Canada’s Species at Risk Act and Atlantic Salmon: Cascade of Promises, Trickles of Protection, Sea of Challenges
Bibliographic record
Abstract
This article reviews through a three-part format the role and efficacy of the Species at Risk Act (SARA) in trying to save SARA-listed inner Bay of Fundy (iBoF) Atlantic salmon and other Atlantic salmon populations at risk from the brink of extinction. The cascade of SARA promises is first discussed, including: the independent assessment of the status of the species based on best available scientific information; the protection of listed species, their residences and critical habitat; and the two-stage recovery planning process. The trickles of protection actually delivered by SARA in relation to Atlantic salmon are next described, including the recent adoption of a Recovery Strategy and identification of critical freshwater habitat. The sea of challenges in implementing SARA and in strengthening the protective net outside SARA is finally highlighted. Particular challenges include: overcoming the slow implementation of the Act; addressing scientific limitations of the Recovery Strategy; forging a clear agenda for recovery actions; confronting limitations in incidental harm permitting; protecting critical habitat; getting a grip on protection and recovery of other Atlantic salmon populations at risk; bolstering environmental assessment; enhancing provincial engagement in recovery efforts; ensuring full implementation of Canada’s Oceans Act; and charting future directions for the North Atlantic Salmon Conservation Organization.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| 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".