Designing A Peer Leader Training Manual for Community-Based Sexual Health Research
Bibliographic record
Abstract
This paper recounts the development and implementation of the Peer Leader Training Manual for the Story-Sharing for Sexual Health Research (SSSH) Study conducted in Toronto, Canada. In the disciplinary integration of health and adult education, the community-engaged health research reported here reflects the successful partnership of academic researchers with a community-based organization. Eight South Asian women peer leaders were collectively recruited and trained as research associates to explore how stories (relative to fact sheets) can be used to promote dialogue and knowledge about sexual health and reduce HIV stigma among South Asian women. This paper is about the adult education tool used to orient them to the SSSH Study and train them for related field work: recruit participants, arrange intervention site and logistics, deliver intervention, administer pre and post surveys, conduct focus groups, and ensure data security. The manual played a significant role in training the peer leaders to further engage in future community health partnerships. This tool will also be helpful for other community-engaged health research involving sexual health initiatives in vulnerable communities.
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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 | 0.048 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.010 |
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".