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Record W4288052952 · doi:10.1007/s10508-022-02354-z

Validating the Screening Scale of Pedophilic Crime Scene Behavior

2022· article· en· W4288052952 on OpenAlexaffabout
Robert Lehmann, Sébastien Brouillette‐Alarie, Amélie Pedneault, Raymond A. Knight

Bibliographic record

VenueArchives of Sexual Behavior · 2022
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPedophiliaPsychologyConvergent validityCutoffPsychometricsClinical psychologyRating scaleScale (ratio)Sex offensePoison controlDevelopmental psychologySexual abuseInjury preventionMedicineMedical emergency

Abstract

fetched live from OpenAlex

The Screening Scale of Pedophilic Crime Scene Behavior (SSPC) is a seven-item structured rating scale assessing pedophilic sexual arousal. In the current study, we cross-validated the scale's convergent validity using multiple measures of sexual interest in children (clinical diagnosis of pedophilia, the high fixation/low social competence type of the MTC:CM4, and phallometric assessment of sexual interests toward children) in two independent samples (USA and Canada). In both samples and in relation to all three criteria, the SSPC showed acceptable (phallometry) to excellent (clinical assessment) diagnostic accuracy. Furthermore, the SSPC showed incremental validity in relation to the Screening Scale for Pedophilic Interest and at times outperformed it in convergent validity analyses. The current study also provides psychometric information that can help users choose an appropriate SSPC cutoff score.

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)0.007
metaresearch head score (Gemma)0.016
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 score0.009
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.048
GPT teacher head0.333
Teacher spread0.284 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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