A New Typology of Men who Perpetrate Intimate Partner Violence: Differentiating Perpetrators Based on Criminal History and Antisocial Attitudes
Bibliographic record
Abstract
Latent class analysis was used to create a typology of men who had perpetrated intimate partner violence (IPV) ( n = 7,781) using data collected with the Service Planning Instrument (SPIn). Perpetrators were classified using variables empirically demonstrated to be related to recidivism risk. The resulting typology includes three classes: High Criminal History—High Antisocial Attitudes (18.5%; n = 1,439), High Criminal History—Low Antisocial Attitudes (51.6%; n = 4,015), and Low Criminal History—Low Antisocial Attitudes (29.9%; n = 2,327). The three classes were compared on additional risk factors and four recidivism outcomes at 1 and 3 years. High Criminal History—High Antisocial Attitudes perpetrators displayed the highest prevalence of risk factors and the highest rate of all recidivism outcomes, the Low Criminal History—Low Antisocial Attitudes class had the lowest rates, and the High Criminal History—Low Antisocial Attitudes class scored intermediate to the other classes.
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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 | 0.000 | 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 | 0.000 | 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".