judgement in the courtroom through a different pathway than a simple reaction to physically disgusting evidence. Russell & {{ic|Use APA style for citations}} Giner-Sorolla (2013) discuss four competing arguments of disgust's role in moral condemnation. Firstly, the most flexible view of moral disgust that can be applied widely for many crimes is the general morality position. It claims that disgust is an all-purpose emotion which is seen through different kinds of moral disapproval, not just a narrow category. Secondly, disgust as a violation of bodily and spiritual purity is more specific. As mentioned prior, this claim is supported by Rozin's CAD (contempt, anger, disgust) triad. The third argument proposes that moral disgust is only a metaphor. The true emotion being experienced is anger, and individuals just use language as a metaphor (e.g., "that's disgusting") for how condemning they feel. Finally, Russell & Ginger-Sorolla's own claim for moral disgust is a middle ground for all the arguments in their research. Regardless of whether harm or justice is involved, they contend that disgust specifically tracks violations pertaining to the body and its products. Anger tends to co-occur with violations that are specifically related to justice, harm, or rights. This disgust behaves more like anger wearing the vocabulary of disgust than it does like bodily moral disgust. One study involved 148 participants ranking their emotions on a scale {{citation needed}}. It was found that moral disgust elicited as much as physical disgust did, which supports a claim that moral disgust is not a watered-down, metaphorical use of the feeling but a genuine, physical feeling of disgust. It was also revealed that moral disgust uniquely triggered a significantly higher feeling of mental contamination (feeling immoral) than core disgust did. This reveals an internalised feeling about your own moral state just from witnessing an immoral act, which ties back to Russell & Giner-Sorolla's bodily-violation pattern and strengthens Rozin et al.'s (1999) definition of moral disgust. This empirical study is evidence that core disgust attaches to bodily violations whilst non-bodily violations. If people respond to contact with an immoral person in a psychologically contaminating way — wanting distance, feeling “dirtied” by proximity — then a question arises about whether jurors exposed to a defendant’s morally disgusting conduct might respond in a similar contamination mode, thus influencing their desire to symbolically “cleanse” the situation via a harsher verdict or sentence. <quiz display="simple"> {Moral disgust and physical disgust are the same emotion: |type="()"} - True + False </quiz> == Psychological Science in the Legal System == * [[Motivation and emotion/Book/2019/Criminal record stigma and emotion#Relevant theories|What psychological theories are present in the legal system]] {{expand}} === Social Identity Theory === Classic social identity theory posits that groups and whole organisations that possess the same cultural and social norms will have perceive themselves as sharing something in common {{citation needed}}. This adds to their own personal self-concept as an individual and as a member of a society/societies. Bronewasser & Bober (1987) argue that this theory describes a class or collective of people (people who may share traits but have no real interdependence) but not a genuine societal group. Groups depend on structure; roles, positions and relationships that require dependence from people. Through this theory, a jury is considered to be a genuine structured group. There are roles, a task and an interdependence through deliberation. This theory may offer a further point on why moral disgust may bias jurors. Moral disgust can function as a social categorisation cue, marking defendants as the out-group rather than in the jury's moral in-group. Bronewasser & Bober claim that even arbitary group labels are enough to produce an in-group favouritism and out-group favouritism. If a defendants act triggers moral disgust, this may mark them as being in the moral "outgroup" in a jurors mind. Independent of the actual evidence being presented, this compounds moral disgust biases. *social identity theory **a theory that posits that whole organisations and groups that possess the same cultural and social norms will all have similar self-concepts (Bornewasser & Bober, 1987). **The theory predicts that behaviours from this group will often be similar due to their similar self-concept. *[[w:Appraisal_theory|appraisal theory of emotion]] **appraisal theory of emotion is theory that specific emotions are extracted from evaluations of events which in turn impact a reaction which may differ depending on certain people. *evolutionary theory of emotion **this theory describes our emotions and reactions being biological reactions to stimuli. ***for example, disgust has come from protecting oneself from poisons. == Disgust as a Legally Relevant Emotion == * Disgust should not be seen as legally relevant, as that would be a personal bias. * How can you create a courtroom that is free from bias if you do not take into account the impact of disgust? * Maybe disgust shouldn't be seen as an impacting emotion but rather a factor that needs to be considered when a jury is shown pictures, footage, and witness statements in court. === Arguments For === * Patrick Devlin's belief that we should allow some degree of the shared morality view of society through emotions {{citation needed}} ** Within society, when crimes are viewed as "disgusting" or cause widespread intolerance, there is an importance to the intervention of the legal system (Lacey, 2023). * Informing the "Reasonable Person" Standard ** This is a theory that jurors will judge acts (particularly those involving negligence or abuse) based on what they believe they would have done in that situation. Or more accurately to the theory, what would a reasonably prudent person (RPP) have done (Alicke & Weigel, 2021)? === Arguments Against === * [[wikipedia:Harm_principle|harm principle limitation]] ** Developed by John Stuart Mills, the harm principle limitation states the following: ** "The only purpose for which power can be rightfully exercised over any member of a civilised community, against his will, is to prevent harm to others." [[wikisource:On_Liberty/Chapter_1|(Mill, 1869).]] ** This principle bars people within the legal system from criminalising an action because it makes most people feel moral disgust. * a tool for discrimination ** Historically, moral disgust has been a tool against those being charged with crimes of homosexuality and interracial marriages. == Moral Disgust and Juror Judgements == A jury is a group of 12 individuals that are carefully chosen to determine the guilt of an offender{{fact}} {{ic|Don't juries vary in size, depending on the juridstiction?}}. They are picked to be impartial, unbiased opinions that can aid in the determining of a person's guilt. Jurors are asked to make judgements based on the evidence presented to them in court. However, emotions play a large, unsuspecting role in determining the guilt of a person. Such is the reason why, in high-stakes cases, jurors are not allowed contact with the outside world or media during trials. Moral disgust in particular seems to have a large impact on the way that jurors perceive and shape jurors' judgements. Different emotions elicit different reactions based on the emotion and a person's appraisal patterns.{{fact}} === Emotional Response Patterns === Fishbein & Ajzen's (1975) expectancy-value model states that a person's given attitude towards an object is a direct function of the value that a person attaches to that object's attributes or outcomes. In explicit terms, a person's value on an object will be a direct function of the value that they place on said item and the positive or negative emotions they associate with it. Furthermore, the positive or negative characteristics that they associate with the object will be a weighted decision on the direct outcome that may occur due to the object. In a review of the role of emotion-induced expectancies, Desteno et al. (2004) argue that positive and negative emotions have been grouped together and oversimplified, which makes distinguishing them difficult. The studies found that specificity operates through an emotion-matching process. Whilst the study did not touch on disgust specifically, it found that persuasion about a situation increased when a person's current emotional state matched the emotional framing of a message. The broader emotion-specificity principle suggests a comparable mechanism that may apply to disgust. Older discourse has allowed for all emotions to be pushed into one category, but not all emotions push judgement in the same direction. Emotional appraisal patterns are the specific mental evaluations that an individual's brain makes about an event to determine how they feel about a situation. INSERT TABLE HERE W/ EVIDENCE == Moderating Factors == * private body consciousness ** people who are more prone to experience their private bodily sensations show stronger disgust-driven bias *** An experiment conducted by Schnall et al. (2008) revealed that people who were more aware of their Private Body Consciousness (PBC) were more prone to feelings of disgust and expressing these feelings outwards to the situation at hand. * type of violation ** purity vs harm == Practical Implications == * evidentiary admissibility ** courts allow for the admission of gruesome photographic evidence but findings suggest this may be wrong *** research shows that people view crimes harsher if exposed to gruesome photos *** Additionally, Bright & Goodman-Delahunty's (2006) research discusses a person's use of their inner emotional states as a way to reason with information they are being given. *** In their affective influences model, affect is a judgement-simplifying heuristic device. People generally consult their affective state, meaning they consult their inner emotion to infer a judgement before looking at the facts. * jury selection * how evidence is presented ==Figures== [[File:Thought bubble.svg|right|140px|thumb|'''Figure 2'''. Example of an image with a descriptive caption.]] * 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": ==Conclusion== * What does this mean going further {{vague}} * What would future research benefit from in this specific section? *Moral disgust does not come with jurors' judgements, but rather it can measurably shift guilt, certainty, blame attribution and punishment severity. *This may be stronger for certain people; it cannot just be a blanket claim for all jurors. *The idea that jurors decide on the basis of facts alone is not psychologically sustainable. The practice of law {{ic|The practice of law goes beyond the target topic}} needs to consider this, rather than seeing emotions as a bias. * The Conclusion is arguably the most important section * 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: * [[Motivation and emotion/Book/About/Collaborative authoring using wiki|Collaborative authoring using wiki]] (Wikiversity) * [[Motivation and emotion/Book/2021/Light triad|Light triad]] (Book chapter, 2021) * [[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= Alicke, M. D., & Weigel, S. H. (2021). The reasonable person standard: Psychological and legal perspectives. Annual Review of Law and Social Science, 17(1), 123–138. Bornewasser, M., & Bober, J. (1987). Individual, social group and intergroup behaviour. Some conceptual remarks on the social identity theory. European Journal of Social Psychology, 17(3), 267–276. https://doi-org.ezproxy.canberra.edu.au/10.1002/ejsp.2420170303 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 Chapman, H. A., & Anderson, A. K. (2012). Understanding disgust. Annals of the New York Academy of Sciences, 1251(1), 62–76. https://doi.org/10.1111/j.1749-6632.2011.06369.x  DeSteno, D., Petty, R. E., Rucker, D. D., Wegener, D. T., & Braverman, J. (2004). Discrete emotions and persuasion: The role of emotion-induced expectancies. Journal of Personality and Social Psychology, 86(1), 43–56. https://doi.org/10.1037/0022-3514.86.1.43 Ekman, P. (1992). Are there basic emotions? Psychological Review, 99(3), 550–553. https://doi.org/10.1037/0033-295X.99.3.550 Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: an introduction to theory and research. Addison-Wesley Pub. Co. Lacey, N. (2023). Patrick Devlin, The enforcement of morals (1965). In [Book title] (1st ed.). Routledge. https://doi.org/10.4324/9781003193982-5 Russell, P. S., & Giner-Sorolla, R. (2013). Bodily moral disgust: What it is, how it is different from anger, and why it is an unreasoned emotion. Psychological Bulletin, 139(2), 328–351. https://doi-org.ezproxy.canberra.edu.au/10.1037/a0029319 Schnall, S., Haidt, J., Clore, G. L., & Jordan, A. H. (2008). Disgust as embodied moral judgment. Personality and Social Psychology Bulletin, 34(8), 1096–1109. https://doi.org/10.1177/0146167208317771 {{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/watch?v=u-TmKo75gJI How Disgust Shapes our Thoughts on Moral Wrong & the Political Right] (David Pizzaro) {{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/Disgust]] [[Category:Motivation and emotion/Book/Morality]] [[Category:Motivation and emotion/Book/Legal]] s4vo4loeful2yt4v50poy0eh82qsd7s 0 331141 2835043 2831464 2026-09-29T13:28:21Z JSINST 3110286 Undo all revisions. Resource is empty, but not [[Wikiversity:Deletion policy|deleted]]. 2835043 wikitext text/x-wiki phoiac9h4m842xq45sp7s6u21eteeq1 0 331149 2835136 2834642 2026-09-30T08:42:40Z U3254168 3106320 /* Empathy with defendants */ 2835136 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{{g}} reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors{{g}} 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 defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Titchener, 1909; 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 == * Evidence of the influence of victim impact statements is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced 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. * Having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). * Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). * Jurors are more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). <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) findings may be explained by attribution theory (Kelley & Michela, 1980). 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 (INSERT REFERENCE). * 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). <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 cause 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 empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasis 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 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 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]] m33gobqnvokhxzljij1xf6heccubl4j 2835137 2835136 2026-09-30T08:43:20Z U3254168 3106320 /* References */ 2835137 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{{g}} reasoning and in particular, verdict decisions. This is essential to understand as if empathy influences juror decision-making, then this will impact jurors{{g}} 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 defined empathy as a process of projecting oneself into what one observes, or in colloquial terms "putting yourself into someone else's shoes" (Titchener, 1909; 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 == * Evidence of the influence of victim impact statements is inconsistent. In studies conducted by Myers et al. (2002) and Luginbuhl & Burkhad (1995), victim impact statements influenced 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. * Having similar experiences to victims, such as sexual abuse, leads to higher empathy, a higher likelihood of finding the defendant guilty and harsher sentences (Kahhale et al., 2026). * Having empathy with victims can lead to a higher emphasis on the harm suffered, and less notice taken of mitigating factors (Bandes, 1996). * Jurors are more likely to feel empathy towards the victim when shown gruesome and graphic images (Bright & Goodman-Delahunty, 2006; Phalen at al., 2021). <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) findings may be explained by attribution theory (Kelley & Michela, 1980). 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 (INSERT REFERENCE). * 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). <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 cause 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 empathy (Bright & Goodman-Delahunty, 2006; Kahhale et al., 2026). When jurors feel empathy towards victims, they are more likely to emphasis 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]] 0nj5lh864mtlxvhbzar5r0dm24inf4z 2 331218 2835084 2834788 2026-09-30T00:35:25Z StretchBeyond 3105744 2835084 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] q52w17xyl6ef6ojpzng428f9t9r5r4b 0 331262 2835091 2834782 2026-09-30T02:13:31Z U3228742 3005570 /* The dark tetrad */ updates to include citations 2835091 wikitext text/x-wiki {{title|Dark empathy:<br>What is dark empathy, what are its consequences, and what can be done to address it?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}}{{ic|Make it more clear how this connects to dark empathy}} Imagine your extroverted friend, Nikki, has lost their confidence and is isolating herself. After months of attempting to catch up for coffee, she shows up late and spend most of the time glued to her phone. She apologizes as she sends messages every 10 minutes to let her partner know what she is doing. You ask her how she has been and she spends all her time talking about her partner and mentions she is no longer participating in her usual hobbies. You have noticed since she met her partner, Fedrick. She rarely goes anywhere without him. She says he has the same interests as her and enjoys spending time with her. After an hour, Fedrick turns up at the cafe to join the conversation. His stories are often focused on himself and his shared trauma with Nikki. You are starting to suspect that Fedrick has been manipulating Nikki and your friend seems unhappy despite telling you otherwise. {{RoundBoxBottom}} * Dark empathy is a developed skill that uses the understanding of emotion and people's vulnerabilities against them to control and manipulate for their advantage * Understanding why and how people use dark empathy is important to preventing and addressing the the concern * Research indicates understanding emotional intelligence, the dark triad, theory of mind, and the schemas could assist with understanding the motivation behind dark empathy {{RoundBoxTop|theme=3}} ;Focus questions *How do we develop empathy? *What drives an individual to use empathy to control and manipulate other people in their life? *How can psychological theory develop strategies to understand and assist individuals mitigate the negative effects of empathy? {{RoundBoxBottom}} == The development of empathy == * [[Empathy]] is the ability to share feelings and thoughts of others while remaining self-other determination (Håkansson Eklund & Summer Meranius, 2021). *Empathy is not an innate, rather learned and developed. It can be cultivated through techniques to understand other's feelings and foster pro-social behaviour (Abramson, A, 2021) *Although, empathy does not have have a natural morality which means the individual has to choose how to use their understanding of other's emotions and feelings. === Types of empathy === Empathy is a large element of [[emotional intelligence]] in an understanding and sharing feeling with others. Empathy has bright and dark sides as well two types: * Affective empathy is physical and emotional sharing of feelings **This empathy is experiencing with the other person which is found more commonly in bright empathy () * Cognitive empathy is the intellectual understanding of another’s emotions and thoughts without feeling their pain. **This empathy is the understanding, yet keeping that self-other determination which makes it easier for manipulating by utilising emotions against another [[File:The Dark Triad Traits.svg|thumb|'''Figure 1.''' The dark triad and subsets of the three elements ]] === The dark tetrad === * Dark personality traits were called the 'dark triad' (Paulhus & Williams, 2002). An expansion on these traits were to include a fourth element, sadism (Mededovic & Petrovic, 2015). There are four elements to the dark tetrad: ** Narcissism ** Machiavellianism ** Psychopathy ** Sadism === Making of a dark empath === *Dark Empathy is understanding those feelings and harnessing against others * Development of dark empathy is when an individual has high levels of dark traits (narcissism, machiavellianism, psychopathy, and sadism) and alongside retained or high cognitive and affective empathy capacity (Gojković et al., 2022) * Dark empath isn't a psychological diagnosis, yet a term how an individual differences from other diagnosis from the dark triad * Dark empathy is found in individuals with high dark triad traits and cognitive empathy. Cognitive empathy rather than affective empathy allows the individual to understanding emotions and thoughts without having to feel the emotions which in turn makes it easier to manipulate others * '''An individual with affective dissonance is another indicator of dark empathy. It is''' having twisted or contradictory emotional reactions, such as feeling happy when someone else is suffering that is present in those with high dark traits (Gojković et al., 2022). *Research demonstrates experiencing trauma as a child where you had to predict and understand other's emotion to keep safe may lead to the develop of dark empathy == Consequences of dark empathy == *The person using dark empathy and those they are manipulating are both impacted by the behaviour and will harm their wellbeing *While the use of empathy may bring people together through a shared emotion and experience, dark empathy isolates from community === Effects on victims of dark empathy === *The immediate impacts are startle and unlikely to be noticed, yet over time an individual will develop chronic anxiety, lower self-esteem and emotional dependency === Outcome for dark empaths === *An individual using dark empathy will find the control and manipulation effective and after time keeping up this level of deception is exhausting. *It will impact their mental health potentially leading to depression, mood instability, difficulty maintaining long-term relationships and identity confusion == Address dark empathy == *Dark empathy is not easily recognised in others *A narcissist or sociopath may use understanding of schemas to influence others while a dark empath uses their empathy to control and most likely enjoy other's vulnerable emotions === Regaining themselves: recovering from a dark empathy === *Recognise the patterns used by the dark empath *Prioritise your self and trust your instincts *Set healthy emotional boundaries in this relationship *Seek therapy particularly CBT *Seperation from the dark empath === Unravelling from dark empathy === *Recognising and acknowledging the pattern of behaviour of controlling those around them and the impacts on theirs and other’s wellbeing *Attending therapy is the best way to address and understand the behaviours. Some therapies that would be appropriate and effective for dark empaths are: **Trauma-informed therapy **[[w:Cognitive_behavioral_therapy|Cognitive Behaviour Therapy]] (CBT) **[[w:Schema_therapy|Schema therapy]] **Emotional regulation and accountability training == Conclusion == * Emotional intelligence does not come with morality * The dark triad is an indicator of dark empathy if individual have high dark traits and affective cognitive empathy * Cognitive empathy and trauma patterns can develop the drive for using dark empathy * Effective identification and therapy will assist with managing an individual using empathy against others ==Figures== [[File:Thought bubble.svg|right|140px|thumb|'''Figure 2'''. Example of an image with a descriptive caption.]] * For the book chapter, use several figures to illustrate concepts, add interest, and to serve as examples * For the topic development, use at least one figure (even if not ideal) to show that you know how to embed, caption, and cite a figure * Figures can show any kind of media such as photos, diagrams, graphs, video, audio, and so on * Embed figures throughout the chapter, starting with the scenario in the Overview section * Provide descriptive figure captions (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== Learning features help to bring book chapters to life and can be embedded throughout the chapter. Here are some options: {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples that illustrate concepts in action * Present using [[#Feature boxes|feature boxes]]; can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Can be real or fictional; if real, provide citation(s) {{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 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 Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing the Relationship Between Known/Unknown and 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 * 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 the 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> {The purpose of quizzes is to provide an interactive learning feature: |type="()"} + True - False {Long and complex quiz questions are recommended: |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/2020/Dark triad personality and emotion|Dark triad personality and emotion]] (Book chapter, 2020) *[[Motivation and emotion/Book/2019/Emotional intelligence and anti-social behaviour|Emotional intelligence and antisocial behaviour]] (Book chapter, 2019) *[[Motivation and emotion/Book/2021/Emotional intelligence and the dark triad|Emotional intelligence and the dark triad]] (Book chapter, 2021) *[[wikipedia:Machiavellianism_(psychology)|Machiavellianism]] (Wikipedia) *[[wikipedia:Narcissism|Narcissism]] (Wikipedia) *[[wikipedia:Psychopathy|Psychopathy]] (Wikipedia) *[[wikipedia:Dark_triad|The Dark Triad]] (Wikipedia) ==References== {{Hanging indent|1= Abramson, A. (2021, November 1). Cultivating empathy. Monitor on Psychology, 52(8). https://www.apa.org/monitor/2021/11/feature-cultivating-empathy Gojković, V., Dostanić, J. S., & Đurić, V. (2022). Structure of darkness: The Dark Triad, the ‘Dark’ Empathy and the ‘Dark’ Narcissism. Primenjena psihologija (Online), 15(2), 237-268. https://doi.org/10.19090/pp.v15i2.2380 Håkansson Eklund, J., & Summer Meranius, M. (2021). Toward a consensus on the nature of empathy: A review of reviews. Patient education and counseling, 104(2), 300-307. https://doi.org/10.1016/j.pec.2020.08.022 Heym, N., Firth, J., Kibowski, F., Sumich, A., Egan, V., & Bloxsom, C. A. (2019). Empathy at the heart of darkness: Empathy deficits that bind the dark triad and those that mediate indirect relational aggression. Frontiers in psychiatry, 10, 95. Heym, N., Kibowski, F., Bloxsom, C. A. J., Blanchard, A., Harper, A., Wallace, L., Firth, J., & Sumich, A. (2021). The Dark Empath: Characterising dark traits in the presence of empathy. Personality and Individual Differences, 169, 110172-110172. https://doi.org/10.1016/j.paid.2020.110172 Huang, C., Wu, Z., Sha, S., Liu, C., Yang, L., Jiang, P., Zhang, H., & Yang, C. (2025). The Dark Side of Empathy: The Role of Excessive Affective Empathy in Mental Health Disorders. Biological psychiatry (1969), 98(5), 404-415. https://doi.org/10.1016/j.biopsych.2024.12.020 Kaufman, S. B., Yaden, D. B., Hyde, E., & Tsukayama, E. (2019). The Light vs. Dark Triad of Personality: Contrasting Two Very Different Profiles of Human Nature [Original Research]. Frontiers in psychology, Volume 10 - 2019. https://doi.org/10.3389/fpsyg.2019.00467 Mikkelsen, E. N., Geraldi, J., & Clegg, S. (2026). The Dark Side of Empathy and Organization Studies. Organization studies. https://doi.org/10.1177/01708406261459079 Paulhus, D. L., & Williams, K. M. (2002). The Dark Triad of personality: Narcissism, Machiavellianism, and psychopathy. Journal of research in personality, 36(6), 556-563. https://doi.org/10.1016/S0092-6566(02)00505-6 }} {{tip|Suggestions for this section: * 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) ** Hanging indent: 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> * 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== * [https://www.sciencefocus.com/wellbeing/dark-empaths Dark Empaths] (Science Focus) * [https://www.psychologytoday.com/au/basics/dark-triad Dark Triad] (Psychology Today) * [https://www.theguardian.com/science/2024/nov/10/narcissists-only-more-devious-the-truth-about-dark-empaths 'Narcissists - only more devious': the truth about dark empaths] (the Guardian) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] ssszko58yl7kxenp4qf4on0ytzapt8w 2835107 2835091 2026-09-30T03:27:14Z U3254168 3106320 Clarification templates added and spelling errors corrected 2835107 wikitext text/x-wiki {{title|Dark empathy:<br>What is dark empathy, what are its consequences, and what can be done to address it?