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Predicting Recidivism in Sex Offenders Using the VRAG and SORAG: The Contribution of Age-at-Release

2007· article· en· W2003407621 on OpenAlexaff
Howard E. Barbaree, Calvin M. Langton, Ray Blanchard

Bibliographic record

VenueInternational Journal of Forensic Mental Health · 2007
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsRecidivismPsychologyRisk assessmentSex offenderDemographyPsychiatryClinical psychologyComputer security

Abstract

fetched live from OpenAlex

Sex offenders (N = 468) were released from custody and recidivism outcome recorded. The Violence Risk Appraisal Guide (VRAG) and Sex Offender Risk Appraisal Guide (SORAG) were scored for each offender. Results indicated that, for the majority of actuarial items contained in the VRAG and SORAG and for VRAG and SORAG bin scores, offenders with lower actuarial scores were released from custody at a significantly older age. Actuarial scores were regressed on age-at-release and residuals saved as age-corrected actuarial scores. Using ROC analysis, predictive accuracy was evaluated comparing original actuarial scores with age-corrected scores. For most item scores and both bin scores, the ability to predict recidivism was significantly reduced after the effects of age-at-release had been removed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.373
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2007
Admission routes1
Has abstractyes

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