Documenting Indigenous Knowledge to Identify and Understand the Stressors of Muskoxen (<i>Ovibos moschatu</i>s) in Nunavut, Canada
Bibliographic record
Abstract
Indigenous knowledge provides valuable information on wildlife health and ecology, contributing to a broader understanding of the patterns and phenomena observed. Muskoxen (Ovibos moschatus), an important species for the subsistence and culture of Inuit communities in the Arctic, are increasingly exposed to diverse stressors linked to rapid climate change and other anthropogenic changes. Identifying and understanding these stressors and their impacts on muskoxen will inform management, health monitoring, and future research. To achieve this understanding, we documented Indigenous knowledge through seven semi-structured small group interviews, each involving two to three purposely chosen muskox harvesters in Kugluktuk, Nunavut, Canada to (1) establish the characteristics of healthy muskoxen, (2) determine the factors considered to impact muskoxen, and (3) understand, from an Indigenous knowledge perspective, the results from a study on the sex, seasonal, and annual patterns of glucocorticoids (described as “stress hormones” for the purposes of the interviews) in muskox hair. Key outcomes include (1) a more holistic understanding of muskox health and what it encompasses, (2) recognition and exploration of a rich One Health perspective expressed by participants around factors influencing muskoxen in a changing world and highlighting the multiple socioecological connections, and (3) a broader comprehension of the glucocorticoid (stress) patterns measured in muskox hair, the various factors that influence them, and their interrelations. This study represents a meaningful advancement in the process of actively involving communities at all steps of the research and highlights the important contributions Indigenous knowledge can offer to the complex field of wildlife endocrinology research.
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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 | 0.001 | 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 | 0.005 | 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 | 0.000 |
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".