Do Pregnancy Intentions Matter? A Research Note Revisiting Relationships Among Pregnancy, Birth, and Maternal Outcomes
Why this work is in the frame
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Bibliographic record
Abstract
The prevention of unplanned or unintended pregnancies continues to be a cornerstone of U.S. reproductive health policy, but the evidence that such pregnancies cause adverse maternal and child outcomes is limited. In this research note, we examine these relationships using recent large-scale data and inverse propensity weights estimated from generalized boosted models. We find that pregnancy timing is related to maternal experience during pregnancy, but not to infant outcomes at birth-both of which are consistent with prior research. In an addition to the literature, we show that pregnancy timing is relevant for a number of maternal outcomes, such as the onset of depression and intimate partner violence, changes in smoking behavior, and receipt of medical care. These findings suggest that policy intended to improve infant welfare by preventing unintended pregnancies has little empirical support, but that policy focused on increasing reproductive autonomy and maternal well-being has the potential to improve outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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