What Difference does it Make if they have Children? A Mixed Methods Study of the Impact of Children on Service Providers’ Perception of Mandatory Reporting of Intimate Partner Violence
Bibliographic record
Abstract
Abstract Purpose Whether professionals consider children to be an important factor regarding mandatory reporting of intimate partner violence (MR-IPV) remains unknown. In the present study, we examined to what extent the presence of children had an impact on service providers’ decision making when faced with IPV, and the parents’ reported consequences of MR-IPV for the children. Methods The present study is a mixed methods study combining quantitative ( N = 374 service providers and N = 86 IPV victims) and qualitative ( N = 59 service providers and N = 10 IPV victims) data in a convergent parallel design. Descriptive analyses and Kruskal- Wallis H-tests from the quantitative data were used. The analytic process for the qualitative analyses was informed by Braun and Clarke’s thematic analysis. Results The service providers found it easier to set aside confidentiality in IPV cases when the purpose was safeguarding children. The findings indicated some confusion about the difference and interface between the obligation to notify the child welfare service and to report under MR-IPV to the police. IPV victims who had experienced MR-IPV reported mixed consequences for their children. However, more than half reported that their children were better off after the MR-IPV. Conclusions The recognition of the impact of IPV on children in practice, research and policy-making might lead to some inconsistencies and contradictions in how service providers respond to IPV. Accordingly, service providers must take into account the challenges in situations where MR-IPV might be applicable in order to protect both the child(ren) and the victimized adult from IPV.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".