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Record W2987788800 · doi:10.1027/1015-5759/a000551

Predictive Properties and Factor Structure of the VRS-SO in an Austrian Sample

2019· article· en· W2987788800 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Psychological Assessment · 2019
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRecidivismPsychologyConfirmatory factor analysisNormativeSample (material)Receiver operating characteristicStatisticsClinical psychologyStructural equation modelingMathematics

Abstract

fetched live from OpenAlex

Abstract. We examined the structural and predictive properties of the Violence Risk Scale-Sexual Offense (VRS-SO) version in an Austrian sample of N = 666 men incarcerated for sexual offenses; 353 of whom were followed up an average of 11 years post-release. Results of a confirmatory factor analysis of dynamic item scores supported a three-factor model (Sexual Deviance, Criminality, and Treatment Responsivity) consistent with prior research. VRS-SO static, dynamic, and total scores showed good properties of discrimination for sexual (area under the receiver operating curve [AUC] = .68–.80) and violent (AUC = .65–.68) recidivism, while the factor scores showed differential prediction of these outcomes. Calibration analyses demonstrated lower estimated rates of 5-year sexual reoffense associated with VRS-SO score bands in the present sample compared to observed rates from the normative sample, with closest correspondence observed for the highest risk band (E/O index = 1.01). Implications for the psychometric properties and application of the VRS-SO in international settings are discussed.

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.

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)0.001
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 score0.083
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.349
Teacher spread0.279 · 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