The Evolution of Risk Perceptions Related to Bovine Spongiform Encephalopathy—Canadian Consumer and Producer Behavior
Bibliographic record
Abstract
In this study the dynamics of risk perceptions related to bovine spongiform encephalopathy (BSE) held by Canadian consumers and cow-calf producers were evaluated. Since the first domestic case of BSE in 2003, Canadian consumers and cow-calf producers have needed to make decisions on whether or not their purchasing/production behavior should change. Such changes in their behavior may relate to their levels of risk perceptions about BSE, risk perceptions that may be evolving over time and be affected by BSE media information available. An econometric analysis of the behavior of consumers and cow-calf producers might identify the impacts of evolving BSE risk perceptions. Risk perceptions related to BSE are evaluated through observed market behavior, an approach that differs from traditional stated preference approaches to eliciting risk perceptions at a particular point in time. BSE risk perceptions may be specified following a Social Amplification of Risk Framework (SARF) derived from sociology, psychology, and economics. Based on the SARF, various quality and quantity indices related to BSE media information are used as explanatory variables in risk perception equations. Risk perceptions are approximated using a predictive difference approach as defined by Liu et al. (1998). Results showed that Canadian consumer and cow-calf producer risk perceptions related to BSE have been amplified or attenuated by both quantity and quality of BSE media information. Government policies on risk communications need to address the different roles of BSE information in Canadian consumers' and cow-calf producers' behavior.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".