MétaCan
Menu
Back to cohort
Record W2139818471 · doi:10.1093/heapro/dau017

Policies on pets for healthy cities: a conceptual framework

2014· article· en· W2139818471 on OpenAlexafffundabout
Melanie Rock, Cindy L. Adams, Chris Degeling, Alessandro Massolo, Gavin R. McCormack

Bibliographic record

VenueHealth Promotion International · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsProvincial Laboratory of Public HealthUniversity of Calgary
FundersCanadian Institutes of Health ResearchUniversity of Calgary
KeywordsConceptual frameworkHealth promotionPublic healthPromotion (chess)CharterPublic relationsDynamismPopulationThe Conceptual FrameworkPolitical scienceSociologyEnvironmental healthMedicineNursingSocial science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.061
GPT teacher head0.443
Teacher spread0.381 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations48
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueHealth Promotion InternationalSame topicHuman-Animal Interaction StudiesFrench-language works237,207