Documenting Inuit perspectives on the significances of Arctic Char (<i>Salvelinus alpinus</i>; Iqaluppik) in food security, health, and well-being in Nunavik, their dietary preferences, and factors impacting fish quality
Bibliographic record
Abstract
Arctic Char ( Salvelinus alpinus) is a salmonid that is the second-most frequently consumed country food by Inuit in Nunavik, Northern Québec, Canada, valued for its taste, high nutritional quality, and low contaminant levels. However, climate change is increasingly impacting Arctic Char, in a region where food insecurity is highly prevalent. Inuit views on this fish are poorly documented yet provide valuable insights for improving food security and health in a context of changing subsistence fisheries. Guided by a community-based participatory research approach, we conducted interviews, focus groups, and workshops in 2022–2023 with Nunavummiut (Inuit of Nunavik) in Kangiqsualujjuaq, Aupaluk, and Kangirsuk. The objectives were to explore (1) the significance of Arctic Char to Inuit diet, culture, health, and well-being, (2) Inuit preferences regarding body parts, preparation methods, and quality attributes, and (3) Inuit knowledge on factors impacting its quality. Participants shared common views on the significance of Arctic Char. Environmental conditions, fish behavior, and fishing methods were linked to the quality of Arctic Char and Inuit-related dietary preferences. Gender roles and generational shifts were highlighted throughout discussions. Inuit shared resilient strategies when facing less preferred fish characteristics, which could help addressing the expected challenges related to climate change.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".