Sharing country food: connecting health, food security and cultural continuity in Chesterfield Inlet, Nunavut
Bibliographic record
Abstract
Food security is a complex topic defined not just by having enough nutritious food to eat but also by cost, safety and cultural considerations. In Arctic Inuit communities, food security is intimately connected to culture through traditional methods of harvesting country food. In Chesterfield Inlet, Nunavut, community-based research was conducted in collaboration with Chesterfield Inlet community members using interviews and community engagement. Community members were consulted about the design of the interview guide, recruitment of participants, analysis and validation of results. This study aims to develop a theoretical framework of how food security, cultural continuity and community health and well-being are interconnected to allow for a richer understanding of how increased shipping, climate change and social changes are impacting community members. In Chesterfield Inlet, harvesting and consuming country food (e.g., seal) is perceived as the mechanism that connects food, culture and community health. Sharing of freshly harvested country food supports the food security of community members without hunters in their families, aligns with hunters’ cultural beliefs and promotes community health and well-being. Changes that reduce a hunter’s success in harvesting country food limit her or his ability to share country food, which negatively impacts community health and well-being. The results of this study support existing community efforts to adapt to changes that impact harvesting success.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".