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}}{{ic|Make it more clear how this connects to dark empathy}} Imagine your extroverted friend, Nikki, has lost their confidence and is isolating herself. After months of attempting to catch up for coffee, she shows up late and spends most of the time glued to her phone. She apologizes as she sends messages every 10 minutes to let her partner know what she is doing. You ask her how she has been and she spends all her time talking about her partner and mentions she is no longer participating in her usual hobbies. You have noticed that since she met her partner, Fedrick, she rarely goes anywhere without him. She says he has the same interests as her and enjoys spending time with her. After an hour, Fedrick turns up at the cafe to join the conversation. His stories are often focused on himself and his shared trauma with Nikki. You are starting to suspect that Fedrick has been manipulating Nikki and your friend seems unhappy despite telling you otherwise. {{RoundBoxBottom}} * Dark empathy is a developed skill that uses the understanding of emotion and people's vulnerabilities against them to control and manipulate for their advantage {{citation needed}} {{expand}} * Understanding why and how people use dark empathy is important to preventing and addressing the concern {{citation needed}} {{grammar}} * Research indicates understanding emotional intelligence, the dark triad, theory of mind, and the schemas could assist with understanding the motivation behind dark empathy {{citation needed}} {{RoundBoxTop|theme=3}} ;Focus questions *How do we develop empathy? *What drives an individual to use empathy to control and manipulate other people in their life? *How can psychological theory develop strategies to understand and assist individuals mitigate the negative effects of empathy? {{RoundBoxBottom}} == The development of empathy == * [[Empathy]] is the ability to share feelings and thoughts of others while remaining self-other determination (Håkansson Eklund & Summer Meranius, 2021). *Empathy is not an innate, rather learned and developed. It can be cultivated through techniques to understand other's feelings and foster pro-social behaviour (Abramson, A, 2021) {{check citation consistency with APA7}} *Although, empathy does not have have a natural morality which means the individual has to choose how to use their understanding of other's emotions and feelings {{citation needed}}. === Types of empathy === Empathy is a large element of [[emotional intelligence]] in an understanding and sharing feeling with others {{citation needed}}. Empathy has bright and dark sides as well two types: * Affective empathy is physical and emotional sharing of feelings **This empathy is experiencing with the other person which is found more commonly in bright empathy () * Cognitive empathy is the intellectual understanding of another’s emotions and thoughts without feeling their pain. **This empathy is the understanding, yet keeping that self-other determination which makes it easier for manipulating by utilising emotions against another [[File:The Dark Triad Traits.svg|thumb|'''Figure 1.''' The dark triad and subsets of the three elements ]] === The dark tetrad === * Dark personality traits were called the 'dark triad' (Paulhus & Williams, 2002). An expansion on these traits were to include a fourth element, sadism (Mededovic & Petrovic, 2015). There are four elements to the dark tetrad: ** Narcissism ** Machiavellianism ** Psychopathy ** Sadism === Making of a dark empath === *Dark Empathy is understanding those feelings and harnessing against others {{citation needed}} * Development of dark empathy is when an individual has high levels of dark traits (narcissism, machiavellianism, psychopathy, and sadism) and alongside retained or high cognitive and affective empathy capacity (Gojković et al., 2022) * Dark empathy isn't a psychological diagnosis, yet a term how an individual differences from other diagnoses from the dark triad {{grammar}} {{citation needed}} {{clarify}} * Dark empathy is found in individuals with high dark triad traits and cognitive empathy {{citation needed}}. Cognitive empathy rather than affective empathy allows the individual to understanding emotions and thoughts without having to feel the emotions which in turn makes it easier to manipulate others * '''An individual with affective dissonance is another indicator of dark empathy.''' It is having twisted or contradictory emotional reactions, such as feeling happy when someone else is suffering that is present in those with high dark traits (Gojković et al., 2022). *Research demonstrates that experiencing trauma as a child where you had to predict and understand other's emotions to keep safe may lead to the development of dark empathy {{citation needed}} == Consequences of dark empathy == *The person using dark empathy and those they are manipulating are both impacted by the behaviour and will harm their wellbeing {{citation needed}} *While the use of empathy may bring people together through a shared emotion and experience, dark empathy isolates from community {{grammar}} {{citation needed}} === Effects on victims of dark empathy === *The immediate impacts are startle and unlikely to be noticed, yet over time an individual will develop chronic anxiety, lower self-esteem and emotional dependency {{citation needed}} === Outcome for dark empaths === *An individual using dark empathy will find the control and manipulation effective and after time keeping up this level of deception is exhausting. {{citation needed}} *It will impact their mental health potentially leading to depression, mood instability, difficulty maintaining long-term relationships and identity confusion {{citation needed}} == Address dark empathy == *Dark empathy is not easily recognised in others {{citation needed}} *A narcissist or sociopath may use understanding of schemas to influence others while a dark empath uses their empathy to control and most likely enjoy other's vulnerable emotions {{citation needed}} === Regaining themselves: recovering from a dark empathy === *Recognise the patterns used by the dark empath {{citation needed}} *Prioritise your self and trust your instincts {{citation needed}} *Set healthy emotional boundaries in this relationship *Seek therapy particularly CBT {{citation needed}} *Seperation from the dark empath {{citation needed}} === Unravelling from dark empathy === *Recognising and acknowledging the pattern of behaviour of controlling those around them and the impacts on theirs and other’s wellbeing {{citation needed}} *Attending therapy is the best way to address and understand the behaviours {{citation needed}}. Some therapies that would be appropriate and effective for dark empaths are: **Trauma-informed therapy **[[w:Cognitive_behavioral_therapy|Cognitive Behaviour Therapy]] (CBT) **[[w:Schema_therapy|Schema therapy]] **Emotional regulation and accountability training {{citation needed}}. == Conclusion == * Emotional intelligence does not come with morality {{citation needed}} * The dark triad is an indicator of dark empathy if individual have high dark traits and affective cognitive empathy {{citation needed}} * Cognitive empathy and trauma patterns can develop the drive for using dark empathy {{citation needed}} * Effective identification and therapy will assist with managing an individual using empathy against others {{citation needed}} ==Figures== [[File:Thought bubble.svg|right|140px|thumb|'''Figure 2'''. Example of an image with a descriptive caption.]] * For the book chapter, use several figures to illustrate concepts, add interest, and to serve as examples * For the topic development, use at least one figure (even if not ideal) to show that you know how to embed, caption, and cite a figure * Figures can show any kind of media such as photos, diagrams, graphs, video, audio, and so on * Embed figures throughout the chapter, starting with the scenario in the Overview section * Provide descriptive figure captions (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== Learning features help to bring book chapters to life and can be embedded throughout the chapter. Here are some options: {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples that illustrate concepts in action * Present using [[#Feature boxes|feature boxes]]; can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Can be real or fictional; if real, provide citation(s) {{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 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 Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing the Relationship Between Known/Unknown and 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 * 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 the 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> {The purpose of quizzes is to provide an interactive learning feature: |type="()"} + True - False {Long and complex quiz questions are recommended: |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/2020/Dark triad personality and emotion|Dark triad personality and emotion]] (Book chapter, 2020) *[[Motivation and emotion/Book/2019/Emotional intelligence and anti-social behaviour|Emotional intelligence and antisocial behaviour]] (Book chapter, 2019) *[[Motivation and emotion/Book/2021/Emotional intelligence and the dark triad|Emotional intelligence and the dark triad]] (Book chapter, 2021) *[[wikipedia:Machiavellianism_(psychology)|Machiavellianism]] (Wikipedia) *[[wikipedia:Narcissism|Narcissism]] (Wikipedia) *[[wikipedia:Psychopathy|Psychopathy]] (Wikipedia) *[[wikipedia:Dark_triad|The Dark Triad]] (Wikipedia) ==References== {{Hanging indent|1= Abramson, A. (2021, November 1). Cultivating empathy. Monitor on Psychology, 52(8). https://www.apa.org/monitor/2021/11/feature-cultivating-empathy Gojković, V., Dostanić, J. S., & Đurić, V. (2022). Structure of darkness: The Dark Triad, the ‘Dark’ Empathy and the ‘Dark’ Narcissism. Primenjena psihologija (Online), 15(2), 237-268. https://doi.org/10.19090/pp.v15i2.2380 Håkansson Eklund, J., & Summer Meranius, M. (2021). Toward a consensus on the nature of empathy: A review of reviews. Patient education and counseling, 104(2), 300-307. https://doi.org/10.1016/j.pec.2020.08.022 Heym, N., Firth, J., Kibowski, F., Sumich, A., Egan, V., & Bloxsom, C. A. (2019). Empathy at the heart of darkness: Empathy deficits that bind the dark triad and those that mediate indirect relational aggression. Frontiers in psychiatry, 10, 95. Heym, N., Kibowski, F., Bloxsom, C. A. J., Blanchard, A., Harper, A., Wallace, L., Firth, J., & Sumich, A. (2021). The Dark Empath: Characterising dark traits in the presence of empathy. Personality and Individual Differences, 169, 110172-110172. https://doi.org/10.1016/j.paid.2020.110172 Huang, C., Wu, Z., Sha, S., Liu, C., Yang, L., Jiang, P., Zhang, H., & Yang, C. (2025). The Dark Side of Empathy: The Role of Excessive Affective Empathy in Mental Health Disorders. Biological psychiatry (1969), 98(5), 404-415. https://doi.org/10.1016/j.biopsych.2024.12.020 Kaufman, S. B., Yaden, D. B., Hyde, E., & Tsukayama, E. (2019). The Light vs. Dark Triad of Personality: Contrasting Two Very Different Profiles of Human Nature [Original Research]. Frontiers in psychology, Volume 10 - 2019. https://doi.org/10.3389/fpsyg.2019.00467 Mikkelsen, E. N., Geraldi, J., & Clegg, S. (2026). The Dark Side of Empathy and Organization Studies. Organization studies. https://doi.org/10.1177/01708406261459079 Paulhus, D. L., & Williams, K. M. (2002). The Dark Triad of personality: Narcissism, Machiavellianism, and psychopathy. Journal of research in personality, 36(6), 556-563. https://doi.org/10.1016/S0092-6566(02)00505-6 }} {{tip|Suggestions for this section: * 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) ** Hanging indent: 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> * 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== * [https://www.sciencefocus.com/wellbeing/dark-empaths Dark Empaths] (Science Focus) * [https://www.psychologytoday.com/au/basics/dark-triad Dark Triad] (Psychology Today) * [https://www.theguardian.com/science/2024/nov/10/narcissists-only-more-devious-the-truth-about-dark-empaths 'Narcissists - only more devious': the truth about dark empaths] (the Guardian) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] dtno4ibbgh1pu0zh5y054ew427gffwe 2835129 2835107 2026-09-30T07:00:23Z U3228742 3005570 /* The dark tetrad */ adding citations and another point 2835129 wikitext text/x-wiki {{title|Dark empathy:<br>What is dark empathy, what are its consequences, and what can be done to address it?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}}{{ic|Make it more clear how this connects to dark empathy}} Imagine your extroverted friend, Nikki, has lost their confidence and is isolating herself. After months of attempting to catch up for coffee, she shows up late and spends most of the time glued to her phone. She apologizes as she sends messages every 10 minutes to let her partner know what she is doing. You ask her how she has been and she spends all her time talking about her partner and mentions she is no longer participating in her usual hobbies. You have noticed that since she met her partner, Fedrick, she rarely goes anywhere without him. She says he has the same interests as her and enjoys spending time with her. After an hour, Fedrick turns up at the cafe to join the conversation. His stories are often focused on himself and his shared trauma with Nikki. You are starting to suspect that Fedrick has been manipulating Nikki and your friend seems unhappy despite telling you otherwise. {{RoundBoxBottom}} * Dark empathy is a developed skill that uses the understanding of emotion and people's vulnerabilities against them to control and manipulate for their advantage {{citation needed}} {{expand}} * Understanding why and how people use dark empathy is important to preventing and addressing the concern {{citation needed}} {{grammar}} * Research indicates understanding emotional intelligence, the dark triad, theory of mind, and the schemas could assist with understanding the motivation behind dark empathy {{citation needed}} {{RoundBoxTop|theme=3}} ;Focus questions *How do we develop empathy? *What drives an individual to use empathy to control and manipulate other people in their life? *How can psychological theory develop strategies to understand and assist individuals mitigate the negative effects of empathy? {{RoundBoxBottom}} == The development of empathy == * [[Empathy]] is the ability to share feelings and thoughts of others while remaining self-other determination (Håkansson Eklund & Summer Meranius, 2021). *Empathy is not an innate, rather learned and developed. It can be cultivated through techniques to understand other's feelings and foster pro-social behaviour (Abramson, A, 2021) {{check citation consistency with APA7}} *Although, empathy does not have have a natural morality which means the individual has to choose how to use their understanding of other's emotions and feelings {{citation needed}}. === Types of empathy === Empathy is a large element of [[emotional intelligence]] in an understanding and sharing feeling with others {{citation needed}}. Empathy has bright and dark sides as well two types: * Affective empathy is physical and emotional sharing of feelings **This empathy is experiencing with the other person which is found more commonly in bright empathy () * Cognitive empathy is the intellectual understanding of another’s emotions and thoughts without feeling their pain. **This empathy is the understanding, yet keeping that self-other determination which makes it easier for manipulating by utilising emotions against another [[File:The Dark Triad Traits.svg|thumb|'''Figure 1.''' The dark triad and subsets of the three elements ]] === The dark tetrad === * Dark personality traits were called the 'dark triad' (Paulhus & Williams, 2002). An expansion on these traits were to include a fourth element, sadism (Mededovic & Petrovic, 2015). There are four elements to the dark tetrad: ** Narcissism ** Machiavellianism ** Psychopathy ** Sadism === Making of a dark empath === *Dark Empathy is understanding those feelings and harnessing against others {{citation needed}} * Development of dark empathy is when an individual has high levels of dark traits (narcissism, machiavellianism, psychopathy, and sadism) and alongside retained high cognitive and affective empathy capacity (Gojković et al., 2022) * Research assessing individuals with high levels of dark traits concluded these personality types do not share ethics and morality meaning they are more likely to be honest and fair towards others (Mededovic & Petrovic, 2015) * Dark empathy isn't a psychological diagnosis, yet a term how an individual differences from other diagnoses from the dark triad {{grammar}} {{citation needed}} {{clarify}} * Dark empathy is found in individuals with high dark triad traits and cognitive empathy {{citation needed}}. Cognitive empathy rather than affective empathy allows the individual to understanding emotions and thoughts without having to feel the emotions which in turn makes it easier to manipulate others * '''An individual with affective dissonance is another indicator of dark empathy.''' It is having twisted or contradictory emotional reactions, such as feeling happy when someone else is suffering that is present in those with high dark traits (Gojković et al., 2022). *Research demonstrates that experiencing trauma as a child where you had to predict and understand other's emotions to keep safe may lead to the development of dark empathy {{citation needed}} == Consequences of dark empathy == *The person using dark empathy and those they are manipulating are both impacted by the behaviour and will harm their wellbeing {{citation needed}} *While the use of empathy may bring people together through a shared emotion and experience, dark empathy isolates from community {{grammar}} {{citation needed}} === Effects on victims of dark empathy === *The immediate impacts are startle and unlikely to be noticed, yet over time an individual will develop chronic anxiety, lower self-esteem and emotional dependency {{citation needed}} === Outcome for dark empaths === *An individual using dark empathy will find the control and manipulation effective and after time keeping up this level of deception is exhausting. {{citation needed}} *It will impact their mental health potentially leading to depression, mood instability, difficulty maintaining long-term relationships and identity confusion {{citation needed}} == Address dark empathy == *Dark empathy is not easily recognised in others {{citation needed}} *A narcissist or sociopath may use understanding of schemas to influence others while a dark empath uses their empathy to control and most likely enjoy other's vulnerable emotions {{citation needed}} === Regaining themselves: recovering from a dark empathy === *Recognise the patterns used by the dark empath {{citation needed}} *Prioritise your self and trust your instincts {{citation needed}} *Set healthy emotional boundaries in this relationship *Seek therapy particularly CBT {{citation needed}} *Seperation from the dark empath {{citation needed}} === Unravelling from dark empathy === *Recognising and acknowledging the pattern of behaviour of controlling those around them and the impacts on theirs and other’s wellbeing {{citation needed}} *Attending therapy is the best way to address and understand the behaviours {{citation needed}}. Some therapies that would be appropriate and effective for dark empaths are: **Trauma-informed therapy **[[w:Cognitive_behavioral_therapy|Cognitive Behaviour Therapy]] (CBT) **[[w:Schema_therapy|Schema therapy]] **Emotional regulation and accountability training {{citation needed}}. == Conclusion == * Emotional intelligence does not come with morality {{citation needed}} * The dark triad is an indicator of dark empathy if individual have high dark traits and affective cognitive empathy {{citation needed}} * Cognitive empathy and trauma patterns can develop the drive for using dark empathy {{citation needed}} * Effective identification and therapy will assist with managing an individual using empathy against others {{citation needed}} ==Figures== [[File:Thought bubble.svg|right|140px|thumb|'''Figure 2'''. Example of an image with a descriptive caption.]] * For the book chapter, use several figures to illustrate concepts, add interest, and to serve as examples * For the topic development, use at least one figure (even if not ideal) to show that you know how to embed, caption, and cite a figure * Figures can show any kind of media such as photos, diagrams, graphs, video, audio, and so on * Embed figures throughout the chapter, starting with the scenario in the Overview section * Provide descriptive figure captions (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== Learning features help to bring book chapters to life and can be embedded throughout the chapter. Here are some options: {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples that illustrate concepts in action * Present using [[#Feature boxes|feature boxes]]; can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Can be real or fictional; if real, provide citation(s) {{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 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 Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing the Relationship Between Known/Unknown and 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 * 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 the 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> {The purpose of quizzes is