The reporting of the risks from severe acute respiratory syndrome (SARS) in the news media, 2003–2004
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".