The effect of parental race on fetal and infant mortality in twin gestations.
Bibliographic record
Abstract
Previous work has found that singleton birth outcomes are better if the father is black and the mother is white than if the father is white and the mother is black. We sought to examine the effects of parental race on fetal and infant mortality in twins. We analyzed the fetal and infant mortality rates in four groups [both parents white (W-W), both parents black (B-B), father black and mother white (FB-MW), and father white and mother black (FW-MB)], using the 1995--1997 U.S. twin registry data (249,221 twins). Compared to W-W, the infant mortality for B-B, FW-MB, and FB-MW (respectively, relative risk [RR] 1.84, 95% confidence interval [CI] 1.73-1.95; RR 1.39, 95% CI 1.03-1.51; and RR 1.49, 95% CI 1.26-1.77) were all significantly different from W-W but not from each other. When fetal mortality was added to infant mortality, the combined mortality was highest for B-B (RR 1.66, 95% CI 1.58-1.75), intermediate for FW-MB (RR 1.18, 95% CI 0.92-1.51) and FB-MW (RR 1.37, 95% CI 1.19-1.58) and lowest for W-W. Thus, twin infants born to black parents have higher risk of fetal and infant mortality compared with twin infants born to white parents and infants of mixed race parents generally have intermediate outcomes.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".