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Record W4318932487 · doi:10.1177/10790632221149696

The Predictive Validity of the Revised Screening Scale for Pedophilic Interests (SSPI-2)

2023· article· en· W4318932487 on OpenAlexafffund
Martina Faitakis, Skye Stephens, Michael C. Seto

Bibliographic record

VenueSexual Abuse · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsRoyal Ottawa Mental Health CentreSaint Mary's UniversityUniversity of Guelph
FundersResearch Nova Scotia
KeywordsRecidivismPsychologyPredictive validityPedophiliaSexual abuseClinical psychologyPoison controlDevelopmental psychologyDemographyInjury preventionMedicineMedical emergencySociology

Abstract

fetched live from OpenAlex

The Revised Screening Scale for Pedophilic Interests (SSPI-2) is a five-item measure that assesses for pedohebephilia (sexual attraction to prepubescent and pubescent children) based on child victim characteristics. We aimed to replicate findings by Seto, Sandler et al. (2017) by examining the predictive validity of the SSPI-2 in an independent sample of 626 men referred for a sexological assessment because of sexual offending against children. SSPI-2 scores were associated with an increased likelihood of sexual recidivism but were not significantly associated with non-sexually violent or non-violent recidivism. When they were entered together, the SSPI-2 did not contribute additional variance to the Static-99R in the prediction of sexual recidivism. Results are consistent with the findings of Seto, Sandler et al. (2017) and suggest that higher scores on the SSPI-2 may be indicative of an increased risk for sexual recidivism in individuals who have sexually offended against children.

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)0.003
metaresearch head score (Gemma)0.013
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 score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.073
GPT teacher head0.351
Teacher spread0.278 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

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