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Record W2170926910 · doi:10.1177/1079063210372142

The Recidivism Rates of Female Sexual Offenders Are Low: A Meta-Analysis

2010· review· en· W2170926910 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSexual Abuse · 2010
Typereview
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsPublic Safety CanadaUniversité de Montréal
FundersPublic Safety Canada
KeywordsRecidivismPsychologySex offenseSexual violenceSex offenderDemographyClinical psychologyPoison controlInjury preventionCriminologySexual abuseMedicineMedical emergencySociology

Abstract

fetched live from OpenAlex

This study examined the recidivism rates of female sexual offenders. A meta-analysis of 10 studies (2,490 offenders; average follow-up 6.5 years) showed that female sexual offenders have extremely low rates of sexual recidivism (less than 3%). The recidivism rates for violent (including sexual) offences and for any type of crime were predictably higher than the recidivism rates for sexual offences but still lower than the recidivism rates of male sexual offenders. These findings indicate the need for distinct policies and procedures for assessing and managing the risk of male and female sexual offenders. Risk assessment tools developed specifically for male sexual offenders would be expected to substantially overestimate the recidivism risk of female sexual 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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.665
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.004
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.207
GPT teacher head0.417
Teacher spread0.210 · 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