Indigenous Governance is an Adaptive Climate Change Strategy
Bibliographic record
Abstract
Since the 1960s, scientists have been aware that human activity has resulted in a warming climate. This reality has and will continue to result in changes to the way we live.The Arctic and Subarctic have held prominent places in discussions on climate change, in part because impacts here are so stark and clearly connected to the effects of changes in temperature. In popular discourse internationally, media narratives often focus on “charismatic megafauna”: polar bears starving, venturing into towns, disoriented, hungry, drowning.1 In Canada, Indigenous and ally activism on climate change make the link with food security, personal safety, and cultural survival, employing stories of Indigenous hunters no longer able to reliably read the signs of the land due to “strange weather.”2 Indigenous Peoples provide critical insights into how climate change results in immediate and important implications for humans.3 However, using Indigenous experiences as evidence for climate change is often where the conversation stops—it should instead be a starting point. The conversation needs to turn to how Indigenous Knowledge, cultures, and the ways of life grounding Indigenous decision-making authority are a viable, legitimate, sustainable, and adaptive climate change strategy. ...... continued
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".