Incremental Contributions of Static and Dynamic Sexual Violence Risk Assessment: Integrating Static-99R and VRS-SO Common Language Risk Levels
Bibliographic record
Abstract
We examined the incremental contributions of static and dynamic sexual violence risk assessment in a multisite sample of 1,289 men treated for sexual offending. The study extends validation work that established new risk categories and recidivism estimates for the Violence Risk Scale–Sexual Offense version (VRS-SO), using the risk assessment common language (CL) framework. Different rates of sexual recidivism were observed at different thresholds of static risk (Static-99R) as a function of dynamic risk and treatment change, particularly for men who were actuarially above or well above average risk (Levels IVa and IVb, respectively). A framework integrating CL risk levels for Static-99R and VRS-SO dynamic scores into overall CL risk levels is presented. We discuss implications for dynamic sexual violence risk assessment regarding the language used for risk communication and the importance of dynamic risk instruments in sexual violence evaluations, particularly when credible agents of risk change may be present.
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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 | 0.001 | 0.000 |
| 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".