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Record W4415962044 · doi:10.1037/lhb0000616

The psychometric properties of the Child Pornography Offender Risk Tool (CPORT) in different subgroups of individuals convicted of offenses related to child sexual exploitation material (CSEM).

2025· article· en· W4415962044 on OpenAlexaff
Alexander Seiser, Reinhard Eher, L. Maaike Helmus, Daniel Turner, Martin Rettenberger

Bibliographic record

VenueLaw and Human Behavior · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGermanChild pornographyHuman factors and ergonomicsLegal psychologyPoison controlInjury preventionSuicide preventionSex offenderOccupational safety and health

Abstract

fetched live from OpenAlex

OBJECTIVE: Despite the increasing number of individuals convicted of offenses related to child sexual exploitation material (CSEM), empirical research on the psychometric properties of actuarial risk assessment instruments for this population is limited. RESEARCH QUESTION: Does the German version of the Child Pornography Offender Risk Tool (CPORT) demonstrate predictive validity in an Austrian sample of individuals incarcerated for CSEM offenses? METHOD: Using an exploratory, retrospective, file-based research design, we calculated effect sizes for the total sample (N = 128; follow-up period: M = 8.5 years, SD = 3.68), a subsample with fixed 5-year follow-up periods (n = 104), and subgroups of individuals convicted of either CSEM offenses only or both CSEM and sexual contact offenses. The study was exploratory in nature, evaluating the discriminatory power of a German CPORT and a shortened version (CPORT-SV), with scoring rules adapted for correctional settings. RESULTS: The German CPORT validly classified CSEM recidivism in the total sample (Harrell's C = 0.72, 95% confidence interval [CI] [0.62, 0.82]), the subsample with fixed 5-year follow-up periods (n = 104, area under the curve [AUC] = .73, 95% CI [0.60, 0.86]), individuals with additional sexual contact offenses (n = 57, AUC = .82, 95% CI [0.69, 0.94]), and individuals convicted of CSEM offenses only (n = 47, AUC = .70, 95% CI [0.55, 0.86]). The CPORT-SV performed comparably with the CPORT full version. Furthermore, in a subsample of individuals with additional sexual contact offenses, the CPORT (AUC = .84, 95% CI [0.70, 0.97]) and the CPORT-SV (AUC = .82, 95% CI [0.67, 0.97]) yielded effect sizes that were comparable with those of the Static-99 (AUC = .81, 95% CI [0.64, 0.97]). CONCLUSION: Our findings suggest that the German version of the CPORT has potential as a risk assessment tool for professionals working in correctional settings, but further validation is needed before it can be fully implemented. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.275
Teacher spread0.258 · 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 teacher head, 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
Published2025
Admission routes1
Has abstractyes

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