Indigenous perspectives on and expertise within climate change, justice, technology & sciences
Bibliographic record
Abstract
Panel: Indigenous perspectives on and expertise within climate change, justice, technology & sciences – 20 November 2025 Online and in-person parallel session at the Climate Existence Symposium 2025, Uppsala University Place: Engelska parken, Uppsala University and online Time: 16.00 -17.30 Session Summary Presentations on research in progress within Powering Change With Justice: Weaving Indigenous perspectives to uncover impacts of the wind energy transition, funded by FORMAS, led by Dr Vanessa Masterson, Stockholm Resilience Centre; ⴰⵔⵔⴰⵎⴰⵜ Ărramăt: Strengthening Health And Wellbeing Through Indigenous-Led Conservation and Sustainable Relationships With Biodiversity, based at University of Alberta, Edmonton, and SING Sábme: Questioning “Green Energy” and its Impact on Indigenous Livelihoods in Sweden, all co-led by Dr May-Britt Öhman, Centre for Multidisciplinary Studies on Racism, CEMFOR, Uppsala University Moderator: May-Britt Öhman
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.009 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.054 | 0.003 |
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".