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Record W2163100893 · doi:10.1177/1079063213492343

A Multimodal Examination of Sexual Interest in Children

2013· article· en· W2163100893 on OpenAlexaffabout
Kelly M. Babchishin, Kevin L. Nunes, Nicolas Kessous

Bibliographic record

VenueSexual Abuse · 2013
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCarleton University
FundersAssociation for the Treatment of Sexual Abusers
KeywordsPedophiliaPsychologyClinical psychologyDevelopmental psychologyChild sexual abuseSexual abuseHuman factors and ergonomicsPoison controlMedicine

Abstract

fetched live from OpenAlex

Research and theoretical models have consistently identified sexual interest in children as a key factor involved in child sexual offending. However, there is only moderate agreement in the diagnosis of pedophilia and different assessment methods identify different offenders as pedophiles. The current study examined the discriminative and convergent validity of three different measures of sexual interest in children. Participants included sex offenders and nonsex offenders recruited from federal prisons (i.e., offenders serving sentences of more than 2 years) in Ontario, Canada. Child molesters' responses (n = 35) were not significantly different from nonsex offenders (n = 21) on an implicit measure of sexual interest in children (Sexual Attraction to Children Implicit Association Test [SAC-IAT] d = 0.44, 95% CI [-0.11, 0.99]), but differed on the self-report (Sexual Interest Profiling System; d = 0.83, 95% CI [0.27, 1.39]) and viewing time (d = 1.15, 95% CI [0.54, 1.75]) measures. Findings did not provide clear support for the superiority of a multimodal approach, possibly due to the relatively small sample. More often than not, convergence between the three measures was observed (n = 74). Findings from the present study are an important step toward understanding the relationship between different measures of sexual interest in children and establishing their validity.

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 score0.396
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.034
GPT teacher head0.293
Teacher spread0.259 · 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

Citations33
Published2013
Admission routes2
Has abstractyes

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