An Examination of Police Culture and its Effects on Patrol Officers Attitudes towards Restorative Justice
Bibliographic record
Abstract
The purpose of this research is to examine the relationship between restorative justice and police culture, and the level to which this culture acts as barrier to the successful implementation and use of restorative justice by frontline police officers. Using a multi-level work group framework, frontline officer’s attitudes and understanding of restorative justice and police culture beliefs are examined, and then their impact on frontline police work is assessed. This study employs an explanatory sequential mixed methods design and is conducted in two phases. The initial quantitative phase involved distributing a Likert-style survey to frontline officers to measure their attitudes and understanding of restorative justice and police culture variables. After analysis of the initial quantitative findings, semi-structured interview questions were developed building on these findings to provide for a more in-depth qualitative analysis. Results indicate that police culture variables such as solidarity, teamwork, crime fighting and tough on crime attitudes are still persistent in policing, but frontline officers are generally accepting of restorative justice, and believe that it has a place in their frontline work as a dispositional tool. Findings indicate, however, that officers perceive restorative justice as another option only for less serious crimes and low risk offenders, and not as a new method of managing offender activity. Restorative justice is not being used to its fullest potential. To increase use of RJ diversion more thorough training, specialist designations and supervisory and middle management direction is recommended.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".