Relationship of Paternity Status, Welfare Reform Period, and Racial/Ethnic Disparities in Infant Mortality
Bibliographic record
Abstract
The objective of this study was to examine the relationship of paternity status, welfare reform period, and racial/ethnic disparities in infant mortality. The study used retrospective analysis of birth outcomes data from singleton birth/infant death data in Milwaukee, Wisconsin, from 1993 to 2009. Multivariate logistic regression was used to examine the relationship between paternity status, welfare reform period, and infant mortality, adjusting for maternal and infant characteristics. Data consisted of almost 185,000 singleton live births and 1,739 infant deaths. Although unmarried women with no father on record made up about 32% of the live births, they accounted for over two thirds of the infant deaths compared with married women with established paternity who made up 39% of live births but had about a quarter of infant deaths. After adjustments, any form of paternity establishment was protective against infant mortality across all racial/ethnic groups. Unmarried women with no father on record had twice to triple the odds of infant mortality among all racial/ethnic groups. The likelihood of infant mortality was only significantly greater for African American women in the postwelfare (1999-2004; odds ratio = 1.27; 95% confidence interval = 1.10-1.46) period compared with the 1993 to 1998 period. Study findings suggest that any form of paternity establishment may have protective effect against infant mortality. Welfare reform changes may have reduced some of the protection against infant mortality among unmarried African American women that was present before the welfare legislation. Policies and programs that promote or support increased paternal involvement and establishment of paternity may improve birth outcomes and help reduce infant mortality.
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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 | 0.003 | 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 | 0.000 | 0.001 |
| 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".