Assessing Risk of Extinction of Marine Fishes in Canada—The COSEWIC Experience
Bibliographic record
Abstract
Abstract Canada's Species at Risk Act (SARA; 2003) legally established the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) with a mandate to assess the status of wildlife species it considers to be at risk. Species assessed by COSEWIC as at risk are then considered by the federal government for conservation action, including listing on SARA's Schedule I. COSEWIC‘s Marine Fishes Specialist Subcommittee focuses on five groups of high vulnerability: anadromous species, elasmobranchs, long‐lived species, species of large maximum size, and species that have shown severe decline. COSEWIC‘s assessment protocol uses quantitative criteria based on those developed by the International Union for Conservation of Nature (IUCN) but also considers life history and other biological information in assigning status. Published assessments cover 61 marine fish species: one extirpated, 14 endangered, 14 threatened, 16 special concern, 7 not at risk, and 9 data deficient. Questioned by some stakeholders, COSEWIC's assessment protocol represents a stable, documented framework that should give consistent results. Assessments show a broad pattern of severe declines across a wide range of species that might be expected to stimulate strong coordinated conservation action. Few marine fish species have been listed on SARA Schedule I. Conservation action for COSEWIC‐assessed species has been strong in some cases but not in others.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".