Impact of BSE on Beef Purchases in Alberta and Ontario Quick‐Serve Restaurants
Bibliographic record
Abstract
This analysis employed a highly disaggregated household data set of Alberta and Ontario fast food purchases from May 2000 to May 2005. A double‐hurdle count data model allowed tests of the hypotheses that frequency of Bovine spongiform encephalopathy ( BSE) media coverage affected neither a household's monthly probability of purchasing a beef entree, nor the household's monthly quantity of beef entrees purchased. Ontario consumers were more likely to stop purchasing beef entrees immediately following a surge in BSE media coverage, but those who did buy beef entrees maintained stable quantity levels. BSE media coverage did not systematically affect fast food purchases among Alberta consumers . Dans la présente analyse, nous avons utilisé un ensemble de données fortement désagrégées sur les achats de repas–minute effectués par des ménages de l'Alberta et de l'Ontario, entre mai 2000 et mai 2005. Un modèle de comptage à deux étapes (double hurdle count data model) a permis de vérifier les hypothèses selon lesquelles la concentration de la couverture médiatique de la crise de l'ESB n'influence pas la probabilité mensuelle d'un ménage d'acheter des repas–minute de bœuf ni la quantité mensuelle de repas–minute de bœuf achetés par un ménage. Les consommateurs ontariens étaient plus susceptibles de cesser d'acheter des repas–minute de bœuf immédiatement après une poussée de la couverture médiatique de la crise de l'ESB, mais ceux qui achetaient des repas–minute de bœuf ont maintenu les quantités achetées. La couverture médiatique de la crise de l'ESB n'a pas systématiquement influencé les achats de repas–minute chez les consommateurs albertains .
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".