Mobilizing Inuit <i>Qaujimajatuqangit</i> in Narwhal Management through Community Empowerment: A Case Study in Naujaat, Nunavut
Bibliographic record
Abstract
This research examines the relationship between government wildlife management and the use of Inuit knowledge or Inuit Qaujimajatuqangit (IQ) through a case study focusing on narwhal (Monodon monoceros) harvesting in the community of Naujaat, Nunavut. Since Fisheries and Oceans Canada (DFO) introduced a community quota system in 1971, the ultimate responsibility for decision making has shifted from hunting communities to government. This shift corresponds with changes in the use of IQ within the community. Interviews with hunters, elders, and representatives of the hunters and trappers organization in Naujaat provide insight into the nature of these changes. Key factors influencing the role of IQ in narwhal management decision making included the imposed quota system, the perception of the ongoing role of IQ, communication challenges, modern-day drivers of change, and the lack of decision-making authority at the community level.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".