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Record W2000754729 · doi:10.3138/cjccj.46.5.621

Taking Down the Straw Man: A Reply to Webster and Doob

2004· article· en· W2000754729 on OpenAlexaffvenueabout
Kelley Blanchette, Laurence L. Motiuk

Bibliographic record

VenueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénale · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsMinistry of Community Safety and Correctional Services
Fundersnot available
KeywordsMisconductPsychologyScale (ratio)Empirical researchRating scaleCriminologyActuarial scienceSocial psychologyPolitical scienceLawStatisticsDevelopmental psychologyEconomicsMathematics

Abstract

fetched live from OpenAlex

Introduction The Custody Rating Scale (CRS) was found by Blanchette, Verbrugge, and Wichmann (2002) to be a valid measure of custodial risk for federally sentenced women offenders. CRS validation includes, but is not limited to, its role in predicting institutional adjustment, escape, and reoffending. Nevertheless, in the July 2004 issue of this journal Webster and Doob (2004) question the validity of the CRS for women, primarily because Blanchette et al.'s (2002) study revealed that one of its sub-scales does not predict institutional misconduct. The fact that scores on the Institutional Adjustment (IA) sub-scale of the CRS correlated positively and significantly with violent (r = 0.39) and non-violent (r = 0.47) incidents while in custody indicates that it is a valid measure of institutional risk. The fact that the Security Risk (SR) subscale did not correlate to institutional misconduct is not surprising, as that sub-scale was designed to measure public safety risk. By setting up this straw man, Webster and Doob (2004) demonstrate that their views are misdirected and reflect a narrow understanding of the application and validation of security classification instruments. The framework for our discussions is to challenge the investigation of the CRS presented by Webster and Doob, who provide no new empirical data on the instrument per se and draw some erroneous conclusions. Rather than entering into a theoretical debate about security classification, we have chosen to take down their straw man by presenting the legal and empirical underpinnings of the CRS, offering new validation data on the instrument, and addressing other contentious issues. Legal and empirical underpinnings Unfortunately, Webster and Doob are misinformed when they state that the CRS constitutes the foundation of the security classification system in (2004: 396). In fact, it is s. 30 of the Corrections and Conditional Release Act (CCRA) that legally prescribes how security classification decisions are made. Furthermore, in accordance with ss. 17 and 18 of the Corrections and Conditional Release Regulations (CCRR), the Correctional Service of Canada (CSC) is mandated to take the following factors into consideration in assigning a security classification of maximum, medium, or minimum: (a) seriousness of the offences committed by the inmate; (b) any outstanding charges; (c) the inmate's performance and behaviour while under sentence; (d) the inmate's social, criminal, and, where available, young offender history; (e) any physical or mental illness or disorder suffered by the inmate; (f) the inmate's potential for violent behaviour; and (g) the inmate's continued involvement in criminal activities. In the field of corrections, the purpose of security classification is to protect the public, employees, and offenders through appropriate placement of the inmate. As is true of most classification instruments, CRS development began with a review of existing instrumentation being used in other jurisdictions and proceeded to empirically test common factors used to assign custody levels (Canada, Solicitor General 1987). Not surprisingly, certain factors were common to all these scales: severity of current offence, sentence length, violent criminal background, and various indices of behaviour prior to incarceration. More importantly, the background documentation for the CRS includes descriptions of classification models, two-dimensional in nature, that take into consideration both institutional risk and public risk. In these classification models, scores are integrated (in a matrix fashion) to arrive at a final custody designation. In a similar way, the CRS was designed with two dimensions: an Institutional Adjustment (IA) sub-scale (5 items: history of involvement in institutional incidents, escape history, street stability, alcohol/drug use, age at time of sentencing) and a Security Risk (SR) sub-scale (7 items: number of prior convictions, most severe outstanding charge, severity of current offence, sentence length, street stability, prior parole and/or mandatory supervision/statutory releases, age at time of first federal admission). …

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)0.029
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.082
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.123
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0030.003
Science and technology studies0.0080.022
Scholarly communication0.0110.030
Open science0.0100.008
Research integrity0.0820.139
Insufficient payload (model declined to judge)0.0080.006

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 head0.083
GPT teacher head0.326
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations9
Published2004
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Criminology and Criminal Justice/La Revue canadienne de criminologie et de justice pénaleSame topicCriminal Justice and Corrections AnalysisFrench-language works237,207