Euthanasie, abattage et mise à mort d’animaux : comment interpréter la Loi sur le bien-être et la sécurité de l’animal? Commentaire sur Road to Home Rescue Support c Ville de Montréal (Euthanasia, Slaughter and Killing of Animals: How to Interpret the Animal Welfare and Safety Act? Comments on Road to Home Rescue Support C Ville De Montréal)
Bibliographic record
Abstract
French Abstract: La Cour d’appel declare que la reconnaissance des animaux comme etant des etres doues de sensibilite par l’article 898.1 du Code civil du Quebec ainsi que les protections juridiques corollaires de la Loi sur le bien-etre et la securite de l’animal n’interdisent pas l’euthanasie ou l’abattage d’animaux, notamment lorsque la mise a mort d’un animal dangereux est ordonnee par une municipalite. Quoiqu’ils soient en accord avec le dispositif du jugement, l’auteur et l’autrice critiquent l’interpretation restrictive que la Cour d’appel fait de l’article 6 de cette loi qui, a leur avis, prevoit une prohibition generale de la mise a mort d’animaux, sauf aux fins d’agriculture, de medecine veterinaire, d’enseignement et de recherche scientifique. English Abstract: The Court of Appeal declares that the recognition of animals as sentient beings by Article 898.1 of the Civil Code of Quebec as well as the corollary legal protections of the Animal Welfare and Safety Act do not prohibit animal euthanasia or slaughter, especially when the killing of a dangerous animal is ordered by a municipality. While agreeing with the conclusions, the authors criticize the restrictive interpretation of the Court of Appeal regarding section 6 of this Act which, in their opinion, provides for a general prohibition on the killing of animals, except for the purposes of agriculture, veterinary medicine, teaching and scientific research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.032 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.037 | 0.032 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".