Transforming Learning : Police Officers’ Perspectives on Social Justice Pedagogy in Mental Health Crisis Intervention Training
Bibliographic record
Abstract
This thesis investigates the Mental Health crisis intervention curriculum at an urban police services organization, and its implications for persons experiencing mental health crises. The study advances a learner-focused exploration of police officers’ perspectives on the collaborative education between police officers and mental-health practitioners. The research design utilizes narrative ethnography methodology involving nine participants, consisting of eight police officers, two of whom are dedicated members of the Mobile Crisis Intervention Teams (MCIT) and a Mental Health nurse. MCIT is a collaborative initiative between Toronto Police Service and hospitals and was established for the specific purpose of being first co-responders to persons experiencing mental health and addiction issues, referred to herein as “persons in crisis”. Most participants in this study had taken a Crisis Intervention course, which has a bifurcated curriculum in Mental Health and Law Enforcement. The methodology utilized in this thesis included generating data from interviews with the participants, classroom observation, policy documents, and a ride-along observation in a densely populated section of Toronto. The participants are from diverse racial backgrounds, selected purposively to elicit unique perspectives from their own lived experiences. My post-structural approach to Law Enforcement education was to disrupt prevailing thoughts and views that may be reinforcing the hegemonic status quo of the police over marginalized groups, particularly Black people, who experience mental health challenges. Thematic Analysis was used to analyse the data and it revealed that police officers are generally accepting of Crisis Intervention Training (CIT). Nested in Critical Race Theory lens, this study found a gap in established pedagogies which exclude issues of race, stigma, and other intersectionalities from the police curriculum. Data from the study highlight four major findings: CIT training is essential but is currently inadequate to meet the complex needs of a diverse society, 2. Stigma and racism are normative in police practice; and 3. Critical and social justice pedagogies are a welcome addition to CIT curriculum at the TPS but might face resistance by officers who do not share progressive views; and 4. Police officers admit some degree of responsibility for negative outcomes but blame the media for negative public perceptions. This thesis contributes to the existing knowledge around police education and the symbiotic relationship between Law Enforcement and Health Care sectors, and identifies areas where constructive changes can be made in police curricula.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.020 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".