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Record W3124561868

Context-Dependent BSE Impacts on Canadian Food-at-Home Beef Purchases

2009· preprint· en· W3124561868 on OpenAlexaboutno aff
Leigh J. Maynard, Xin Wang

Bibliographic record

VenueRePEc: Research Papers in Economics · 2009
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicWine Industry and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)BusinessPurchasingAgricultural scienceAgricultural economicsMarketingGeographyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Household-level Canadian scanner data from 2002 – 2005 were used to identify consumer reactions to the early BSE discoveries that severely impacted Canada’s beef industry. In all provinces, consumers reacted to the initial BSE event by purchasing more beef, apparently to support struggling ranchers. Subsequent BSE events, however, met with reduced beef purchases. The results were consistent across three measures of monthly beef purchases: participation, units purchased, and beef expenditure share. Failing to account for the context of individual BSE events would have produced little evidence of consumer reaction, a common finding among prior North American BSE studies.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.000

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.

Opus teacher head0.043
GPT teacher head0.281
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicWine Industry and TourismFrench-language works237,207