Retail food sales in Nunavut, Canada not impacted by short-term weather-related inaccessibility of trails used for Inuit subsistence harvesting
Bibliographic record
Abstract
Inuit have long utilized trail networks for subsistence harvest. Fueled by climate change, increasingly volatile environmental and weather conditions in the Canadian Arctic territory of Nunavut have made these routes less reliable and more dangerous-jeopardizing availability of traditional foods. Qualitative research indicates communities adapt by grocery shopping. We modeled consecutive days of trail inaccessibility on total grocery and meat product sales, respectively, of a market-dominant retailer in 13 Nunavut communities. Although we hypothesized positive associations between trail inaccessibility and store purchasing, we observed negligible negative associations; meanwhile, socioeconomic factors like pay dates yielded strong, positive associations. In light of the null findings with respect to trail inaccessibility, we discuss key limitations of our approach and potential alternative explanations that might account for these unexpected findings, including the ecological level of analysis potentially masking subgroup vulnerabilities relative to exposure or outcomes, hunters' possible risk tolerance elasticities, and food sourced beyond our partner retailer (such as from the other major retail chain or through food sharing networks). Given the local nutrition and economic transitions-away from traditional food and subsistence livelihoods-communities may face reduced day-to-day vulnerability to trail accessibility disruptions. As the wage-based economy expands and the contemporary diet includes more energy-dense, processed store-bought food, Inuit communities may become increasingly sensitive to macro-political and economic pressures on their food system and sovereignty.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".