State Abortion Context and U.S. Women's Contraceptive Choices, 1995–2010
Bibliographic record
Abstract
CONTEXT: The number of women in the United States exposed to restrictive abortion policies has increased substantially over the past decade. It is not well understood whether and how women adjust their contraceptive behavior when faced with restrictive abortion contexts. METHODS: Data from 14,523 women aged 15-44 were drawn from the 1995 and 2010 cycles of the National Survey of Family Growth. A difference-in-differences approach was employed to examine the relationship between state-level changes in women's access to abortion and their contraceptive choices. Multinomial logistic regression analysis was used to determine the relative risk of using highly effective or less effective methods rather than no method for women exposed to varying levels of restrictive abortion contexts. RESULTS: Women who lived in a state where abortion access was low were more likely than women living in a state with greater access to use highly effective contraceptives rather than no method (relative risk ratio, 1.4). Similarly, women in states characterized by high abortion hostility (i.e., states with four or more types of restrictive policies in place) were more likely to use highly effective methods than were women in states with less hostility (1.3). The transition to a more restrictive abortion context was not associated with women's contraceptive behavior, perhaps because states that introduced restrictive abortion legislation between 1995 and 2010 already had significant limitations in place. CONCLUSION: To prevent unwanted pregnancies, it is important to ensure access to highly effective contraceptive methods when access to abortions is limited.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".