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Record W4288742556 · doi:10.1163/15723747-19010007

Strengthening the Monitoring of States’ Compliance with the International Health Regulations

2022· article· en· W4288742556 on OpenAlexaff
Pedro A. Villarreal, Roojin Habibi, Allyn L. Taylor

Bibliographic record

VenueInternational Organizations Law Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsYork University
Fundersnot available
KeywordsInternational Health RegulationsCompliance (psychology)International lawPublic healthPandemicPolitical scienceLawPublic relationsMedicineCoronavirus disease 2019 (COVID-19)PsychologyNursing

Abstract

fetched live from OpenAlex

Abstract The current article aims to undertake a retrospective and a prospective analysis of compliance monitoring under the International Health Regulations of 2005 (ihr (2005)). First, different theoretical understandings of compliance are discussed. The study then focuses on a ‘triad’ of obligations under the ihr (2005): 1) to timely and effectively notify the World Health Organization (who) of events that may constitute public health emergencies of international concern (Article 6 ihr); 2) to notify and justify additional health measures restricting international travel and trade in response to events elsewhere (Article 43 ihr); and, 3) to build minimum core capacities required to conduct pandemic surveillance and response activities (Article 5 ihr). The retrospective analysis revisits the fate of past and current mechanisms of compliance monitoring under the ihr (2005). Lastly, a prospective formulation builds upon the elements of the retrospective analysis, sketching a possible way forward for monitoring of compliance with the ihr (2005).

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)0.102
metaresearch head score (Gemma)0.135
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.542

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1020.135
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0020.005
Scholarly communication0.0070.006
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.365
Teacher spread0.320 · 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 designNot applicable
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

Citations6
Published2022
Admission routes1
Has abstractyes

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