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Record W2163081834 · doi:10.1080/14999013.2010.501846

Psychological Assessment for Adult Sentencing of Juvenile Offenders: An Evaluation of the RSTI and the SAVRY

2010· article· en· W2163081834 on OpenAlexaff
Andrew Spice, Jodi L. Viljoen, Heather M. Gretton, Ronald Roesch

Bibliographic record

VenueInternational Journal of Forensic Mental Health · 2010
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSophisticationPsychologyMaturity (psychological)Juvenile delinquencyJuvenileScale (ratio)Clinical psychologyVariance (accounting)Developmental psychology

Abstract

fetched live from OpenAlex

Two measures relevant to the assessment of juvenile offenders for transfer to adult court, the Risk-Sophistication-Treatment Inventory (RSTI) and the Structured Assessment of Violence Risk in Youth (SAVRY), were evaluated in the present study. Seventy-four adolescents considered for transfer were scored on these tools using file information, and clinicians’ transfer reports were coded for judgments of risk, maturity, and treatment amenability. Scores on RSTI Risk, Criminal Sophistication, and Treatment Amenability scales and SAVRY Total and Protective scales were significantly associated with adult sentences. Further, RSTI Criminal Sophistication explained significant additional variance in the adult sentencing decision beyond other legal criteria such as offense severity. However, scores on the RSTI Sophistication-Maturity scale were not associated with adult sentences. Results provide support for the use of the RSTI and the SAVRY, underscore the potential importance of psychological characteristics to adult sentencing decisions, and reflect challenges inherent in psycho-legal assessments of maturity.

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)0.004
metaresearch head score (Gemma)0.012
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 score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.437
Teacher spread0.377 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

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