Bidirectional Intimate Partner Violence Among Chinese Women: Patterns and Risk Factors
Bibliographic record
Abstract
Bidirectional intimate partner violence (BIPV) refers to the co-occurrence of violence perpetration by both partners. BIPV has been analyzed using samples from different sociodemographic contexts but has yet to be fully explored in China. The present study employed a latent class approach to identify BIPV patterns, rates of prevalence, and associated risk factors among a sample of 1,301 heterosexual adult women in mainland China. Five distinct patterns of BIPV were identified, including (a) bidirectional psychological aggression, (b) bidirectional violence of all types, (c) multi-type victimization with psychological aggression, (d) minimal violence, and (e) bidirectional multi-types without physical violence. Marital status, education, employment status, acceptance of male dominance, and justification of intimate partner violence (IPV) were found to be predictive of different types of BIPV. Our findings suggest a need for a conceptual recognition of the heterogeneity and bidirectionality of IPV among Chinese women. Future research should extend to other diverse populations and sociocultural or clinical contexts in China. IPV assessments, research, and social programs ought to recognize the complexity of IPV and consider various IPV patterns specific to heterosexual women.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".