Food deserts: is it only about a limited access?
Bibliographic record
Abstract
Purpose Previous research has extensively examined “food deserts,” where access to healthy food is limited. However, little is known of the buying behavior at the individual household level in terms of buying habits and consumption in these areas. The purpose of this paper is to determine to what extent other factors than access can account for the purchase of healthy food products, namely, fruits and vegetables. Design/methodology/approach This paper proposes to partially fill this gap through a qualitative (n=55) and quantitative (n=512) study of those people who are in charge of their household purchases in two food deserts in the city of Montreal. Findings Results show that geographical access to supermarkets is not the main factor fostering the purchase of healthy foods (fruits and vegetables). Indeed, food education (e.g. information, simple recipes, cooking classes), associated with a changing mediation process through product diversification (e.g. availability of local products in bulk) and supply (e.g. farmers) seems to be more significant. Research limitations/implications Future studies could compare the results obtained through this study in different socio-demographic contexts. Longitudinal analyses could also increase the understanding of the social and commercial challenges. Originality/value In contrast to previous studies, the results show that geographical access to supermarkets is not the main factor fostering the purchase of fruits and vegetables. Indeed, food education (e.g. information, simple recipes, cooking classes), associated with a changing mediation process through product diversification (e.g. products in bulk) and supply (e.g. farmers) seem to be more significant.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".