Vulnerability to unintentional injuries associated with land-use activities and search and rescue in Nunavut, Canada
Bibliographic record
Abstract
Injury is the leading cause of death for Canadians aged 1 to 44, occurring disproportionately across regions and communities. In the Inuit territory of Nunavut, for instance, unintentional injury rates are over three times the Canadian average. In this paper, we develop a framework for assessing vulnerability to injury and use it to identify and characterize the determinants of injuries on the land in Nunavut. We specifically examine unintentional injuries on the land (outside of hamlets) because of the importance of land-based activities to Inuit culture, health, and well-being. Semi-structured interviews (n = 45) were conducted in three communities that have varying rates of search and rescue (SAR), complemented by an analysis of SAR case data for the territory. We found that risk of land-based injuries is affected by socioeconomic status, Inuit traditional knowledge, community organizations, and territorial and national policies. Notably, by moving beyond common conceptualizations of unintentional injury, we are able to better assess root causes of unintentional injury and outline paths for prevention.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".