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Record W1898536745 · doi:10.1111/bioe.12145

Introducing One Health to the Ethical Debate About Zoonotic Diseases in <scp>S</scp>outheast Asia

2015· article· en· W1898536745 on OpenAlexaff
Benjamin Capps, Michele M Bailey, David Bickford, Richard Coker, Zohar Lederman, Andrew A. Lover, Tamra Lysaght, Paul Anantharajah Tambyah

Bibliographic record

VenueBioethics · 2015
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPublic healthPandemicOutbreakPreparednessOne HealthEnvironmental healthOperationalizationGlobal healthPolitical scienceCoronavirus disease 2019 (COVID-19)DiseaseMedicineInfectious disease (medical specialty)VirologyNursing

Abstract

fetched live from OpenAlex

Pandemic plans recommend phases of response to an emergent infectious disease (EID) outbreak, and are primarily aimed at preventing and mitigating human-to-human transmission. These plans carry presumptive weight and are increasingly being operationalized at the national, regional and international level with the support of the World Health Organization (WHO). The conventional focus of pandemic preparedness for EIDs of zoonotic origin has been on public health and human welfare. However, this focus on human populations has resulted in strategically important disciplinary silos. As the risks of zoonotic diseases have implications that reach across many domains outside traditional public health, including anthropological, environmental, and veterinary fora, a more inclusive ecological perspective is paramount for an effective response to future outbreaks.

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)0.060
metaresearch head score (Gemma)0.059
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.060
Threshold uncertainty score0.319

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.059
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0150.084
Scholarly communication0.0220.022
Open science0.0020.015
Research integrity0.0330.057
Insufficient payload (model declined to judge)0.0040.001

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 head0.091
GPT teacher head0.370
Teacher spread0.279 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations32
Published2015
Admission routes1
Has abstractyes

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