The Impact on Subsequent Violence of Returning to an Abusive Partner
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 examines the consequences, measured by subsequent violence, of returning to a previously abusive relationship. Two stage least squares estimation is used to control for the effect of prior violence on the probability of leaving, thus isolating the independent effect of leaving on later violence. The theoretically expected result is ambiguous: On the one hand, if aggressors view the attempt to leave as disobedience, then violence should increase upon return. If, instead, aggressors believe the temporary leave indicates that the victim will leave permanently (because she is unwilling to tolerate further abuse), then violence should decrease. Using data from the 1985 Physical Violence in American Families survey, the results show that victims who temporarily leave their abusers suffer increased violence relative to those who never leave.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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