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Record W3175864639 · doi:10.1177/10790632211019726

A Preliminary Analysis of Sexual Recidivism and Predictive Validity of the Static-99R in Men Discharged From State Hospitals Pursuant to California’s Sexually Violent Predator Act

2021· article· en· W3175864639 on OpenAlexaff
Allen Azizian, Mark E. Olver, James Rokop, Deirdre M. D’Orazio

Bibliographic record

VenueSexual Abuse · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRecidivismSex offensePredictive validitySexual violencePoison controlDemographyMedicinePsychologyInjury preventionPsychiatrySexual abuseClinical psychologyMedical emergencyCriminology

Abstract

fetched live from OpenAlex

We examined the recidivism rates and the predictive validity of the Static-99R in 335 men who were detained or civilly committed and released from California State Hospitals pursuant to the Sexually Violent Predator (SVP) Act, and followed up for approximately 21 years from date of hospital admission. In all, 8.7% were arrested or convicted for a new sexual offense during the total follow-up ( N = 335) and 7.8% over a fixed 5-year follow-up ( n = 205). The Static-99R demonstrated small in magnitude discrimination for sexual, violent, and general recidivism (area under the curve [AUC]/C = .56 to .63). Calibration analyses, conducted through expected/observed (E/O) index, demonstrated that the Static-99R overpredicted sexual recidivism, irrespective of whether the Routine or High Risk/Need norms were used. Observed recidivism rates were lower than predicted by Static-99R scores and may be the result of the sample’s older age at release, lengthy hospitalization, or other factors.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.023
GPT teacher head0.297
Teacher spread0.274 · 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.

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

Citations6
Published2021
Admission routes1
Has abstractyes

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