Service Providers’ Attitudes Toward Mandatory Reporting of Intimate Partner Violence: The Impact of Professional Experience
Bibliographic record
Abstract
Mandatory reporting (MR) among service providers (SP) working with intimate partner violence (IPV) is controversial, and the research is scarce. The potential association of SPs experience with IPV and MR-IPV and their attitudes is the aim of the current study. A total of 374 SPs working with victims and perpetrators (help-seekers) of IPV participated in this study. Factor analysis was conducted to produce a continuous standardized dependent variable as a measure of attitudes toward MR-IPV. Descriptive results indicated that SPs were generally supportive of MR-IPV. Linear regression analyses showed that a higher degree of professional experience with IPV was significantly associated with less skepticism of MR-IPV. The result was significant regardless of (1) severity of violence, (2) category of help-seeker, (3) time of incidents, and (4) number of cases where MR-IPV was considered relevant. Having substantial experience with IPV and MR-IPV remained significant adjusting for the SP category, years in current position, knowledge of MR, and frequency of mandatory reports. Our results indicate that experience is an important part of SPs attitudes toward MR-IPV.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".