Improving Judicial Protection in Intimate Partner Violence Cases: The Role of Specialized Courts and Judges
Bibliographic record
Abstract
We study the large-scale implementation of a system of specialized domestic violence courts (SDVCs), an innovation in access to justice programs for potential victims of intimate partner violence (IPV) and offenders.Using individual-level administrative data from the universe of civil domestic violence cases in Puerto Rico during the period 2014-2020, we leverage the staggered opening of SDVCs across judicial regions to examine the consequences for victims' judicial protection and offender recidivism.Access to SDVCs leads to a considerable 8 percentage points increase in the probability that judges issue a protection order and a 1.7 percentage point (15 percent) decrease in victim and offender reappearance rates within one year of the start of the case.Effects are more pronounced for cases in which parties have children in common and in which access to SDVCs is more limited.Linking the case data to administrative and survey data on judges, we show that the priorities of judges assigned to SDVCs play a prominent role in explaining these outcomes.
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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 | 0.008 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 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".