Moderator note: We are aware that the ‘Select date range’ field in the search box below is not currently working. We are seeking a solution and once obtained, will remove this warning box. All other fields in the advanced search box below are working correctly. Last updated 6 November 2025.
Results from your search will be shown on this page below the search form – you may need to scroll down to the results if the page does not automatically take you there after you submit your search.
Instructions:
- All blog posts are searched (pages from the menu are not searched)
- Search outputs are weighted by relevance.
- If searching with two or more words, the system uses an AND operator.
- Selecting a tag, author tag and/or category binds the search to only those posts which have those taxonomy term/s.
- A search output can be obtained by filling out any one field (ie., the search box; or, categories; or, tags; or, authors; or, date). If all fields are left blank, then the search returns the blog scroll.
- Exact word combinations can be searched for by using quotation marks (eg., “transdisciplinary learning”).
- Keyword matching is on partial words.
- The reset button (beneath the ‘Submit search’ button) will clear all entries in the search form, as will clicking on the ‘Advanced search…’ link in the top of the right sidebar.
- For more information on how advanced search works, see the ‘in-detail’ instructions below.
The search function checks all blog posts but not pages (ie., it does not check the ‘About’, ‘Index’ and other pages listed in the main menu).
For posts, search checks within titles, body text, category and tag text, and comments.
Searches are weighted by relevance, with affects the order in which posts appear, with titles and content getting the most weighting, tags and categories lesser weighting, and comments the least weighting.
Increasing the number of search terms and selections generally focuses the search output (ie., decreases the number of outputs).
Keyword matching is based on partial word/s, ie., the search will find any word containing the term you are searching on, provided the word begins or ends with the search term (eg., searching for ‘ion’ will not only find the word ‘ion’ but will also find ‘caution’ or ‘ionized’, but not “cautionary’).
If you enter two or more words into the search box, the relationship between the words is based on an AND operator (meaning the more words you add, the tighter (less content is returned in) the search output).
- For example, entering transdisciplinary learning into the search box would provide an output that lists all posts with both the word transdisciplinary and the word learning anywhere in the text, Posts with only transdisciplinary in the text or posts with only learning in the text would not be included in the output.
To find a specific word combination (eg., critical systems), wrap in quotation marks (ie., “critical systems“).
When you open a post that was found by your search, you can find where your specific word or word combination appears by using your computer’s search function (eg., on a computer running Microsoft Windows, Control ‘F’ will allow you to search the post (as well as anything else in the active screen)).
Restrict searches to particular tags, categories and/or author tags by using the dropdown selectors.
- Eg., if you choose the tag Advocacy, the search will only be conducted within posts that have that tag assigned to them.
- If you added the category Cases to that search, then only posts that had both the tag Advocacy and the category Cases assigned to them would be searched.
An alternative to selecting categories, tags or authors from their respective long drop-down list is to type the term or author name you are looking for in the relevant selector field. Typing one letter will jump to the lead word in the alphabetical listing (ie, typing ‘s’ takes you to the first tag or category in the list of those starting with ‘s’). Further addition of letters will home in on a tag, category or author until it is found or until the choice of letters exhausts the possible set of tags, categories or authors (in which case that tag, category or author is not in our list). NOTE: all authors are also available in reverse name order under ‘Authors‘ in the menu bar.
In the category, tag and author dropdown list, the number in brackets after each entry indicates the number of posts with that category, tag or author assigned to them.
Tags or authors with a zero in brackets “(0)”, placed after the tag or author text, are not currently linked to any blog posts. In the case of tags, most of these tags identify alternative tags, which, if searched, will yield a result. For example, “Assumptions – see ‘Mental models’ tag (0)” signifies that blog posts about ‘assumptions’ are tagged with ‘mental models’ and not ‘assumptions.’ Occasionally there will be a tag (or author tag) with “(0)” which refers to a new tag (or author tag) on a blog post which has not yet been made public. This tag (or author tag) will be searchable once the blog post is public (usually within a week).
For the category selector, choosing one of the two parent categories (main topics or resource types) searches all blog posts, as all blog posts are assigned a main topic and a resource type.
Transdisciplinary research with and for artificial intelligence
By Florian Keil, Melina Stein and Flurina Schneider.
