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Record W2515292665 · doi:10.1177/1079063216665837

Age Diversity Among Victims of Hebephilic Sexual Offenders

2016· article· en· W2515292665 on OpenAlexaff
Skye Stephens, Michael C. Seto, Alasdair M. Goodwill, James M. Cantor

Bibliographic record

VenueSexual Abuse · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCentre for Addiction and Mental HealthToronto Metropolitan UniversityRoyal Ottawa Mental Health CentreSaint Mary's University
Fundersnot available
KeywordsPedophiliaPsychologyAssociation (psychology)DemographyClinical psychologyInjury preventionPoison controlMedicineMedical emergency

Abstract

fetched live from OpenAlex

Hebephilia refers to sexual interest in pubescent children who are beginning to show early signs of sexual development but are sexually immature. The present study examined the relationship between hebephilia and victim age choice in a sample of 2,238 adult male sexual offenders. On average, offenders were 39 years old at the time of their assessments, and approximately half (48%) were referred by probation or parole offices. Assessment data included self-report, sexual arousal measured by volumetric phallometry, and victims' ages. Results suggested that, similar to pedophilia, hebephilia had a medium sized association with a greater number of victims under age 11 and a small sized association with a greater number of victims ages 11 to 14. Unlike pedophilia, a small positive association was consistently found between hebephilia and a greater number of victims ages 15 or 16. Furthermore, a small positive association was observed between victim age polymorphism and hebephilia and pedophilia. The present results suggested that hebephilia was associated with a greater number of victims age 14 or younger and had similar victim age correlates to pedophiles.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.037
GPT teacher head0.282
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

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

Citations15
Published2016
Admission routes1
Has abstractyes

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