Marine fish, local ecological knowledge, and the Species at Risk Act in Canada: lessons from a case study of three species of wolfish
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
At a time when commercial fish stocks are overexploited around the globe, it is paramount that measures are taken to protect those species most at risk. Many countries throughout the world have legislation in place to assess and protect species in danger of extinction. \nIn Canada, departments associated with the Species at Risk Act (SARA) and members of the Committee on the Status of Endangered Species in Canada (COSEWIC) work in conjunction to assess and protect species at risk. But this was not always the case. Although \nCOSEWIC was created in 1977, SARA was not passed until 2003. Prior to 2003, COSEWIC could designate indigenous \nwildlife species in Canada as at risk, but there was no legal mechanism in place to support action in response to such a listing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it