Resistance to Antisocial Peers in Adolescents Found Not Criminally Responsible on Account of Mental Disorder: Predictive and Incremental Validity With the VRAG-R
Bibliographic record
Abstract
There has been a recent theoretical shift toward the inclusion of protective factors within risk assessment. However, there is a lack of empirical evidence surrounding this practice in unique forensic populations. Using a long-term retrospective design, we examined the predictive and incremental validity of the protective factor resistance to antisocial peers and the Violence Risk Appraisal Guide—Revised in 119 individuals who were found Not Criminally Responsible on Account of Mental Disorder (NCRMD) as adolescents. The results indicated that resistance to antisocial peers significantly predicted general nonrecidivism (area under the curve [AUC] = .647) and violent nonrecidivism (AUC = .654) in the long term (maximum 35-year follow-up). Incorporation of resistance to antisocial peers into the Violence Risk Appraisal Guide—Revised did not significantly increase the incremental validity for general or violent recidivism. Using logistic regression, adolescents’ age at their NCRMD start date had no significant relationship with recidivism and was unrelated to the protective effect of resistance to antisocial peers.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".