The effect of housing and handling practices on the welfare, behaviour and selection of domestic cats (<i>Felis sylvestris catus</i>) by adopters in an animal shelter
Bibliographic record
Abstract
Abstract As adult cats can often be difficult to re-home, they may spend long periods in rescue shelters where barren housing and inconsistent handling can reduce their welfare. In this study, 165 adult cats in an animal shelter in Vancouver, Canada, were assigned to four treatments. The Basic Single treatment reflected typical conditions in that particular shelter, with cats handled in an inconsistent manner by various staff and housed singly in relatively barren cages. Three alternative treatments involved more consistent, positive handling by only the experimenter and research assistants, plus three housing conditions: Enriched Single (individual cages with opportunities to perch and hide), Basic Communal (group housing with opportunity for each cat to have personal space), and Enriched Communal (group housing enriched to encourage play and cat – cat interaction). The Basic Single treatment had the lowest percentage adopted in 21 days (45% versus 69-76% for other treatment, and higher stress scores than other treatments. The three alternative treatments did not differ significantly on any measure. Cats euthanised for poor health showed higher stress levels when alive than other cats. In a questionnaire, most adopters cited certain behavioural/emotional traits (‘friendly’, ‘playful’, ‘happy’) as reasons for selecting cats; these were generally associated with lower stress scores. The results suggest that consistent handling combined with a range of improved housing options can improve the chances of adoption for adult cats, perhaps by reducing fear-related behaviours that make cats less attractive to adopters.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".