‘This is PEEP’ participatory qualitative study: learning from a provincial consultation and advisory group of people with lived and living experience of substance use in British Columbia, Canada
Bibliographic record
Abstract
OBJECTIVES: To summarise PEEP's (Professionals for Ethical Engagement of Peers-a group of consultants with lived and living experience of substance use) outputs and gain insights into PEEP's impact and suggestions for the future. DESIGN: Included an environmental scan to collate PEEP activities and outputs and a participatory qualitative design using thematic analysis. SETTING: British Columbia, Canada. PARTICIPANTS: Eight members of PEEP and nine staff/people who consulted PEEP were interviewed. RESULTS: PEEP members are co-authors/acknowledged for their input in 25 peer review publications and 16 reports; PEEP members co-presented or were co-authors on 33 presentations. PEEP meets by Zoom two times per week and is paid monthly via honorarium from the Provincial Health Service Authority at a current rate of $C30 per hour. Four themes emerged from our interviews: (1) What is PEEP? (PEEP provides a sense of community, holds systems accountable and inspires others), (2) PEEP Process (suggestions for improvement: consultants should be prepared and involve PEEP throughout the process and report how PEEP's insights were used), (3) PEEP Outcomes (PEEP members gain skills and confidence, PEEP provides a reality check, consultants learn from PEEP, and input leads to practice changes) and (4) Future of PEEP (sustainable funding and opportunities for growth are critical). CONCLUSION: PEEP is a cohesive group whose input is well-respected and influences policy and programmes. Given the ongoing drug toxicity emergency, it is critical to continue to support and expand PEEP.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.037 | 0.017 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".