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Record W2054863205 · doi:10.1007/s10979-007-9114-8

Criminal recidivism among juvenile offenders: Testing the incremental and predictive validity of three measures of psychopathic features.

2007· article· en· W2054863205 on OpenAlexafffund
Kevin S. Douglas, Monica E. Epstein, Norman G. Poythress

Bibliographic record

VenueLaw and Human Behavior · 2007
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsSimon Fraser University
FundersMichael Smith Health Research BC
KeywordsRecidivismPsychopathy ChecklistPsychologyPredictive validityPsychopathyIncremental validityAntisocial personality disorderJuvenile delinquencyTest validityClinical psychologyPoison controlDevelopmental psychologyPsychometricsInjury preventionSocial psychologyPersonality

Abstract

fetched live from OpenAlex

We studied the predictive, comparative, and incremental validity of three measures of psychopathic features (Psychopathy Checklist: Youth Version [PCL:YV]; Antisocial Process Screening Device [APSD]; Childhood Psychopathy Scale [CPS]) vis-à-vis criminal recidivism among 83 delinquent youth within a truly prospective design. Bivariate and multivariate analyses (Cox proportional hazard analyses) showed that of the three measures, the CPS was most consistently related to most types of recidivism in comparison to the other measures. However, incremental validity analyses demonstrated that all of the predictive effects for the measures of psychopathic features disappeared after conceptually relevant covariates (i.e., substance use, conduct disorder, young age, past property crime) were included in multivariate predictive models. Implications for the limits of these measures in applied juvenile justice assessment 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)0.004
metaresearch head score (Gemma)0.024
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 score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.139
GPT teacher head0.339
Teacher spread0.201 · 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

Citations62
Published2007
Admission routes2
Has abstractyes

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