Engaging fathers who commit family violence: Issues and challenges for family courts
Bibliographic record
Abstract
Abstract Intervention with fathers who commit family violence is an essential but often overlooked part of effective family court proceedings. This article provides an overview of how evidence‐informed engagement with fathers around family violence can complement family court efforts to achieve safe and healthy outcomes for children. The focus on fathers is not based on bias against fathers, men, or masculinity, but rather it is consistent with the fact that fathers comprise a substantial proportion of those who use family violence. These men need more effective engagement and interventions. Fathers in these circumstances need to be engaged in services that can assess, monitor, and manage ongoing family violence and risk as well as develop skills to form more positive, healthy relationships with their children and children's mothers. Courts, in turn, need to consider evidence of accountability and change. Application and continued development of the strategies recommended herein would enhance the safety of mothers who experience violence, their children, and the well‐being of fathers who have used family violence. Collaboration with community partners serving families must become cornerstones in promoting the safety for and with all family members.
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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 | 0.052 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".