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Record W2037167397 · doi:10.1177/0093854807309037

Dropout From Sex-Offender Treatment and Dimensions of Risk of Sexual Recidivism

2007· article· en· W2037167397 on OpenAlexaff
Kevin L. Nunes, Franca Cortoni

Bibliographic record

VenueCriminal Justice and Behavior · 2007
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversité de MontréalCarleton University
Fundersnot available
KeywordsRecidivismSex offenderDeviance (statistics)PsychologySex offenseDropout (neural networks)Poison controlHuman factors and ergonomicsInjury preventionClinical psychologyCriminologyPsychiatryMedicineSexual abuseMedical emergencyComputer science

Abstract

fetched live from OpenAlex

The extent to which general criminality and sexual deviance are associated with dropout or expulsion from a sex-offender treatment program was examined. Participants were 52 offenders who dropped out of, or were expelled from, their last sex-offender program and a comparison group of 48 program completers. As expected, the general criminality items of the Static—99 were significantly associated with dropout/expulsion but the sexual deviance items were not. Thus, risk for sexual recidivism and risk for dropout/expulsion from sex-offender programs do not appear to be synonymous. Basing estimates of risk for dropout/expulsion on general criminality rather than sexual deviance may be a more effective and efficient strategy for managing sex offenders.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.058
GPT teacher head0.351
Teacher spread0.293 · 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

Citations33
Published2007
Admission routes1
Has abstractyes

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