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Record W2045404832 · doi:10.1177/0093854800027003005

Reliability, Construct, and Concurrent Validities of the Self-Appraisal Questionnaire

2000· article· en· W2045404832 on OpenAlexaffabout
Wagdy Loza, Gurmeet Kaur Dhaliwal, Daryl G. Kroner, Amel Loza-Fanous

Bibliographic record

VenueCriminal Justice and Behavior · 2000
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsCarleton UniversityQueen's University
Fundersnot available
KeywordsRecidivismPsychologyReliability (semiconductor)Clinical psychologyPoison controlHuman factors and ergonomicsInjury preventionSuicide preventionConstruct validityOccupational safety and healthPsychometricsPsychiatryMedical emergencyMedicine

Abstract

fetched live from OpenAlex

The Self-Appraisal Questionnaire (SAQ) is a recently developed self-report questionnaire designed to predict violent and nonviolent offender recidivism. This 67-item, six-subscale tool measures quantitative criminogenic risk-need areas. The SAQ was administered to 303 federally sentenced Canadian male offenders. The total scale test-retest reliability coefficient was .95 and ranged from .69 to .93 for the subscales. Coefficient alphas ranged from .42 to .87. All the subscales with the exception of one had a one-factor solution. The SAQ subscales correlated with other instruments assessing similar constructs and with other measures of recidivism. Offenders with high SAQ totals and subscale scores committed significantly more offenses than did those with low SAQ scores. Similarly, offenders with a history of violence had higher SAQ total scores than the offenders with no history of violence. These preliminary results support the further study of the SAQ as an instrument for predicting violent and nonviolent recidivism.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.746
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.031
GPT teacher head0.342
Teacher spread0.311 · 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.

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

Citations83
Published2000
Admission routes2
Has abstractyes

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