Ethnic Density and Preterm Birth in African-, Caribbean-, and US-Born Non-Hispanic Black Populations in New York City
Why this work is in the frame
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Bibliographic record
Abstract
Segregation studies suggest that the health of blacks in the United States is poorer in majority-black compared with mixed-race neighborhoods. However, segregation studies have not examined black immigrants, who may benefit from social support and country-of-origin foods in black immigrant areas. The authors used 1995-2003 New York City birth records and a spatial measure of ethnic density to conduct a cross-sectional investigation of the risks of preterm birth for African-, Caribbean-, and US-born non-Hispanic black women associated with neighborhood-level African-, Caribbean-, and US-born non-Hispanic black density, respectively. Preterm birth risk differences were computed from logistic model coefficients, comparing neighborhoods in the 90th percentile of ethnic density with those in the 10th percentile. African black preterm birth risks increased with African density, especially in more deprived neighborhoods, where the risk difference was 6.1 per 1,000 (95% confidence interval: 1.9, 10.2). There was little evidence of an ethnic density effect among non-Hispanic black Caribbeans. Among US-born non-Hispanic blacks, an increase in preterm birth risk associated with US-born black density was observed in more deprived neighborhoods only (risk difference = 12.5, 95% confidence interval: 6.6, 18.4). Ethnic density seems to be more strongly associated with preterm birth for US-born non-Hispanic blacks than for non-Hispanic black immigrants.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it