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Record W3016073667 · doi:10.1111/1467-9566.13065

From more‐than‐human solidarity to multi‐species biographical value: insights from a veterinary school about ethical dilemmas in One Health promotion

2020· article· en· W3016073667 on OpenAlexafffund
Melanie Rock, Chris Degeling, Cindy L. Adams

Bibliographic record

VenueSociology of Health & Illness · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsSolidarityOutreachGeneral partnershipVeterinary medicineScholarshipValue (mathematics)Veterinary educationPromotion (chess)SociologyMedicinePoliticsPublic relationsPolitical scienceCurriculumPedagogyLaw

Abstract

fetched live from OpenAlex

This article features a partnership between a veterinary school and a charity that aims to enhance the wellbeing of low-income people. Through this partnership, the charity periodically hosts veterinary clinics for clients and their pets. Even as the veterinarians and veterinary students duly examine people's pets, these pop-up clinics aim to help people and their pets. Hence our analysis revolves around the ethics of 'more-than-human solidarity'. By 'more-than-human solidarity', we mean efforts to help others that either center on or that implicate non-human beings. To delve into the ethical and sociological implications of subsidised veterinary services, and to assist with program planning, we conducted several in-depth interviews with veterinarians. Most substantively, we found that the veterinary school's outreach clinics give rise to multi-species biographical value, which is prized as a pedagogical resource for veterinary students. The veterinarians whom we interviewed felt troubled by the extent to which the pop-up clinics ultimately benefited the veterinary school, but also by the shortage of subsidised veterinary services in the vicinity. Based on these interviews and our own reflections, we invite more scholarship on cultural, economic and political influences that shape the lives of human beings and non-human animals alike.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.099
GPT teacher head0.417
Teacher spread0.318 · 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 designObservational
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

Citations10
Published2020
Admission routes2
Has abstractyes

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