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Record W2494744987 · doi:10.1111/1477-9552.12187

German and British Consumer Willingness to Pay for Beef Labeled with Food Safety Attributes

2016· article· en· W2494744987 on OpenAlex
Karen E. Lewis, Carola Grebitus, Gregory Colson, Wuyang Hu

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Economics · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsnot available
Fundersnot available
KeywordsGermanWillingness to payFood safetyQuality (philosophy)BusinessConsumption (sociology)Agricultural economicsEuropean unionConsumer demandMixed logitAgricultural scienceMarketingEconomicsLogistic regressionFood scienceGeographyInternational trade

Abstract

fetched live from OpenAlex

Abstract The European Union has implemented some of the most stringent food safety policies for beef globally, ranging from banning growth hormones to mandating country of origin labeling. Using choice experiments and random parameter logit models, we examine German and British consumer willingness to pay ( WTP ) for American, Canadian, Argentinian, French, German and British beef, quality assurance seals, hormone‐free beef production and a gourmet label. We also determine how consumer WTP for these food safety and quality attributes is affected by the extent to which consumers consider food safety issues (FSI). Results indicate that British consumers had the lowest WTP for beef from Argentina and German consumers had the lowest WTP for beef from Great Britain. The hormone‐free label was the relatively most preferred label by consumers in both countries, and by those who considered FSI to affect their meat consumption patterns.

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.

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 score0.039
Threshold uncertainty score0.375

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 communication0.0000.001
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 head0.035
GPT teacher head0.191
Teacher spread0.155 · 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