Genuine Concern for Animals in England's Nineteenth-Century Animal Protection Movement: The Case Against Reductionist Interpretations
Bibliographic record
Abstract
Animal–human history is an increasingly popular area of historical research. 1 Diana Donald's 2020 book, Women Against Cruelty: Protection of Animals in Nineteenth-Century Britain is a must-read for anyone interested in the history of animal protection and the role women have played in moral reform movements. Starting from the premise that the prevention of cruelty to animals is “a pure product of the nineteenth century” (p. 7), this dazzling book takes its reader through a wide range of important topics such as the early history of the Royal Society for the Prevention of Cruelty to Animals (RSPCA), differences between men and women's attitudes toward animals, and the role women played in humane education. 2 This review will particularly highlight the way that Donald consistently attacks reductionist theses that discount the genuine concern women had for animals in the nineteenth-century British animal protection movement, and how her interpretations consistently refocus our attention on historical evidence of that genuine concern.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".