Coexistence between people and polar bears supports Indigenous knowledge mobilization in wildlife management and research
Bibliographic record
Abstract
Polar bears are coming into northern communities more frequently, and human-polar bear conflict is increasing. However, in the community of Churchill, Manitoba, Canada, people live alongside polar bears with high tolerance and reciprocal respect. Through this case study, we explored human-polar bear coexistence in the community through Indigenous voices, documented social-ecological change, and mobilized recommendations as future visions to inform inclusive management and research strategies: elevate Indigenous knowledge, support proactive management and less invasive research, cultivate a culture of coexistence, improve education and safety awareness, and protect polar bears to support tourism. We used community-based participatory research, coproduction of knowledge, hands back, hands forward, and storytelling, mixing methods from the social sciences and Indigenous ways of knowing. Our study revealed coexistence can be a tool to bridge social and ecological knowledge, examine and facilitate wildlife conservation, and promote well-being through applied research on global issues at the local level. In Churchill, Manitoba, Canada, people live alongside polar bears with tolerance and reciprocal respect and the meaning of their coexistence, mobilization of Indigenous knowledge, and recommendations for future wildlife management are explored in an analysis that uses mixed methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".