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Record W1994403146 · doi:10.1007/s10979-006-9065-5

Incarceration and recidivism among sexual offenders.

2007· article· en· W1994403146 on OpenAlexaff
Kevin L. Nunes, Philip Firestone, Audrey F. Wexler, Tamara L. Jensen, John Bradford

Bibliographic record

VenueLaw and Human Behavior · 2007
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsRoyal Ottawa Mental Health CentreCarleton UniversityUniversity of Ottawa
Fundersnot available
KeywordsRecidivismPsychologySex offensePoison controlInjury preventionClinical psychologySexual abuseMedicineMedical emergency

Abstract

fetched live from OpenAlex

The relationship between incarceration and recidivism was investigated in a sample of 627 adult male sexual offenders. Incarceration for the index offense was unrelated to sexual or violent recidivism. This was the case whether incarceration was examined as a dichotomous variable (incarceration vs. community sentence) or as a continuous variable (length of incarceration). Risk for sexual recidivism was assessed with a modified version of the Rapid Risk Assessment for Sexual Offense Recidivism. There was no evidence that the relationship between incarceration and recidivism was confounded or moderated by risk or that length of incarceration and recidivism were non-linearly associated. Sentencing sexual offenders to terms of incarceration appears to have little, if any, impact on sexual and violent recidivism following release.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.035
GPT teacher head0.331
Teacher spread0.296 · 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

Citations33
Published2007
Admission routes1
Has abstractyes

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