Assessment of a government-subsidized supermarket in a high-need area on household food availability and children’s dietary intakes
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of a new government-subsidized supermarket in a high-need area on household food availability and dietary habits in children. DESIGN: A difference-in-difference study design was utilized. SETTING: Two neighbourhoods in the Bronx, New York City. Outcomes were collected in Morrisania, the target community where the new supermarket was opened, and Highbridge, the comparison community. SUBJECTS: Parents/caregivers of a child aged 3-10 years residing in Morrisania or Highbridge. Participants were recruited via street intercept at baseline (pre-supermarket opening) and at two follow-up periods (five weeks and one year post-supermarket opening). RESULTS: Analysis is based on 2172 street-intercept surveys and 363 dietary recalls from a sample of predominantly low-income minorities. While there were small, inconsistent changes over the time periods, there were no appreciable differences in availability of healthful or unhealthful foods at home, or in children's dietary intake as a result of the supermarket. CONCLUSIONS: The introduction of a government-subsidized supermarket into an underserved neighbourhood in the Bronx did not result in significant changes in household food availability or children's dietary intake. Given the lack of healthful food options in underserved neighbourhoods and need for programmes that promote access, further research is needed to determine whether healthy food retail expansion, alone or with other strategies, can improve food choices of children and their families.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".