Beastly Measures: Animal Welfare, Civil Society, and State Policy in Victorian Canada
Bibliographic record
Abstract
This essay analyzes the development of Canada’s animal welfare movement during the nineteenth century. Situating Canada’s experience alongside that of England and the United States, it identifies an enthusiastic but conservative response to animal welfare, which the author argues reflects the high level of dependence among the movement’s upper- and middle-class supporters on animals as resources, sources of labour, and objects of sport. In particular, it focusses on the participation of sportsmen, cattle ranchers, industrialists, foxhunters, veterinarians, and others who recognized in the movement both the material and the ethical benefits that might accrue from the improved treatment of animals. As such, the essay brings to the literature on animal welfare and animal rights a sense of the movement’s economic dimensions, or the ways in which material concerns regarding property and productivity converged with but also limited the animal welfare movement’s ethical parameters. In doing so, it accounts for the near absence in Canada of the more radical agendas that informed the movement’s civil society parameters elsewhere, and in turn the ways in which the moderate vision that informed the nation’s animal welfare nongovernmental organizations contributed to an equally moderate response on the part of the state.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.043 | 0.019 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".