Traditional food attributes must be included in studies of food security in the Canadian Arctic
Bibliographic record
Abstract
OBJECTIVES: The objective was to explore some typically understudied characteristics of food security in Arctic Canada: observed changes to traditional food systems, perceived advantages and health benefits of traditional food and traditional food preferences. STUDY DESIGN: Data analysis used a cross-sectional survey of Yukon First Nations, Dene/Métis and Inuit women in 44 Arctic communities. METHODS: Open-ended responses to 4 questions were used to qualitatively investigate roles traditional foods play in Arctic food security. Chi-square tests were applied to responses to ascertain differences by age and region. A fifth question explored agreement with cultural responses to harvesting and using traditional food. RESULTS: Traditional food was regarded as natural and fresh, tasty, healthy and nutritious, inexpensive, and socially and culturally beneficial. Between 10% and 38% of participants noticed recent changes in the quality or health of traditional food species, with physical changes and decreasing availability being reported most often. Caribou, moose and seal were among the foods considered particularly healthy and held special values in these populations. The opinion that all traditional food was healthy was also popular. More than 85%, of participants agreed with most cultural attributes of traditional food. CONCLUSIONS: This study confirms that traditional food remains important to Arctic indigenous women and that food security in the Arctic is contingent upon access to these foods.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".