Analyzing disparities in transit‐based healthcare accessibility in the Chicago Metropolitan Area
Bibliographic record
Abstract
Public transit is indispensable for car‐free households to access healthcare. Meanwhile, different households have unequal transit‐based healthcare accessibility due to different socio‐economic factors such as race/ethnicity and car ownership. Few studies have comprehensively explored the inequality in transit‐based healthcare accessibility by integrating both racial/ethnic inequity and car ownership. This study fills the gap with an up‐to‐date analysis of transit‐based healthcare accessibility in the Chicago Metropolitan Area at the census tract level. The results show that the percentage of car‐free households is positively related to transit‐based healthcare accessibility; while a higher percentage of minorities (i.e., Black/Hispanic) is negatively related to transit‐based healthcare accessibility. Among all neighbourhoods with higher percentages of higher‐than‐average car‐free households, Hispanic‐majority neighbourhoods fare the worst; while White‐majority neighbourhoods have much better healthcare accessibility than both Black‐majority and Hispanic‐majority neighbourhoods .
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".