The Species at Risk Act (2002) and Transboundary Species Listings along the US–Canada Border
Bibliographic record
Abstract
This paper is a collaborative interdisciplinary examination of the scientific, political, and cultural determinants of the conservation status of mammal species that occur in both Canada and the USA. We read Canada’s Species at Risk Act as a document of bio-cultural nationalism circumscribed by the weak federalism and Crown–Indigenous relations of the nation’s constitution. We also provide a numerical comparison of at-risk species listings either side of the US–Canada border and examples of provincial/state listings in comparison with those at a federal level. We find 17 mammal species listed as at-risk in Canada as distinct from the USA, and only 6 transboundary species that have comparable levels of protection in both countries, and we consider several explanations for this asymmetry. We evaluate the concept of ‘jurisdictional rarity’, in which species are endangered only because a geopolitical boundary isolates a small population. The paper begins and ends with reflections on interdisciplinary collaboration, and our findings highlight the importance of considering and explicitly acknowledging political influences on science and conservation-decision making, including in the context of at-risk-species protection.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".