The Economic Consequences of Being Denied an Abortion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper evaluates the economic consequences of being denied an abortion due to gestational limits. We link credit report data to the Turnaway Study, the first study to collect high-quality, longitudinal data on women receiving or being denied a wanted abortion in the United States. We compare financial outcomes over a ten-year period for women who had pregnancies just above and below a gestational age limit allowing for a wanted abortion. Outcome trajectories are similar for the two groups of women prior to the abortion encounter. Following the encounter, women who were denied an abortion experience a large increase in financial distress that is sustained for several years. There is also some evidence of a short-term reduction in credit access, but no change in measures of borrowing. Our results highlight important financial and economic consequences of restrictions on abortion access.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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