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Record W2132359648 · doi:10.1177/1079063211404249

Adolescents Who Have Sexually Offended

2011· article· en· W2132359648 on OpenAlexaff
Marnie E. Rice, Grant T. Harris, Carol Lang, Terry C. Chaplin

Bibliographic record

VenueSexual Abuse · 2011
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsWaypoint Centre for Mental Health Care
Fundersnot available
KeywordsCommitPsychologyDeviance (statistics)RecidivismSex offenseDevelopmental psychologySexual abusePedophiliaAdult maleHuman factors and ergonomicsPoison controlClinical psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

It is unclear whether deviant sexual preferences distinguish adolescents who commit sex offenses in the same way that such deviance characterizes adult sex offenders. We compared male adolescents (mean age = 15 at the time of a referral sex offense), matched adult sex offenders, and normal men (adult nonoffenders or nonsex offenders). We hypothesized the following: phallometric responses of the adolescents would be similar to those of adult sex offenders and would differ from normals; adolescents with male child victims would exhibit greater evidence of sexual deviance than those whose only victims were female children; among adolescents who had molested children, those with a history of sexual abuse would exhibit more evidence of sexual deviance than those with no such history; and phallometric measures would predict recidivism. With some notable exceptions or qualifications, results confirmed the hypotheses. Phallometry has valid clinical and research uses with adolescent males who commit serious sex offenses.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.301
Teacher spread0.243 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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