Inter‐ and intra‐racial/ethnic disparities in walking accessibility to grocery stores
Bibliographic record
Abstract
Abstract Inequalities in accessibility to grocery stores can lead to disparate health outcomes among the population. Although existing studies have examined grocery accessibility inequality across income and racial/ethnic groups, little research has been dedicated to revealing the intra‐racial disparities of grocery accessibility and comparing inter‐racial and intra‐racial inequalities in grocery accessibility. This study adopts a modified two‐step floating catchment area (2SFCA) method, which accounts for the supply/demand inflation effect, and an alternative distribution inequality metric called the Palma ratio to measure the inequalities in grocery access between the richest 10% and poorest 40% of the census tracts within the same racial/ethnic group in Chicago (USA). The results indicate that in Chicago, inter‐racial inequality in grocery accessibility is more serious than intra‐racial inequality, especially because the Hispanic‐majority census tracts generally suffer from low grocery accessibility regardless of their income levels.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".