The 2022 Minnesota Statewide Food Shelf Survey: Reported Availability of Healthy Foods and Importance of Culturally-specific Foods by Participant Demographic Characteristics
Bibliographic record
Abstract
OBJECTIVE: To determine whether shopper-reported availability of foods from Minnesota food shelves and the importance of cultural foods/cooking items differed by demographic characteristics. METHODS: Cross-sectional survey of food pantry shoppers (n = 4,680) who visited more than or equal monthly with choice over food selection. RESULTS: Hispanic and Black shoppers had higher odds of reporting produce, eggs, and cooking items were always available than White shoppers (odds ratio [OR] > 1.35; P < 0.001-0.02). The odds of Asian participants reporting that meat, poultry, and fish were always available were lower than White participants (OR, 0.55; P = 0.002). Asian, Black, Hispanic, and male shoppers had higher odds of indicating the importance of culturally-specific food and cooking item availability than their counterparts (White, females, respectively) (OR, 1.7-6.1; P <0.001). CONCLUSIONS AND IMPLICATIONS: Inequities exist in the availability of healthy and culturally-specific foods in food pantries that could be addressed via food-sourcing policies/strategies and food bank distribution efforts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".