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Record W2594608204 · doi:10.1080/09581596.2017.1288287

Who or what is ‘the public’ in critical public health? Reflections on posthumanism and anthropological engagements with One Health

2017· article· en· W2594608204 on OpenAlexafffund
Melanie Rock

Bibliographic record

VenueCritical Public Health · 2017
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchAlberta Heritage Foundation for Medical ResearchHealth Research Board
KeywordsProblematizationPublic healthPosthumanismHealth promotionEnvironmental ethicsSociologyNon-humanPolitical scienceEpistemologyMedicine

Abstract

fetched live from OpenAlex

This paper extends the terms of engagement between social science, posthumanist debates and One Health by questioning whether ‘the public’ may include non-human animals. The One Health concept refers to interdependence between human beings and non-human species in socio-ecological systems. One Health interventions and critiques have tended to emphasize the prevention of zoonotic infections, whereas this paper reflects on more than a decade of engaged research in One Health promotion. Repeatedly, this particular approach to One Health promotion has highlighted the imprint of multi-species entanglements in public life, especially the problematization and politicization of people’s pets. Serious consideration for multi-species entanglements cautions against conflating ‘the public’ with human beings and human interests, to the exclusion of all others. Human beings have never lived separate and apart from non-human species, and we all depend on shared environments. To do justice to multi-species entanglements, socio-ecological theory should undergo expansion in health promotion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.067
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.356

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0240.219
Scholarly communication0.0260.033
Open science0.0030.018
Research integrity0.0180.024
Insufficient payload (model declined to judge)0.0050.000

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 head0.383
GPT teacher head0.521
Teacher spread0.137 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
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

Citations41
Published2017
Admission routes2
Has abstractyes

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