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Record W2101081939 · doi:10.1177/0093854803262507

Use of Dynamic Risk/Need Assessment Instruments Among Long-Term Incarcerated Offenders

2004· article· en· W2101081939 on OpenAlexaffabout
David J. Simourd

Bibliographic record

VenueCriminal Justice and Behavior · 2004
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsQueen's University
Fundersnot available
KeywordsRecidivismPredictive validityContext (archaeology)Risk assessmentTerm (time)Reliability (semiconductor)PsychologySample (material)Applied psychologyClinical psychologyComputer securityComputer science

Abstract

fetched live from OpenAlex

Dynamic risk/need assessment instruments are useful tools in the effective treatment and management of offenders. The Level of Service Inventory-Revised (LSI-R) is a dynamic risk/need assessment instrument that has been used extensively among a variety of offender samples. Although considerable research has shown that the instrument is valid and reliable, there is a lack of information on the predictive validity of the instrument among longer term offenders. In the current study the LSI-R was completed on a sample of 129 Canadian federally incarcerated offenders serving a mean sentence length of 5 years. Scores on the LSI-R were compared to various recidivism criteria during a 15-month follow-up period. Results indicated the instrument had acceptable reliability and predictive validity and distinguished recidivists from nonrecidivists. Results are discussed within the context of the assessment and treatment of longer term 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 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 score0.091
Threshold uncertainty score1.000

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 head0.063
GPT teacher head0.363
Teacher spread0.300 · 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

Citations91
Published2004
Admission routes2
Has abstractyes

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