Integrating Peer Support Workers into Mental Health Programs
Bibliographic record
Abstract
Objective: Canadian Mental Health Association - Calgary Region (CMHA Calgary) works to reduce the impact of mental illness and addiction in the community. This is actioned through mental health programming focused on education, prevention, and early intervention. The organization places high value on the inclusion of lived experience in mental health programming in the form of Peer Support (PS). CMHA Calgary’s five-year strategic plan included a goal to formally integrate Peer Support Workers (PSWs) into all established programs with thought and intention. Research Design and Methods: CMHA Calgary integrated peers into mental health programs using a collaborative and developmental approach. The project team developed an evaluation framework as a guide to collect feedback and understand the impact of the pilot initiative. Results: This approach allowed for real-time responses and data collection, which lead to rapid action to improve the approach before it was spread to other programs. The project allowed for the development of program materials for future application. Conclusions: This project provided CMHA Calgary with tangible, actionable information on how to integrate PSWs into all of their programs.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".