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Record W2042503252 · doi:10.1002/bsl.574

Predictive validity of the Psychopathy Checklist: Youth Version for general and violent recidivism

2004· article· en· W2042503252 on OpenAlexaff
Raymond R. Corrado, Gina M. Vincent, Stephen D. Hart, Irwin M. Cohen

Bibliographic record

VenueBehavioral Sciences & the Law · 2004
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of the Fraser ValleySimon Fraser University
Fundersnot available
KeywordsRecidivismPsychopathy ChecklistPsychopathyPsychologyPoison controlChecklistInjury preventionPredictive validityClinical psychologyAntisocial personality disorderHuman factors and ergonomicsSuicide preventionMedicineMedical emergencyPersonalitySocial psychology

Abstract

fetched live from OpenAlex

Several authors have expressed concern regarding the use of youth psychopathy assessments in determinations of risk for general and violent offending. The Psychopathy Checklist: Youth Version (PCL:YV) was completed with 182 male adolescent offenders in this prospective study (average 14.5 month follow-up) of general and violent recidivism. Both a two-factor and three-factor model of the PCL:YV significantly predicted general and violent recidivism at a predictive accuracy ranging from 68 to 63%. However, regression analyses indicated these associations were explained primarily by behavioral psychopathic symptoms, rather than interpersonal or affective traits. Implications for the use of psychopathy assessments for risk during adolescence are discussed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.083
GPT teacher head0.358
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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

Citations204
Published2004
Admission routes1
Has abstractyes

Explore more

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