Contribution of First Nation stewardship programs in monitoring the health of the Salish Sea
Bibliographic record
Abstract
The Tsleil-Waututh are the ‘People of the Inlet’, with Burrard Inlet at the heart of the territory. Our history, identity, and rich culture are deeply connected to our lands and waters. We uphold our obligation to protect our territory. Unchecked urban and industrial development within the territory has degraded the health of our Inlet. In response, Tsleil-Waututh Nation developed a marine stewardship program based on community-identified goals. These goals include the ability to harvest healthy traditional foods from the Inlet, to practice cultural expression and ceremonies in clean waters, and to restore the health of our Inlet. Shellfish closures have been imposed in our territory for decades. TWN is increasing its focus on monitoring and enhancing shellfish stocks within the Inlet. TWN strives to return healthy shellfish as a traditional food source from traditional harvesting sites to the community. In 2013/2014, TWN has made considerable advancements in pursuit of this focus. TWN partnered with Swinomish Tribal Council to assess potential climate change impacts to the respective community’s shellfish beds and effects to the respective community’s health and well-being. TWN continued to monitor contamination in shellfish tissue samples collected from traditional harvesting sites in Burrard Inlet. Community consumption surveys are to be completed by TWN in 2014 to determine existing consumption patterns and to better assess potential exposure to environmental contaminants for community members. TWN has three previous years of shellfish monitoring data in collaboration with Environment Canada and Health Canada. TWN is working with the Canadian Food Inspection Agency (CFIA) to monitor biotoxins in shellfish tissue (DSP and PSP). TWN will be working with the Department of Fisheries and Oceans (DFO) to develop a Community Harvest Plan for a Food, Social, and Ceremonial (FSC) harvest, supported by laboratory analysis of tissues and TWN stock assessments.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".