Sociocultural determinants of traditional food intake across indigenous communities in the Yukon and Denendeh
Bibliographic record
Abstract
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 characterised by highly processed foods with reduced nutrient density. This study used food frequency and 24-hour recall questionnaires to quantify traditional food intake in 18 communities in Denendeh (Western Northwest Territories) and the Yukon. These data allowed comparisons between the two regions (Yukon and Denendeh) and the two seasons of data collection (summer and winter, perceived to be the seasons of highest and lowest traditional food intake, respectively). Food choice in general is affected by a multitude of factors determined by individual, societal and environmental influences. In this study, individual, household, and community correlates of traditional food intake were assessed in order to construct a multivariate statistical model to describe the correlates of the quantity and diversity of traditional food intake in the Western Canadian Arctic. The variables used in this study reflected household demography, market food affordability, access to traditional food, individual characteristics such as age and gender, and perceptions about traditional food. The analysis of the associations between the traditional food correlates and traditional food intake in terms of quantity and diversity allowed for the description of the profile of men and women who are high consumers of traditional food in both regions. This study described and used a tool to measure traditional food diversity, which may be an appropriate indicator of the process of dietary change experienced by Indigenous Peoples in Denendeh and the Yukon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 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".