Bibliographic record
Abstract
As the most populous province in Canada, Ontario is a microcosm of the animal welfare issues which beset Western civilization. The authors of this book, chairman and vice-chairman, respectively, of the Ontario Society for the Prevention of Cruelty to Animals, find themselves constantly being made aware of the atrocities committed in the Society’s jurisdiction. They have been, in turn, puzzled, exasperated and horrified at humanity’s cruelty to our fellow sentient beings. The issues discussed in this book are the most contentious in animal welfare disputes — animal experimentation, fur-farming and trapping, the use of animals for human entertainment and the conditions under which animals are raised for human consumption. They are complex issues and should be thought about fairly and seriously. The authors, standing squarely on the side of the animals, suggest “community” and “belonging” as concepts through which to understand our relationships to other species. They ground their ideas in Wordsworth’s “primal sympathy” and Jung’s “unconscious identity” with the animal realm. The philosophy developed in this book embraces common sense and compromise as the surest paths to the goal of animal welfare. It requires respect and consideration for other species while acknowledging our primary obligations to our fellow humans.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 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; both teacher heads agree on what is shown here.
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".