A cluster analytic examination and validation of adult victim sexual offending subtypes in two Canadian samples
Bibliographic record
Abstract
The development and validation of sexual offense perpetrator typologies remains a useful endeavor with implications for theory and correctional/clinical practice. Most such typologies—which rely on factors such as the individual’s motivation for offending—have not been validated empirically. The current study utilized a validated sexual violence risk-needs instrument, the Violence Risk Scale—Sexual Offense version (VRS-SO; Wong, Olver, Nicholaichuk, & Gordon [2003, 2017], Regional Psychiatric Centre and University of Saskatchewan, Saskatoon, Canada), to develop and validate an empirically-derived adult victim sexual offense (AVSO) typology through model-based cluster analysis of dynamic risk-need domains. The study featured two treated samples of men (n = 283 and 169) convicted for contact sexual offenses against adult victims. A three-cluster solution was identified and replicated across the two samples: high antisociality high deviance (HA-HD), high antisociality low deviance (HA-LD), and low antisociality low deviance (LA-LD). External validation analyses demonstrated that HA-HD men had more dense sexual offense histories, were more likely to be diagnosed with a paraphilia, and had the highest rates of sexual recidivism (Sample 2 only). By contrast, the HA-LD men had greater concerns on indexes of nonsexual criminality, particularly high base rates of antisocial personality and substance use disorders, and high rates of general violent recidivism (particularly Sample 1). The findings suggest that the VRS-SO factors may have utility in discriminating between AVSO types to inform sexual offending theory, case formulation, and risk management.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".