to provide an interactive learning feature: |type="()"} + True - False {Long and complex quiz questions are recommended: |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/2020/Dark triad personality and emotion|Dark triad personality and emotion]] (Book chapter, 2020) *[[Motivation and emotion/Book/2019/Emotional intelligence and anti-social behaviour|Emotional intelligence and antisocial behaviour]] (Book chapter, 2019) *[[Motivation and emotion/Book/2021/Emotional intelligence and the dark triad|Emotional intelligence and the dark triad]] (Book chapter, 2021) *[[wikipedia:Machiavellianism_(psychology)|Machiavellianism]] (Wikipedia) *[[wikipedia:Narcissism|Narcissism]] (Wikipedia) *[[wikipedia:Psychopathy|Psychopathy]] (Wikipedia) *[[wikipedia:Dark_triad|The Dark Triad]] (Wikipedia) ==References== {{Hanging indent|1= Abramson, A. (2021, November 1). Cultivating empathy. Monitor on Psychology, 52(8). https://www.apa.org/monitor/2021/11/feature-cultivating-empathy Gojković, V., Dostanić, J. S., & Đurić, V. (2022). Structure of darkness: The Dark Triad, the ‘Dark’ Empathy and the ‘Dark’ Narcissism. Primenjena psihologija (Online), 15(2), 237-268. https://doi.org/10.19090/pp.v15i2.2380 Håkansson Eklund, J., & Summer Meranius, M. (2021). Toward a consensus on the nature of empathy: A review of reviews. Patient education and counseling, 104(2), 300-307. https://doi.org/10.1016/j.pec.2020.08.022 Heym, N., Firth, J., Kibowski, F., Sumich, A., Egan, V., & Bloxsom, C. A. (2019). Empathy at the heart of darkness: Empathy deficits that bind the dark triad and those that mediate indirect relational aggression. Frontiers in psychiatry, 10, 95. Heym, N., Kibowski, F., Bloxsom, C. A. J., Blanchard, A., Harper, A., Wallace, L., Firth, J., & Sumich, A. (2021). The Dark Empath: Characterising dark traits in the presence of empathy. Personality and Individual Differences, 169, 110172-110172. https://doi.org/10.1016/j.paid.2020.110172 Huang, C., Wu, Z., Sha, S., Liu, C., Yang, L., Jiang, P., Zhang, H., & Yang, C. (2025). The Dark Side of Empathy: The Role of Excessive Affective Empathy in Mental Health Disorders. Biological psychiatry (1969), 98(5), 404-415. https://doi.org/10.1016/j.biopsych.2024.12.020 Kaufman, S. B., Yaden, D. B., Hyde, E., & Tsukayama, E. (2019). The Light vs. Dark Triad of Personality: Contrasting Two Very Different Profiles of Human Nature [Original Research]. Frontiers in psychology, Volume 10 - 2019. https://doi.org/10.3389/fpsyg.2019.00467 Mededovic, J., & Petrovic, B. (2015). The Dark Tetrad: Structural Properties and Location in the Personality Space. Journal of individual differences, 36(4), 228-236. https://doi.org/10.1027/1614-0001/a000179 Mikkelsen, E. N., Geraldi, J., & Clegg, S. (2026). The Dark Side of Empathy and Organization Studies. Organization studies. https://doi.org/10.1177/01708406261459079 Paulhus, D. L., & Williams, K. M. (2002). The Dark Triad of personality: Narcissism, Machiavellianism, and psychopathy. Journal of research in personality, 36(6), 556-563. https://doi.org/10.1016/S0092-6566(02)00505-6 }} {{tip|Suggestions for this section: * 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) ** Hanging indent: 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> * 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== * [https://www.sciencefocus.com/wellbeing/dark-empaths Dark Empaths] (Science Focus) * [https://www.psychologytoday.com/au/basics/dark-triad Dark Triad] (Psychology Today) * [https://www.theguardian.com/science/2024/nov/10/narcissists-only-more-devious-the-truth-about-dark-empaths 'Narcissists - only more devious': the truth about dark empaths] (the Guardian) [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Empathy]] kqfs2uiio0vtk4nj16q2hytihbkda9r 2 331308 2835096 2834614 2026-09-30T02:59:26Z U3254168 3106320 /* Social contributions */ 2835096 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]] # 1je2noxfbii5ko6r9w0a5shva5rh4sf 2835105 2835096 2026-09-30T03:15:32Z U3254168 3106320 /* Social contributions */ 2835105 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] 5a6ksnfslccczyoni7cvydxargtru5m 2835108 2835105 2026-09-30T03:27:45Z U3254168 3106320 /* Social contributions */ 2835108 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] qpnzhzdmkce6mp5jm0xf3v6yldq0yqf 2835134 2835108 2026-09-30T08:12:32Z U3254168 3106320 /* Social contributions */ 2835134 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] nlery1isw7euh2btp1t3qjkurnjfgi0 2835141 2835134 2026-09-30T09:01:55Z U3254168 3106320 /* Social contributions */ 2835141 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]] ejbzvwf5gs2unxdvy7vm5ap3jv3a76u 0 331389 2835071 2832421 2026-09-29T19:50:04Z JSINST 3110286 /* BYLAWS in edition */ 2835071 wikitext text/x-wiki == '''BYLAWS''' <small>in edition</small> == '''Definition of the Institute''' The Institute is a non-profit, international network of clinical-, research- and educational institutes to collaborate on the early diagnostics and prevention on prediabetes, prehypertension and other metabolic diseases. (Alberto et al., 2022) The target countries are in the low- and middle-income countries where the availability of essential diagnostics remains a challenge. It is a brick-free center that unites interested institutions with activities in public- and occupational health research and education and application for fundings. '''Objectives''' · Create a network of health clinics producing data from the routine health examinations · Create a network of public health schools to analyse and publish the data · Main focus on early diagnosis and prevention of prediabetes and other metabolic diseases · Apply for fundings to establish data collection and remission of prediabetes. - The primary objective of an AI-steered prediabetes remission project is <mark>to halt progression to type 2 diabetes and return blood glucose levels to normal using personalized, data-driven interventions</mark>. '''Ethical requirements''' The ethical rules for database research in the respective Universities and other centers. The ICOH Code of ethics are complied with. Confidentiality in handling personal information is done according to the rules set out by the national Data Protection Agencies.Nno personal sensitive information is included so approval from the Ethics Committee is not necessary. All questionnaires ask for informed consent as the first question. The supervisors take care to secure that the data is processed under the Act on medical confidentiality as guidelines for good epidemiological practice. The participants' anonymity will be protected in every way and this will be indicated in the project description. It will be ensured that the electronic table is locked so that the information can not be seen by anyone other than the researchers. The researchers respect individual ownership of the data and share publications and the data where this is convenient and keep always good partnerships. The European Code of Conduct for Research Integrity for self-regulation in all research '''Steering committee''' The Institute's main decision-making authority is the '''steering committee, which''' is made up of representatives from the associate institutions. The '''steering committee''' consisting of the leading physicians and professors from the participating research units. The chairmanship of this steering committee, the Institute Coordinator typically rotates between the partners. '''Institute Cordinator''' The '''steering committee''' selects a Coordinator of the Institute for 1 year to be reelected at the annual meeting of the Board in August, in presence and hybrid meeting · One Board meeting is held annually, in presence and hybrid · The Coordinator is responsible for convening Board meetings '''Advisory Committee''' Representatives from the relevant Universities, Clinics and Scientific Associations are asked to serve as the Advisory Committee. '''Goals''' In collaboration with the Coordinator, the Board establishes objectives for which research and educational areas and applications for fundings should be prioritized and what results are expected to be obtained from research in these areas. '''Evaluation of the activities of the Institute''' The Board of Directors understands every year an evaluation of the activities of the Institute. The Coordinator presents an annual report to the Board in late December. Financial Accounting. There are no separate accounts for the Institute since the economy is placed with each of the participants. '''Financial Accounting''' There are no separate accounts for the Institute since the economy is placed with each of the participants’ projects. '''Financial Resources''' The main financial resources for the Institute activity is the existing resources of individual participants and national and international research foundations. Indication of the affiliations in the publications The publications from the Institute are listed like: Own institution, John Snow Institute ... '''Annual status report''' The Coordinator is responsible for preparing an annual status report that is approved by the Board of Directors. The progress report should include a brief overview of last year's results with signatures and dates '''Financial Funds.''' European Foundation Study of Diabetes (EFSD)- http://www.europeandiabetesfoundation.org/ ITF Seafarers Trust https://www.seafarerstrust.org/ Novo Nordisk Found https://www.eshonline.org/online-education/teaching-seminars/ Hypertension Research Foundation http://www.hypertensionresearchfoundation.ch/EN/projets.html https://research-and-innovation.ec.europa.eu/research-area/health/diabetes_en The European Social Fund Danish Diabetes Academy The European Society of Hypertension https://www.eshonline.org/ And others…. '''DATA COME FROM THE CLINICS''' 1.     American out-patient clinic (American Hospital,Inc) Metro Manila, National Capital Region, Philippines Medical Director Dr. Joseph Bien Abesamis, MD 2.     Nordic Medical Clinic Unit 1B, Maria Daniel Building, 470 San Andres Street Corner MH Del Pilar Street, Malate, Manila, 1004, Philippines +63 2 85627774 AOH: Medical Director Dr Margarita Huerte Mobile +63 917 1050252 PHILIPPINES peme@nordicmedical.no 3.     Other '''RESEARCH''' (in collaboration with the clinics) ... 1. The John Snow Prediabetes Institute 2. Public Health Schools in Manila https://edurank.org/medicine/public/manila/ https://maritimefairtrade.org/top-maritime-schools-in-the-philippines/ 3. Medical schools in Manila https://en.wikipedia.org/wiki/List_of_medical_schools_in_the_Philippines 3. Public Health Schools in PANAMAMetropolitan University of Education, Science and Technology (UMECIT), University of South Florida (USF) Health 4. University of Panama: school of public health within its medical faculty ----'''Reference:''' Alberto, Nicole Rose I., Isabelle Rose I. Alberto, Michelle Ann B. Eala, Edward Christopher Dee, y Johanna Patricia A. Cañal. «Availability of essential diagnostics in the Philippines». The Lancet Regional Health: Western Pacific 19 (enero de 2022): 100375. https://doi.org/10.1016/j.lanwpc.2021.100375. d1lvwaypsva9nu8l2k8wujjrsrzz4bf 1 331408 2835094 2832762 2026-09-30T02:58:35Z U3254168 3106320 /* Feedback */ new section 2835094 wikitext text/x-wiki == Heading casing == {| style="float: center; background:transparent;color:inherit;" |- | [[File:Crystal Clear app ktip.svg|48px|left]] | {{#if:U3261236|Hi [[User:U3261236|U3261236]].|}} FYI, the recommended [[Wikiversity]] heading style uses [[w:Letter case#Sentence_case|sentence casing]]. For example:<br> <big><big>Self-determination theory</big></big> rather than <big><big>Self-Determination Theory</big></big> Here's an example chapter with correct heading casing: [[Motivation and emotion/Book/2019/Growth mindset development|Growth mindset development]] -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 02:39, 23 August 2026 (UTC) |} ==Overview== Hi, Really interesting topic and you have made a great progress. Three case study in the overview provide useful examples of different motivation for using sex work services. However, the section could be strengthened by adding brief analysis explaining what these cases collectively demonstrate. Additionally, it is useful to acknowledge that these individual experiences should not be generalised to represent all people who seek paid sexual services. All the best.--[[User:P U3270518|P U3270518]] ([[User talk:P U3270518|discuss]] • [[Special:Contributions/P U3270518|contribs]]) 12:28, 26 August 2026 (UTC) == Stress and Trauma Recommendation == Hi, I found your chapter really interesting, particularly how you've separated physical and emotional motivations and considered the experiences of both men and women. I noticed that you have included a "Stress and trauma" subsection under emotional motivation but it doesn't have any key points yet. I think this could be an interesting area to develop further by looking at whether stress, previous experiences or coping motivations contribute to the use of sex work services. It would also help strengthen your emotional motivation section and provide another perspective beyond intimacy and power/control. Looking forward to seeing how your chapter develops! Best of luck with it all! [[User:U3260591|U3260591]] ([[User talk:U3260591|discuss]] • [[Special:Contributions/U3260591|contribs]]) 03:40, 27 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= <!-- Heading structure --> <!-- 2-level --> # Excellent – Well developed [[Motivation and emotion/Assessment/Major project/Structure|2-level heading structure]]. Meaningful headings clearly relate directly to the core topic. <!-- Alignment with focus questions --> # Good alignment between sub-title, focus questions, and heading structure, but there is room for improvement |3= <!-- Overview--> # Excellent – Scenario, image, evocative description of the problem/topic, and focus questions <!-- Scenario --> # A scenario or case study is presented in a feature box with an image at the start of this section <!-- Description --> # A promising description of the problem/topic is planned or presented <!-- Focus questions --> # Reasonably good alignment between focus questions and heading structure, but consider closer alignment # Note that only FQ4 directly addresses the topic |4= <!-- Key points--> <!-- Overall --> # Promising development <!-- Scope --> # It may be that all planned aspects cannot be reasonably covered within the book chapter word count, so be selective and concentrate on key aspects that address the question in the sub-title. There may be too much background material planned. Abbreviate the general sexual motivations and description of sex work services to concentrate on theory and research about the motivations of SWS clients. <!-- Conclusion --> # Conclusion hasn't been developed # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> # Excellent - Relevant figure(s) presented, captioned, and cited <!-- Caption --> # Figure caption(s) grammatical error <!-- Cite --> # Figure(s) are cited at least once in the main text |6= <!-- Learning feature --> <!-- Interwiki links ---> # Two in-text [[m:Help:Interwiki linking|interwiki links]] for first mention of key terms to [[w:|Wikipedia]]. Also embed links to [[Motivation and emotion/Book|book chapters]]. <!-- Scenarios/examples/case studies --> # Consider incorporating additional scenarios, examples, or case studies to illustrate key concepts. These could build on the Overview scenario or introduce new real-world situations in the main body of the chapter to demonstrate how the concepts apply in practice. <!-- Quiz --> # Promising use of quiz question(s) # Place each quiz question in the most relevant section # Focus the quiz question(s) on the take-home messages <!-- Tables --> # Also consider using [[Motivation and emotion/Wikiversity/Tables|table(s)]] to summarise key information |7= <!-- References --> <!-- Overall --> # Very good <!-- Systematic reviews --> # What are the most relevant systematic reviews/meta-analyses about this topic? <!-- APA style --> # Check and correct [https://apastyle.apa.org/instructional-aids/reference-guide.pdf APA referencing style]: ## [[Help:Wikitext quick reference|italicisation]] |8= <!-- Resources --> <!-- See also --> # See also ## Excellent # External links ## Excellent <!-- User page --> # Excellent <!-- Description about self --> # Excellent description about self provided <!-- 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 |10= <!-- Social contribution --> # Excellent – at least three different types of contributions with direct link(s) to evidence }} == Feedback == This is a really interesting topic and I really enjoyed what you have so far! A few bits of feedback: - in the pink overview box, ensure your citations are before the full stop. - in the sexual motivation section, you could mention LGBTQIA+ relationships alongside heteronormative relationships for example saying something along the lines of "this perception has expanded over time to include LGBTQIA+ relationships". - Inserting Buss and Schmitt's (1993) spectrum of mating relationships as a figure would greatly strengthen this point and help visual learners. - Include some examples of the 237 motivations humans have for engaging in sexual activity according to Meston and Buss (2007) to strengthen this point. - change the heading 'theory of sexual motivation' to 'theories of sexual motivation' as you discuss multiple theories. Well done so far and keep up the good work! [[User:U3254168|U3254168]] ([[User talk:U3254168|discuss]] • [[Special:Contributions/U3254168|contribs]]) 02:58, 30 September 2026 (UTC) 18gdvppodugfuj9mofk3h6gsslhz23v 2835095 2835094 2026-09-30T02:58:55Z U3254168 3106320 /* Feedback */ 2835095 wikitext text/x-wiki == Heading casing == {| style="float: center; background:transparent;color:inherit;" |- | [[File:Crystal Clear app ktip.svg|48px|left]] | {{#if:U3261236|Hi [[User:U3261236|U3261236]].|}} FYI, the recommended [[Wikiversity]] heading style uses [[w:Letter case#Sentence_case|sentence casing]]. For example:<br> <big><big>Self-determination theory</big></big> rather than <big><big>Self-Determination Theory</big></big> Here's an example chapter with correct heading casing: [[Motivation and emotion/Book/2019/Growth mindset development|Growth mindset development]] -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 02:39, 23 August 2026 (UTC) |} ==Overview== Hi, Really interesting topic and you have made a great progress. Three case study in the overview provide useful examples of different motivation for using sex work services. However, the section could be strengthened by adding brief analysis explaining what these cases collectively demonstrate. Additionally, it is useful to acknowledge that these individual experiences should not be generalised to represent all people who seek paid sexual services. All the best.--[[User:P U3270518|P U3270518]] ([[User talk:P U3270518|discuss]] • [[Special:Contributions/P U3270518|contribs]]) 12:28, 26 August 2026 (UTC) == Stress and Trauma Recommendation == Hi, I found your chapter really interesting, particularly how you've separated physical and emotional motivations and considered the experiences of both men and women. I noticed that you have included a "Stress and trauma" subsection under emotional motivation but it doesn't have any key points yet. I think this could be an interesting area to develop further by looking at whether stress, previous experiences or coping motivations contribute to the use of sex work services. It would also help strengthen your emotional motivation section and provide another perspective beyond intimacy and power/control. Looking forward to seeing how your chapter develops! Best of luck with it all! [[User:U3260591|U3260591]] ([[User talk:U3260591|discuss]] • [[Special:Contributions/U3260591|contribs]]) 03:40, 27 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= <!-- Heading structure --> <!-- 2-level --> # Excellent – Well developed [[Motivation and emotion/Assessment/Major project/Structure|2-level heading structure]]. Meaningful headings clearly relate directly to the core topic. <!-- Alignment with focus questions --> # Good alignment between sub-title, focus questions, and heading structure, but there is room for improvement |3= <!-- Overview--> # Excellent – Scenario, image, evocative description of the problem/topic, and focus questions <!-- Scenario --> # A scenario or case study is presented in a feature box with an image at the start of this section <!-- Description --> # A promising description of the problem/topic is planned or presented <!-- Focus questions --> # Reasonably good alignment between focus questions and heading structure, but consider closer alignment # Note that only FQ4 directly addresses the topic |4= <!-- Key points--> <!-- Overall --> # Promising development <!-- Scope --> # It may be that all planned aspects cannot be reasonably covered within the book chapter word count, so be selective and concentrate on key aspects that address the question in the sub-title. There may be too much background material planned. Abbreviate the general sexual motivations and description of sex work services to concentrate on theory and research about the motivations of SWS clients. <!-- Conclusion --> # Conclusion hasn't been developed # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> # Excellent - Relevant figure(s) presented, captioned, and cited <!-- Caption --> # Figure caption(s) grammatical error <!-- Cite --> # Figure(s) are cited at least once in the main text |6= <!-- Learning feature --> <!-- Interwiki links ---> # Two in-text [[m:Help:Interwiki linking|interwiki links]] for first mention of key terms to [[w:|Wikipedia]]. Also embed links to [[Motivation and emotion/Book|book chapters]]. <!-- Scenarios/examples/case studies --> # Consider incorporating additional scenarios, examples, or case studies to illustrate key concepts. These could build on the Overview scenario or introduce new real-world situations in the main body of the chapter to demonstrate how the concepts apply in practice. <!-- Quiz --> # Promising use of quiz question(s) # Place each quiz question in the most relevant section # Focus the quiz question(s) on the take-home messages <!-- Tables --> # Also consider using [[Motivation and emotion/Wikiversity/Tables|table(s)]] to summarise key information |7= <!-- References --> <!-- Overall --> # Very good <!-- Systematic reviews --> # What are the most relevant systematic reviews/meta-analyses about this topic? <!-- APA style --> # Check and correct [https://apastyle.apa.org/instructional-aids/reference-guide.pdf APA referencing style]: ## [[Help:Wikitext quick reference|italicisation]] |8= <!-- Resources --> <!-- See also --> # See also ## Excellent # External links ## Excellent <!-- User page --> # Excellent <!-- Description about self --> # Excellent description about self provided <!-- 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 |10= <!-- Social contribution --> # Excellent – at least three different types of contributions with direct link(s) to evidence }} == Feedback == This is a really interesting topic and I really enjoyed what you have so far! A few suggestions: - in the pink overview box, ensure your citations are before the full stop. - in the sexual motivation section, you could mention LGBTQIA+ relationships alongside heteronormative relationships for example saying something along the lines of "this perception has expanded over time to include LGBTQIA+ relationships". - Inserting Buss and Schmitt's (1993) spectrum of mating relationships as a figure would greatly strengthen this point and help visual learners. - Include some examples of the 237 motivations humans have for engaging in sexual activity according to Meston and Buss (2007) to strengthen this point. - change the heading 'theory of sexual motivation' to 'theories of sexual motivation' as you discuss multiple theories. Well done so far and keep up the good work! [[User:U3254168|U3254168]] ([[User talk:U3254168|discuss]] • [[Special:Contributions/U3254168|contribs]]) 02:58, 30 September 2026 (UTC) rgu2damm4b3ko0ouzu943fnp4rvqzct 2835097 2835095 2026-09-30T03:03:22Z U3254168 3106320 /* Feedback */ 2835097 wikitext text/x-wiki == Heading casing == {| style="float: center; background:transparent;color:inherit;" |- | [[File:Crystal Clear app ktip.svg|48px|left]] | {{#if:U3261236|Hi [[User:U3261236|U3261236]].|}} FYI, the recommended [[Wikiversity]] heading style uses [[w:Letter case#Sentence_case|sentence casing]]. For example:<br> <big><big>Self-determination theory</big></big> rather than <big><big>Self-Determination Theory</big></big> Here's an example chapter with correct heading casing: [[Motivation and emotion/Book/2019/Growth mindset development|Growth mindset development]] -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 02:39, 23 August 2026 (UTC) |} ==Overview== Hi, Really interesting topic and you have made a great progress. Three case study in the overview provide useful examples of different motivation for using sex work services. However, the section could be strengthened by adding brief analysis explaining what these cases collectively demonstrate. Additionally, it is useful to acknowledge that these individual experiences should not be generalised to represent all people who seek paid sexual services. All the best.