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Record W4414402548 · doi:10.22215/cujs.v5i2.5311

Are Core Correctional Practice Strategies Associated with Positive Change Among Clients on Probation Irrespective of Gender, Indigeneity, or Mental Health and Substance Misuse?

2025· article· en· W4414402548 on OpenAlexaffabout
Sohaila Abdelhadi, Victoria Di Virgilio, Rebecca Wieler, Ellen Coady, Shelley L. Brown

Bibliographic record

VenueCarleton undergraduate journal of science. · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsCarleton University
Fundersnot available
KeywordsCognitive reframingMental healthCriminal justiceChristian ministryEconomic JusticeMental illnessScale (ratio)Substance use

Abstract

fetched live from OpenAlex

The intersection of mental health, substance use, and the criminal justice system presents significant challenges for probation and parole officers (PPOs), particularly when supervising justice-impacted persons (JIPs) with complex needs. Grounded in the risk-need-responsivity (RNR) model (Andrews et al., 1990), this research explores the relationship between core correctional strategies (e.g., teaching clients to reframe thinking styles) and client outcomes while on probation (e.g., less substance use, employment stability) and whether gender and Indigeneity moderate these effects. The study also explores if the presence of acute mental health crises and substance misuse influences the relationship between probation and parole officers’ use of Core Correctional Practice (CCP) strategies and client outcomes. The study analyzes 193 probation case notes following the introduction of the Ontario Solicitor General’s Made-in-Ontario Core Correctional Practices (CCP) Model of Community Supervision. A subset of six items from the Client Change Scale (CCS, Serin & Lloyd, 2018) is used to assess behavioural change across key life domains (e.g., employment, substance use, program engagement). Findings will inform evidence-based training enhancements and policy reforms to improve probation outcomes for diverse populations. The opinions and views expressed in this report reflect those of the author and not the Ontario Ministry of the Solicitor General. This project was done with the support of the Ontario Ministry of the Solicitor General.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
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 head0.071
GPT teacher head0.377
Teacher spread0.307 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueCarleton undergraduate journal of science.Same topicCriminal Justice and Corrections AnalysisFrench-language works237,207