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Record W3132118182

The Stellenbosch Consensus on Legal National Responses to Public Health Risks

2020· article· en· W3132118182 on OpenAlexaff
Roojin Habibi, Steven J. Hoffman, Gian Luca Burci, Thana Cristina de Campos, Danwood Mzikenge Chirwa, Margherita Cinà, Stéphanie Dagron, Mark Eccleston-Turner, Lisa Forman, Lawrence O. Gostin, Benjamin Mason Meier, Stefania Negri, Gorik Ooms, Sharifah Sekalala, Allyn L. Taylor, Alicia Ely Yamin

Bibliographic record

VenueArchive ouverte UNIGE (University of Geneva) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsInternational Health RegulationsPolitical sciencePublic healthConventionSolidarityInternational lawGlobal healthSovereigntyResilience (materials science)PandemicFace (sociological concept)Public relationsPublic administrationLawCoronavirus disease 2019 (COVID-19)Health carePoliticsSociologyMedicineSocial science
DOInot available

Abstract

fetched live from OpenAlex

The International Health Regulations (ihr), of which the World Health Organization is custodian, govern how countries collectively promote global health security, including prevention, detection, and response to global health emergencies such as the ongoing covid-19 pandemic. Countries are permitted to exercise their sovereignty in taking additional health measures to respond to such emergencies if these measures adhere to Article 43 of this legally binding instrument. Overbroad measures taken during recent public health emergencies of international concern, however, reveal that the provision remains inadequately understood. A shared understanding of the measures legally permitted by Article 43 is a necessary step in ensuring the fulfillment of obligations, and fostering global solidarity and resilience in the face of future pandemics. In this consensus statement, public international law scholars specializing in global health consider the legal meaning of Article 43 using the interpretive framework of the Vienna Convention on the Law of Treaties.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.137
GPT teacher head0.315
Teacher spread0.177 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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