Officer and Organizational Correlates With Police Interventions in Domestic Violence in China
Bibliographic record
Abstract
Although domestic violence has long been identified as a serious social problem in China, little is known about police officers' attitudinal and behavioral tendencies toward such incidents. Drawing upon survey data collected from police officers in two Chinese provinces, this study assesses whether officer and organizational factors are correlated to police inaction and intervention in resolving family violence. More than a quarter of Chinese police officers often and sometime did not take any action when responding to domestic violence. Chinese officers favored most the least punitive approaches of mediation and separation, with the most punitive actions, written warning and criminal sanction as the least preferred interventions. We found that Chinese officers with low levels of knowledge about the domestic violence law, higher degrees of tolerance of violence and less supportive attitudes toward an active police role in handling domestic violence are less willing to take any action against the offenders. Chinese police officers who perceived stronger supervisory support and expressed better knowledge about China's new domestic violence law are more likely to intervene in domestic violence, whereas police officers who expressed greater degrees of tolerance of violence and believed in gender equality in society are less inclined to intervene. Policy makers and police administrators ought to pay greater attention to frontline supervisors' attitudes and behavior toward proper responses to family violence. If active intervention is preferred, then measures and programs should be put into place to improve police officers' legal knowledge and communication and problem-solving skills pertaining to conflict resolution.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".