Associations between gambling, substance abuse, impulsivity, and recidivism among Canadian offenders: A multi-faceted exploration of poor impulse control
Bibliographic record
Abstract
Research has revealed that offenders who display poor impulse control are more likely to engage in substance use and abuse, as well as gambling (Vitaro, Ferland, Jacques, & Ladoucer, 1998). What remains unclear is how these impulsive behaviours interact with each other and in turn affect offenders’ criminal behaviour post release. In the current study, 140 male participants incarcerated in minimum and medium security institutions reported their substance use, gambling involvement, and several features of impulsive personality (including sensation seeking, behavioural inhibition, and general impulsivity). Use of multiple questionnaires provided a unique opportunity to examine the multi-faceted dimensions of this personality trait. Data were also collected over a four year period post-release to assess recidivism rates. A survival analysis was conducted to assess if offenders with a history of impulsive behaviour in multiple contexts (gambling, substance abuse) were more likely to reoffend. Findings are discussed regarding the ability to predict post-release outcomes as well as implications for the development of effective treatment strategies for this sample of offenders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.014 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".