US and Canadian cat caregiver’s ratings of cat-cat interactions: A video-based survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
) were recruited to participate in an online cross-sectional questionnaire to assess: (1) knowledge of inter-cat behaviour; (2) the frequency of positive and negative cat-cat interactions in the home; and (3) factors associated with positive and negative cat-cat interactions in the home. The questionnaire included ten videos (five negatively valenced, five positively valenced), in which participants scored: the overall cat-cat interaction; cat 1's experience; and cat 2's experience, using a Likert scale. Participants were also asked to report how often they see each interaction in their own two cats. Cat behaviour experts (n = 5) were recruited to rate their interpretations of the videos using the same Likert scale as the cat caregiver participants. Overall, our results suggest that overt positive interactions (allo-grooming, co-sleeping) were more likely reported if cat dyads were related or spent more time living together, were neutered males, indoor-only, and/or had a single feeding area. Overt negative interactions (fighting, striking) were more likely reported if dyads were older or had a larger age gap, showed animal-directed aggression, were declawed, and/or had a single litter-box. Participant versus expert ratings of the videos were similar, however caregivers reported certain affiliative behaviours more positively than experts. Caregivers appeared to have a good understanding of their cats' overall relationship, as this aligned with reported cat-cat interactions. These results increase our understanding of the cat-cat relationship in two-cat households, which may be used to inform cat adoption strategies, in-home management, and promote a positive cat-cat relationship.
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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 it