Industrialization and food safety for the Tsleil-Waututh Nation: An analysis of chemical levels in shellfish in Burrard Inlet
Bibliographic record
Abstract
While Indigenous food systems remain critical for community well-being, traditionally harvested foods are a potential source of toxic exposures. The Tsleil-Waututh Nation (TWN) is seeking to restore shellfish harvesting in Burrard Inlet (British Columbia [BC], Canada), where the cumulative effects of industrial activity have nearly eliminated safe harvesting. The Trans Mountain Expansion project would triple the capacity to transport oil through the inlet, threatening TWN's progress to restore shellfish harvesting. To inform ongoing efforts we assessed contamination by heavy metals (arsenic, cadmium, lead, and mercury) and 48 polycyclic aromatic hydrocarbons (PAHs) congeners in different shellfish species (Softshell clams, Varnish clams, and Dungeness crab) in three areas. We compared our results against local screening values (SVs) established by the TWN and BC Ministry of Environment and Climate Change Strategy, as well as provincial and national benchmarks. In total, we analyzed 18 composite samples of Softshell clams and Varnish clams (5 individuals per sample), as well as 17 individual crabs. We found chemical contamination in all species at all sites. PAHs were most frequently detected in Softshell clams, highest in the site closest to the pipeline terminus. Clams presented higher levels of contamination than crabs for PAHs, but not for heavy metals. For Softshell and Varnish clams, all heavy metals across study sites exceeded at least one of the population-specific SVs. Of the 14 PAHs detected, benzo(a)pyrene presented a median concentration in Softshell clams of 3.25 μ/kg, exceeding local SV for subsistence fisher. Our results call for further assessment of human health impacts related to food harvesting within Burrard Inlet and establishing a long-term coordinated program co-led by the TWN to monitor contamination and inform future harvesting programs. The study draws attention to the need to consider locally-relevant toxicity benchmarks, and include potential health impacts of food contamination in appraising development project proposals.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".