Bibliographic record
Abstract
In the 2011, Chief Justice Fraser of the Alberta Court of Appeal raised an interesting question in her dissenting judgment in Reece v Edmonton (City): Should elephants have standing? Drawing on the ideas in her dissent and the Alberta’s Animal Protection Act on which the decision is based, I argue that granting animals standing is a pragmatic solution to overcoming the limitations and obstacles behind enforcing animal protection laws. This is demonstrated by exploring both the practicality and feasibility of granting standing to animals. On the point of practicality, I explain why this solution is preferable over other possibilities, such as granting public interest standing to interested parties. On the point of feasibility, I consider how legal tools (such as guardianship ad litem) may be applicable to this situation. I conclude that granting animals standing will remove barriers to enforcing animal welfare laws. This paper demonstrates that the judiciary already has at its disposal the legal tools necessary to accommodate standing for animals; judges need only make use of them.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".