The Importance of Marine Foods to a Near-Urban First Nation Community in Coastal British Columbia, Canada: Toward a Risk-Benefit Assessment
Bibliographic record
Abstract
There is increasing concern that some subsistence-oriented consumer groups may be exposed to elevated levels of persistent organic pollutants (POPs) through the consumption of certain traditional foods, including fish and other aquatic resources. Exposure to POPs has been associated with adverse health effects including immunotoxicity, endocrine disruption, and altered development in moderate to highly exposed humans and wildlife. The Sencoten (Saanich) First Nation consists of approximately 1900 people inhabiting communities in a near-urban setting in coastal British Columbia, Canada. A survey was conducted to document the relative importance of traditional foods in the diet of the Sencoten people, as a basis for the future assessment of exposure to, and risks associated with, environmental contaminants in such a diet. Salmon represented 42% of the total marine meals, but at least 24 other marine species were also consumed. Our study suggests that traditional marine foods remain very important to the social and economic well-being of the Sencoten, despite their proximity to an urban center. This information will be of value to those interested in nutritional, cultural, and health issues concerning subsistence-oriented First Nations peoples, and provides an important first step in risk assessment.
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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 | 0.002 |
| 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 | 0.001 | 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".