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How do U.S. and Canadian consumers value credence attributes associated with beef labels after the North American BSE crisis of 2003?

2010· article· en· W2150162115 on OpenAlexaffabout
Bodo Steiner, Jun Yang

Bibliographic record

VenueInternational Journal of Consumer Studies · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCredenceBovine spongiform encephalopathyBusinessValuation (finance)Food safetyBeef industryAgricultural scienceMarketingEconomicsAgricultural economicsFood scienceMedicine

Abstract

fetched live from OpenAlex

Abstract A consumer survey conducted in 2006 ( n = 419), and therefore after the first confirmed bovine spongiform encephalopathy (BSE) cases in North America in 2003, employs attribute‐based choice experiments for a cross‐country comparison of consumers' valuation of credence attributes associated with beef steak labels; specifically a guarantee that beef was tested for BSE, a guarantee that the steaks were produced without genetically modified organisms (GMOs) and a guarantee that beef steaks were produced without growth hormones and antibiotics. Considering consumers' socio‐economic characteristics, the results suggest that consumers in Montana (U.S.) and Alberta (Canada) are significantly heterogeneous in their valuation of the above attributes, although consumers' relative valuation of these process attributes does not appear to have changed since the 2003 BSE crisis in each region. Alberta consumers place a significant valuation on beef tested for BSE, which is striking because Canada's current legal environment does not permit testing and labelling of such beef by private industry participants. Montana consumers' valuation was found highest for a guarantee that the steaks were produced without GMO. Effective supply‐chain responses to consumers' valuation of credence attributes, for example, in the form of labelling, should therefore take consumers' heterogeneity into account.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.261
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.224
Teacher spread0.211 · 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 teacher head, 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

Citations7
Published2010
Admission routes2
Has abstractyes

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