Inuit Attitudes towards Co-Managing Wildlife in Three Communities in the Kivalliq Region of Nunavut, Canada
Bibliographic record
Abstract
We explored Inuit attitudes towards co-managing wildlife in the Kivalliq Region of Nunavut, Canada, working in partnership with the hunters and trappers’ organizations of Igluligaarjuk (Chesterfield Inlet), Tikirarjuaq (Whale Cove), and Qamani’tuaq (Baker Lake). In mixed-methods interviews, study participants in the two coastal communities described dissatisfaction with polar bear (Ursus maritimus) management outcomes, in contrast to a general satisfaction with (or indifference to) the management of other species. Interviewees expressed concern about grizzly bear (Ursus arctos) and, more prominently, caribou (Rangifer tarandus groenlandicus) populations in Qamani’tuaq, the inland community. Researchers have predicted that conflicts specific to polar bear management could lead to regulations being ignored or even defied and endanger the entire system of wildlife co-management. Our results indicate that dissatisfaction over decisions is specific to polar bear management outcomes and does not necessarily apply to the broader system of wildlife co-management. The results suggest that the Nunavut wildlife co-management system is quite functional: polar bear issues aside, Inuit in Qamani’tuaq, Tikirarjuaq, and Igluligaarjuk are largely content with the current functioning of the wildlife co-management regime.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".