Mandatory Reporting of Intimate Partner Violence: Examining Predictors and Experiences Among Intimate Partner Violence Victims
Bibliographic record
Abstract
Mandatory reporting of intimate partner violence (MR-IPV) is a controversial topic. This study examined the practice of MR-IPV by investigating what factors were associated with MR-IPV experience among victims of intimate partner violence (IPV). The study also investigated the experiences of IPV victims who have experienced MR-IPV, to better understand the consequences of MR-IPV. Eighty-six IPV victims were recruited through help services and administered a questionnaire about their experiences with IPV and MR-IPV. Multivariate logistic regression was used to explore statistical predictors of having experienced MR-IPV. Candidate predictors included IPV characteristics and risk factors, sociodemographic/contextual variables, and contact with the help services. IPV severity and persistence were of particular interest, as these define the threshold for whether MR-IPV applies in Norwegian law. IPV victims with MR-IPV experience were asked questions about the experienced consequences of MR-IPV. Neither characteristics of the IPV victimization, risk factors, sociodemographic variables nor contact with the help services were predictive of MR-IPV experience. However, having perpetrated severe psychological aggression was predictive of MR-IPV experience (OR = 4.99). Participants with MR-IPV experience ( n = 39) reported both positive and negative consequences of MR-IPV, but generally more positive consequences for themselves. A majority agreed that, overall, they were better off after MR-IPV was used. Our results indicate that the Norwegian MR-IPV law might not be practiced as intended. The consequences of MR-IPV for IPV victims appear complex and warrant further study. However, overall, the use of MR-IPV led to positive reported consequences for the majority of the participants in this study.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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 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".