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Record W4323642547 · doi:10.1017/jme.2023.30

Embed Multisectoral Governance Mechanisms in the Pandemic Instrument for One Health Action

2022· article· en· W4323642547 on OpenAlexafffund
Michèle Palkovits, Susan Rogers Van Katwyk, Steven J. Hoffman

Bibliographic record

VenueThe Journal of Law Medicine & Ethics · 2022
Typearticle
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsYork University
FundersCanadian Institutes of Health ResearchPublic Health AgencyPublic Health Agency of CanadaGovernment of CanadaWellcome Trust
KeywordsPandemicAction (physics)Corporate governanceCoronavirus disease 2019 (COVID-19)Political scienceBusinessMedicine

Abstract

fetched live from OpenAlex

Despite recognition of the health threat posed at the human-animal-environment interface long ago, One Health has yet to be meaningfully integrated into global pandemic prevention, preparedness, and response. With the negotiation of the forthcoming pandemic instrument under the auspices of the World Health Organization (WHO) - which is inherently restricted by its own constitutional mandate of human health - One Health risks being sidelined once again. Genuine integration of a One Health approach into this treaty will require the institutionalization of formal One Health coordination mechanisms.

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)0.040
metaresearch head score (Gemma)0.020
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 score0.040
Threshold uncertainty score0.211

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.020
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.035
Scholarly communication0.0110.011
Open science0.0020.013
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0040.000

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 head0.288
GPT teacher head0.450
Teacher spread0.162 · 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

Citations5
Published2022
Admission routes2
Has abstractyes

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