Examining food purchasing patterns from sales data at a full-service grocery store intervention in a former food desert
Bibliographic record
Abstract
BACKGROUND: The Good Food Junction Grocery Store was opened in a former food desert in the inner city of Saskatoon, Canada. OBJECTIVE: The purpose of this research was to examine, using grocery store sales data, healthy and less healthful food purchasing over a one-year period beginning eight months after opening by shoppers' neighborhood of residence. DESIGN: A multilevel cross sectional design was used. The sample consisted of members of the Good Food Junction with a valid address in Saskatoon, Saskatchewan. All purchases made by members who reported their postal code of residence from May 15, 2013 to April 30, 2014 were analyzed. The outcome variable was the total amount spent on foods in 11 food groups. Linear random intercept models with three levels were fit to the data. RESULTS: Shoppers who were residents of former food desert neighborhoods spent $0.7 (95% CI: 0.2 to 1.2) more on vegetables, and $1.2 (95% CI: - 1.8 to - 0.6) less on meat, and $1.1 (95% CI: - 2.0 to - 0.3) less on prepared foods than shoppers who did not reside in those neighborhoods. CONCLUSIONS: When given geographical access to healthy food, people living in disadvantaged former food desert neighborhoods will take advantage of that access.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".