Incarceration exposure during pregnancy and maternal disability: findings from the Pregnancy Risk Assessment Monitoring System
Bibliographic record
Abstract
BACKGROUND: Extant research reveals that currently and formerly incarcerated individuals exhibit higher rates of disability. Moreover, recent research highlights that women exposed to incarceration during pregnancy -either personally or vicariously through a partner- face poorer health. However, prior research has not detailed the connection between incarceration exposure and risk for maternal disability. METHODS: The aim of this study is to evaluate the association between a women's exposure to incarceration during pregnancy and disability including difficulty with: communication, hearing, remembering, seeing, self-care, or walking. Data are from Pregnancy Risk Assessment Monitoring System (PRAMS), 2019 (N = 12,712). Logistic and negative binomial regression were used to assess the relationship between incarceration exposure and maternal disability. RESULTS: Among the sample of women who delivered a recent live birth, approximately 3.3% of the sample indicated they were personally or vicariously exposed to incarceration in the 12 months before birth. Compared to those who did not have incarceration exposure, women with incarceration exposure have elevated odds of several disabilities, including difficulty remembering (Adjusted Odds Ratio [AOR] = 1.971; 95% Confidence Interval [CI] = 1.429, 2.718), difficulty seeing (AOR = 1.642, 95% CI = 1.179, 2.288), difficulty walking (AOR = 1.896, 95% CI = 1.413, 2.544), and a greater number of cumulative disabilities (Incidence Risk Ratio [IRR] = 1.483; 95% CI = 1.271, 1.731). CONCLUSIONS: Women personally or vicariously exposed to incarceration during pregnancy endure greater odds of having a disability. Considering both incarceration and disability are important public health issues with implications for maternal and child well-being, these findings highlight the need for further research that can better understand the connection between incarceration and disability.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".