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Record W3170349781 · doi:10.1093/heapro/daab130

Responsibility-sharing for pets in disasters: Lessons for One Health promotion arising from disaster management challenges

2021· erratum· en· W3170349781 on OpenAlexaboutno aff
Cheryl Travers, Melanie Rock, Chris Degeling

Bibliographic record

VenueHealth Promotion International · 2021
Typeerratum
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPublic relationsEmergency managementCommitPromotion (chess)Health promotionAction (physics)BusinessFirst responderPublic healthMedicineNursingPolitical scienceMedical emergencyLaw

Abstract

fetched live from OpenAlex

During disasters, the behaviour of pet owners and of pets themselves may compromise the ability of emergency responders to perform their duties safely. Furthermore, pet loss can have deleterious effects on personal and community recovery. To explore these issues and their implications for health promotion and disaster management practice, we conducted semi-structured interviews with 27 emergency responders in Australia, where disaster policy embraces shared responsibility yet does not acknowledge pets. We found that responders commit to being responsible for protecting human lives, especially members of their teams. Frontline emergency responders did not regard pets as their responsibility, yet decisions made with tragic consequences for pets exacted an emotional toll. Emergency managers consider community education as a pivotal strategy to support building people's capacity to reduce their own risk in disasters. While important, we question whether this is sufficient given that human life is lived in more-than-human contexts. Reformulating the parameters of the Ottawa Charter for Health Promotion as 'One Health Promotion' may help to account for the intermeshed lives of people and pets, while acknowledging human priority in public policy and programming. To acknowledge the influence of people's pets in disaster responses and recovery, we recommend five overlapping spheres of action: (i) integrate pets into disaster management practice and policy; (ii) create pet-friendly environments and related policies; (iii) engage community action in disaster management planning; (iv) develop personal skills by engaging owners in capacity building and (v) reorient health and emergency services toward a more-than-human approach.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.163
GPT teacher head0.463
Teacher spread0.300 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations7
Published2021
Admission routes1
Has abstractyes

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