Risks and Impacts to First Nation Health and the Mount Polley Mine Tailings Dam Failure
Bibliographic record
Abstract
In August 2014, the Mount Polley Mine tailings dam was breached, releasing millions of cubic metres of tailings water and tailings into Polley Lake, Quesnel Lake, and Hazeltine Creek in British Columbia (BC), Canada. To date, no assessment has identified the communities impacted by this event, nor how they were impacted, from a social or health perspective. This qualitative study uses a community-based participatory research approach to identify (1) First Nations impacted by this incident and (2) impacts to Aboriginal health experienced by these communities. To address these gaps in knowledge, the First Nations Health Authority funded the project team to complete the first two phases of a health impact assessment. This work draws attention to the strong links between First Nations, the land and resources, culture, and associated health outcomes. In considering the importance of Aboriginal health and culturally appropriate health pathways, the project team identified 4 key impacts: environmental dispossession, emotional stress, altered dietary patterns, and changes in physical activity. The similarity in impacts associated with the Mount Polley tailings dam failure for many First Nations in BC is best understood through an in-depth understanding of the importance of the Fraser River as a source of salmon for their communities. This work documents the unidentified and unfulfilled need to ameliorate the extent of emotional trauma prompted by real or perceived threat to salmon health, a threat exacerbated by a lack of reliable information from trusted sources in the aftermath of the breach. Relevant recommendations are also provided.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".