Plight of the endangered redside dace (<i>Clinostomus elongatus</i>) in Canada: end of the road?
Bibliographic record
Abstract
Conservation of biodiversity is recognized as a priority, with many jurisdictions having legislation protecting species at risk. Such protections are of value only if they are enforced, regardless of the strength of the laws. Redside dace ( Clinostomus elongatus) is a fish listed as endangered by both the Canadian and Ontario governments. We review the biological characteristics and the threats that contribute to its vulnerability and the reductions in its population status during recent decades. Initiatives related to infrastructure developments present risks to core redside dace populations, raising questions regarding the future of this species, and other federally listed species, in Canada. Proposed developments and modifications of protection to at-risk species by the Government of Ontario show little regard for the Ontario Endangered Species Act, and it is unclear whether the Government of Canada will enforce protections of its own Species at Risk Act. Redside dace provides an exemplar of challenges facing conservation-based legislation and the willingness of governments to enforce their own legal frameworks or challenge those of lower levels of government.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".