Exposure to interparental violence and justification of intimate partner violence among women in Papua New Guinea
Bibliographic record
Abstract
BACKGROUND: Previous studies have demonstrated that exposure to interparental violence is associated with intimate partner violence justification in a variety of contexts. In this study, we examined the association between exposure to interparental violence and justification of intimate partner violence among women in Papua New Guinea. METHODS: We used data from the 2016-18 Papua New Guinea Demographic and Health Survey. We included 2839 women of reproductive age (15-49 years) in a sexual union (married and cohabiting) in the study. We used a multivariable binary multilevel regression analysis to examine the association between interparental violence and justification of intimate partner violence. We presented the results of the regression analysis using crude odds ratio (cOR) and adjusted odds ratios (aORs), with their 95% confidence intervals (CIs). RESULTS: Women exposed to interparental violence were 1.26 (95%CI = 1.05, 1.53) times more likely to justify intimate partner violence than those who were not exposed. Women who resided in the Highlands (aOR = 2.50, 95%CI = 1.78, 3.51), Momase (aOR = 1.96, 95%CI = 1.40, 2.75), and Islands (aOR = 1.42, 95%CI = 1.01, 1.99) were more likely to justify intimate partner violence compared to those in the Southern region. Women who were exposed to one (aOR = 1.38, 95%CI = 1.06, 1.82) mass media were more likely to justify intimate partner violence compared to those who had no exposure to mass media. On the other hand, women aged 25-34 years (aOR = 0.66, 95%CI = 0.48, 0.91) and 35-49 years (aOR = 0.66, 95%CI = 0.44, 0.97) were less likely to justify intimate partner violence compared to those aged 15-24 years. CONCLUSIONS: Our study has shown that exposure to interparental violence is a predictor of intimate partner violence justification. This study suggests the need for conscious and continuous efforts to identify and assist women who have been exposed to interparental violence to help prevent its transition to later life. Policies and interventions should be developed and implemented to curtail children's exposure to domestic violence in their households. Also, laws and policies need to condemn any violence and demystify community justification and acceptance of intimate partner violence, taking into consideration the significant sociodemographic characteristics of the women highlighted in the study.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".