Supporting peer researchers: recommendations from our lived experience/expertise in community-based research in Canada
Bibliographic record
Abstract
Community-based research in HIV in Canada is a complex undertaking. Including peer researchers living with HIV meaningfully is intricate and costly. However, this inclusion guarantees results that translate to community action, policy-making, and public awareness. Including HIV+ peer researchers expedites the path from research to intervention. However, we must constantly review our support in light of three implicit tasks performed by peer researchers: constant disclosure, emotional labor, and advocating for meaningful participation. Our team offers four pillars of support to reduce harm and strengthen the self-determination, confidence, advocacy, and impact for HIV+ peer researchers. The provision of emotional, instrumental, educational, and cultural/spiritual support might seldom be standardized within a study, but to successfully engage in community-based research, study teams must articulate what support can be offered in each area.
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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 | 0.109 | 0.199 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.038 | 0.020 |
| Scholarly communication | 0.027 | 0.015 |
| Open science | 0.011 | 0.024 |
| Research integrity | 0.011 | 0.018 |
| Insufficient payload (model declined to judge) | 0.010 | 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".