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Record W2965988925 · doi:10.1093/aepp/ppz017

Consumer Preferences for Country‐of‐Origin Labeling in Protected Markets: Evidence from the Canadian Dairy Market

2019· article· en· W2965988925 on OpenAlexaffabout
Amanda Norris, John Cranfield

Bibliographic record

VenueApplied Economic Perspectives and Policy · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTraceabilityBusinessValuation (finance)Product (mathematics)Dairy industryCountry of originCommerceMarketingEconomicsFood scienceAccounting

Abstract

fetched live from OpenAlex

Abstract Recent trade agreements will expand Canada's market access commitments for dairy products. We explore whether Canadian consumers will respond to the increased presence of imported dairy products using a discrete choice experiment that accounts for price, country‐of‐origin (COO), production method, brand, and traceability. We use four processed dairy products to illustrate potential trade‐offs: Gouda and cheddar cheese, ice cream, and yogurt. There are statistically significant discounts associated with COO effects. These discounts vary with the dairy product and are large compared to consumer valuation of other included attributes. We find large premiums for traceability programs, suggesting that the absence of assurances related to traceability may mute actual market penetration arising from increased access to the Canadian dairy market.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.054
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.057
GPT teacher head0.245
Teacher spread0.188 · 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

Citations25
Published2019
Admission routes2
Has abstractyes

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