Bibliographic record
Abstract
Purpose The purpose of this paper is to propose a focus for mental health training efforts to better equip officers to provide interventions and supports to help facilitate improved outcomes for people experiencing mental health crises. Design/methodology/approach A reflection on key evidence relating to mental health training programmes delivered to police, focussing on Australia, the USA and Canada. Findings While there are a number of similarities in the core content of mental health training programmes offered internationally, the availability and uptake of training across jurisdictions remains piecemeal and idiosyncratic. Police officers report a strong preference for hands-on experiential learning; this has immediate and direct relevance to their operational duties, and is consistent with core principles of andragogy. While all police employees require mental health training, specialised mental health training programmes should clearly be reserved for a select group of officers who volunteer after acquiring sufficient operational experience. Research limitations/implications Priorities should centre on measuring the effectiveness of mental health training packages and discerning the active elements associated with changes in police skills and confidence, as well as identifying elements that support improved outcomes for people who experience mental illness and who have contact with the police. Practical implications Police need to continue to need to seek legitimacy with respect to their guardianship role as mental health interventionists. Training should tap into practice-based wisdom. Training should be practical, applied and reinforced through wider knowledge-based learning and workplace reinforcement. Training is needed for everyone, but specialised training is not for all. Police need to focus on the partnerships and expend time, energy and resources to maintain and grow them. Specialist (and other forms of) training needs to be evaluated so we understand what works? Originality/value There may be opportunities to streamline the delivery of knowledge-based aspects of mental health training and focus much more on experiential learning, both in specialised training courses as well as shorter mental health awareness sessions.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Qualitative | high |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: yes | Not applicable | high |
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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.010 | 0.020 |
| Insufficient payload (model declined to judge) | 0.042 | 0.007 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".