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Record W2097479495 · doi:10.1093/shm/hki056

At the Epicentre: Hong Kong and the SARS Outbreak

2005· article· en· W2097479495 on OpenAlexaboutno aff
Pamela Michael

Bibliographic record

VenueSocial History of Medicine · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsnot available
Fundersnot available
KeywordsOutbreakCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Epicenter2019-20 coronavirus outbreakMedicineGeographyVirologyInfectious disease (medical specialty)DiseaseSeismologyInternal medicine

Abstract

fetched live from OpenAlex

had great difficulty in imposing quarantine restrictions and disrupting the travel plans of tens of thousands of citizens of the USA.If confronted with litigious individuals in a country awash with lawyers, WHO efforts might have been put on hold for months by order of a District Court.Fortunately, the accidents of chance saw to it that SARS outbreaks were limited to nation-states, China and Canada, where citizens are more accustomed to accepting measures taken by the authorities to protect the well-being of all members of the community.At a time when the executive and legislative branches of the government of the world's sole super-power are calling into question the need for any international agency which might challenge that country's claims to moral authority over all areas of human activity everywhere on the globe, this book is particularly timely.Of these international agencies, the World Health Organization is surely one of the most worthy of preservation.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.602

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.005
Scholarly communication0.0060.003
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.027
GPT teacher head0.291
Teacher spread0.264 · 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 designQualitative
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

Citations10
Published2005
Admission routes1
Has abstractyes

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