Recent amendments to the <i>Endangered Species Act</i> and an uncertain future for species at risk: a case study of Ontario’s Niagara Region
Bibliographic record
Abstract
The biodiversity crisis is a pressing global issue. In Ontario, Canada, species at risk are protected under the Endangered Species Act (2007) . The current government amended that legislation through the More Homes, More Choice Act (2019), leaving species at risk with an uncertain future. This paper uses the Niagara Region as a case study and relies on interviews and data collection about listed species to illuminate the possible implications for the new amendments. The results indicate a total of 71 species at risk that exist in the Region, with as many as 37 species that could be delisted and stripped of protection under the recent changes. There is also concern around the prioritization of the economics over science in the amendments. While uncertainty surrounding the implementation of the amendments to the Ontario Endangered Species Act exists, there is agreement that species at risk should be protected.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".