Anticipating workshop fatigue to navigate power relations in international transdisciplinary partnerships: A climate change case study
Bibliographic record
Abstract
Workshop fatigue is a colloquialism to describe apathy towards facilitated discussions that, in interventions designed to build partnerships, tends to be viewed as somewhat inevitable. To challenge this assumption, this article theorises fatigue as a subtle form of resistance. Evidence is based on qualitative research as part of a climate change collaboration, with a focus on a methodology called ‘transformative scenario planning’. The author combines Goffman, Scott and Pratt to analyse interactions between facilitators, researchers and stakeholders in meetings and workshops. Historical representations of scientific endeavours are contrasted with performances of participation in Namibia, India and Botswana. The article concludes that anticipating workshop fatigue could be an accessible way to surface power relations in inherently unequal international partnerships, and bring a sociological sensibility to transdisciplinary climate change research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".