--[[User:P U3270518|P U3270518]] ([[User talk:P U3270518|discuss]] • [[Special:Contributions/P U3270518|contribs]]) 12:28, 26 August 2026 (UTC) == Stress and Trauma Recommendation == Hi, I found your chapter really interesting, particularly how you've separated physical and emotional motivations and considered the experiences of both men and women. I noticed that you have included a "Stress and trauma" subsection under emotional motivation but it doesn't have any key points yet. I think this could be an interesting area to develop further by looking at whether stress, previous experiences or coping motivations contribute to the use of sex work services. It would also help strengthen your emotional motivation section and provide another perspective beyond intimacy and power/control. Looking forward to seeing how your chapter develops! Best of luck with it all! [[User:U3260591|U3260591]] ([[User talk:U3260591|discuss]] • [[Special:Contributions/U3260591|contribs]]) 03:40, 27 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= <!-- Heading structure --> <!-- 2-level --> # Excellent – Well developed [[Motivation and emotion/Assessment/Major project/Structure|2-level heading structure]]. Meaningful headings clearly relate directly to the core topic. <!-- Alignment with focus questions --> # Good alignment between sub-title, focus questions, and heading structure, but there is room for improvement |3= <!-- Overview--> # Excellent – Scenario, image, evocative description of the problem/topic, and focus questions <!-- Scenario --> # A scenario or case study is presented in a feature box with an image at the start of this section <!-- Description --> # A promising description of the problem/topic is planned or presented <!-- Focus questions --> # Reasonably good alignment between focus questions and heading structure, but consider closer alignment # Note that only FQ4 directly addresses the topic |4= <!-- Key points--> <!-- Overall --> # Promising development <!-- Scope --> # It may be that all planned aspects cannot be reasonably covered within the book chapter word count, so be selective and concentrate on key aspects that address the question in the sub-title. There may be too much background material planned. Abbreviate the general sexual motivations and description of sex work services to concentrate on theory and research about the motivations of SWS clients. <!-- Conclusion --> # Conclusion hasn't been developed # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> # Excellent - Relevant figure(s) presented, captioned, and cited <!-- Caption --> # Figure caption(s) grammatical error <!-- Cite --> # Figure(s) are cited at least once in the main text |6= <!-- Learning feature --> <!-- Interwiki links ---> # Two in-text [[m:Help:Interwiki linking|interwiki links]] for first mention of key terms to [[w:|Wikipedia]]. Also embed links to [[Motivation and emotion/Book|book chapters]]. <!-- Scenarios/examples/case studies --> # Consider incorporating additional scenarios, examples, or case studies to illustrate key concepts. These could build on the Overview scenario or introduce new real-world situations in the main body of the chapter to demonstrate how the concepts apply in practice. <!-- Quiz --> # Promising use of quiz question(s) # Place each quiz question in the most relevant section # Focus the quiz question(s) on the take-home messages <!-- Tables --> # Also consider using [[Motivation and emotion/Wikiversity/Tables|table(s)]] to summarise key information |7= <!-- References --> <!-- Overall --> # Very good <!-- Systematic reviews --> # What are the most relevant systematic reviews/meta-analyses about this topic? <!-- APA style --> # Check and correct [https://apastyle.apa.org/instructional-aids/reference-guide.pdf APA referencing style]: ## [[Help:Wikitext quick reference|italicisation]] |8= <!-- Resources --> <!-- See also --> # See also ## Excellent # External links ## Excellent <!-- User page --> # Excellent <!-- Description about self --> # Excellent description about self provided <!-- 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 |10= <!-- Social contribution --> # Excellent – at least three different types of contributions with direct link(s) to evidence }} == Feedback == This is a really interesting topic and I really enjoyed what you have so far! A few suggestions: - in the pink overview box, ensure your citations are before the full stop. - in the sexual motivation section, you could mention LGBTQIA+ relationships alongside heteronormative relationships for example saying something along the lines of "this perception has expanded over time to include LGBTQIA+ relationships". - Inserting Buss and Schmitt's (1993) spectrum of mating relationships as a figure would greatly strengthen this point and help visual learners. - Include some examples of the 237 motivations humans have for engaging in sexual activity according to Meston and Buss (2007) to strengthen this point. - change the heading 'theory of sexual motivation' to 'theories of sexual motivation' as you discuss multiple theories. - There are a few typos and grammatical issues at the end of your 'theory of sexual motivation' section but I assume this is because they are notes of what you are planning to write - Ensure your (Kingston, Hammond & Redman, 2021) citation is consistent with APA 7th Well done so far and keep up the good work! [[User:U3254168|U3254168]] ([[User talk:U3254168|discuss]] • [[Special:Contributions/U3254168|contribs]]) 02:58, 30 September 2026 (UTC) l3fx6x48wlibkj85bj11em4hxkel34d 1 331614 2835140 2832012 2026-09-30T09:01:33Z U3254168 3106320 /* Feedback */ new section 2835140 wikitext text/x-wiki == An Australian source on gender and race interacting == Hi U3242837, Your sub-title asks under what conditions achievement motivation is expressed, so you may already be thinking about context. If you want a recent Australian study where gender and race interact rather than operate separately, this one is useful: * Guerzoni, M. A., Prehn, J., & Peacock, H. (2024). Mothers and sportsmen: The gendered and racialised nature of role model selection for Aboriginal and/or Torres Strait Islander youths. ''Australian Journal of Social Issues, 59''(2), 281–296. https://doi.org/10.1002/ajs4.311 They found role model selection among Aboriginal and Torres Strait Islander young people is strongly gendered - family members, particularly mothers, and male sportspeople dominate nominations - which has consequences for whose achievement gets modelled as attainable. Stronach et al. (2023) pairs well with it if you want a media angle: * Stronach, M., O'Shea, M., & Maxwell, H. (2023). 'You can't be what you can't see': Indigenous Australian sportswomen as powerful role models. ''Sport in Society, 26''(6), 970–984. https://doi.org/10.1080/17430437.2022.2088356 I am writing [[Motivation and emotion/Book/2026/Indigenous Australian role models and motivation|Indigenous Australian role models and motivation]] if any of that is useful to you. [[User:Jshottt|Jshottt]] ([[User talk:Jshottt|discuss]] • [[Special:Contributions/Jshottt|contribs]]) 14:23, 27 August 2026 (UTC) == Heading casing == {| style="float: center; background:transparent;color:inherit;" |- | [[File:Crystal Clear app ktip.svg|48px|left]] | {{#if:U3242837|Hi [[User:U3242837|U3242837]].|}} FYI, the recommended [[Wikiversity]] heading style uses [[w:Letter case#Sentence_case|sentence casing]]. For example:<br> <big><big>Self-determination theory</big></big> rather than <big><big>Self-Determination Theory</big></big> Here's an example chapter with correct heading casing: [[Motivation and emotion/Book/2019/Growth mindset development|Growth mindset development]] -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 12:30, 7 September 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 --> # See earlier comment about [[#heading casing|heading casing]] <!-- Heading structure --> <!-- 2-level --> # Promising [[Motivation and emotion/Assessment/Major project/Structure|2-level heading structure]] – could benefit from further development and/or refinement <!-- Alignment with focus questions --> # Insufficient alignment between sub-title, focus questions, and top-level headings <!-- GenAI ---> # Are the headings based on [[Motivation and emotion/Assessment/Using generative AI|genAI content]]? If so, this needs to be acknowledged in the edit summaries, otherwise it violates academic integrity. |3= <!-- Overview--> # Basic <!-- 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 --> # A basic description of the problem/topic is planned or presented <!-- Focus questions --> # Develop closer alignment between the sub-title, focus questions, and top-level headings |4= <!-- Key points--> <!-- Overall --> # Basic development # What are the differences in achievement motivation between genders? <!-- Scope --> # The scope is limited; I think a clearer understanding of what the gender differences are and how theory and research accounts for those differences is needed # Some cultural context is needed; do the gender d9fferences vary between cultures # Consider the role of self-concept <!-- Theory and research --> # Strive for an integrated balance of the best psychological theory and research about this topic, with practical examples. <!-- Other --> # For sections with sub-sections, provide key points for an overview paragraph prior to branching into the sub-headings # Use correct capitalisation ([https://apastyle.apa.org/style-grammar-guidelines/capitalization APA style is a "down" style]) – [https://polishedpaper.com/blog/capitalization-apa-style more info] <!-- Conclusion --> # Conclusion hasn't been developed # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> <!-- Caption --> # Figure caption(s) could better explain how the image connects to key points being made in the main text # Figure caption(s) should include '''Figure X'''. [bold] ... <!-- Cite --> # Cite each figure at least once in the main text using APA style (e.g., see Figure 1) |6= <!-- Learning feature --> <!-- Interwiki links ---> # One in-text [[m:Help:Interwiki linking|interwiki link]] for first mention of key term to [[w:|Wikipedia]]. Also embed links to [[Motivation and emotion/Book|book chapters]]. <!-- Scenarios/examples/case studies --> # Consider incorporating additional scenarios, examples, or case studies to illustrate key concepts. These could build on the Overview scenario or introduce new real-world situations in the main body of the chapter to demonstrate how the concepts apply in practice. <!-- Quiz --> # Consider including quiz question(s) about the take-home messages <!-- Tables --> # Also consider using tables to summarise key information |7= <!-- References --> <!-- Overall --> # Basic # Only cite sources that you have consulted # To be developed <!-- Systematic reviews --> # What are the most relevant systematic reviews/meta-analyses about this topic? <!-- APA style --> # Check and correct [https://apastyle.apa.org/instructional-aids/reference-guide.pdf APA referencing style]: ## capitalisation ## [[Help:Wikitext quick reference|italicisation]] ## make doi hyperlinks active (i.e., clickable) ## use dois where available instead of other links # A more thorough literature search is recommended. The goal is to identify and use the best academic theory and research about this topic. |8= <!-- Resources --> <!-- See also --> # See also ## Good ## Use bullet-points (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Use [[w:Letter case#Sentence casing|sentence casing]] ## Rename links so that they are more user friendly (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Use alphabetical order <!-- External links --> # External links ## To be developed (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Link to the most relevant external resources about this topic |9= <!-- User page --> # Excellent <!-- Description about self --> # Description about self provided <!-- 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 |10= <!-- Social contribution --> # Good – two out of three types of contributions made with direct link(s) to evidence. The other type of contribution is making: #* direct improvements to other [[Motivation and emotion/Book|chapters (past or current)]] # To add direct links to evidence of Wikiversity edits or comments: view the page history, select the version of the page before and after your contributions, click "compare selected revisions", and paste the comparison URL on your user page. For more info, see [[Motivation and emotion/Assessment/Chapter#Making and summarising social contributions|Making and summarising social contributions]]. This was demonstrated in [[Motivation and emotion/Tutorials/Wiki editing#Social contributions|Tutorial 2]]. }} -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 12:30, 7 September 2026 (UTC) == Feedback == I look forward to reading this chapter when it is complete! If you wanted to broaden the applicability of this chapter you could also look into whether the phenomenon you describe also apply in transgender people or whether it is based on biological sex. I found the below dissertation on this topic - whilst it may only be a dissertation it provides an interesting lens. https://scholarworks.waldenu.edu/cgi/viewcontent.cgi?article=14660&context=dissertations [[User:U3254168|U3254168]] ([[User talk:U3254168|discuss]] • [[Special:Contributions/U3254168|contribs]]) 09:01, 30 September 2026 (UTC) lgub47whllo5887gt3bwytscxj9pmqk 0 331630 2835061 2834388 2026-09-29T14:36:42Z UU3231448 3110120 2835061 wikitext text/x-wiki {{title|Reinforcement sensitivity theory:<br>How does reinforcement sensitivity theory explain individual differences in motivation and emotion?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} Case Study Imagine two students are given the opportunity to give a presentation in front of their class. Patricia is excited about the possibility of receiving praise from her teacher and getting a good grade, so they confidently put their hand up first to present. This shows a stronger Behavioural Activation System (BAS) response to the reward. Ben becomes nervous because they are worried about making a mistake and being judged, so he hesitate's more and consider the possible consequences of not doing a good job. This demonstrates the Behavioural Inhibition System (BIS). If Ben felt an immediate need to escape the situation because they felt threatened, this then could involve the Fight–Flight–Freeze System (FFFS). {{RoundBoxBottom}} Reinforcement Sensitivity Theory (RST) is a biological theory of personality originally developed by psychologist Jeffrey Gray to explain individual differences in personality, especially when looking at motivation, emotion, and behaviour. RST proposes that people differ in the sensitivity of their brain-based motivational systems, this means that individuals may respond differently to rewards, punishment, threats, and situations involving uncertainty or grey areas (Gray, 1970; Corr, 2004). RST developed from earlier theories of personality and learning, and has since undergone significant revisions. These revisions  particularly focused through the work of Gray and McNaughton (2000). The revised theory identifies three different major systems: the Behavioural Activation System (BAS), the Behavioural Inhibition System (BIS), and the Fight–Flight–Freeze System (FFFS). Together the three systems help explain how people approach desirable outcomes, respond to conflict and uncertainty, as well as protect themselves from threatening or aversive situations. Those systems '''Behavioural Activation System (BAS),''' which motivates approach towards rewards; the '''Behavioural Inhibition System (BIS'''), which responds to conflict and potential threats; and the '''Fight–Flight–Freeze System (FFFS)''', which responds to immediate threats and punishment. Overall, RST suggests that these systems influence how individuals make decisions as well as respond emotionally and behaviour in different situations (Gray & McNaughton, 2000). {{RoundBoxTop|theme=3}} '''Focus questions''' {{ic|}} What is Reinforcement Sensitivity Theory (RST), and who developed it? How do the BAS, BIS, and FFFS influence behaviour? How does sensitivity to reward and punishment differ between individuals? How can RST explain differences in personality and emotional responses? How can RST be applied to real-life situations and everyday behaviour? {{RoundBoxBottom}} ==Reinforcement Sensitivity Theory == The '''Behavioural Activation System (BAS)''' is primarily associated with sensitivity to rewards and appetitive stimuli. It motivates individuals to move towards desirable goals and positive outcomes and is associated with approach-related behaviours such as reward seeking, goal pursuit, excitement, and motivation (Gray & McNaughton, 2000; Corr, 2004). Individuals with a greater BAS sensitivity may therefore be more responsive to opportunities for reward and may be more likely to actively pursue pleasurable or desirable experiences. Research has also linked BAS sensitivity with aspects of personality such as extraversion, impulsivity, and reward responsiveness, although the exact relationship depends on how BAS is measured (Corr, 2004; Smillie et al., 2006). The '''Behavioural Inhibition System (BIS''') is associated with situations involving conflict, uncertainty, and competing behavioural goals. Rather than simply responding to punishment, as was emphasised in earlier versions of RST, the revised theory proposes that the BIS becomes particularly important when an individual experiences a conflict between approach and avoidance tendencies (Gray & McNaughton, 2000). For example, a person may want to approach a social situation because it could provide a reward but simultaneously want to avoid it because they are worried about being judged. Activation of the BIS can result in an increase of attention, caution, risk assessment, worry, and anxiety while the individual attempts to resolve the conflict (Corr, 2004; McNaughton & Corr, 2004). The '''Fight–Flight–Freeze System (FFFS)''' is primarily responsible for responding to aversive and threatening stimuli and is associated with fear and defensive behaviour. When an individual encounters an immediate threat, the FFFS can motivate behaviours such as fighting, escaping, avoiding, or freezing in response to danger (Gray & McNaughton, 2000). An important development in revised RST was the separation of the FFFS from the BIS. The FFFS is more closely associated with direct fear and avoidance of threats, whereas the BIS is associated with anxiety arising from conflict and uncertainty (Corr, 2004; Smillie et al., 2006). This distinction allows RST to provide a more detailed explanation of why people can experience different emotional and behavioural responses to threatening situations. == Behavioural Activation System == ''The Behavioural Activation System (BAS) stands for Behavioural Activation System and is one of the major motivational systems described within Jeffrey Gray’s Reinforcement Sensitivity Theory (RST). The BAS is primarily concerned with sensitivity to rewards and appetitive stimuli, encouraging individuals to move towards desirable outcomes rather than away from them (Gray, 1970; Corr, 2008). According to RST, the BAS becomes activated when the  individual perceives a possibility of obtaining something desirable. This could be anything from money, to social approval, success, food, pleasurable experiences, or new opportunities. Rather than simply responding to rewards after they have been received, the BAS is particularly important for motivating behaviour when a reward is anticipated or considered achievable (Gray & McNaughton, 2000).'' ''BAS activation can also occur in response to cues that signal the potential possibility of receiving a reward. These cues as mentioned may include seeing an opportunity to receiving positive feedback or recognising that a particular behaviour could lead to a desirable consequence. This means that BAS activity can then influence behaviour before the reward is actually obtained.'' ''Individual differences in BAS sensitivity make up an important component of RST. People differ in how strongly they respond to reward-related cues, meaning that the same opportunity may produce different levels of motivation in different individuals (Corr, 2004). A person with relatively higher BAS sensitivity may respond particularly strongly to opportunities for reward, as well as may be more motivated to pursue positive outcomes. They may be more likely to seek out exciting or enjoyable experiences, take advantage of opportunities that could produce positive consequences, and respond strongly to praise, achievement, recognition, or other forms of positive reinforcement. They may also be quicker to initiate behaviour when a potentially rewarding opportunity becomes available (Corr, 2008; Smillie et al., 2006).'' == Fight-Flight-Freeze System == ''The Fight–Flight–Freeze System (FFFS) is another of the three major motivational and defensive systems identified in the revised version of Jeffrey Gray’s Reinforcement Sensitivity Theory (RST), focusing more through the work of Gray and McNaughton (2000). The FFFS’s primary concern is with responding to aversive stimuli, such as threats, fear and punishment, and its central function is to protect the individual from immediate danger by producing defensive responses (Gray & McNaughton, 2000; Corr, 2004). Unlike the before mentioned Behavioural Inhibition System (BIS), which is primarily associated with conflict and uncertainty in situations, in which competing behavioural tendencies need to be resolved, the FFFS is then activated by stimuli that are perceived as directly threatening or aversive (McNaughton & Corr, 2004; Corr & McNaughton, 2008). When a person encounters an immediate threat, the FFFS can produce rapid defensive responses that are commonly described as fight, flight, or freeze. The fight response involves confronting or attempting to defend against the source of danger, while the flight response involves escaping or moving away from the threatening stimulus. The freeze response involves becoming temporarily still, reducing movement, or experiencing a temporary inability to initiate an immediate behavioural response when confronted with danger (Gray & McNaughton, 2000; Kozlowska et al., 2015). These responses can be understood as different defensive strategies that may be selected depending on the characteristics and perceived proximity of the threat.'' ''For example, if an individual encounters an aggressive person, they may attempt to defend themselves, escape from the situation, or momentarily freeze while assessing what to do next. The FFFS is therefore closely associated with fear and defensive behaviour, whereas anxiety is more strongly associated with BIS activation when there is conflict or uncertainty about what action should be taken (McNaughton & Corr, 2004; Corr, 2008). This distinction between fear and anxiety represents an important development in the revised RST because earlier versions of Gray’s theory placed greater emphasis on the BIS as a system responding to punishment, whereas the revised model separated immediate fear responses from anxiety-related conflict processing (Gray & McNaughton, 2000; Corr, 2004). FFFS activation can occur rapidly because detecting and responding to potential danger can be important for survival, particularly when an individual encounters a threat that requires immediate action (LeDoux, 2012). From an evolutionary perspective, defensive responses such as fighting or escaping can help an organism avoid injury or remove itself from a dangerous environment, while freezing may provide an alternative response when immediate movement is not possible or may increase danger (Blanchard et al., 2001; Kozlowska et al., 2015). Corr, 2004). Overall, the FFFS provides an important component of RST by explaining how individuals detect and respond to immediate threats, punishment, and aversive stimuli.'' == Behavioural Inhibition System == ''The Behavioural Inhibition System (BIS) is the last of the three major systems within the revised version of Jeffrey Gray’s Reinforcement Sensitivity Theory (RST) and is primarily involved in responding to conflict, uncertainty, and situations in which an individual has  to evaluate competing behavioural options (Gray & McNaughton, 2000; McNaughton & Corr, 2004). Rather than simply causing a person to stop behaving, the BIS is supposed to interrupt or slow ongoing behaviour when an individual encounters a situation that requires further evaluation, thus allowing them to assess  further potential risks and determine an appropriate response (Corr, 2004). The BIS is particularly relevant when a person experiences competing motivational tendencies, such as wanting to approach a potentially rewarding situation while simultaneously wanting to avoid a possible negative outcome. This is known as an approach–avoidance conflict, where the same situation contains both desirable and undesirable consequences (Gray & McNaughton, 2000). For example, a student may want to answer a question in class because they could receive recognition for providing the correct answer, but may also worry about embarrassment if they are incorrect. The conflict between the potential reward of answering and the potential negative consequence of making a mistake can result in increased BIS activity and greater caution before acting. The BIS may also become relevant during avoidance–avoidance conflicts, in which an individual must choose between two undesirable outcomes, as well as during situations involving uncertainty about what will happen next (McNaughton & Corr, 2004).'' ''This makes the BIS particularly important for situations where the appropriate behavioural response is unclear. Activation of the BIS is associated with psychological experiences such as anxiety, worry, cautiousness, vigilance, and increased attention to potentially relevant environmental information (Gray & McNaughton, 2000; Corr, 2011). Importantly, the revised RST distinguishes BIS-related anxiety from the fear response associated with the Fight–Flight–Freeze System (FFFS). Whereas the FFFS is primarily responsible for immediate defensive responses to direct threats, the BIS is activated when there is conflict between competing behavioural tendencies or uncertainty regarding the appropriate response (McNaughton & Corr, 2004; Corr & McNaughton, 2008). Consequently, BIS activation does not necessarily result in immediate escape or avoidance; instead, the BIS encourages the individual to pause, gather information, assess potential consequences, and determine which behavioural response is most appropriate (Corr, 2011). The BIS has therefore been described as an important system for conflict detection and resolution, allowing behaviour to be adjusted when an individual's existing response tendencies are insufficient to deal with a particular situation (Gray & McNaughton, 2000).'' == Figures == * For the topic development, use at least one figure (even if not ideal) to show that you know how to embed, caption, and cite a figure; this can be the figure in the scenario * For the book chapter, use several figures to illustrate concepts, add interest, and to serve as examples * Images must be embedded from [[commons:|Wikimedia Commons]] which hosts free-to-use media such as photos, diagrams, graphs, video, and audio[[File:Reinforcement learning diagram.svg|thumb|140x140px|'''Figure 2'''. Example of an image with a descriptive caption.]