Design of a human biomonitoring community-based project in the Northwest Territories Mackenzie Valley, Canada, to investigate the links between nutrition, contaminants and country foods
Bibliographic record
Abstract
Community-based projects place emphasis on a collaborative approach and facilitate research among Indigenous populations regarding local issues and challenges, such as traditional foods consumption, climate change and health safety. Country foods (locally harvested fish, game birds, land animals and plants), which contribute to improved food security, can also be a primary route of contaminant exposure among populations in remote regions. A community-based project was launched in the Dehcho and Sahtù regions of the Northwest Territories (Canada) to: 1) assess contaminants exposure and nutrition status; 2) investigate the role of country food on nutrient and contaminant levels and 3) understand the determinants of message perception on this issue. Consultation with community members, leadership, local partners and researchers was essential to refine the design of the project and implement it in a culturally relevant way. This article details the design of a community-based biomonitoring study that investigates country food use, contaminant exposure and nutritional status in Canadian subarctic First Nations in the Dehcho and Sahtù regions. Results will support environmental health policies in the future for these communities. The project was designed to explore the risks and benefits of country foods and to inform the development of public health strategies.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".