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Record W4281653865 · doi:10.1093/cdn/nzac097

Development and Validation of a Short Questionnaire Assessing the Behavior of Local Food Procurement in Quebec, Canada

2022· article· en· W4281653865 on OpenAlex
Annie-Pier Mercier, Gabrielle Rochefort, Julie Fortier, Geneviève J. Parent, Véronique Provencher, Simone Lemieux, Benoı̂t Lamarche

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

VenueCurrent Developments in Nutrition · 2022
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCronbach's alphaProcurementConstruct validityFood frequency questionnaireSample (material)Metropolitan areaPsychologyFace validityScale (ratio)Internal consistencyGeographyMedicineEnvironmental healthDemographyMarketingPsychometricsBusinessClinical psychologyCartographySociology

Abstract

fetched live from OpenAlex

Very few validated instruments, particularly screening tools applicable to large-cohort studies, are available to assess the behavior of local food procurement. The aim was to develop and validate a short questionnaire that measures local food procurement in a sample of French-speaking adults from Quebec, Canada, and to assess the association between local food-procurement behavior and diet quality. A comprehensive questionnaire developed previously to measure local food procurement [Locavore-Index (Locavore-I)] was simplified through a series of steps that included face-validity, exploratory factor analysis, and reliability testing (internal consistency). Construct validity of the resulting short Locavore-I Short Form (Locavore-I-SF) was examined in a sample of 299 adults (85% women) from the Quebec City metropolitan community. The Locavore-I-SF comprises 12 questions that measure the frequency of short food supply chain use (self-production, farmers’ markets, and community-supported agriculture box scheme) for 3 locally produced foods (carrot, tomato, and lettuce) as well as the geographical origin of those 3 foods. The Locavore-I-SF, which is scored on a 12-point scale, had a high internal consistency (Cronbach ɑ: 0.74). The Locavore-I-SF scores were strongly correlated with the reference scores obtained from the Locavore-I from which it was developed (r = 0.84, P < 0.0001). Locavore-I-SF scores also correlated (r = 0.50, P < 0.0001) with the geographical origin of foods measured by pictures of food labels taken by participants. Higher Locavore-I-SF scores were associated with behaviors consistent with eating local foods, such as gardening (vs. not gardening; mean ± SEM difference: 2.3 ± 0.4 points; P < 0.0001) and not being preoccupied by the foods’ appearance standards (vs. being preoccupied; 1.4 ± 0.4 points; P = 0.0002). Finally, the Locavore-I-SF scores were weakly associated with the Healthy Eating Food Index-2019 score (B = 0.05 ± 0.02; P = 0.02). The Locavore-I-SF, a short questionnaire based on 3 locally produced foods in Quebec, measures the behavior of local food procurement with good reliability and acceptable validity metrics.

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)0.001
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 score0.636
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.151
GPT teacher head0.432
Teacher spread0.281 · 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