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Embed figures throughout the chapter, starting with the scenario in the Overview section * Provide descriptive figure captions (use '''Figure #''' and explain the relevance of the image to the text) * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Learning features help to bring book chapters to life and can be embedded throughout the chapter. Here are some options: {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples that illustrate concepts in action * Present using [[#Feature boxes|feature boxes]]; can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Can be real or fictional; if real, provide citation(s) {{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 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 Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing the Relationship Between Known/Unknown and 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 * 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 the 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> {The purpose of quizzes is to provide an interactive learning feature: |type="()"} + True - False {Long and complex quiz questions are recommended: |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== {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} [[Anxiety]] (Wikiversity) [[wikipedia:Gray's_biopsychological_theory_of_personality|Jeffery Gray's Behavioural Action/Inhibition Theory]] (Wikiversity) [[wikipedia:Reinforcement_sensitivity_theory|Reinforcement Sensitivity Theory]] (Wikipedia) ==References== {{Hanging indent|1= Corr, P. J. (Ed.). (2008). The reinforcement sensitivity theory of personality. Cambridge University Press. https://doi.org/10.1017/CBO9780511819389 Gray, J. A. (1982). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system. Oxford University Press. Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). Oxford University Press. Smillie, L. D., Pickering, A. D., & Jackson, C. J. (2006). The new Reinforcement Sensitivity Theory: Implications for personality measurement. Personality and Social Psychology Review, 10(4), 320–335. https://doi.org/10.1207/s15327957pspr1004_3 Corr, P. J. (2004). Reinforcement sensitivity theory and personality. Neuroscience & Biobehavioral Reviews, 28(3), 317–332. https://doi.org/10.1016/j.neubiorev.2004.01.005 Firth, J., Standen, B., Sumich, A., Fino, E., & Heym, N. (2024). The neural correlates of reinforcement sensitivity theory: A systematic review of the frontal asymmetry and spectral power literature. Psychophysiology, 61(9), e14594. https://doi.org/10.1111/psyp.14594 Gray, J. A. (1970). The psychophysiological basis of introversion-extraversion. Behaviour Research and Therapy, 8(3), 249–266. https://doi.org/10.1016/0005-7967(70)90069-0 Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). Oxford University Press. McNaughton, N., & Corr, P. J. (2004). A two-dimensional neuropsychology of defense: Fear/anxiety and defensive distance. Neuroscience & Biobehavioral Reviews, 28(3), 285–305. https://doi.org/10.1016/j.neubiorev.2004.03.005 Smillie, L. D., Pickering, A. D., & Jackson, C. J. (2006). The new reinforcement sensitivity theory: Implications for personality measurement. Personality and Social Psychology Review, 10(4), 320–335. https://doi.org/10.1207/s15327957pspr1004_3 Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. Journal of Personality and Social Psychology, 67(2), 319–333. https://doi.org/10.1037/0022-3514.67.2.319 Corr, P. J. (2004). Reinforcement sensitivity theory and personality. Neuroscience & Biobehavioral Reviews, 28(3), 317–332. https://doi.org/10.1016/j.neubiorev.2004.01.005 Corr, P. J. (2008). The reinforcement sensitivity theory of personality. Cambridge University Press. Gray, J. A. (1970). The psychophysiological basis of introversion-extraversion. Behaviour Research and Therapy, 8(3), 249–266. https://doi.org/10.1016/0005-7967(70)90069-0 Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). Oxford University Press. Smillie, L. D., & Jackson, C. J. (2006). Functional impulsivity and reinforcement sensitivity theory. Journal of Personality, 74(1), 47–84. https://doi.org/10.1111/j.1467-6494.2005.00369.x Smillie, L. D., Pickering, A. D., & Jackson, C. J. (2006). The new reinforcement sensitivity theory: Implications for personality measurement. Personality and Social Psychology Review, 10(4), 320–335. https://doi.org/10.1207/s15327957pspr1004_3 Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. Journal of Personality and Social Psychology, 67(2), 319–333. https://doi.org/10.1037/0022-3514.67.2.319 Corr, P. J. (2008). The reinforcement sensitivity theory of personality. Cambridge University Press. Corr, P. J. (2011). Anxiety: Splitting the phenomenological atom. Personality and Individual Differences, 50(7), 889–897. https://doi.org/10.1016/j.paid.2010.09.013 Corr, P. J., & McNaughton, N. (2008). Reinforcement sensitivity theory and personality. In G. J. Boyle, G. Matthews, & D. H. Saklofske (Eds.), The SAGE handbook of personality theory and assessment: Vol. 1. Personality theories and models (pp. 155–187). SAGE. De Pascalis, V., Strippoli, E., Riccardi, P., & Vergari, M. (2000). Psychophysiological responses to emotional stimuli in subjects with different levels of anxiety. Personality and Individual Differences, 28(3), 529–544. https://doi.org/10.1016/S0191-8869(99)00114-8 Gray, J. A. (1982). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system. Oxford University Press. Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). Oxford University Press. McNaughton, N., & Corr, P. J. (2004). A two-dimensional neuropsychology of defense: Fear/anxiety and defensive distance. Neuroscience & Biobehavioral Reviews, 28(3), 285–305. https://doi.org/10.1016/j.neubiorev.2004.03.005 }} ==External links== {{expand}} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Reward]] 63zcbwdfxk1rfzo2uzb3wpkl7iblz9v 2835063 2835061 2026-09-29T15:29:18Z UU3231448 3110120 added a table for easier understanding of the different systems 2835063 wikitext text/x-wiki {{title|Reinforcement sensitivity theory:<br>How does reinforcement sensitivity theory explain individual differences in motivation and emotion?}} __TOC__ ==Overview== {{RoundBoxTop|theme=3}} Case Study Imagine two students are given the opportunity to give a presentation in front of their class. Patricia is excited about the possibility of receiving praise from her teacher and getting a good grade, so they confidently put their hand up first to present. This shows a stronger Behavioural Activation System (BAS) response to the reward. Ben becomes nervous because they are worried about making a mistake and being judged, so he hesitate's more and consider the possible consequences of not doing a good job. This demonstrates the Behavioural Inhibition System (BIS). If Ben felt an immediate need to escape the situation because they felt threatened, this then could involve the Fight–Flight–Freeze System (FFFS). {{RoundBoxBottom}} Reinforcement Sensitivity Theory (RST) is a biological theory of personality originally developed by psychologist Jeffrey Gray to explain individual differences in personality, especially when looking at motivation, emotion, and behaviour. RST proposes that people differ in the sensitivity of their brain-based motivational systems, this means that individuals may respond differently to rewards, punishment, threats, and situations involving uncertainty or grey areas (Gray, 1970; Corr, 2004). RST developed from earlier theories of personality and learning, and has since undergone significant revisions. These revisions  particularly focused through the work of Gray and McNaughton (2000). The revised theory identifies three different major systems: the Behavioural Activation System (BAS), the Behavioural Inhibition System (BIS), and the Fight–Flight–Freeze System (FFFS). Together the three systems help explain how people approach desirable outcomes, respond to conflict and uncertainty, as well as protect themselves from threatening or aversive situations. Those systems '''Behavioural Activation System (BAS),''' which motivates approach towards rewards; the '''Behavioural Inhibition System (BIS'''), which responds to conflict and potential threats; and the '''Fight–Flight–Freeze System (FFFS)''', which responds to immediate threats and punishment. Overall, RST suggests that these systems influence how individuals make decisions as well as respond emotionally and behaviour in different situations (Gray & McNaughton, 2000). {{RoundBoxTop|theme=3}} '''Focus questions''' {{ic|}} What is Reinforcement Sensitivity Theory (RST), and who developed it? How do the BAS, BIS, and FFFS influence behaviour? How does sensitivity to reward and punishment differ between individuals? How can RST explain differences in personality and emotional responses? How can RST be applied to real-life situations and everyday behaviour? {{RoundBoxBottom}} ==Reinforcement Sensitivity Theory == The '''Behavioural Activation System (BAS)''' is primarily associated with sensitivity to rewards and appetitive stimuli. It motivates individuals to move towards desirable goals and positive outcomes and is associated with approach-related behaviours such as reward seeking, goal pursuit, excitement, and motivation (Gray & McNaughton, 2000; Corr, 2004). Individuals with a greater BAS sensitivity may therefore be more responsive to opportunities for reward and may be more likely to actively pursue pleasurable or desirable experiences. Research has also linked BAS sensitivity with aspects of personality such as extraversion, impulsivity, and reward responsiveness, although the exact relationship depends on how BAS is measured (Corr, 2004; Smillie et al., 2006). The '''Behavioural Inhibition System (BIS''') is associated with situations involving conflict, uncertainty, and competing behavioural goals. Rather than simply responding to punishment, as was emphasised in earlier versions of RST, the revised theory proposes that the BIS becomes particularly important when an individual experiences a conflict between approach and avoidance tendencies (Gray & McNaughton, 2000). For example, a person may want to approach a social situation because it could provide a reward but simultaneously want to avoid it because they are worried about being judged. Activation of the BIS can result in an increase of attention, caution, risk assessment, worry, and anxiety while the individual attempts to resolve the conflict (Corr, 2004; McNaughton & Corr, 2004). The '''Fight–Flight–Freeze System (FFFS)''' is primarily responsible for responding to aversive and threatening stimuli and is associated with fear and defensive behaviour. When an individual encounters an immediate threat, the FFFS can motivate behaviours such as fighting, escaping, avoiding, or freezing in response to danger (Gray & McNaughton, 2000). An important development in revised RST was the separation of the FFFS from the BIS. The FFFS is more closely associated with direct fear and avoidance of threats, whereas the BIS is associated with anxiety arising from conflict and uncertainty (Corr, 2004; Smillie et al., 2006). This distinction allows RST to provide a more detailed explanation of why people can experience different emotional and behavioural responses to threatening situations. == Behavioural Activation System == ''The Behavioural Activation System (BAS) stands for Behavioural Activation System and is one of the major motivational systems described within Jeffrey Gray’s Reinforcement Sensitivity Theory (RST). The BAS is primarily concerned with sensitivity to rewards and appetitive stimuli, encouraging individuals to move towards desirable outcomes rather than away from them (Gray, 1970; Corr, 2008). According to RST, the BAS becomes activated when the  individual perceives a possibility of obtaining something desirable. This could be anything from money, to social approval, success, food, pleasurable experiences, or new opportunities. Rather than simply responding to rewards after they have been received, the BAS is particularly important for motivating behaviour when a reward is anticipated or considered achievable (Gray & McNaughton, 2000).'' ''BAS activation can also occur in response to cues that signal the potential possibility of receiving a reward. These cues as mentioned may include seeing an opportunity to receiving positive feedback or recognising that a particular behaviour could lead to a desirable consequence. This means that BAS activity can then influence behaviour before the reward is actually obtained.'' ''Individual differences in BAS sensitivity make up an important component of RST. People differ in how strongly they respond to reward-related cues, meaning that the same opportunity may produce different levels of motivation in different individuals (Corr, 2004). A person with relatively higher BAS sensitivity may respond particularly strongly to opportunities for reward, as well as may be more motivated to pursue positive outcomes. They may be more likely to seek out exciting or enjoyable experiences, take advantage of opportunities that could produce positive consequences, and respond strongly to praise, achievement, recognition, or other forms of positive reinforcement. They may also be quicker to initiate behaviour when a potentially rewarding opportunity becomes available (Corr, 2008; Smillie et al., 2006).'' == Fight-Flight-Freeze System == ''The Fight–Flight–Freeze System (FFFS) is another of the three major motivational and defensive systems identified in the revised version of Jeffrey Gray’s Reinforcement Sensitivity Theory (RST), focusing more through the work of Gray and McNaughton (2000). The FFFS’s primary concern is with responding to aversive stimuli, such as threats, fear and punishment, and its central function is to protect the individual from immediate danger by producing defensive responses (Gray & McNaughton, 2000; Corr, 2004). Unlike the before mentioned Behavioural Inhibition System (BIS), which is primarily associated with conflict and uncertainty in situations, in which competing behavioural tendencies need to be resolved, the FFFS is then activated by stimuli that are perceived as directly threatening or aversive (McNaughton & Corr, 2004; Corr & McNaughton, 2008). When a person encounters an immediate threat, the FFFS can produce rapid defensive responses that are commonly described as fight, flight, or freeze. The fight response involves confronting or attempting to defend against the source of danger, while the flight response involves escaping or moving away from the threatening stimulus. The freeze response involves becoming temporarily still, reducing movement, or experiencing a temporary inability to initiate an immediate behavioural response when confronted with danger (Gray & McNaughton, 2000; Kozlowska et al., 2015). These responses can be understood as different defensive strategies that may be selected depending on the characteristics and perceived proximity of the threat.'' ''For example, if an individual encounters an aggressive person, they may attempt to defend themselves, escape from the situation, or momentarily freeze while assessing what to do next. The FFFS is therefore closely associated with fear and defensive behaviour, whereas anxiety is more strongly associated with BIS activation when there is conflict or uncertainty about what action should be taken (McNaughton & Corr, 2004; Corr, 2008). This distinction between fear and anxiety represents an important development in the revised RST because earlier versions of Gray’s theory placed greater emphasis on the BIS as a system responding to punishment, whereas the revised model separated immediate fear responses from anxiety-related conflict processing (Gray & McNaughton, 2000; Corr, 2004). FFFS activation can occur rapidly because detecting and responding to potential danger can be important for survival, particularly when an individual encounters a threat that requires immediate action (LeDoux, 2012). From an evolutionary perspective, defensive responses such as fighting or escaping can help an organism avoid injury or remove itself from a dangerous environment, while freezing may provide an alternative response when immediate movement is not possible or may increase danger (Blanchard et al., 2001; Kozlowska et al., 2015). Corr, 2004). Overall, the FFFS provides an important component of RST by explaining how individuals detect and respond to immediate threats, punishment, and aversive stimuli.'' == Behavioural Inhibition System == ''The Behavioural Inhibition System (BIS) is the last of the three major systems within the revised version of Jeffrey Gray’s Reinforcement Sensitivity Theory (RST) and is primarily involved in responding to conflict, uncertainty, and situations in which an individual has  to evaluate competing behavioural options (Gray & McNaughton, 2000; McNaughton & Corr, 2004). Rather than simply causing a person to stop behaving, the BIS is supposed to interrupt or slow ongoing behaviour when an individual encounters a situation that requires further evaluation, thus allowing them to assess  further potential risks and determine an appropriate response (Corr, 2004). The BIS is particularly relevant when a person experiences competing motivational tendencies, such as wanting to approach a potentially rewarding situation while simultaneously wanting to avoid a possible negative outcome. This is known as an approach–avoidance conflict, where the same situation contains both desirable and undesirable consequences (Gray & McNaughton, 2000). For example, a student may want to answer a question in class because they could receive recognition for providing the correct answer, but may also worry about embarrassment if they are incorrect. The conflict between the potential reward of answering and the potential negative consequence of making a mistake can result in increased BIS activity and greater caution before acting. The BIS may also become relevant during avoidance–avoidance conflicts, in which an individual must choose between two undesirable outcomes, as well as during situations involving uncertainty about what will happen next (McNaughton & Corr, 2004).'' ''This makes the BIS particularly important for situations where the appropriate behavioural response is unclear. Activation of the BIS is associated with psychological experiences such as anxiety, worry, cautiousness, vigilance, and increased attention to potentially relevant environmental information (Gray & McNaughton, 2000; Corr, 2011). Importantly, the revised RST distinguishes BIS-related anxiety from the fear response associated with the Fight–Flight–Freeze System (FFFS). Whereas the FFFS is primarily responsible for immediate defensive responses to direct threats, the BIS is activated when there is conflict between competing behavioural tendencies or uncertainty regarding the appropriate response (McNaughton & Corr, 2004; Corr & McNaughton, 2008). Consequently, BIS activation does not necessarily result in immediate escape or avoidance; instead, the BIS encourages the individual to pause, gather information, assess potential consequences, and determine which behavioural response is most appropriate (Corr, 2011). The BIS has therefore been described as an important system for conflict detection and resolution, allowing behaviour to be adjusted when an individual's existing response tendencies are insufficient to deal with a particular situation (Gray & McNaughton, 2000).'' == Figures == * For the topic development, use at least one figure (even if not ideal) to show that you know how to embed, caption, and cite a figure; this can be the figure in the scenario * For the book chapter, use several figures to illustrate concepts, add interest, and to serve as examples * Images must be embedded from [[commons:|Wikimedia Commons]] which hosts free-to-use media such as photos, diagrams, graphs, video, and audio[[File:Reinforcement learning diagram.svg|thumb|140x140px|'''Figure 2'''. Example of an image with a descriptive caption.]] * Images can be uploaded to [[commons:|Wikimedia Commons]] if they are openly licensed * Embed figures throughout the chapter, starting with the scenario in the Overview section * Provide descriptive figure captions (use '''Figure #''' and explain the relevance of the image to the text) * Cite each figure at least once in the main text (e.g., see Figure 2) ==Learning features== Learning features help to bring book chapters to life and can be embedded throughout the chapter. Here are some options: {{anchor|Scenarios}} ;Scenarios * Scenarios, case studies, or examples that illustrate concepts in action * Present using [[#Feature boxes|feature boxes]]; can be split into multiple boxes throughout a chapter (e.g., to illustrate different theories or stages) * Can be real or fictional; if real, provide citation(s) {{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 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 Explains The Table Contents and its Relevance to the Text e.g., The 2 x 2 Johari Window Model Showing the Relationship Between Known/Unknown and Self/Other {| class="wikitable" style="margin: auto; |- ! System !! What It Responds To !! Primary Function !Typical Emotional Response !Typical Behaviour |- | '''Behavioural Activation System (BAS)''' || Rewards, appetitive, Stimuli, Opportunities for positive outcomes. || Motivates towards desirable goals. |Excitement/Enthusiasm |Approach, reward seeking, goal pursuit |- |'''Behavioural Inhibition System (BIS)''' |Conflict, uncertainty, competing goals as well as ambiguous situation. |Detects and resolves conflict between competing behavioural tendencies. |Anxiety, worry, and caution. |Pausing, evaluating, and increased attention. |- | '''Fight-Flight-Freeze System (FFFS)''' || Immediate threats, aversive stimuli, danger and punishment. || Protects the individual from direct threats. |Fear and Panic. |Fight, flight, freeze, avoidance. |} ;Quizzes * 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 the 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> {The purpose of quizzes is to provide an interactive learning feature: |type="()"} + True - False {Long and complex quiz questions are recommended: |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== {{ic|Use bullet points as shown in [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]}} [[Anxiety]] (Wikiversity) [[wikipedia:Gray's_biopsychological_theory_of_personality|Jeffery Gray's Behavioural Action/Inhibition Theory]] (Wikiversity) [[wikipedia:Reinforcement_sensitivity_theory|Reinforcement Sensitivity Theory]] (Wikipedia) ==References== {{Hanging indent|1= Corr, P. J. (Ed.). (2008). The reinforcement sensitivity theory of personality. Cambridge University Press. https://doi.org/10.1017/CBO9780511819389 Gray, J. A. (1982). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system. Oxford University Press. Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). Oxford University Press. Smillie, L. D., Pickering, A. D., & Jackson, C. J. (2006). The new Reinforcement Sensitivity Theory: Implications for personality measurement. Personality and Social Psychology Review, 10(4), 320–335. https://doi.org/10.1207/s15327957pspr1004_3 Corr, P. J. (2004). Reinforcement sensitivity theory and personality. Neuroscience & Biobehavioral Reviews, 28(3), 317–332. https://doi.org/10.1016/j.neubiorev.2004.01.005 Firth, J., Standen, B., Sumich, A., Fino, E., & Heym, N. (2024). The neural correlates of reinforcement sensitivity theory: A systematic review of the frontal asymmetry and spectral power literature. Psychophysiology, 61(9), e14594. https://doi.org/10.1111/psyp.14594 Gray, J. A. (1970). The psychophysiological basis of introversion-extraversion. Behaviour Research and Therapy, 8(3), 249–266. https://doi.org/10.1016/0005-7967(70)90069-0 Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). Oxford University Press. McNaughton, N., & Corr, P. J. (2004). A two-dimensional neuropsychology of defense: Fear/anxiety and defensive distance. Neuroscience & Biobehavioral Reviews, 28(3), 285–305. https://doi.org/10.1016/j.neubiorev.2004.03.005 Smillie, L. D., Pickering, A. D., & Jackson, C. J. (2006). The new reinforcement sensitivity theory: Implications for personality measurement. Personality and Social Psychology Review, 10(4), 320–335. https://doi.org/10.1207/s15327957pspr1004_3 Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. Journal of Personality and Social Psychology, 67(2), 319–333. https://doi.org/10.1037/0022-3514.67.2.319 Corr, P. J. (2004). Reinforcement sensitivity theory and personality. Neuroscience & Biobehavioral Reviews, 28(3), 317–332. https://doi.org/10.1016/j.neubiorev.2004.01.005 Corr, P. J. (2008). The reinforcement sensitivity theory of personality. Cambridge University Press. Gray, J. A. (1970). The psychophysiological basis of introversion-extraversion. Behaviour Research and Therapy, 8(3), 249–266. https://doi.org/10.1016/0005-7967(70)90069-0 Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). Oxford University Press. Smillie, L. D., & Jackson, C. J. (2006). Functional impulsivity and reinforcement sensitivity theory. Journal of Personality, 74(1), 47–84. https://doi.org/10.1111/j.1467-6494.2005.00369.x Smillie, L. D., Pickering, A. D., & Jackson, C. J. (2006). The new reinforcement sensitivity theory: Implications for personality measurement. Personality and Social Psychology Review, 10(4), 320–335. https://doi.org/10.1207/s15327957pspr1004_3 Carver, C. S., & White, T. L. (1994). Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS scales. Journal of Personality and Social Psychology, 67(2), 319–333. https://doi.org/10.1037/0022-3514.67.2.319 Corr, P. J. (2008). The reinforcement sensitivity theory of personality. Cambridge University Press. Corr, P. J. (2011). Anxiety: Splitting the phenomenological atom. Personality and Individual Differences, 50(7), 889–897. https://doi.org/10.1016/j.paid.2010.09.013 Corr, P. J., & McNaughton, N. (2008). Reinforcement sensitivity theory and personality. In G. J. Boyle, G. Matthews, & D. H. Saklofske (Eds.), The SAGE handbook of personality theory and assessment: Vol. 1. Personality theories and models (pp. 155–187). SAGE. De Pascalis, V., Strippoli, E., Riccardi, P., & Vergari, M. (2000). Psychophysiological responses to emotional stimuli in subjects with different levels of anxiety. Personality and Individual Differences, 28(3), 529–544. https://doi.org/10.1016/S0191-8869(99)00114-8 Gray, J. A. (1982). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system. Oxford University Press. Gray, J. A., & McNaughton, N. (2000). The neuropsychology of anxiety: An enquiry into the functions of the septo-hippocampal system (2nd ed.). Oxford University Press. McNaughton, N., & Corr, P. J. (2004). A two-dimensional neuropsychology of defense: Fear/anxiety and defensive distance. Neuroscience & Biobehavioral Reviews, 28(3), 285–305. https://doi.org/10.1016/j.neubiorev.2004.03.005 }} ==External links== {{expand}} [[Category:{{#titleparts:{{PAGENAME}}|3}}]] [[Category:Motivation and emotion/Book/Reward]] 4h00q62awmpsxa2m2a4oix0w00ttwu0 1 331836 2835080 2834991 2026-09-29T23:56:10Z Jtneill 10242 Move comment 2835080 wikitext text/x-wiki == Heading casing == {| style="float: center; background:transparent;color:inherit;" |- | [[File:Crystal Clear app ktip.svg|48px|left]] | {{#if:ChelsSchofield|Hi [[User:ChelsSchofield|ChelsSchofield]].|}} FYI, the recommended [[Wikiversity]] heading style uses [[w:Letter case#Sentence_case|sentence casing]]. For example:<br> <big><big>Self-determination theory</big></big> rather than <big><big>Self-Determination Theory</big></big> Here's an example chapter with correct heading casing: [[Motivation and emotion/Book/2019/Growth mindset development|Growth mindset development]] -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 08:24, 5 September 2026 (UTC) |} :Thank you for the detailed marking. I will actively work towards these improvements. [[User:ChelsSchofield|ChelsSchofield]] ([[User talk:ChelsSchofield|discuss]] • [[Special:Contributions/ChelsSchofield|contribs]]) 00:58, 9 September 2026 (UTC) <!-- Official topic development feedback --> {{METF/2026 |1= <!-- Title --> # Title and/or subtitle not correctly worded and/or didn't use [[w:Letter case#Sentence casing|sentence casing]] (fixed) |2= <!-- Headings --> # See earlier comment about [[#heading casing|heading casing]] <!-- Heading structure --> <!-- 2-level --> # Promising [[Motivation and emotion/Assessment/Major project/Structure|2-level heading structure]] – could benefit from further development and/or refinement <!-- Alignment with focus questions --> # Develop closer alignment between sub-title, focus questions, and top-level headings <!-- GenAI ---> # Are the headings based on [[Motivation and emotion/Assessment/Using generative AI|genAI content]]? If so, this needs to be acknowledged in the edit summaries, otherwise it violates academic integrity. |3= <!-- Overview--> # Good <!-- Scenario --> # A scenario or case study is presented in a feature box at the start of this section # Add an image (not a diagram) to the scenario to help attract reader interest <!-- Description --> # A clear description of the problem/topic is planned or presented <!-- Focus questions --> # Develop closer alignment between the sub-title, focus questions, and top-level headings |4= <!-- Key points--> <!-- Overall --> # Solid development # Include an introductory paragraph before branching into sub-sections <!-- Scope --> # The scope is excellent (i.e., not too little/narrow or too big/broad) # Use correct capitalisation ([https://apastyle.apa.org/style-grammar-guidelines/capitalization APA style is a "down" style]) – [https://polishedpaper.com/blog/capitalization-apa-style more info] <!-- Conclusion --> # Conclusion is well underway # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> # Excellent - Relevant figure(s) presented, captioned, and cited # Relevant figure(s) are presented and captioned # Relevant figure(s) are presented # The relevance of the figure to the topic is unclear # A relevant figure is not presented and cited (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) <!-- Caption --> # Figure caption(s) could better explain how the image connects to key points being made in the main text # Figure caption(s) should include '''Figure X'''. ... (fixed) <!-- 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 --> # Promising use of quiz question(s) # Place each quiz question in the most relevant section <!-- Tables --> # Promising use of table(s) |7= <!-- References --> <!-- Overall --> # Basic <!-- Systematic reviews --> # What are the most relevant systematic reviews/meta-analyses about this topic? <!-- APA style --> # Check and correct [https://apastyle.apa.org/instructional-aids/reference-guide.pdf APA referencing style]: ## [[Help:Wikitext quick reference|italicisation]] ## include hyperlinked dois |8= <!-- Resources --> <!-- See also --> # See also ## Excellent ## Very good ## Good ## Basic ## One of two link types provided ### Also link to related [[Motivation and emotion/Book|motivation and emotion book chapters]] ### Also link to relevant [[w:|Wikipedia]] pages ## Use bullet-points (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Use [[w:Letter case#Sentence casing|sentence casing]] ## Rename links so that they are more user friendly (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Include source in brackets after link (e.g., (Wikipedia) or (Book chapter, year) for Wikiversity book chapters) ## Use alphabetical order ## To be developed (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) <!-- External links --> # External links ## Excellent ## Very good ## Good ## Basic ## One of two required external links provided ## Move Wikipedia link(s) to the "See also" section ## Move academic sources into the "References" sections and provide in-text citation ## Only include links directly related to the sub-title ## Target an international audience; Australians only represent 0.33% of the world population ## Good choice of links, but poorly formatted (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Use bullet-points (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Use [[w:Letter case#Sentence casing|sentence casing]] ## Rename links so that they are more user friendly (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Include source in brackets after link ## Use alphabetical order ## To be developed (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Link to the most relevant external resources about this topic |9= <!-- User page --> # Very good <!-- Description about self --> # Excellent description about self provided <!-- 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 --> # Rename the link to the book chapter to make it more user-friendly (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) |10= <!-- Social contribution --> # One out of three types of contributions made with direct link(s) to evidence. The other types of contribution are making: #* direct improvements to other [[Motivation and emotion/Book|chapters (past or current)]] #* 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> 08:24, 5 September 2026 (UTC) ==Comment== Hi! I really like how you've connected pain perception with different technologies and psychological theories. I noticed that parts of the “Understanding pain perception and management” section still read like planning notes, for example, “Relate this distinction to technology” and “Refer to increased attention towards bodily sensations.” It might help to turn these into complete paragraphs explaining the ideas directly to the reader. I think this would make the section flow more smoothly and clarify the connection between the psychological theory and technology. Hope this helps! [[User:U3239236|U3239236]] ([[User talk:U3239236|discuss]] • [[Special:Contributions/U3239236|contribs]]) 07:47, 29 September 2026 (UTC) 2fjkw3zt0seulfxcgn6r08bdz9e9608 2835089 2835080 2026-09-30T01:38:17Z ChelsSchofield 3106760 /* Comment */ Reply 2835089 wikitext text/x-wiki == Heading casing == {| style="float: center; background:transparent;color:inherit;" |- | [[File:Crystal Clear app ktip.svg|48px|left]] | {{#if:ChelsSchofield|Hi [[User:ChelsSchofield|ChelsSchofield]].|}} FYI, the recommended [[Wikiversity]] heading style uses [[w:Letter case#Sentence_case|sentence casing]]. For example:<br> <big><big>Self-determination theory</big></big> rather than <big><big>Self-Determination Theory</big></big> Here's an example chapter with correct heading casing: [[Motivation and emotion/Book/2019/Growth mindset development|Growth mindset development]] -- [[User:Jtneill|Jtneill]] - <small>[[User talk:Jtneill|Talk]] - [[Special:Contributions/Jtneill|c]]</small> 08:24, 5 September 2026 (UTC) |} :Thank you for the detailed marking. I will actively work towards these improvements. [[User:ChelsSchofield|ChelsSchofield]] ([[User talk:ChelsSchofield|discuss]] • [[Special:Contributions/ChelsSchofield|contribs]]) 00:58, 9 September 2026 (UTC) <!-- Official topic development feedback --> {{METF/2026 |1= <!-- Title --> # Title and/or subtitle not correctly worded and/or didn't use [[w:Letter case#Sentence casing|sentence casing]] (fixed) |2= <!-- Headings --> # See earlier comment about [[#heading casing|heading casing]] <!-- Heading structure --> <!-- 2-level --> # Promising [[Motivation and emotion/Assessment/Major project/Structure|2-level heading structure]] – could benefit from further development and/or refinement <!-- Alignment with focus questions --> # Develop closer alignment between sub-title, focus questions, and top-level headings <!-- GenAI ---> # Are the headings based on [[Motivation and emotion/Assessment/Using generative AI|genAI content]]? If so, this needs to be acknowledged in the edit summaries, otherwise it violates academic integrity. |3= <!-- Overview--> # Good <!-- Scenario --> # A scenario or case study is presented in a feature box at the start of this section # Add an image (not a diagram) to the scenario to help attract reader interest <!-- Description --> # A clear description of the problem/topic is planned or presented <!-- Focus questions --> # Develop closer alignment between the sub-title, focus questions, and top-level headings |4= <!-- Key points--> <!-- Overall --> # Solid development # Include an introductory paragraph before branching into sub-sections <!-- Scope --> # The scope is excellent (i.e., not too little/narrow or too big/broad) # Use correct capitalisation ([https://apastyle.apa.org/style-grammar-guidelines/capitalization APA style is a "down" style]) – [https://polishedpaper.com/blog/capitalization-apa-style more info] <!-- Conclusion --> # Conclusion is well underway # What are the practical, take-home messages? (address the focus questions) |5= <!-- Figure --> # Excellent - Relevant figure(s) presented, captioned, and cited # Relevant figure(s) are presented and captioned # Relevant figure(s) are presented # The relevance of the figure to the topic is unclear # A relevant figure is not presented and cited (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) <!-- Caption --> # Figure caption(s) could better explain how the image connects to key points being made in the main text # Figure caption(s) should include '''Figure X'''. ... (fixed) <!-- 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 --> # Promising use of quiz question(s) # Place each quiz question in the most relevant section <!-- Tables --> # Promising use of table(s) |7= <!-- References --> <!-- Overall --> # Basic <!-- Systematic reviews --> # What are the most relevant systematic reviews/meta-analyses about this topic? <!-- APA style --> # Check and correct [https://apastyle.apa.org/instructional-aids/reference-guide.pdf APA referencing style]: ## [[Help:Wikitext quick reference|italicisation]] ## include hyperlinked dois |8= <!-- Resources --> <!-- See also --> # See also ## Excellent ## Very good ## Good ## Basic ## One of two link types provided ### Also link to related [[Motivation and emotion/Book|motivation and emotion book chapters]] ### Also link to relevant [[w:|Wikipedia]] pages ## Use bullet-points (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Use [[w:Letter case#Sentence casing|sentence casing]] ## Rename links so that they are more user friendly (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Include source in brackets after link (e.g., (Wikipedia) or (Book chapter, year) for Wikiversity book chapters) ## Use alphabetical order ## To be developed (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) <!-- External links --> # External links ## Excellent ## Very good ## Good ## Basic ## One of two required external links provided ## Move Wikipedia link(s) to the "See also" section ## Move academic sources into the "References" sections and provide in-text citation ## Only include links directly related to the sub-title ## Target an international audience; Australians only represent 0.33% of the world population ## Good choice of links, but poorly formatted (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Use bullet-points (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Use [[w:Letter case#Sentence casing|sentence casing]] ## Rename links so that they are more user friendly (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Include source in brackets after link ## Use alphabetical order ## To be developed (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) ## Link to the most relevant external resources about this topic |9= <!-- User page --> # Very good <!-- Description about self --> # Excellent description about self provided <!-- 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 --> # Rename the link to the book chapter to make it more user-friendly (see [[Motivation and emotion/Tutorials/Wiki editing|Tutorial 2]]) |10= <!-- Social contribution --> # One out of three types of contributions made with direct link(s) to evidence. The other types of contribution are making: #* direct improvements to other [[Motivation and emotion/Book|chapters (past or current)]] #* 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> 08:24, 5 September 2026 (UTC) ==Comment== Hi! I really like how you've connected pain perception with different technologies and psychological theories. I noticed that parts of the “Understanding pain perception and management” section still read like planning notes, for example, “Relate this distinction to technology” and “Refer to increased attention towards bodily sensations.” It might help to turn these into complete paragraphs explaining the ideas directly to the reader. I think this would make the section flow more smoothly and clarify the connection between the psychological theory and technology. Hope this helps! [[User:U3239236|U3239236]] ([[User talk:U3239236|discuss]] • [[Special:Contributions/U3239236|contribs]]) 07:47, 29 September 2026 (UTC) :thank you [[User:ChelsSchofield|ChelsSchofield]] ([[User talk:ChelsSchofield|discuss]] • [[Special:Contributions/ChelsSchofield|contribs]]) 01:38, 30 September 2026 (UTC) b2hx7mi3hqd2v3iwbeokrrbnsur7068 0 331984 2835067 2835031 2026-09-29T19:21:47Z The Citer 3110681 The phylogeny is *complete* (and definitely improved)! 2835067 wikitext text/x-wiki [[Image:Lunularia cruciata.jpg|thumb|300px|right|This is a Liverwort.]] Marchantiophytes are non-vascular land plants in the division Marchantiophyta, also known as hepatics. ==Information== Name Meaning: Marchantia-like plant, liver plant English Common Name: Liverworts Major distinguishing characteristics: Ephemeral unbranched sporophytes, no vascular system Approximate number of species described: 9,000 ==Classes== Haplomitriopsida – Jungermanniopsida – Marchantiopsida ==Evolutionary History== [https://en.wikipedia.org/wiki/Epiphyte Epiphytic] thalloid liverworts evolved during the Triassic to the Cretaceous. ==Phylogeny== {{Clade | style=font-size:90%;line-height:80% |label1=Marchantiophyta |1={{clade |1={{clade |label1=Haplomitriopsida |1={{clade |1=Haplomitriales [[File:Untersuchungen über Haplomitrium Hookeri (1843) plate XIII.jpg|60px]] |2=Treubiales [[File:Treubia lacunosa (Colenso) Prosk. (AM AK322391-1).jpg|60px]] }} }} |2={{clade |label1=Marchantiopsida |1={{clade |label1=Blasiidae |1=Blasiales [[File:Blasia pusilla 231011.jpg|60px]] |label2=Marchantiidae |2={{clade |1=Neohodgsoniales [[File:Carpocephala of Neohodgsonia.jpg|60px]] |2={{clade |1=Sphaerocarpales [[File:Sphaerocarpos texanus 351874556.jpg|60px]] |2={{clade |1=Lunulariales [[File:Lunularia cruciata 252749453.jpg|60px]] |2=Marchantiales [[File:Conocephalum conicum (d, 144739-474747) 3155.jpg|60px]] }} }} }} }} |label2=Jungermanniopsida |2={{clade |1={{clade |label1=Pelliidae |1={{clade |1=Pelliales [[File:Pellia epiphylla7 ies.jpg|60px]] |2={{clade |1=Fossombroniales [[File:Petalophyllum preissii.jpg|60px]] |2=Pallaviciniales [[File:Pallavicinia xiphoides (Hook.f. and Tayl.) Trev. (AM AK298944).jpg|60px]] }} }} }} |2={{clade |label1=Metzgeriidae |1={{clade |1=Metzgeriales [[File:Riccardia multifida (a, 144643-474753) 0264.jpg|60px]] |2=Pleuroziales [[File:Pleurozia purpurea36373 580 360.jpg|60px]] }} |label2=Jungermanniidae |2={{clade |1=Jungermanniales [[File:Jungermannia subulata (b, 144634-474722) 7627.JPG|60px]] |2={{clade |1=Porellales [[File:Cololejeunea macounii 358541811.jpg|60px]] |2=Ptilidiales [[File:Ptilidium pulcherrimum (e, 144846-474705) 3522.JPG|60px]] }} }} }} }} }} }} }} ==References== [[Wikipedia:Liverwort]] 1lo2jp5en66vzwu1n4w5z33tvsz54g1 2835073 2835067 2026-09-29T21:01:03Z The Citer 3110681 Switch-a-roo! 2835073 wikitext text/x-wiki [[Image:Lunularia cruciata.jpg|thumb|300px|right|This is a Liverwort.]] Marchantiophytes are non-vascular land plants in the division Marchantiophyta, also known as hepatics. ==Information== Name Meaning: Marchantia-like plant, liver plant English Common Name: Liverworts Major distinguishing characteristics: Ephemeral unbranched sporophytes, no vascular system Approximate number of species described: 9,000 ==Evolutionary History== [https://en.wikipedia.org/wiki/Epiphyte Epiphytic] thalloid liverworts evolved during the Triassic to the Cretaceous. ==Classes== Haplomitriopsida – Jungermanniopsida – Marchantiopsida ==Phylogeny== {{Clade | style=font-size:90%;line-height:80% |label1=Marchantiophyta |1={{clade |1={{clade |label1=Haplomitriopsida |1={{clade |1=Haplomitriales [[File:Untersuchungen über Haplomitrium Hookeri (1843) plate XIII.jpg|60px]] |2=Treubiales [[File:Treubia lacunosa (Colenso) Prosk. (AM AK322391-1).jpg|60px]] }} }} |2={{clade |label1=Marchantiopsida |1={{clade |label1=Blasiidae |1=Blasiales [[File:Blasia pusilla 231011.jpg|60px]] |label2=Marchantiidae |2={{clade |1=Neohodgsoniales [[File:Carpocephala of Neohodgsonia.jpg|60px]] |2={{clade |1=Sphaerocarpales [[File:Sphaerocarpos texanus 351874556.jpg|60px]] |2={{clade |1=Lunulariales [[File:Lunularia cruciata 252749453.jpg|60px]] |2=Marchantiales [[File:Conocephalum conicum (d, 144739-474747) 3155.jpg|60px]] }} }} }} }} |label2=Jungermanniopsida |2={{clade |1={{clade |label1=Pelliidae |1={{clade |1=Pelliales [[File:Pellia epiphylla7 ies.jpg|60px]] |2={{clade |1=Fossombroniales [[File:Petalophyllum preissii.jpg|60px]] |2=Pallaviciniales [[File:Pallavicinia xiphoides (Hook.f. and Tayl.) Trev. (AM AK298944).jpg|60px]] }} }} }} |2={{clade |label1=Metzgeriidae |1={{clade |1=Metzgeriales [[File:Riccardia multifida (a, 144643-474753) 0264.jpg|60px]] |2=Pleuroziales [[File:Pleurozia purpurea36373 580 360.jpg|60px]] }} |label2=Jungermanniidae |2={{clade |1=Jungermanniales [[File:Jungermannia subulata (b, 144634-474722) 7627.JPG|60px]] |2={{clade |1=Porellales [[File:Cololejeunea macounii 358541811.jpg|60px]] |2=Ptilidiales [[File:Ptilidium pulcherrimum (e, 144846-474705) 3522.JPG|60px]] }} }} }} }} }} }} }} ==References== [[Wikipedia:Liverwort]] krbaxqmwavx31durf1m48873doebsxn 1 331992 2835076 2833642 2026-09-29T21:51:10Z The Citer 3110681 2835076 wikitext text/x-wiki == Can we divide Magnoliophyta into usable classes? == :We could Put ''Amborella'' into its own class (Amborellaopsida), we could also put Nymphaeales into its own class (Nymphaeaopsida), we could also put Austrobaileyales into its own class (Austrobaileyaopsida), and we could even have Core Angiosperms have its own class (Mesangiospermopsida or Mesomagnoliopsida). [[User:The Citer|The Citer]] ([[User talk:The Citer|discuss]] • [[Special:Contributions/The Citer|contribs]]) 20:21, 17 September 2026 (UTC) 6c1xskvfhkj1cn7086fa7waoypjy119 0 332156 2835075 2833824 2026-09-29T21:33:30Z The Citer 3110681 Added phylogeny! 2835075 wikitext text/x-wiki [[Image:Flickr - brewbooks - Angiopteris evecta - Mule's foot fern (1).jpg|thumb|300px|right|This is a fern.]] Polypodiophytes are a group of vascular plants that reproduce via spores and have neither seeds nor flowers. ==Information== Name Meaning: Many foot plant, Polypodium-like plant English Common Name: ferns, horsetails Major distinguishing characteristics: Prothallus gametophytes and vascular system Approximate number of species described: 9000 ==Evolutionary History== The fern crown group is estimated to have originated {{circa|423}} million years ago (mya), during the [[Wikipedia:Ludlow|Ludlow]] epoch and the rapid radiation of Embryophytes, but Polypodiales, the group that makes up 80% of extant fern diversity, didn't appear and diversify until the [[Wikipedia:Cretaceous|Cretaceous]] ({{circa|lk=no|143}} to 66 mya), contemporaneous with the heightened diversification of [[Plant_Divisions_(Phyla)/Magnoliophyta|Magnoliophytes]]. ==Subclasses== Equisetidae – Marattiidae – Ophioglossidae – Polypodiidae ===Extinct=== †Stauropterididae – †Zygopterididae ==Phylogeny== {{clade |style=line-height:140%;font-size:100%; |label1= Tracheophyta |sublabel1= (vascular plants) |1={{clade |1= [[Plant_Divisions_(Phyla)/Lycopodiophyta (Lycophyta)|Lycophytes]] [[File:2021-03 Amsterdam Island - lycopodium clavatum 10.jpg|50px]] |label2= Euphyllophyta |2={{clade |1='''Ferns''' [[File:California Arena Point fern.jpg|70px]] |label2= Spermatophyta |sublabel2=(seed plants) |2={{clade |1=Gymnospermae [[File:Flore des serres v15 147a.jpg|50px]] |2=[[Plant_Divisions_(Phyla)/Magnoliophyta|Magnoliophyta]] [[File:160 Ranunculus repens.jpg|50px]] }} }} }} }} ==References== [[Wikipedia:fern]] [[Category:Plants]] [[Category:Taxonomy]] [[Category:Botany]] [[Category:Biology]] shl2m3xh0m0wkoj2ia6cilqv9z02mx4 0 332222 2835074 2835022 2026-09-29T21:06:34Z The Citer 3110681 Pinales 2835074 wikitext text/x-wiki [[File:Diversity of plants (Streptophyta) version 2.png|thumb|500x500px|Different Plant species from different phyla.]] Streptophyta (/strɛpˈtɒfɪtə, ˈstrɛptoʊfaɪtə/), informally the streptophytes (/ˈstrɛptəfaɪts/, from the Greek strepto 'twisted', for the morphology of the sperm of some members), is a clade of plants. The composition of the clade varies considerably between authors, but the definition employed here includes land plants and all green algae except the Chlorophyta and the more basal Prasinodermophyta.