A Seat at the Table: Designing an Activity-Based Community Advisory Committee With People Living With HIV Who Use Drugs
Bibliographic record
Abstract
Recently, scholars have begun to critically interrogate the way community participation functions discursively within community-based participatory research (CBPR) and raise questions about its function and limits. Community advisory committees (CACs) are often used within CBPR as one way to involve community members in research from design to dissemination. However, CACs may not always be designed in ways that are accessible for communities experiencing the intersections of complex health issues and marginalization. This article draws on our experience designing and facilitating Research Rec'-a flexible, and activity-based CAC for a project about the acute-care hospital stays of people living with HIV who use drugs. Using Research Rec' as a case study, we reflect on ethical, methodological, and pedagogical considerations for designing and facilitating CACs for this community. We discuss how to critically reflect on the design and facilitation of advisory committees, and community engagement processes in CBPR more broadly.
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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 | 0.059 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.028 | 0.013 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".