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Record W2062367872 · doi:10.1177/0886260509336961

Comparison of Measures of Risk for Recidivism in Sexual Offenders

2009· article· en· W2062367872 on OpenAlexaff
Jan Looman, Jeffrey Abracen

Bibliographic record

VenueJournal of Interpersonal Violence · 2009
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsKingston Health Sciences Centre
Fundersnot available
KeywordsRecidivismPsychologySex offensePoison controlRisk assessmentSex offenderInjury preventionClinical psychologyHuman factors and ergonomicsSexual violenceDemographySexual abusePsychiatryMedicineCriminologyMedical emergencyComputer securitySociologyComputer science

Abstract

fetched live from OpenAlex

Data for both sexual and violent recidivism for the Static-99, Risk Matrix 2000 (RM 2000), Rapid Risk Assessment for Sex Offense Recidivism (RRASOR), and Static-2002 are reported for 419 released sexual offenders assessed at the Regional Treatment Centre Sexual Offender Treatment Program. Data are analyzed by offender type as well as the group as a whole. Overall, the Static-2002 performed best for both outcomes, although differences between measures were not significant. The one exception to this was the RRASOR, which overall performed poorly. For rapists, the Static-2002 performed best for sexual recidivism, and the Risk Matrix 2000 performed best for violent recidivism. None of the measures performed well in predicting recidivism for child molesters. The components of the Static-2002 were examined in a regression analysis predicting sexual recidivism. Persistence of Sexual Offending and Age at Release were the only significant predictors for the group as a whole and for rapists. For child molesters, only the Deviant Sexual Interests component was significant. Results are discussed in terms of the current debate concerning age and risk for reoffence.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.389
Teacher spread0.315 · 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

Citations42
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Interpersonal ViolenceSame topicPsychopathy, Forensic Psychiatry, Sexual OffendingFrench-language works237,207