2. Melina Stein (biography)
3. Flurina Schneider (biography)
Is artificial intelligence, a technology aggressively advertised as the ultimate cure-all, fundamentally incompatible with transdisciplinarity and its decades-old insight that the “wicked” problems of the real world do not lend themselves to one-dimensional solutions? Should transdisciplinary research outright reject a technology that is already undermining efforts to achieve social and environmental justice? Or can artificial intelligence actually support transdisciplinary research when used responsibly?
Using artificial intelligence in transdisciplinary research requires a critical mindset
Three social mechanisms leading to fake interdisciplinary collaborations / 形成伪跨学科合作的三种社会形成机制
A Chinese version of this post is available
What are fake interdisciplinary collaborations and how do they arise?
Fake interdisciplinary collaborations are a form of performative scientific behaviour that claims to be interdisciplinary but lacks knowledge integration across disciplines. There are three social mechanisms that can result in such fake collaborations.
1. Irresponsible project management
Irresponsible project management has two manifestations:
Building co-production capabilities in researchers: Strengthening reflexivity via learning opportunities
By Emma Ligtermoet, Claudia Munera-Roldan, Cathy Robinson, Zaynel Sushil and Peat Leith.
What forms of learning can support interdisciplinary teams to rapidly build reflexivity capabilities, especially in preparation for doing transdisciplinary (engaged) science with non-researcher societal actors?
Transdisciplinary co-production requires deep and reflexive learning. Reflexivity is a key capability for researchers doing inter- and transdisciplinary science, involving the critical enquiry of existing assumptions, values and norms underlying our decisions and actions, with the aim to adapt or change current practices or discourses.
Such learning is foundational for understanding and proactively engaging with knowledge-power dynamics, including potentially catalysing shifts in incumbent dynamics when preparing to engage with non-societal actors.
Seven quality choice points for contemporary action research
By Hilary Bradbury.
How can action researchers empower system actors in impactfully responding to our deepening eco-social crisis? How can action research be a catalyst to successfully transmute the inexhaustible resource of human creativity in all spaces—self to society—toward addressing our global problems? How can we encourage deepening clarity of choices made to navigate a middle path between responding to problems within living communities and contributing to research-based theory?
Mitigating the worst of our global problems requires action research that draws on many kinds and sources of knowledge. In fact, it requires drawing much more from diverse people on the ground, who understand the problems at hand and can offer solutions anchored in their experience of what is meaningful for them.
The aim of the seven choice points described below is to support action researchers in:
- deepening and speeding up the proliferation of good work,
- connecting local niche experiments to global reach.
A tool for developing shared awareness of team member research interests and expertise
By Melanie Bauer, Joshua Roney and Stephen M. Fiore.
2. Joshua Roney (biography)
3. Stephen M. Fiore (biography)
How can team members who have been working together for a while check assumptions, ensuring they are aware of each other’s breadth of expertise and research interests?
We have developed the “Linking-Relinking” tool to facilitate such a process. This tool supports science teams through development of a transactive memory system, which is a form of shared cognition having to do with “who knows what” on a team. Studies continually show that teams that develop an accurate transactive memory system are better able to coordinate their knowledge when working on challenging problems. The Linking-Relinking Tool can support transactive memory system development by helping members determine how accurate their knowledge is of their teammates and calibrate appropriately.
Combining subjectivity and objectivity in systems thinking: The SOS sandwich
By James Stauch and Daniela Papi-Thornton.
2. Daniela Papi-Thornton (biography)
In seeking to understand, map, and then act to intervene in a system, how can we make the best use of both subjectivity and objectivity? How can we effectively toggle between facts and norms, between what is true (or at least broadly verifiable) and what is valued (or valuable)?
In the book that this i2Insights contribution is based on (Stauch et al., 2025), the case is made for people to spend far more time understanding a problem, and proportionally less time acting to “solve” the problem. To help frame this approach, the SOS (subjective-objective-subjective) sandwich is used as a simple heuristic to show where subjectivity and objectivity can be taken into account when dealing with a system.
In this work, objectivity is considered as a vector, not a destination, with true objectivity always out of reach, as we can never be completely objective in our approach to research. That said, we can strive for it by recognizing our biases and seeking diverse viewpoints.