Initiating a Non-Anthropocentric Jurisprudence: The Rule of Law and Animal Vulnerability Under a Property Paradigm
Bibliographic record
Abstract
This article discusses a recent Canadian entry to the accretion of legal texts which question, to various degrees, law’s anthropocentrism: the dissenting judgment of the Alberta Court of Appeal in Reece v. Edmonton (City of). Written by Chief Justice Catherine Fraser, the 162-paragraph dissent stands out in the Canadian landscape (and is impressive even in the international scene) given the existing Canadian law addressing animal issues that either regulate animals as objects and/or subordinate animal interests to human or corporate ones. This article argues that the dissent in Reece departs from the standard legal instrumentalist view of animals by providing a non-anthropocentric analysis of the animal interests at stake. The decision thus provides a new way of thinking about animals when compared to the existing Canadian jurisprudence. The dissent’s departure from the traditional anthropocentric legal view of animals is seen in three main ways: (1) the level of importance it assigns to the animal interest legally at issue by connecting it to the rule of law; (2) the respect it affords to critiques of animals’ current legal status (including the animal rights critique seeking to abolish the property status of animals and the default subordination of animal interests to human or corporate ones); and (3) the empathy and respect it gives to the individual animal at the heart of the legal dispute by recognizing her as a sentient and vulnerable being whose subjectivity matters. The cumulative effect is a judgment that not only provides the most sophisticated Canadian judicial analysis to date of the law’s relationship to animals, but impugns the traditional anthropocentric paradigm through which the law minimally responds to (some) animal suffering.
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 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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".