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Record W1972691615 · doi:10.1177/0093854804268755

The Measures of Criminal Attitudes and Associates (MCAA)

2004· article· en· W1972691615 on OpenAlexaff
Jeremy F. Mills, Daryl G. Kroner, Toni Hemmati

Bibliographic record

VenueCriminal Justice and Behavior · 2004
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCarleton University
Fundersnot available
KeywordsRecidivismPsychologyPredictive validityHuman factors and ergonomicsPoison controlRisk assessmentInjury preventionEntitlement (fair division)Suicide preventionJuvenile delinquencyClinical psychologyDevelopmental psychologyMedical emergencyMedicineComputer securityComputer science

Abstract

fetched live from OpenAlex

Recent research has demonstrated that antisocial attitudes and antisocial associates are among the better predictors of antisocial behavior. This study tests the predictive validity of the Measures of Criminal Attitudes and Associates (MCAA) in a sample of adult male offenders. The MCAA comprises two parts: Part A is a quantified self-report measure of criminal friends, and Part B contains four attitude scales: Violence, Entitlement, Antisocial Intent, and Associates. The MCAA scales showed predictive validity for the outcomes of general and violent recidivism. In addition, the MCAA significantly improved the prediction of violent recidivism over an actuarial risk assessment instrument alone. Discussion centers on the contribution that antisocial attitudes and associates make to risk assessment.

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)0.002
metaresearch head score (Gemma)0.013
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.079
GPT teacher head0.363
Teacher spread0.283 · 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

Citations146
Published2004
Admission routes1
Has abstractyes

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