Evaluating the Impact of Collaborative Art, Therapy and Training on Police Legitimacy: The Perceptions Held by Individuals with Substance Abuse Disorder and Police Officers
Bibliographic record
Abstract
This qualitative pilot study was funded by a federal micro-grant to seek to fill a void in the literature on police legitimacy. The focus of this pilot study was to determine if collaborative art therapy and training can change the perceptions of police legitimacy held by individuals with substance use disorder (SUD) or the perceptions of the police toward individuals with SUD. Besides the collaborative activities, individuals with SUD and police officers were provided with therapy and/or training sessions during the period of collaboration. The methodology for this study included the use of electronic survey instruments to evaluate any changes in perception. These instruments were administered anonymously before and after all therapy, training, and collaboration activities occurred. Each instrument contained open-ended questions relating to Police Legitimacy Scale (PLS) (Tankebe et al., 2016) categories, as well as additional measures. Analysis included qualitative methods to provide context and identify themes for content analysis. Findings did not confirm change overall however, positive responses support police legitimacy, perceptual changes and relationship building. Recommendations are made for relationship building through increased interaction, excluding enforcement activities between individuals with SUD and the police using collaborative projects such as art therapy.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".