LAW ENFORCEMENT PERCEPTIONS OF YOUTH DIVERSION: A CASE STUDY OF THE DURHAM REGIONAL POLICE SERVICE
Bibliographic record
Abstract
Enacted in 2003, the Youth Criminal Justice Act (YCJA) began the transition into a new era of youth justice in Canada (Bala 2015). As a result, the CJS saw a drastic increase in the use of extrajudicial measures and decrease in the use of courts and custodial sentences for minor offences (Bala 2003). The YCJA’s emphasis on the use of alternative measures has produced many favourable outcomes for youth offenders, the legal system, and society (Bala 2015). Despite favourable outcomes, when police officers—the gatekeepers of the CJS—hold unfavourable attitudes towards diversion, diversionary measures are applied in an inconsistent manner (Schulenberg 2015; Marinos and Innocente 2008; Prenzler and Hayes 2000; Maclure Campbell and Dufresne 2003; Lurigio and Skogan 1994; Skogan 2008; Lumb and Brezeale 2003). Considering that the overall success of pre-charge diversion programs is limited to a police officer’s willingness to apply diversionary measures, this study explores the perception and attitudes of Durham Regional Police Service (DRPS) officers around the DRPS Youth Diversion Program (YDP). An original 41-item anonymous online survey was administered to 36 DRPS officers. Findings from the survey suggest that officers generally hold favourable views of the YDP and are willing to engage with the YDP. Officers are knowledgeable of the YDP and believe that their diversion-related training is sufficient. That said, findings also indicate that officers require additional training in order for the YDP to be implemented as it was intended by the YCJA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".