Federalism and Animal Law in Canada: A Case for Federal Animal Welfare Legislation
Bibliographic record
Abstract
This article explores the subject of laws as they influence animals within Canadian federalism. Part I explains the division of powers as a barrier for animal protections in Canada. As the subject of animals is not expressly articulated within the division of powers, laws have been passed by both federal and provincial legislatures (including municipal by-laws) which relate to animals. Unfortunately, the resulting jurisdiction-specific laws result in patchwork protections and a lack of uniformity in animal laws across Canada. Federal legislation is needed to ensure uniform protections for animals nation-wide. Part II addresses the question of jurisdiction: which level of government has the jurisdiction to legislate laws about animals? Jurisprudence from the Supreme Court is reviewed, and the division of powers test is applied to two current – albeit highly aspirational – pieces of draft animal rights legislation. Part III offers guidelines and considerations for future draft federal legislation which may withstand constitutional scrutiny. Legislation which criminalizes the abuse of animals has a high chance of withstanding a constitutional challenge as it is firmly rooted in the federal powers of criminal law.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.033 | 0.028 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".