Exploring the social and neighbourhood predictors of diabetes: a comparison between Toronto and Chicago
Bibliographic record
Abstract
OBJECTIVES: This report examined the impact and extent that spatial access to primary care physicians (PCPs) and social neighbourhood-/community-level factors have on diabetes prevalence for Toronto and Chicago. METHODS: The two-step floating catchment area method was used to compute spatial access scores. Bivariate correlation and multivariate linear regression identified the factors that were associated with, and/or predicted, diabetes prevalence. RESULTS: Potential spatial access to PCPs had no strong associations with diabetes prevalence. Low socio-economic status factors and certain ethnic groups were strongly associated with diabetes prevalence for both cities. For Toronto, South American place of birth, households below poverty and high school-level education predicted diabetes prevalence. African ethnicity and households below poverty predicted diabetes prevalence for Chicago. CONCLUSION: Although this report found no strong association between diabetes prevalence and access to PCPs, contextual factors significant in past individual-level diabetes studies were associated with diabetes prevalence at the neighbourhood/community level for Toronto and Chicago.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".