BSE and the Dynamics of Beef Consumption: Influences of Habit and Trust
Bibliographic record
Abstract
This study relates habit persistence and trust to recurring food safety incidents in the context of a series of three BSE incidents in Canada. We examined the dynamics of monthly beef expenditure shares of a sample of Canadian households for monthly time periods during year 2002 through 2005 using micro level panel data which followed meat expenditures by Canadian households before and after the first three BSE cases which were discovered in 2003 and 2005. Our results suggest that households’ reactions to the first three BSE events followed a similar general pattern: households reduced beef purchase expenditures following the discovery of BSE but these expenditures subsequently recovered, suggesting that concern diminished over time. Following the first BSE event, we identified an immediate negative impact on beef expenditures. However, in the case of the second and third BSE events, this negative impact was not evident until two months after these BSE announcements. In each of the three cases, the negative impact of BSE on beef purchase expenditures was limited to no more than four months. Assessment of how habit persistence affected beef expenditures indicates that this influence limited households reductions of beef purchases following the BSE events, but the effects of habit diminished subsequent to the initial event. Regarding the role of trust in shaping households’ reactions to BSE, we found that households’ respondents whose answers to standardized questions suggest that they are not “trusting” individuals were more sensitive to the food risks identified by the BSE events.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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.
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".