Estimation of traditional food intake in indigenous communities in Denendeh and the Yukon.
Bibliographic record
Abstract
Objectives. Chronic non-communicable diseases related to excessive or unbalanced dietary intakes are on the rise among some Indigenous populations in Canada. Nutritional problems of Indigenous peoples arise in the transition from a traditional diet to a market diet characterized by highly processed foods with reduced nutrient density. This study aimed at assessing traditional food intake of Indigenous people in 18 communities. Study design. This study was cross-sectional with a sample size of 1,356. Methods. This study used food frequency and 24-hour recall questionnaires to quantify traditional food intake in 18 communities in the McKenzie basin of the Northwest Territories (Denendeh and the Yukon). Results. Typical daily intakes of groups of traditional food items were generated and intake of an extensive list of traditional food detailed for adult men and women. Per capita intake of traditional food items was also calculated. Conclusion. Reliance on traditional food intake is still high in Denendeh, as well as in the Yukon. The detailed description of the traditional food system presented here allows an accurate identification of the contribution of traditional food items to nutrient and contaminant intake by Indigenous people for future studies. (Int J Circumpolar Health 2005; 64(1):46-54) Keywords: Canada, Denendeh, food intake, Indigenous People, traditional food, Yukon
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".