DUI Offenders Who Delay Relicensing: A Quantitative and Qualitative Investigation
Bibliographic record
Abstract
OBJECTIVES: As in many jurisdictions, individuals convicted of driving under the influence (DUI) in the province of Quebec are mandated to relicensing programs, which include obligatory participation in intervention programs. However, prolonged delay in relicensing is widespread, potentially contributing to unlicensed driving, untreated substance misuse problems, and drink-driving risk. Information about the characteristics of DUI offenders who delay relicensing (DR) is sparse. This investigation compares the characteristics of DR offenders with those offenders who do not delay (NoDR). In addition, the rationales of DR offenders for delaying relicensing are explored qualitatively. METHODS: Two studies were conducted to explore the characteristics of DR offenders. In Study 1, DR offenders (n = 46) were compared to NoDR offenders (n = 74) on multidimensional measures of psychosocial functioning, driving behavior, substance use, and psychological and neurocognitive characteristics. In Study 2, a qualitative examination of 20 DR offenders' reasons underlying delayed relicensing was undertaken, with verbatims content analyzed to identify major themes. A questionnaire, based upon this preliminary analysis, was then administered to another sample of DR participants (N = 37) to appraise and confirm thematic comprehensiveness. RESULTS: The main findings of Study 1 were that, compared to NoDR offenders, DR offenders had more past DUI convictions, were at greater risk for drink driving per kilometer (km) driven, were more likely to have received substance abuse treatment, and exhibited indices of poorer neurocognitive performance in visual memory and behavioral inhibition domains. No group differences were uncovered on substance use measures. The findings of Study 2 revealed that the expense of participation, availability of alternate transportation, lack of interest, and no access to a vehicle were the most frequent explanations for delayed relicensing. CONCLUSIONS: Overall, these findings suggest that both individual and contextual factors influence timely fulfillment of relicensing requirements. While the cost of relicensing may succeed in removing some offenders from the road, it may also be a barrier for others at risk for drink driving, preventing exposure to needed intervention programs. Reducing this barrier may need to be weighted against the risks of relicensing more DUI offenders. Neurocognitive factors may need to be taken into account to not only decrease delay in relicensing but also increase the benefits from participation in interventions that are part of current relicensing programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, not a consensus.
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".