MétaCan
Menu
Back to cohort
Record W2148957666 · doi:10.1177/0306624x12469507

Effectiveness of Correctional Programs With Ethnically Diverse Offenders

2012· review· en· W2148957666 on OpenAlexafffundabout
Amelia M. Usher, Lynn A. Stewart

Bibliographic record

VenueInternational Journal of Offender Therapy and Comparative Criminology · 2012
Typereview
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsToronto Metropolitan UniversityMinistry of Community Safety and Correctional Services
FundersChina Scholarship CouncilPublic Safety Canada
KeywordsRecidivismEthnic groupEthnically diverseClinical psychologyPsychologyCriminal justiceMedicineGerontologyPsychiatryCriminologyPolitical science

Abstract

fetched live from OpenAlex

Numerous studies have examined the effects of cognitive-behavioural therapy (CBT) on criminal recidivism, and several meta-analyses have confirmed the overall effectiveness of this approach. Few studies, however, have examined the efficacy of these programs specifically with adult offenders from diverse ethnic backgrounds. The present research uses meta-analytic techniques to examine the outcomes for Canadian federal offenders participating in correctional programs according to self-identified ethnic group (Caucasian, Aboriginal, Black, and Other). Correctional programs within the Correctional Service of Canada adhere to the Risk, Need, Responsivity principles outlined in the effective correctional literature. Within-group analyses compared offenders from the same ethnic background who participated in correctional programs with a nontreatment comparison group. Odds ratios ranged from 1.36 to 1.76, indicating significant reductions in recidivism for offenders participating in correctional programs, regardless of ethnic status. Furthermore, the difference in effect size magnitude between ethnic groups was nonsignificant suggesting offenders from a wide variety of ethnic backgrounds can benefit from correctional programs rigorously developed and implemented using a CBT framework.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.522
GPT teacher head0.448
Teacher spread0.074 · 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 designOther design
Domainnot available
GenreReview

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
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Offender Therapy and Comparative CriminologySame topicPsychopathy, Forensic Psychiatry, Sexual OffendingFrench-language works237,207