<ref name=Jeffrey1967>{{cite journal | author = Jeffrey C | year = 1967 | title = The origin and differentiation of the Archegoniate land plants: A second contribution | journal = Kew Bull. | volume = 21 | issue = 2| pages = 335–349 | doi=10.2307/4108533| jstor = 4108533 | bibcode = 1967KewBu..21..335J }}</ref><ref>{{Cite journal|last1=Sánchez-Baracaldo|first1=Patricia|last2=Raven|first2=John A.|last3=Pisani|first3=Davide|last4=Knoll|first4=Andrew H.|date=2017-09-12|title=Early photosynthetic eukaryotes inhabited low-salinity habitats|journal=Proceedings of the National Academy of Sciences|volume=114|issue=37|pages=E7737–E7745|doi=10.1073/pnas.1620089114|url=https://research-information.bristol.ac.uk/ws/files/132985852/pnas.1620089114.sapp.pdf|pmid=28808007|pmc=5603991|bibcode=2017PNAS..114E7737S |doi-access=free}}</ref> ==Information== Name Meaning: Twisted plant English Common Name: Streptophytes Major distinguishing characteristics: Approximate number of species described: >350,000 ==Classification== The composition of Streptophyta and similar groups (Streptophytina, [[Plant_Divisions_(Phyla)/Charophyta|Charophyta]]) varies in each classification.<ref>{{Cite web |title=Die Schwestergruppe der Landpflanzen |trans-title=The sister group of land plants |url=https://www.protisten.de/german/docs/Phylogeny_in_Streptophyta.pdf |access-date=7 November 2023 |website=www.protisten.de |language=de}}</ref>{{citation needed|reason=cited source is in German. An English-language source is required|date=September 2026}} Some authors include only the Charales and Embryophyta (e.g., Streptophyta,<ref name=Jeffrey1967/><ref name=Adletal2012>{{cite journal |author=Adl, S.M.; Simpson, A.G.B.; Lane, C.E.; Lukeš, J.; Bass, D.; Bowser, S.S.; Brown, M.W.; Burki, F.; Dunthorn, M mentioned as source without citation.; Hampl, V.; Heiss, A.; Hoppenrath, M.; Lara, E.; le Gall, L.; Lynn, D.H.; McManus, H.; Mitchell, E.A.D.; Mozley-Stanridge, S.E.; Parfrey, L.W.; Pawlowski, J.; Rueckert, S.; Shadwick, L.; Schoch, C.L.; Smirnov, A.; Spiegel, F.W. |date=2012 |title=The revised classification of Eukaryotes |journal=Journal of Eukaryotic Microbiology |volume=59 |issue=5 |pages=429–514 |doi=10.1111/j.1550-7408.2012.00644.x| pmc=3483872|pmid=23020233 }}</ref> Streptophytina); others include more groups (e.g., Charophyta<!-- Karol et al. 2009--><ref name=Adletal2012/> Streptophyta,<ref name=Bremer1985>{{cite journal |author=Bremer, K. |date=1985 |title=Summary of green plant phylogeny and classification |journal=Cladistics |volume=1 |issue=4 |pages=369–385 |doi=10.1111/j.1096-0031.1985.tb00434.x |pmid=34965683 }}</ref><!-- de Reviers 2002; --><ref name=Leliaert-2012>{{cite journal |last1=Leliaert |first1=Frederik |last2=Smith |first2=David R. |last3=Moreau |first3=Hervé |last4=Herron |first4=Matthew D. |last5=Verbruggen |first5=Heroen |last6=Delwiche |first6=Charles F. |last7=De Clerck |first7=Olivier |title=Phylogeny and Molecular Evolution of the Green Algae |date=2012 |journal=Critical Reviews in Plant Sciences |volume=31 |issue=1 |pages=1–46 |bibcode=2012CRvPS..31....1L |doi=10.1080/07352689.2011.615705 |url=http://www.vliz.be/imisdocs/publications/248853.pdf }}</ref> Streptobionta<ref>{{cite book|last1=Kenrick|first1=Paul|last2=Crane|first2=Peter|title=The Origin and Early Diversification of Land Plants: A Cladistic Study|date=1997|publisher=[[Smithsonian Institution Press]]|location=Washington, D.C. |isbn=9781560987291}}</ref>); some authors use this broader definition, but exclude the Embryophyta (e.g., Charophyta,<ref name="Cavalier-Smith1993">{{cite book|author=Cavalier-Smith, T. |date=1993| chapter=The origin, losses and gains of chloroplasts. |title=Origins of plastids |pages=291–348 |publisher=Springer US}}</ref><ref name=Leliaert-2012/> Charophyceae{{citation needed|reason=Mattox & Stewart, 1984 mentioned as source without citation|date=September 2026}}, Streptophycophytes{{citation needed|reason=de Reviers, 2002 meantion as source without citation|date=April 2024}}). The clade Streptophyta includes both unicellular and multicellular organisms. Streptophyta contains the freshwater charophyte green algae and all land plants that reproduce sexually by conjugation. ''Mesostigma viride'', a unicellular green flagellate alga may be a basal Streptophyte.<ref name=Liang2020>{{cite journal |last1=Liang |first1=Z |last2=Geng |first2=Y |last3=Ji |first3=C |last4=Du |first4=H |last5=Wong |first5=CE |last6=Zhang |first6=Q |last7=Yu |first7=H |date=2020 |title=''Mesostigma viride'' genome and transcriptome provide insights into the origin and evolution of Streptophyta |journal=Advanced Science |volume=7 |issue=1 |doi=10.1002/advs.2019018501901850 |doi-broken-date=11 August 2026 |doi-access=free }}</ref><ref name=Nedelcu2006>{{cite journal |last1=Nedelcu |first1=AM |last2=Borza |first2=T |last3=Lee |first3=RW |date=2006 |title=A land plant–specific multigene family in the unicellular ''Mesostigma'' argues for its close relationship to Streptophyta |journal=Molecular Biology and Evolution |volume=23 |issue=5 |pages=1011–1015 |doi=10.1093/molbev/msj108 |pmid=16476689 }}</ref> ==Phylogeny== Below is a reconstruction of '''Streptophyta''' relationships, based on genomic data.<ref>{{Cite journal|author1=Linzhou Li|author2=Sibo Wang|author3=Hongli Wang|author4=Sunil Kumar Sahu|author5=Birger Marin|author6=Haoyuan Li|author7=Yan Xu|author8=Hongping Liang|author9=Zhen Li|author10=Shifeng Chen|author11=Tanja Reder|date=22 June 2020|title=The genome of Prasinoderma coloniale unveils the existence of a third phylum within green plants|journal=Nature Ecology & Evolution|volume=4|issue=9|pages=1220–1231|doi=10.1038/s41559-020-1221-7|pmc=7455551|pmid=32572216|doi-access=free|author22=Yves Van de Peer|author23=Michael Melkonian|author24=Huan Liu|author21=Xin Liu|author20=Xun Xu|author19=Gane Ka-Shu Wong|author17=Huanming Yang|author16=Hongli Du|author15=Barbara Melkonian|author14=Morten Petersen|author13=Sebastian Wittek|author12=Zehra Çebi|author18=Jian Wang|bibcode=2020NatEE...4.1220L }}</ref><ref>{{Cite journal|last1=Puttick|first1=Mark N.|last2=Morris|first2=Jennifer L.|last3=Williams|first3=Tom A.|last4=Cox|first4=Cymon J.|last5=Edwards|first5=Dianne|last6=Kenrick|first6=Paul|last7=Pressel|first7=Silvia|last8=Wellman|first8=Charles H.|last9=Schneider|first9=Harald|date=2018|title=The Interrelationships of Land Plants and the Nature of the Ancestral Embryophyte|journal=Current Biology|volume=28|issue=5|pages=733–745.e2|doi=10.1016/j.cub.2018.01.063|pmid=29456145|doi-access=free|bibcode=2018CBio...28E.733P |hdl=1983/ad32d4da-6cb3-4ed6-add2-2415f81b46da|hdl-access=free}}</ref><ref>{{Cite journal|last1=Sánchez-Baracaldo|first1=Patricia|last2=Raven|first2=John A.|last3=Pisani|first3=Davide|last4=Knoll|first4=Andrew H.|date=2017-09-12|title=Early photosynthetic eukaryotes inhabited low-salinity habitats|journal=Proceedings of the National Academy of Sciences|volume=114|issue=37|pages=E7737–E7745|doi=10.1073/pnas.1620089114|url=https://research-information.bristol.ac.uk/ws/files/132985852/pnas.1620089114.sapp.pdf|pmid=28808007|pmc=5603991|bibcode=2017PNAS..114E7737S |doi-access=free}}</ref> {{clade |label1=Streptophyta |1={{clade |1=Mesostigmatophyceae [[File:Mesostigma viride 534857918.jpg|60px]]` |2={{clade |1=Chlorokybophyceae [[File:Chlorokybus atmophyticus.jpg|60px]] |2={{clade |1=''Streptofilum'' [[File:Streptofilum capillatum.pdf|60px]] |2={{clade |1=Klebsormidiophyceae [[File:Klebsormidium bilatum Belgium (14759117646).jpg|60px]] |label2=Phragmoplastophyta |2={{clade |1=Charophyceae (Stoneworts & musk grasses) [[File:CharaFragilis.jpg|60px]] |2={{clade |1=Zygnematophyceae (desmids, water silk etc.) [[File:The freshwater alga Spirogyra.jpg|60px]] |2={{clade |1=Coleochaetophyceae [[File:Spirogyra-bgiu.jpg|60px]] |2=Embryophytes [[File:GINKGOBAUM-2.jpg|60px]] }} }} }} }} }} }} }}}} ==Diversity== There are many species of Streptophytes. These are just the phyla: ===Anthocerotophytes=== [[File:Dendroceros.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Anthocerotophyta]]<br> Name Meaning: Anthoceros-like plant English Common Name: Hornworts Major distinguishing characteristics: Horn-shaped sporophytes, no vascular system Approximate number of species described: 100-300 Classes: Anthocerotopsida, Leiosporocerotopsida ===Bryophytes=== [[File:Tionesta-ac-moss2.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Bryophyta]]<br> Name Meaning: Bryum-like plant, moss plant English Common Name: Moss Major distinguishing characteristics: Persistent branched sporophytes, no vascular system Approximate number of species described: 12,000 Classes: Andreaeobryopsida, Andreaeopsida, Bryopsida, Oedipodiopsida, Sphagnopsida, Takakiopsida, Tetraphidopsida ===Cycadophytes=== [[File:Starr 060905-8736 Zamia furfuracea.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Cycadophyta]]<br> Name Meaning: Cycas-like plant, palm-like plant English Common Name: Cycads Major distinguishing characteristics: Seeds, crown of compound leaves Approximate number of species described: 100 - 200 Classes: Cycadopsida ===Ginkgophytes=== [[File:Ginkgo biloba in Lucenec2.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Ginkgophyta]]<br> Name Meaning: Ginkgo-like plant English Common Name: Ginkgo, maidenhair tree Major distinguishing characteristics: Seeds not protected by fruit Approximate number of species described: 1 living, about 50 extinct Classes: Ginkgoopsida ===Gnetophytes=== [[File:Welwitschia at Ugab River basin.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Gnetophyta]]<br> Name Meaning: Gnetum-like plant English Common Name: Gnetophytes Major distinguishing characteristics: Seeds and woody vascular system with vessels. Approximate number of species described: 70 Classes: Gnetopsida—Actually, it's a subclass: Gnetidae ===Lycopodiophytes=== [[File:Clubmoss - Flickr - pellaea (1).jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Lycopodiophyta (Lycophyta)]]<br> Name Meaning: Lycopodium-like plants, wolf plant English Common Name: Clubmosses, spikemosses Major distinguishing characteristics: Microphyll leaves, vascular system Approximate number of species described: 1290 living Classes: Lycopodiopsida, †Zosterophyllopsida ====Clades ''Incertae sedis''==== †Drepanophycales – †''Nothia'' ===Magnoliophytes=== [[File:Acer pseudoplatanus Chaltenbrunnen.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Magnoliophyta]]<br> Name Meaning: Magnolia-like plant English Common Name: Flowering plants, angiosperms Major distinguishing characteristics: Flowers and fruit, vascular system with vessels Approximate number of species described: 300,000 Classes: Magnoliopsida ===Marchantiophytes=== [[File:Lunularia cruciata.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Marchantiophyta]]<br> Name Meaning: Marchantia-like plant, liver plant English Common Name: Liverworts Major distinguishing characteristics: Ephemeral unbranched sporophytes, no vascular system Approximate number of species described: 9,000 Classes: Haplomitriopsida, Jungermanniopsida, Marchantiopsida ===Pinophytes=== [[File:Pinus lambertiana ProspectOR.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Pinophyta (Coniferophyta)]]<br> Name Meaning: Pinus-like plant, cone-bearing plant English Common Name: Conifers Major distinguishing characteristics: Cones containing seeds and wood composed of tracheids Classes: Pinopsida ==References== [[Category:Plants]] [[Category:Taxonomy]] [[Category:Botany]] [[Category:Biology]] 5b7c0c2yw0gafjhi6801ikk7qiqonx5 2835078 2835074 2026-09-29T22:24:30Z The Citer 3110681 Yes, the diversity section might be done! 2835078 wikitext text/x-wiki [[File:Diversity of plants (Streptophyta) version 2.png|thumb|500x500px|Different Plant species from different phyla.]] Streptophyta (/strɛpˈtɒfɪtə, ˈstrɛptoʊfaɪtə/), informally the streptophytes (/ˈstrɛptəfaɪts/, from the Greek strepto 'twisted', for the morphology of the sperm of some members), is a clade of plants. The composition of the clade varies considerably between authors, but the definition employed here includes land plants and all green algae except the Chlorophyta and the more basal Prasinodermophyta.<ref name=Jeffrey1967>{{cite journal | author = Jeffrey C | year = 1967 | title = The origin and differentiation of the Archegoniate land plants: A second contribution | journal = Kew Bull. | volume = 21 | issue = 2| pages = 335–349 | doi=10.2307/4108533| jstor = 4108533 | bibcode = 1967KewBu..21..335J }}</ref><ref>{{Cite journal|last1=Sánchez-Baracaldo|first1=Patricia|last2=Raven|first2=John A.|last3=Pisani|first3=Davide|last4=Knoll|first4=Andrew H.|date=2017-09-12|title=Early photosynthetic eukaryotes inhabited low-salinity habitats|journal=Proceedings of the National Academy of Sciences|volume=114|issue=37|pages=E7737–E7745|doi=10.1073/pnas.1620089114|url=https://research-information.bristol.ac.uk/ws/files/132985852/pnas.1620089114.sapp.pdf|pmid=28808007|pmc=5603991|bibcode=2017PNAS..114E7737S |doi-access=free}}</ref> ==Information== Name Meaning: Twisted plant English Common Name: Streptophytes Major distinguishing characteristics: Approximate number of species described: 332,339 ==Classification== The composition of Streptophyta and similar groups (Streptophytina, [[Plant_Divisions_(Phyla)/Charophyta|Charophyta]]) varies in each classification.<ref>{{Cite web |title=Die Schwestergruppe der Landpflanzen |trans-title=The sister group of land plants |url=https://www.protisten.de/german/docs/Phylogeny_in_Streptophyta.pdf |access-date=7 November 2023 |website=www.protisten.de |language=de}}</ref>{{citation needed|reason=cited source is in German. An English-language source is required|date=September 2026}} Some authors include only the Charales and Embryophyta (e.g., Streptophyta,<ref name=Jeffrey1967/><ref name=Adletal2012>{{cite journal |author=Adl, S.M.; Simpson, A.G.B.; Lane, C.E.; Lukeš, J.; Bass, D.; Bowser, S.S.; Brown, M.W.; Burki, F.; Dunthorn, M mentioned as source without citation.; Hampl, V.; Heiss, A.; Hoppenrath, M.; Lara, E.; le Gall, L.; Lynn, D.H.; McManus, H.; Mitchell, E.A.D.; Mozley-Stanridge, S.E.; Parfrey, L.W.; Pawlowski, J.; Rueckert, S.; Shadwick, L.; Schoch, C.L.; Smirnov, A.; Spiegel, F.W. |date=2012 |title=The revised classification of Eukaryotes |journal=Journal of Eukaryotic Microbiology |volume=59 |issue=5 |pages=429–514 |doi=10.1111/j.1550-7408.2012.00644.x| pmc=3483872|pmid=23020233 }}</ref> Streptophytina); others include more groups (e.g., Charophyta<!-- Karol et al. 2009--><ref name=Adletal2012/> Streptophyta,<ref name=Bremer1985>{{cite journal |author=Bremer, K. |date=1985 |title=Summary of green plant phylogeny and classification |journal=Cladistics |volume=1 |issue=4 |pages=369–385 |doi=10.1111/j.1096-0031.1985.tb00434.x |pmid=34965683 }}</ref><!-- de Reviers 2002; --><ref name=Leliaert-2012>{{cite journal |last1=Leliaert |first1=Frederik |last2=Smith |first2=David R. |last3=Moreau |first3=Hervé |last4=Herron |first4=Matthew D. |last5=Verbruggen |first5=Heroen |last6=Delwiche |first6=Charles F. |last7=De Clerck |first7=Olivier |title=Phylogeny and Molecular Evolution of the Green Algae |date=2012 |journal=Critical Reviews in Plant Sciences |volume=31 |issue=1 |pages=1–46 |bibcode=2012CRvPS..31....1L |doi=10.1080/07352689.2011.615705 |url=http://www.vliz.be/imisdocs/publications/248853.pdf }}</ref> Streptobionta<ref>{{cite book|last1=Kenrick|first1=Paul|last2=Crane|first2=Peter|title=The Origin and Early Diversification of Land Plants: A Cladistic Study|date=1997|publisher=[[Smithsonian Institution Press]]|location=Washington, D.C. |isbn=9781560987291}}</ref>); some authors use this broader definition, but exclude the Embryophyta (e.g., Charophyta,<ref name="Cavalier-Smith1993">{{cite book|author=Cavalier-Smith, T. |date=1993| chapter=The origin, losses and gains of chloroplasts. |title=Origins of plastids |pages=291–348 |publisher=Springer US}}</ref><ref name=Leliaert-2012/> Charophyceae{{citation needed|reason=Mattox & Stewart, 1984 mentioned as source without citation|date=September 2026}}, Streptophycophytes{{citation needed|reason=de Reviers, 2002 meantion as source without citation|date=April 2024}}). The clade Streptophyta includes both unicellular and multicellular organisms. Streptophyta contains the freshwater charophyte green algae and all land plants that reproduce sexually by conjugation. ''Mesostigma viride'', a unicellular green flagellate alga may be a basal Streptophyte.<ref name=Liang2020>{{cite journal |last1=Liang |first1=Z |last2=Geng |first2=Y |last3=Ji |first3=C |last4=Du |first4=H |last5=Wong |first5=CE |last6=Zhang |first6=Q |last7=Yu |first7=H |date=2020 |title=''Mesostigma viride'' genome and transcriptome provide insights into the origin and evolution of Streptophyta |journal=Advanced Science |volume=7 |issue=1 |doi=10.1002/advs.2019018501901850 |doi-broken-date=11 August 2026 |doi-access=free }}</ref><ref name=Nedelcu2006>{{cite journal |last1=Nedelcu |first1=AM |last2=Borza |first2=T |last3=Lee |first3=RW |date=2006 |title=A land plant–specific multigene family in the unicellular ''Mesostigma'' argues for its close relationship to Streptophyta |journal=Molecular Biology and Evolution |volume=23 |issue=5 |pages=1011–1015 |doi=10.1093/molbev/msj108 |pmid=16476689 }}</ref> ==Phylogeny== Below is a reconstruction of '''Streptophyta''' relationships, based on genomic data.<ref>{{Cite journal|author1=Linzhou Li|author2=Sibo Wang|author3=Hongli Wang|author4=Sunil Kumar Sahu|author5=Birger Marin|author6=Haoyuan Li|author7=Yan Xu|author8=Hongping Liang|author9=Zhen Li|author10=Shifeng Chen|author11=Tanja Reder|date=22 June 2020|title=The genome of Prasinoderma coloniale unveils the existence of a third phylum within green plants|journal=Nature Ecology & Evolution|volume=4|issue=9|pages=1220–1231|doi=10.1038/s41559-020-1221-7|pmc=7455551|pmid=32572216|doi-access=free|author22=Yves Van de Peer|author23=Michael Melkonian|author24=Huan Liu|author21=Xin Liu|author20=Xun Xu|author19=Gane Ka-Shu Wong|author17=Huanming Yang|author16=Hongli Du|author15=Barbara Melkonian|author14=Morten Petersen|author13=Sebastian Wittek|author12=Zehra Çebi|author18=Jian Wang|bibcode=2020NatEE...4.1220L }}</ref><ref>{{Cite journal|last1=Puttick|first1=Mark N.|last2=Morris|first2=Jennifer L.|last3=Williams|first3=Tom A.|last4=Cox|first4=Cymon J.|last5=Edwards|first5=Dianne|last6=Kenrick|first6=Paul|last7=Pressel|first7=Silvia|last8=Wellman|first8=Charles H.|last9=Schneider|first9=Harald|date=2018|title=The Interrelationships of Land Plants and the Nature of the Ancestral Embryophyte|journal=Current Biology|volume=28|issue=5|pages=733–745.e2|doi=10.1016/j.cub.2018.01.063|pmid=29456145|doi-access=free|bibcode=2018CBio...28E.733P |hdl=1983/ad32d4da-6cb3-4ed6-add2-2415f81b46da|hdl-access=free}}</ref><ref>{{Cite journal|last1=Sánchez-Baracaldo|first1=Patricia|last2=Raven|first2=John A.|last3=Pisani|first3=Davide|last4=Knoll|first4=Andrew H.|date=2017-09-12|title=Early photosynthetic eukaryotes inhabited low-salinity habitats|journal=Proceedings of the National Academy of Sciences|volume=114|issue=37|pages=E7737–E7745|doi=10.1073/pnas.1620089114|url=https://research-information.bristol.ac.uk/ws/files/132985852/pnas.1620089114.sapp.pdf|pmid=28808007|pmc=5603991|bibcode=2017PNAS..114E7737S |doi-access=free}}</ref> {{clade |label1=Streptophyta |1={{clade |1=Mesostigmatophyceae [[File:Mesostigma viride 534857918.jpg|60px]]` |2={{clade |1=Chlorokybophyceae [[File:Chlorokybus atmophyticus.jpg|60px]] |2={{clade |1=''Streptofilum'' [[File:Streptofilum capillatum.pdf|60px]] |2={{clade |1=Klebsormidiophyceae [[File:Klebsormidium bilatum Belgium (14759117646).jpg|60px]] |label2=Phragmoplastophyta |2={{clade |1=Charophyceae (Stoneworts & musk grasses) [[File:CharaFragilis.jpg|60px]] |2={{clade |1=Zygnematophyceae (desmids, water silk etc.) [[File:The freshwater alga Spirogyra.jpg|60px]] |2={{clade |1=Coleochaetophyceae [[File:Spirogyra-bgiu.jpg|60px]] |2=Embryophytes [[File:GINKGOBAUM-2.jpg|60px]] }} }} }} }} }} }} }}}} ==Diversity== There are many species of Streptophytes. These are just the phyla: ===Anthocerotophytes=== [[File:Dendroceros.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Anthocerotophyta]]<br> Name Meaning: Anthoceros-like plant English Common Name: Hornworts Major distinguishing characteristics: Horn-shaped sporophytes, no vascular system Approximate number of species described: 100-300 Classes: Anthocerotopsida, Leiosporocerotopsida ===Bryophytes=== [[File:Tionesta-ac-moss2.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Bryophyta]]<br> Name Meaning: Bryum-like plant, moss plant English Common Name: Moss Major distinguishing characteristics: Persistent branched sporophytes, no vascular system Approximate number of species described: 12,000 Classes: Andreaeobryopsida, Andreaeopsida, Bryopsida, Oedipodiopsida, Sphagnopsida, Takakiopsida, Tetraphidopsida ===Cycadophytes=== [[File:Starr 060905-8736 Zamia furfuracea.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Cycadophyta]]<br> Name Meaning: Cycas-like plant, palm-like plant English Common Name: Cycads Major distinguishing characteristics: Seeds, crown of compound leaves Approximate number of species described: 100 - 200 Classes: Cycadopsida ===Ginkgophytes=== [[File:Ginkgo biloba in Lucenec2.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Ginkgophyta]]<br> Name Meaning: Ginkgo-like plant English Common Name: Ginkgo, maidenhair tree Major distinguishing characteristics: Seeds not protected by fruit Approximate number of species described: 1 living, about 50 extinct Classes: Ginkgoopsida ===Gnetophytes=== [[File:Welwitschia at Ugab River basin.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Gnetophyta]]<br> Name Meaning: Gnetum-like plant English Common Name: Gnetophytes Major distinguishing characteristics: Seeds and woody vascular system with vessels. Approximate number of species described: 70 Classes: Gnetopsida—Actually, it's a subclass: Gnetidae ===Lycopodiophytes=== [[File:Clubmoss - Flickr - pellaea (1).jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Lycopodiophyta (Lycophyta)]]<br> Name Meaning: Lycopodium-like plants, wolf plant English Common Name: Clubmosses, spikemosses Major distinguishing characteristics: Microphyll leaves, vascular system Approximate number of species described: 1290 living Classes: Lycopodiopsida, †Zosterophyllopsida ====Clades ''Incertae sedis''==== †Drepanophycales – †''Nothia'' ===Magnoliophytes=== [[File:Acer pseudoplatanus Chaltenbrunnen.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Magnoliophyta]]<br> Name Meaning: Magnolia-like plant English Common Name: Flowering plants, angiosperms Major distinguishing characteristics: Flowers and fruit, vascular system with vessels Approximate number of species described: 300,000 Classes: Magnoliopsida ====Proposed==== Amborellaopsida, Austrobaileyaopsida, Mesomagnoliopsida, Nymphaeaopsida ===Marchantiophytes=== [[File:Lunularia cruciata.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Marchantiophyta]]<br> Name Meaning: Marchantia-like plant, liver plant English Common Name: Liverworts Major distinguishing characteristics: Ephemeral unbranched sporophytes, no vascular system Approximate number of species described: 9,000 Classes: Haplomitriopsida, Jungermanniopsida, Marchantiopsida ===Pinophytes=== [[File:Pinus lambertiana ProspectOR.jpg|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Pinophyta (Coniferophyta)]]<br> Name Meaning: Pinus-like plant, cone-bearing plant English Common Name: Conifers Major distinguishing characteristics: Cones containing seeds and wood composed of tracheids Approximate number of species described: 629 Classes: Pinopsida ===Polypodiophytes=== [[File:Osmunda regalis Moore50.png|thumb|200x200px]] Main article: [[Plant Divisions (Phyla)/Polypodiophyta]]<br> Name Meaning: Many foot plant, Polypodium-like plant English Common Name: ferns, horsetails Major distinguishing characteristics: Prothallus gametophytes and vascular system Approximate number of species described: 9000 Classes: Polypodiopsida ====Proposed==== Equisetiopsida, Marattiopsida, Ophioglossiopsida, Polypodiopsida, †Stauropteriopsida, †Zygopteriopsida ===Conclusion=== If you added these numbers up, you get...332,339, meaning it's more diverse than all deuterostome phyla ([[Animal_Phyla/Chordata|Chordata]], [[Animal Phyla/Echinodermata|Echinodermata]], and [[Animal Phyla/Hemichordata|Hemiechinodermata]]) combined! Even magnoliophyta on its own is more diverse than [[Animal_Phyla/Chordata|Chordata]]. From tiny ''Wolffia'' to towering sequoias, the streptophytes are comparable to Diaphoretickes (In fact, they are part of that group, and streptophytes are the ones making them "diverse"*), and [[Animal Phyla/Arthropoda|Arthropoda]]. ==References== [[Category:Plants]] [[Category:Taxonomy]] [[Category:Botany]] [[Category:Biology]] 59wib1uvgvgt3de8b9mrqa10j6cba4e 0 332225 2835077 2834850 2026-09-29T22:23:11Z 202 Xup iartkab lakarg 3111500 2835077 wikitext text/x-wiki {{Infobox | title = The Lost Zodiac | image = | caption = | label1 = Author | data1 = Tahmid Arian Borno | label2 = Year | data2 = 2026 | label3 = Status | data3 = Proposed hypothesis; under development | label4 = Subject | data4 = Astrology / stellar symbolism }} == The Lost Zodiac == '''The Lost Zodiac''' is a proposed hypothesis developed by [[Tahmid Arian Borno]] in 2026. It is an experimental astrological framework based on selected stars and constellational figures, their associated date ranges, and a proposed method for converting conventional natal-chart positions into Lost Zodiac positions. <div style="clear: both; width: auto; margin: 1em 0;"> <!