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Record W2170128799 · doi:10.1177/0093854809340991

Assessment of Reoffense Risk in Adolescents Who Have Committed Sexual Offenses

2009· article· en· W2170128799 on OpenAlexaff
Jodi L. Viljoen, Natasha Elkovitch, Mario J. Scalora, Daniel Ullman

Bibliographic record

VenueCriminal Justice and Behavior · 2009
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRecidivismPsychopathy ChecklistPsychologyPsychopathySex offenderSex offenseClinical psychologyChecklistPredictive validityPoison controlInjury preventionSexual abuseSocial psychologyAntisocial personality disorderMedical emergencyMedicinePersonality

Abstract

fetched live from OpenAlex

Clinicians are often asked to assess the likelihood that an adolescent who has committed a sexual offense will reoffend. However, there is limited research on the predictive validity of available assessment tools. To help address this gap, this study examined the ability of the Estimate of Risk of Adolescent Sexual Offense Recidivism (ERASOR), the Youth Level of Service/Case Management Inventory (YLS/CMI), the Psychopathy Checklist: Youth Version (PCL:YV), and the Static-99 to predict reoffending in a sample of 193 adolescents. Youth were followed for an average of 7.24 years after discharge from a residential sex offender treatment program. Although none of the instruments significantly predicted detected cases of sexual reoffending, ERASOR’s structured professional judgments nearly reached significance ( p = .069). Both the YLS/CMI and the PCL:YV predicted nonsexual violence, any violence, and any offending; however, the YLS/CMI demonstrated incremental validity over the PCL:YV. Although the Static-99 has considerable support with adult sex offenders, it did not predict sexual or general reoffending in the present sample of adolescents.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.370
Teacher spread0.325 · 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.

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

Citations93
Published2009
Admission routes1
Has abstractyes

Explore more

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