Birth Outcomes Among First Nations Birthing Parents Incarcerated While Pregnant: A Linked Administrative Data Study From Manitoba, Canada
Bibliographic record
Abstract
BACKGROUND: In Canada, colonial policies have resulted in health inequities between First Nations and other Canadians. These policies contribute to overrepresentation of First Nations in the criminal legal system, where incarcerated people and their infants face elevated health risks. We investigated the association between prenatal incarceration and adverse birth outcomes among First Nations and other birthing parents in Manitoba, Canada. METHODS: Using linked whole-population administrative data, we identified all live births (2004-2017) in which the birthing parent (First Nations n = 1,449; other Manitoban n = 278) was prenatally incarcerated and compared them to birthing parents who were postnatally incarcerated (First Nations n = 5,290; other Manitoban n = 790) or not incarcerated (First Nations n = 19,950; other Manitoban n = 3,203). We used generalized linear models adjusted for measured confounders with propensity score weighting to calculate risk differences and 95% confidence intervals for adverse birth outcomes among those prenatally versus postnatally incarcerated in each group. RESULTS: Low birthweight births were more likely among First Nations birthing parents who were prenatally (vs. postnatally) incarcerated (risk difference 1.59, 95% CI [.79, 2.38]) but less likely among other Manitoban birthing parents (risk difference -2.33, 95% CI [-4.50, -.16]) who were prenatally (vs. postnatally) incarcerated. Among First Nations, prenatal incarceration was also associated with large-for-gestational-age births, low Apgar scores, and no breastfeeding (vs. postnatal incarceration), as well as preterm births (vs. no incarceration). Among other Manitobans, prenatal incarceration was also associated with small-for-gestational-age births, low Apgar scores, and no breastfeeding (vs. postnatal incarceration), as well as preterm births (vs. no incarceration). CONCLUSIONS: The findings suggest that incarceration may contribute to intergenerational systems of oppression by compromising birth outcomes among First Nations and other birthing parents in Canada and underscore the need to both improve care for pregnant people who are incarcerated and invest in alternatives to incarceration.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".