Policies on pets for healthy cities: a conceptual framework
Bibliographic record
Abstract
Drawing on the One Health concept, and integrating a dual focus on public policy and practices of caring from the Ottawa Charter for Health Promotion, we outline a conceptual framework to help guide the development and assessment of local governments' policies on pets. This framework emphasizes well-being in human populations, while recognizing that these outcomes relate to the well-being of non-human animals. Five intersecting spheres of activity, each associated with local governments' jurisdiction over pets, are presented: (i) preventing threats and nuisances from pets, (ii) meeting pets' emotional and physical needs, (iii) procuring pets ethically, (iv) providing pets with veterinary services and (v) licensing and identifying pets. This conceptual framework acknowledges the tenets of previous health promotion frameworks, including overlapping and intersecting influences. At the same time, this framework proposes to advance our understanding of health promotion and, more broadly, population health by underscoring interdependence between people and pets as well as the dynamism of urbanized ecologies.
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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".