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Record W1482514180 · doi:10.1002/agr.21291

The Effect of Attitudinal and Sociodemographic Factors on the Likelihood of Buying Locally Produced Food

2012· article· en· W1482514180 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAgribusiness · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMultivariate probit modelOrdered probitProbit modelBivariate analysisMarketingProbitQuality (philosophy)EconLitAdvertisingBusinessEconomicsEconometricsMathematicsStatisticsPolitical science

Abstract

fetched live from OpenAlex

ABSTRACT This study explores the factors associated with Canadian consumers locally produced food purchase intention. Data from an Internet‐based survey of consumers ( n = 1,139) was analyzed using a bivariate probit model. The bivariate probit model related attitudinal, behavioral and sociodemographic factors to the intention to purchase fresh and nonfresh locally produced foods. Although sociodemographic characteristics play a limited role in shaping local food purchase intentions, attitudinally based variables have far greater influence. Positive views towards local farmers and agriculture in general, as well as food quality, are positively related to purchase intention. The importance placed on brand‐specific quality is inversely related to the intention to buy local food. Consumers with heightened levels of food involvement, either growing food or preparing most meals from scratch, are more likely to purchase local foods. (EconLit Citations: L660; Q130; Q180)

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.230

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 head0.012
GPT teacher head0.192
Teacher spread0.180 · 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