Consistency of COSEWIC species at risk designations: freshwater fishes as a case study
Bibliographic record
Abstract
The Committee on the Status of Endangered Wildlife in Canada (COSEWIC) is responsible for the assessment of Canadian wildlife at risk. The COSEWIC assessment process is primarily based on five quantitative criteria developed by the International Union for the Conservation of Nature, but allows for further modification of designations under certain conditions. This study investigated the consistency of designations predicted using the quantitative COSEWIC criteria compared with observed designations reported by COSEWIC. A total of 49 COSEWIC designations for freshwater fishes from 2000 to 2007 were compared for consistency in decision-making. Overall, there was a 57.1% agreement between predicted and observed designations. A substantial number (35.1%) of COSEWIC designations were downlisted from “Endangered” or “Threatened” without sufficient explanation to justify the modifications. For the cases of uplisting, these differences were associated with qualitative criteria not effectively represented in our algorithm. Recommendations are offered to improve the transparency and accountability of COSEWIC decision-making, including enhancements to reporting and the explicit incorporation of uncertainty in the COSEWIC risk assessment protocol.
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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 | 0.067 | 0.153 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".