Bibliographic record
Abstract
It is commonplace to affirm that animal law is much more developed in the United States than in Canada; animal abuser registries are being implemented,' animal law degrees are offered,2 and prosecutions ofanimal abusers occur frequently,3 for example. However, the tide is changing in Canada as well, the legal norms and case law becoming increasingly aligned with the social norms surrounding the treatment of animals. An example ofthis is the recent adoption by Quebec ofa new status for animals in its Civil Code, the Loi visant 1'amiliorationde la situationjuridiquede l'animal, adopted on December 4th, 2015.' There are also new challenges the courts must face in issuing judgments on laws relating to animals. Recent manifestations of this have been, for example, the Her Majesty the Queen v. D.L. W' case before the Supreme Court, the first time the highest court of our land ruled on an animal protection provision.6 Also, a highly anticipated trial by the animal rights community is that of Anita Krajnc, charged with criminal mischief for giving water to dehydrated pigs in a slaughterhouse transportation truck.' The trial, set to be held in the summer of 2016, will be a decisive moment in defining a sustainable balance between morality and (il)legality as concerns animal activism. Animal law is thus a burgeoning field in Canada, which renders Canadian PerspectivesonAnimals andthe Law all the more relevant.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.034 | 0.029 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.025 | 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".