Correlates of In-Law Conflict and Intimate Partner Violence Against Chinese Pregnant Women in Hong Kong
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 study examines correlates of in-law conflict with intimate partner violence (IPV) against pregnant women in a cohort of Chinese pregnant women who visited antenatal clinics in Hong Kong. This was a territory-wide, cross-sectional study of 3,245 pregnant women recruited from seven hospitals in Hong Kong. Participants were invited to complete the Chinese Abuse Assessment Screen and a demographic questionnaire. About 9% of the pregnant women reported having been abused by their partners in the preceding year. In-law conflict was the characteristic most significantly associated with preceding-year abuse against pregnant women, after controlling for covariates. Findings underscore the need to obtain information on in-law conflict as a risk factor for IPV. In-law conflict should be included in the assessment of risk for IPV. For the prevention of IPV, family-based intervention is needed to work with victims as well as in-laws.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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