<i>Uqsuqtuurmiut inuita tuktumi qaujimaningit</i>(Inuit knowledge of caribou from Gjoa Haven, Nunavut): Collaborative research contributions to co-management efforts
Bibliographic record
Abstract
Abstract Caribou (tuktuit) are embedded in northern life, and have been part of Inuit culture and seasonal rounds for generations. InInuit Nunangat(Inuit homelands),tuktuitare the most prevalent of country foods consumed, and remain interconnected with Inuit values, beliefs and practices. Despite co-management mandates to consider Inuit and scientific knowledge equally, the intertwined colonial legacies of research and wildlife management render this challenging. In Uqsuqtuuq (Gjoa Haven, Nunavut), community members identified the importance of documenting Inuit knowledge in order to be taken more seriously by researchers and government managers. To address this priority we worked with Uqsuqtuurmiut (people of Uqsuqtuuq) to articulate which types oftuktuitare found on or near Qikiqtaq (King William Island), provide a historical perspective oftuktuitpresence/absence in the region, and describe seasonal movements oftuktuiton and off the island. In reflecting on potential intersections of our work with the Government of Nunavut strategy “Working Together for Caribou”, we identify several considerations in support ofQanuqtuurniq(information and knowledge acquisition): defining information needs, recognising and valuing Inuit knowledge, and developing and implementing credible research. By sharing lessons from our collaborative process we aim to contribute to broader cross-cultural research and co-management efforts in Nunavut.
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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 | 0.003 | 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 | 0.010 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".