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Record W2613312448 · doi:10.1111/cjag.12138

Trust and Consumer Preferences for Pig Production Attributes in Canada

2017· article· en· W2613312448 on OpenAlexafffundvenueabout
Violet Muringai, Ellen Goddard, Heather L. Bruce, Graham Plastow, Lifen Ma

Bibliographic record

VenueCanadian Journal of Agricultural Economics/Revue canadienne d agroeconomie · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsAlberta Ministry of Agriculture and ForestryUniversity of Alberta
FundersMinistry of Advanced Education, Government of Alberta
KeywordsCredenceCredence goodProduction (economics)BusinessCertificationPreferenceTasteGovernment (linguistics)MarketingPsychologyAgricultural scienceEconomicsInformation asymmetryMicroeconomicsMathematics

Abstract

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Consumers’ trust in general and specifically in food system agents may reduce uncertainties when they make choices among credence attributes such as production methods. In this study, we assess the linkages between consumers’ trust (generalized and institutional trust) and their preferences for traditionally raised pork. Data were collected through an online survey including a stated preference experiment in Canada in 2011. Results suggest that both low and high trusting consumers are willing to pay significant premiums for traditionally raised pork over conventional pork. Willingness to pay values are higher for the high trust group as compared to the low trust group. Respondents with higher levels of trust rated traditionally raised pork more positively (in comparison to conventional pork) in terms of taste, freshness, safety, healthiness, and not containing hormones and antibiotics as compared to those respondents who have lower levels of trust. Government certification of traditionally raised pork is important for both consumers with low and high trust. The fact that high trust respondents were more in favor of this production credence attribute suggests that providing it in the market may require additional efforts to convince more of the lower trust individuals that this attribute is worth additional expenditure. La confiance générale et plus précisément pour les agents du système alimentaire pourrait réduire l'incertitude des consommateurs lorsqu'ils choisissent parmi des caractéristiques liées à la confiance comme les méthodes de production. Cette étude tente de comprendre le lien entre la confiance du consommateur (générale et institutionnelles) et leur préférence pour la production traditionnelle de porc. Les données ont été recueillies par sondage sur le Web incluant une expérience de préférences prescrites au Canada en 2011. Les résultats de modèles logits aux paramètres conditionnels et aléatoires suggèrent que les consommateurs ayant un niveau de confiance élevé, ainsi que ceux en démontrant un niveau inférieur sont disposés à payer des sommes supplémentaires pour du porc de production traditionnelle au désavantage de celui de production conventionnelle. Les valeurs de la volonté de payer sont plus élevées chez le groupe démontrant une plus grande confiance que chez celui qui démontre un plus faible niveau de confiance. Les répondants ayant des niveaux de confiance plus élevés ont coté le porc de production traditionnelle plus positivement (en comparaison au porc d'élevage conventionnel) en matière de goût, de fraîcheur, de sécurité, de santé et d'absence d'hormones et d'antibiotiques, en comparaison à ceux ayant démontré un moindre niveau de confiance. La certification gouvernementale de porc de production traditionnelle est importante, à la fois pour les consommateurs à grande et faible confiance. La plus importante proportion de répondants à confiance élevée se disant en faveur de cette caractéristique de confiance suggère que sa disponibilité au sein du marché pourrait nécessiter de considérables efforts pour convaincre les répondants démontrant une plus faible confiance de sa valeur ajoutée.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.097
GPT teacher head0.172
Teacher spread0.074 · 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.

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

Citations16
Published2017
Admission routes4
Has abstractyes

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