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Record W2167786797 · doi:10.1080/13698570802160962

The reporting of the risks from severe acute respiratory syndrome (SARS) in the news media, 2003–2004

2008· article· en· W2167786797 on OpenAlexfundaboutno aff
Grant Lewison

Bibliographic record

VenueHealth Risk & Society · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMisinformation and Its Impacts
Canadian institutionsnot available
FundersEuropean CommissionGovernment of CanadaUniversity of Kentucky
KeywordsMedicineSevere acute respiratory syndromeSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakIntensive care medicineInternal medicineVirologyDisease

Abstract

fetched live from OpenAlex

This paper analyses coverage of the risks from Severe Acute Respiratory Syndrome (SARS) in March 2003 to April 2004 in 15 news media from seven countries (Canada, France, Germany, Hong Kong, Spain, the UK and the USA) as part of an analysis of risk management for the European Commission. A total of 1014 relevant news articles were found and coded for their presentational tone or ‘scariness,’ the types of risk (health, financial and political) mentioned, the countries involved, and the documents, people and organizations cited. The main period of the epidemic (as reported internationally) lasted 3 months from the end of March to the end of June 2003, by which time over 770 people had died worldwide. In the early weeks, the tone of the articles was somewhat scary, but by the end of May much had been learned about the disease, its likely death rate and how to contain it, and the articles became less numerous and more moderate in tone. Because of the rapid spread of the disease, there was not time for it to become politicized. Some 62 documents were cited in the news articles, mostly research papers. The people and organizations most cited were the WHO, medical personnel, officials, governments, politicians and scientists; the latter tended to make the news articles less scary. Public reaction to the news, in the form of statistics on air travellers to the Far East and to Toronto, Canada, suggests that the health risks of the latter were seen as much less serious than those of the former.

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)0.003
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0130.014
Science and technology studies0.0010.001
Scholarly communication0.0050.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.128
GPT teacher head0.395
Teacher spread0.267 · 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 designObservational
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

Citations46
Published2008
Admission routes2
Has abstractyes

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