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Record W2101430198 · doi:10.1177/0886260515570745

Individual Community-Based Treatment of Offenders With Mental Illness

2015· article· en· W2101430198 on OpenAlexaffabout
Jeffrey Abracen, Alessandra Gallo, Jan Looman, Alasdair M. Goodwill

Bibliographic record

VenueJournal of Interpersonal Violence · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsToronto Metropolitan UniversityMinistry of Community Safety and Correctional Services
Fundersnot available
KeywordsRecidivismContext (archaeology)AttendanceMental healthPsychologyPsychiatryRehabilitationMental illnessRisk assessmentIntervention (counseling)Clinical psychologyMedicine

Abstract

fetched live from OpenAlex

This study explores the effectiveness of psychological intervention at reducing the risk of recidivism among a group of high-risk, high-need offenders housed in a Community Correctional Centre (CCC) operated by the Correctional Service of Canada (CSC). File reviews on 136 male federal offenders living in a CCC in a large metropolitan area were included in the present investigation. Previous research on this sample by our team indicated that the majority of this sample met diagnostic criteria for a variety of psychiatric conditions. Data on the number of individual counseling sessions received and progress in treatment were collected from official file information for the purpose of the present investigation. After accounting for actuarially assessed risk, moderate doses of treatment were found to be associated with 7.7 times less likelihood of recidivism, and high doses of treatment were found to be associated with 11.6 times less likelihood of recidivism, when compared with offenders who received no treatment or were only assessed for treatment. These results are discussed in the context of correctional models of offender risk assessment and rehabilitation. It is notable that a very simple measure of global mental health treatment attendance, with no consideration of such factors as responsiveness, added considerable incremental predictive validity to the results after having statistically accounted for actuarially assessed risk of recidivism.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.086
GPT teacher head0.342
Teacher spread0.256 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations39
Published2015
Admission routes2
Has abstractyes

Explore more

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