The Impact of Social Amplification and Attenuation of Risk and the Public Reaction to Mad Cow Disease in Canada
Bibliographic record
Abstract
Following the detection of bovine spongiform encephalopathy (BSE) in Canada, and subsequently in the United States, confidence in the safety of beef products remained high. Consumers actually increased their consumption of beef slightly after the news of an increased risk from mad cow disease, which has been interpreted as public support for beef farmers and confidence in government regulators. The Canadian public showed a markedly different reaction to the news of domestic BSE than the furious and panicked responses observed in the United Kingdom, Germany, and Japan. Using the social amplification of risk framework, we show that, while other countries displayed social amplification of risk, Canada experienced a social attenuation of risk. The attenuated reaction in Canada toward mad cow disease and increased human health risks from variant Creutzfeldt-Jakob disease (vCJD) was due to the social context at the time when BSE was discovered domestically. Mortality, morbidity, and psychosocial impacts resulting from other major events such as severe acute respiratory syndrome (SARS), West Nile virus (WNV), and the U.S.-Iraq war made the theoretical risks of BSE and vCJD a lower priority, reducing its concern as a risk issue.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".