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Record W1541709579 · doi:10.1108/jfp-10-2013-0048

The use of a structured guide to assess proxies of offending behaviours and change in custodial settings

2015· article· en· W1541709579 on OpenAlexaff
Audrey Gordon, Stephen C. P. Wong

Bibliographic record

VenueJournal of Forensic Practice · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPsychologySanctionsAggressionProxy (statistics)Social psychologyApplied psychologyComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Purpose – Within controlled environments such as prisons or forensic facilities, strong sanctions and other factors can inhibit the expression of offence-linked behaviours otherwise observable in community settings. For example, institutional restrictions may distort the offender’s habitual expression of aggressive behaviours such that the individual’s aggressive characteristics are less intense or observable. Thus, the influences of controlled settings can make it difficult for staff to capture idiosyncratic evidence of change or lack thereof over time or with treatment. The purpose of this paper is to describe an assessment and measurement framework that can be used to assist treatment and correctional staff collectively focus attention on relevant characteristics and behaviours idiosyncratically linked to offending. Design/methodology/approach – The authors use the terms “offence analogue behaviours (OAB)” to describe proxies of offence behaviours observable in controlled settings and “offence replacement behaviours (ORB)” as the contrasting positive, pro-social skills and strategies that the individual implements to change and manage problem areas linked to aggression and criminality. This paper discusses the application and practical utility of the framework and an associated assessment and measurement tool; the Offence Analogue and Offence Replacement Behaviour Guide (Gordon and Wong, 2009-2013). Findings – The OAB and ORB Guide has shown to be useful by directing the attention of treatment personnel to the here-and-now offence related behaviours displayed by offenders in custodial settings. In the absence of such focused attention, relevant proxy behaviours can often be masked in these highly controlled environments. The Guide is therefore a useful adjunct to identify such behaviours for treatment and for assessing treatment-related changes. Research limitations/implications – The OAB/ORB Guide was developed based on a conceptual framework derived from the empirical literature on correctional treatment, risk assessment, psychological theories and clinical practice. While there has been some positive pilot use of the Guide’s utility and preliminary research, at this point, empirical evidence is still lacking. Practical implications – The OAB/ORB Guide provides quantified and structured guidelines to assess offence proxy and offence replacement behaviours observable day-to-day within controlled environments, such as during custody or supervised release to the community. Originality/value – This guide was developed to assist staff with the identification, documentation and measurement of idiosyncratic negative and positive offence-related proxy behaviours observable across custodial or supervised contexts. Accordingly, the authors suggest that OAB/ORB guide information can be used to evaluate changes in risk over treatment and/or time. Further, the authors describe how this framework may enhance the efficacy of multi-disciplinary treatment and management teams. Two cases are used to illustrate the application of the Guide.

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)0.018
metaresearch head score (Gemma)0.032
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.005

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 head0.157
GPT teacher head0.410
Teacher spread0.252 · 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

Citations12
Published2015
Admission routes1
Has abstractyes

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