Bibliographic record
Abstract
One of the integral components of Canada’s Species at Risk Act (SARA) is recovery planning for threatened, endangered, or extirpated species in Canada. The recovery planning process is guided by recovery strategies, to be published within one year of listing for endangered species and within two years of listing for threatened or extirpated species, though publication has rarely met statutory timelines. Here I investigate factors associated with recovery strategy completion as well as factors associated with strategy content, specifically recovery feasibility, information gaps, and critical habitat identification. Despite significant delays in strategy publication, I find no evidence of internal prioritization of species for strategy completion, with only administrative factors retained in predictive models; species listed on Schedule 1, for which the Department of Fisheries and Oceans (DFO) or Parks Canada Agency (PCA) is the Responsible Authority, or which there was a smaller backlog of due strategies one year after listing were more likely to have recovery strategies submitted on time. Analysis of factors associated with recovery feasibility show a higher likelihood of feasible recovery for species for which critical habitat is identified, the DFO or PCA is the Responsible Authority, there are more identified information gaps, or for which the recovery strategy contains a section on potential socioeconomic conflict. There were fewer identified information gaps in recovery strategies for those species for which recovery strategies were published after the judgments of the Nooksack Dace (ND) and Greater Sage-Grouse (SG) court proceedings, there was a greater time elapsed between strategy due date and date of draft publication, or whose range does not fall on a provincial or federal protected area. Pre-ND and SG court judgements, critical habitat was less likely to be identified for species with a lower threat status, species included in multi-species or ecosystem plans, or species not found within provincial or federal protected areas. None of these biases were detected post-judgement, however, as rates of identification increased significantly and only recovery feasibility was associated with CH identification. These results point to some potential problems in the recovery planning process as currently implemented under SARA, and inform recommendations as to how these might be addressed.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".