Trap, Snip, Repeat: Cat Overpopulation and Gendered Labour in a Feral Sterilisation Programme
Bibliographic record
Abstract
Cat overpopulation in Toronto, Canada, is a serious and growing problem. Small, and frequently isolated, groups of volunteers work in a variety of capacities to help mitigate the large numbers of litters produced by stray and feral cats. One such organisation is Toronto Street Cats. This volunteer group works with the help of the Toronto Humane Society to operate a monthly trap/neuter/release (TNR) programme. Groups of caretakers look after registered feral cat colonies and capture cats of breeding age. Once a month these cats are sterilised, vaccinated, treated for parasites, and microchipped in an evening-long marathon. Volunteers in veterinary medicine (registered veterinary technicians [RVTs], veterinary assistants and veterinarians) comprise the medical staff who provide treatment and perform the assembly-line surgeries. Post-surgery, the cats are taken by the volunteers to a recovery facility and
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".