Enhancing judicial skills in domestic violence cases: the development, implementation, and preliminary evaluation of a model US programme
Bibliographic record
Abstract
The overwhelming number and complexity of domestic violence cases in criminal and family courts has resulted in the development of education programmes to assist judges. There is limited research on judicial education in this area. This paper reviews one such initiative entitled ‘Enhancing Judicial Skills in Domestic Violence Cases’ (EJS) that has been developed and implemented over the last 20 years by the National Judicial Institute on Domestic Violence, a partnership of the US Department of Justice Office on Violence Against Women, National Council of Juvenile and Family Court Judges and Futures Without Violence. We present findings of a preliminary evaluation of the programme based on the self-reports of 480 judges who had taken the four-day workshop between 2006 and 2010. Overall, judges reported the programme to be engaging and effective. At a six-month follow‐up, most of the judges identified specific benefits and behavior changes in the areas of access to justice, judicial leadership, victim safety, and abuser accountability as a result of participating in the programme. Critical issues in judicial education are highlighted based on the authors’ experiences in the development and implementation of this programme.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".