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Record W1974169659 · doi:10.1037/a0021229

Exploring differences in youth and parent reports of antisociality among adolescent sexual and nonsexual offenders.

2011· article· en· W1974169659 on OpenAlexaff
Tracey A. Skilling, James Doiron, Michael C. Seto

Bibliographic record

VenuePsychological Assessment · 2011
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychologyDevelopmental psychologyConduct disorderImpulsivityNarcissismJuvenile delinquencyPoison controlClinical psychologyAntisocial personality disorderSexual abusePersonalityInjury preventionSocial psychology

Abstract

fetched live from OpenAlex

This study examined the extent of, and explored several possible explanations for, the discrepancies found between adolescent and parent reports of conduct problems in adolescent sexual and nonsexual offenders. We found that adolescent sexual offenders scored lower on measures of conduct problems than did nonsexual offenders, whether on the basis of adolescent or parent report, though the difference was much larger for parent reports. Examining this discrepancy more closely, we found that parents of sexual offenders reported less antisocial behavior than did their sons, whereas parents of nonsexual offenders reported more antisocial behavior than did their sons. The same pattern of results was obtained for reports on impulsivity, but much less so with respect to antisocial personality traits such as narcissism and callousness. Measures of family functioning were generally not related to these parent-adolescent discrepancies in reports of conduct problems, but these discrepancies were positively correlated with parental reports of stress. The implications of these findings for the interpretation of research on adolescent sexual offenders and comparisons of sexual and nonsexual offenders 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 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)0.001
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.420
GPT teacher head0.380
Teacher spread0.040 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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