-- Research Project Box --> <div style="border-left: 10px solid #0066cc; background-color: #f0f8ff; padding: 0.5em 1em; margin-bottom: 0.5em; box-sizing: border-box; width: 100%;"> '''This is a research project at Wikiversity.''' </div> <!-- Hypothesis Warning Box --> <div style="border-left: 10px solid #f28500; background-color: #fef6e7; padding: 0.5em 1em; box-sizing: border-box; width: 100%;"> '''This article describes a personal hypothesis that is currently under development. It is not presented as an established astronomical or astrological system. The astronomical information underlying individual stars and constellations is supported by external sources; the organization of the periods and the natal-chart conversion methodology are proposed by the author.''' </div> </div> == Background == The Lost Zodiac is based on a set of zodiacal periods associated with prominent stars and constellational figures. The source system on which the reconstruction is based contains 31 periods representing 22 distinct constellational figures. Several figures recur in non-adjacent periods because different stars associated with the same figure are assigned to different parts of the year. The Lost Zodiac system used as the basis for this project was created by astrologer Catherine Tennant and features 22 "lost" star signs based on major constellations located north and south of the main zodiac belt.<ref name="Interactive Stars">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac_sign.php |title=The Lost Zodiac |publisher=InteractiveStars.com |access-date=2026-09-23 }}</ref> The period boundaries, associated figures, and principal stars used in this project are derived directly from that source; the organization of the periods within this article and the natal-chart conversion methodology described below remain original to the author. The present project does not claim that the organization of these periods or their relationship to the modern natal zodiac has been historically established. Instead, the source material is used as the astronomical and symbolic foundation for a proposed reconstruction. == The Lost Zodiac Signs == {| class="wikitable sortable" ! Sign ! Period ! Associated star(s) ! Sources |- | The Lyre of Orpheus | December 29 – January 13 | Vega | <ref name="The Lyre of Orpheus">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=orpheus&date=Dec-29th@Jan-13th |title=The Lyre of Orpheus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Eagle | January 14 – January 28 | Altair | <ref name="The Eagle">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Eagle.pdf |title=The Eagle |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dolphin | January 29 – February 8 | Rotanev and Sualocin | <ref name="The Dolphin">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=dolphin&date=Jan-29th@Feb-8th |title=The Dolphin |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Swan | February 9 – February 28/29 | Sadir | <ref name="The Swan">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Swan.pdf |title=The Swan |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The River of Night | March 1 – March 12 | Achernar | <ref name="The River of Night">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_River_of_Night.pdf |title=The River of Night |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Pegasus | March 13 – April 1 | Markab, Scheat and Algenib | <ref name="Pegasus">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Pegasus.pdf |title=Pegasus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Andromeda | April 2 – April 9 | Alpheratz | <ref name="Andromeda">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Andromeda.pdf |title=Andromeda |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The River of Night | April 10 – April 18 | Acamar | <ref name="The River of Night"/> |- | Andromeda | April 19 – May 8 | Mirach and Alamach | <ref name="Andromeda"/> |- | The River of Night | May 9 – May 15 | Rana and Zanrak | <ref name="The River of Night"/> |- | Perseus | May 16 – May 31 | Algol and Mirfak | <ref name="Perseus">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=perseus&date=May16th@31st |title=Perseus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Orion | June 1 – June 7 | Rigel | <ref name="Orion">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Orion.pdf |title=Orion |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Charioteer | June 8 – June 16 | Capella | <ref name="The Charioteer">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Charioteer.pdf |title=The Charioteer |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Orion | June 17 – June 27 | Betelgeuse | <ref name="Orion"/> |- | The Dogs | June 28 – July 7 | Sirius | <ref name="The Dogs">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dogs.pdf |title=The Dogs |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Ship of the Argonauts | July 8 – July 17 | Canopus | <ref name="Ship of the Argonauts">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Ship_of_the_Argonauts.pdf |title=The Ship of the Argonauts |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dogs | July 18 – July 25 | Procyon | <ref name="The Dogs"/> |- | The Dragon | July 26 – August 7 | Gianfar | <ref name="The Dragon">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dragon.pdf |title=The Dragon |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Great Bear | August 8 – August 15 | Dubhe and Merak | <ref name="The Great Bear">{{cite web |url=https://www.interactivestars.com/beyond_zodiac/lost_zodiac.php?sign=great_bear&date=Aug-8th@15th |title=The Great Bear |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Sea Serpent | August 16 – August 23 | Alphard | <ref name="The Sea Serpent">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Sea_Serpent.pdf |title=The Sea Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Great Bear | August 24 – September 10 | Phekda, Megrez, Alioth and Mizar | <ref name="The Great Bear"/> |- | The Cup | September 11 – September 21 | Alkes | <ref name="The Cup">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Cup.pdf |title=The Cup |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Ship of the Argonauts | September 22 – September 28 | Markeb | <ref name="Ship of the Argonauts"/> |- | The Raven | September 29 – October 11 | Minkar and Algorab | <ref name="The Raven">{{cite web |url=https://jumpshare.com/share/plV6yw6ulAAMDx81uL72 |title=The Raven |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Bear Keeper | October 12 – October 26 | Arcturus and Izar | <ref name="The Bear Keeper">{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Bear_Keeper.pdf |title=The Bear Keeper |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Crown of the North Wind | October 27 – November 10 | Alphecca | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Crown_of_the_North_Wind.pdf |title=The Lost Zodiac |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Serpent | November 11 – November 19 | Unuk Elhaia | <ref>{{cite web |url=https://jumpshare.com/share/ht2Iim8ke1VrgYzEPIFQ |title=The Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Wise Centaur | November 20 – December 5 | Toliman (Alpha Centauri) | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Wise_Centaur.pdf |title=The Wise Centaur |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | Ophiuchus | December 6 – December 16 | Han, Sabik and Ras Alhague | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/Ophiuchus.pdf |title=Ophiuchus |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Dragon | December 17 – December 23 | Grumium and Etanin | <ref>{{cite web |url=https://www.interactivestars.com/zodiac_pdf/The_Dragon.pdf |title=The Dragon |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |- | The Serpent | December 24 – December 28 | Alya | <ref>{{cite web |url=https://jumpshare.com/share/ht2Iim8ke1VrgYzEPIFQ |title=The Serpent |publisher=InteractiveStars.com |access-date=2026-09-24 }}</ref> |} == Natal chart conversion methodology == The Lost Zodiac proposes a proportional conversion between a conventional zodiacal position and the corresponding Lost Zodiac period. A placement is first treated as a position within its conventional zodiac sign. That position is converted into a corresponding calendar date and time. The resulting date and time are then located within the relevant Lost Zodiac period. Each listed period includes the full span of every calendar date in its range. The starting date begins at 12:00 a.m., and the ending date concludes at 11:59 p.m. For example, a period ending on February 28 includes the entire day of February 28. In leap years, the Swan period ends at 11:59 p.m. on February 29. For a Lost Zodiac period, the beginning of the period is treated as 0°00′ and the end of the period as 29°59′. The beginning boundary is midnight at the start of the first listed date, while the ending boundary is 11:59 p.m. on the last listed date. The proposed formula is: <math> L = \frac{t-t_0}{t_1-t_0}\times29^\circ 59' </math> where: * <math>L</math> = resulting Lost Zodiac degree * <math>t</math> = the corresponding date and time of the natal placement * <math>t_0</math> = beginning of the Lost Zodiac period * <math>t_1</math> = end boundary of the Lost Zodiac period === Example === A tropical Sun position of Pisces 1°29′ corresponds to February 20, 2009 at approximately 6:25 AM in the example used by the author. The Swan period runs from February 9 through the last day of February, ending on February 28 in a common year or February 29 in a leap year. The position of February 20 at 6:25 AM is approximately 56.34% through the Swan period. Therefore: <math> 29^\circ 59'\times0.5634\approx16^\circ 53' </math> The resulting proposed Lost Zodiac position is therefore: '''Swan 16°53′''' == Reference natal chart == The following conventional natal-chart placements are used as the reference positions for the Lost Zodiac conversion. {| class="wikitable" ! Natal point ! Conventional natal position ! House |- | Sun | Pisces 1°29′ | 1st House |- | Ascendant | Aquarius 29°24′ | — |- | Moon | Capricorn 5°24′ | 11th House |- | Mercury | Aquarius 6°07′ | 12th House |- | Venus | Aries 11°30′ | 2nd House |- | Mars | Aquarius 11°55′ | 12th House |- | Jupiter | Aquarius 10°38′ | 12th House |- | Saturn | Virgo 19°41′ Rx | 7th House |- | Uranus | Pisces 21°25′ | 1st House |- | Neptune | Aquarius 24°13′ | 12th House |- | Pluto | Capricorn 2°47′ | 10th House |- | North Node | Aquarius 8°18′ Rx | 12th House |- | Lilith | Capricorn 5°16′ | 11th House |- | Chiron | Aquarius 21°52′ | 12th House |- | Fortune | Aries 25°29′ | 2nd House |- | Vertex | Virgo 17°15′ | 7th House |- | MC | Sagittarius 8°28′ | — |} == Example: Author's Lost Zodiac natal chart == Using the conversion methodology described above, the author's proposed Lost Zodiac natal placements are: {| class="wikitable" ! Natal point ! Lost Zodiac placement |- | Sun | Swan 16°53′ |- | Ascendant | Swan 14°06′ |- | Moon | Serpent 20°23′ |- | Mercury | Eagle 24°13′ |- | Venus | Pegasus 29°14′ |- | Mars | Dolphin 7°57′ |- | Jupiter | Dolphin 4°27′ |- | Saturn | Cup 1°52′ |- | Uranus | River of Night 28°32′ |- | Neptune | Swan 6°19′ |- | Pluto | Serpent 4°42′ |- | North Node | Eagle 28°35′ |- | Lilith | Serpent 19°35′ |- | Chiron | Swan 2°48′ |- | Fortune | River of Night 18°16′ |- | Vertex | Great Bear 27°04′ |- | MC | Wise Centaur 19°37′ |} == In case you don't know basic astrology == To interpret any astrological framework, including the Lost Zodiac, it is necessary to understand the four foundational components of a natal chart. These components work together to describe ''what'' is happening (Planets), ''how'' it is happening (Signs), ''where'' it is happening (Houses), and the ''dynamic relationships'' between these factors (Aspects). === 1. Zodiac Signs === Signs represent the ''style'' or ''manner'' in which planetary energy is expressed. They describe the overarching psychological themes, energetic qualities, and core motivations associated with different segments of the ecliptic. {| class="wikitable sortable" ! Sign ! Overall Concept ! Main Energy ! Need / Goal |- | Aries | Independence, Autonomy | Follows Own Impulses | Self-Expression |- | Taurus | Self-Value, Secure Self-Concept | Steady, Harmonious Doing | Peaceful Environment |- | Gemini | Perception, Thinking, Communicating | Electrical, Speedy | To Connect |- | Cancer | Sensitivity to Other People's Energies | Subtle awareness of Surroundings | Protection, Nurturing Environment |- | Leo | Self-Identity, Ego, Self-Development | Engaging | Recognition, Affirmation, Applause |- | Virgo | To be of Great Service | Analytical | To Deeply Understand |- | Libra | Knowing Self thru Relating w/Others | Back and Forth Energy Exchanges | Harmonious Interactions |- | Scorpio | Self-Mastery through Self-Knowledge | Investigative | Privacy to Do Inner Work |- | Sagittarius | Self-Expansion | Growing, Changing, Assimilating | New Experiences |- | Capricorn | Knowing Self from the Inside Out | Listens to Inner Guidance & Wisdom | Work Hard, Be Captain, Boss |- | Aquarius | Individuation, I've Got To Be Me | Separates Self Out From Others | Freedom of Thought |- | Pisces | Not of This World, Mystic, Empath | Creative, Spiritual | New Vision of Self |} === 2. Houses === Houses represent the ''areas of life'' or specific environments where planetary energies manifest. The chart is divided into 12 houses, each governing a distinct domain of human experience, from personal identity to public status. {| class="wikitable sortable" ! House ! Overall Concept ! Main Energy ! Need |- | 1st House | How One Presents and is Seen by Others, Body, Early Childhood Experiences | Energetic, Enthusiasm, Action-oriented | To Assert Oneself, To be Seen, To be Heard |- | 2nd House | Self-Concept, Self-Value, Material Security | Building, works steadily with a sense of rhythm and harmony | Sense of Self-Value, Comfort, Stability, Needs met |- | 3rd House | Perception, Thinking, Communicating, Connecting | Electrical, Mentally-Oriented | To connect |- | 4th House | Family Conditioning, Modeling Parents' Reactions, Emotional Needs | Sensitive Awareness of How Others Relate to Us | Love, Nurturing |- | 5th House | Ego-Development, Self-identity, Play, Fun, Art, Children | Joyful Creativity, Role-Playing | To Play, Have Fun, Try New Things |- | 6th House | Service, Science, Medicine, Pets, Mentors | Desire to Help, Be of Service | To Perfect a Skill, Serve Others |- | 7th House | All one-on-one close relationships | Energy Exchanges with Others | A Harmonious Environment |- | 8th House | Self-Transformation, Self-Mastery through Self-Knowledge, Renewal | Inner Work - digging up the unconscious emotions | Courage to do it, Desire to Change |- | 9th House | Self-Expansion, Seeks Meaning in Life | Assimilation of New Experiences | Meaningful New Experiences |- | 10th House | Outer-Most Social Self, Position, Status | Being of Service through Having Mastered Skill | Confidence in Inner Wisdom, Sense of Integrity |- | 11th House | One's Tribe, Audience, Allies, People w/ Commonality | Wants to Improve Society, Impact It | To be inventive, Have new ideas |- | 12th House | To let go of what is no longer needed; grieve losses, embrace gifts | Release negatives of sign; embrace positives of sign | To connect with Soul-Spirit, one's creativity, Reinvent Self |} === 3. Planets === Planets represent the ''driving forces'' or archetypal functions within the psyche. Each planet governs a specific type of energy or psychological need that seeks expression through the sign and house it occupies. {| class="wikitable sortable" ! Planet ! Overall Concept ! Main Energy ! Need / Goal |- | Sun | Self-Identity, Ego Development | Creative Play, Fun, Expressing | Recognition, Applause |- | Moon | Consciousness, Awareness, Emotional Body | Sensitivity, Awareness of Other People's Energies | Emotional Wellbeing, What makes us Happy |- | Mercury | Perception, Thinking, Communicating | Electrical, Speedy | Connection |- | Venus | Balance, Beauty, Values, Emotional Processes/Attitudes | Attractive, Magnetic | Love, Harmony, Meaning |- | Mars | Actions, Doing, Going for it | Expressive, Assertive, Defending | Good Use of Outgoing Energy, Good Boundaries |- | Jupiter | Expansiveness, Growth | Reaching out, Learning, Growing, Expanding, Assimilating | Assimilation of New Ideas, Qualities, Beliefs |- | Saturn | Steady Focus, Work, Career, Social Position / Authority | Holding, Maintaining | Maintaining Structures, to remain focused |- | Uranus | Individuation, Change, Growth, Authenticity | Dividing, Separating, Distinguishing Self from Other, Breaks Up Old Patterns | Strong Inner Focus on Authentic Self, Independent Thinking |- | Neptune | Spiritual Connection, Creativity, Dissolution | Attention to Higher Self or Soul, Erodes, Dissolves the Negative | To help you let go of what inhibits Soul life |- | Pluto | The Soul's Intention, Profound Evolution | Powerful Demand for Change, Doesn't take NO for an answer | Needs you to listen, take yourself seriously |- | Chiron | Core Wounds, Healing | Nagging, Persistence | Demands Attention for Healing |} === 4. Aspects === Aspects are the specific angular distances (measured in degrees) between planets in a chart. They describe the ''dynamic relationship'' between planetary energies, indicating whether they work together harmoniously, create tension that demands action, or require conscious integration. {| class="wikitable sortable" ! Degree ! Aspect ! Key Words |- | 0° | Conjunction | Blending Energies; Power in Union; New Beginning; Creative Impulse; Innate Potential |- | 30° | Semi-Sextile | Nagging Itch; Awakening Urge or Desire; Stimulated Imagination; Initiating Action |- | 45° | Semi-Square | Something's Not Right Feeling; Resistance; Misalignment; Friction; Reality Check |- | 60° | Sextile | Stimulation / Support to Grow, Learn, Plan, Organize, Explore, Progress & Reach Out |- | 90° | Square | Something's Got to Give; Crisis; Stress; Tension; Time for Courage, Honesty, & Decisiveness |- | 120° | Trine | Support; Easy Flow of Energy; Need Conscious Attention and Intention to Make Use of It |- | 135° | Sesqui-Square | Adjusting Personal Goals/Desires to Outer Conditions, Obstacles, or Other People's Needs |- | 150° | Quincunx | Nagging Voice of Dissatisfaction; Desire for Improvement; Attention to Details; Discernment |- | 180° | Opposition | Two Sides of One Coin; Stimulates Awareness to Balance, Integrate, & Become Whole |} '''Note on Application:''' When analyzing a Lost Zodiac chart, these four components are synthesized. The converted Lost Zodiac sign provides the thematic style, the house indicates the life area of expression, the planet identifies the driving psychological force, and the aspects reveal how these forces interact with the rest of the chart. 1pjpgfd8nsib4mng1g8635kmov4pm3l 0 332271 2835036 2835018 2026-09-29T12:32:17Z MathXplore 2888076 Added {{[[Template:BookCat|BookCat]]}} using [[User:1234qwer1234qwer4/BookCat.js|BookCat.js]] 2835036 wikitext text/x-wiki {{0% done}} An important "forerunner" of neo-classical economics was [[:w:en:William Stanley Jevons|William Stanley Jevons]] (1835–1882).<ref name=Stiglitz>G.J. Stiglitz 1946 - Production and Distribution Theories. New York, pp. 13, 135.<!-- check this reference --></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>Preface to 2nd ed. of ''Theory of Political Economy'' (1879)<!-- check this reference --> as cited by {{harvnb|Dobb|1973|p=166}}</ref> == 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 }} {{BookCat}} thmtk4abpo199b3vtbygd8xgqii12dr 2835041 2835036 2026-09-29T13:24:34Z Dick Bos 24466 Stigler ref 2835041 wikitext text/x-wiki {{0% 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://books.google.nl/books?id=c4z5t4GTlxwC&lpg=PP1&hl=nl&pg=PA13#v=onepage&q&f=false }}</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>Preface to 2nd ed. of ''Theory of Political Economy'' (1879)<!-- check this reference --> as cited by {{harvnb|Dobb|1973|p=166}}</ref> == 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 }} {{BookCat}} 2hrfx4lmfvcrnwx464w1qrviky59gi8 2835058 2835041 2026-09-29T14:01:58Z Dick Bos 24466 Menger > Jevons and ref quote Ric 2835058 wikitext text/x-wiki {{0% 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. == 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 }} {{BookCat}} n9god9uzois7tlc2874m095bkqg2t4a 2835059 2835058 2026-09-29T14:11:46Z Dick Bos 24466 Menger, Walras 2835059 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. == 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 }} {{BookCat}} hkvkzke47zrvquq7xg9gddht52fc0kk 2835060 2835059 2026-09-29T14:15:45Z Dick Bos 24466 see Walras 2835060 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 }} {{BookCat}} l7mbf3ox51uuubkd7iq9vszxhm5yvei 3 332273 2835035 2026-09-29T12:31:23Z MathXplore 2888076 advert1 ([[m:User:ZbVl/VD|Vandoom]]) 2835035 wikitext text/x-wiki == 2026-09-29 == <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/Valena181|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 @ 1790685079765.9s --><nowiki></nowiki> [[User:MathXplore|MathXplore]] ([[User talk:MathXplore|discuss]] • [[Special:Contributions/MathXplore|contribs]]) 12:31, 29 September 2026 (UTC) 1tktzjy3kgr0zjs9dsc127bx0lxlcjg 3 332274 2835037 2026-09-29T12:33:06Z MathXplore 2888076 vandalism1 ([[m:User:ZbVl/VD|Vandoom]]) 2835037 wikitext text/x-wiki == 2026-09-29 == [[File:Information.svg|25px|alt=Information icon]] Hello, I’m letting you know that one or more of your recent contributions have been reverted because they did not appear constructive. If you would like to experiment, please use the [[Wikiversity:Sandbox|sandbox]] or ask for assistance at the [[Wikiversity:Colloquium|Colloquium]]. Thank you.<!-- Glow-vandalism1 @ 1790685183511s --><nowiki></nowiki> [[User:MathXplore|MathXplore]] ([[User talk:MathXplore|discuss]] • [[Special:Contributions/MathXplore|contribs]]) 12:33, 29 September 2026 (UTC) 0tasgga9u6qryc7c2rcvrylrnvrl8ud 6 332275 2835050 2026-09-29T13:45:57Z Young1lim 21186 {{Information |Description=Block CLA 2B Single Level (20260928 - 20260926) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835050 wikitext text/x-wiki == Summary == {{Information |Description=Block CLA 2B Single Level (20260928 - 20260926) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. 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}} 9mp2ta6e8da77fhrvk061uj2v7f027b 2835051 2835050 2026-09-29T13:46:31Z Young1lim 21186 /* Summary */ 2835051 wikitext text/x-wiki == Summary == {{Information |Description=Block CLA 2C Multi Level (20260928 - 20260926) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. 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}} rgg84gt39sm9pkysyottojs0mwsyau1 6 332276 2835053 2026-09-29T13:47:39Z Young1lim 21186 {{Information |Description=Block CLA 2B Single Level (20260928 - 20260926) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835053 wikitext text/x-wiki == Summary == {{Information |Description=Block CLA 2B Single Level (20260928 - 20260926) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. 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}} 9mp2ta6e8da77fhrvk061uj2v7f027b 6 332277 2835054 2026-09-29T13:48:22Z Young1lim 21186 {{Information |Description=Block CLA 2C Multi Level (20260928 - 20260926) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835054 wikitext text/x-wiki == Summary == {{Information |Description=Block CLA 2C Multi Level (20260928 - 20260926) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. 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}} rgg84gt39sm9pkysyottojs0mwsyau1 6 332278 2835056 2026-09-29T13:49:56Z Young1lim 21186 {{Information |Description=Laurent.5: Permutation 6C (20260928 - 20260921) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. Lim |Permission={{self|GFDL|cc-by-sa-4.0,3.0,2.5,2.0,1.0}} }} 2835056 wikitext text/x-wiki == Summary == {{Information |Description=Laurent.5: Permutation 6C (20260928 - 20260921) |Source={{own|Young1lim}} |Date=2026-09-29 |Author=Young W. 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}} 5iunboow4i9e68l3s9lxyrjqexjrdtl 0 332279 2835155 2026-09-30T10:48:15Z Jtneill 10242 Created page with "{{5%done}} This page is about teaching [[psychology]], especially open approaches. ==External links== * [https://www.timeshighereducation.com/campus/five-ways-integrate-open-research-teaching Five ways to integrate open research into teaching] (Times Higher Education) * [https://www.apa.org/pubs/journals/stl Scholarship of Teaching and Learning in Psychology] (Journal) * [https://journals.sagepub.com/home/top Teaching of Psychology] (Journal) [[Category:Psychology]] ..." 2835155 wikitext text/x-wiki {{5%done}} This page is about teaching [[psychology]], especially open approaches. ==External links== * [https://www.timeshighereducation.com/campus/five-ways-integrate-open-research-teaching Five ways to integrate open research into teaching] (Times Higher Education) * [https://www.apa.org/pubs/journals/stl Scholarship of Teaching and Learning in Psychology] (Journal) * [https://journals.sagepub.com/home/top Teaching of Psychology] (Journal) [[Category:Psychology]] [[Category:Teaching]] imgd2h3xc4d3ftjuuevkpxlv73lczg4