Community-based Peer Sexual Health Educators: Lessons from Youth
Bibliographic record
Abstract
Abstract Developing and utilizing youth community members as peer educators is a growing and common phenomenon in health and social services, largely because of the organic learning and modelling processes in their everyday lives made possible by peer-to-peer processes. Part of what makes peer education effective over professional education is the potential rapport and trust built through shared lived experiences and identities between peers. There is significant potential for engaging peers in sexual health education specifically. This small-scale qualitative study explores the sexual health education needs of youth staying/living in York Region who identify as part of LGBTQ+ communities, as well as youth who either experience homelessness or experience serious mental health problems using a focus group methodology. The objective of this study is to report on the findings from the first session in a series of focus groups. Findings suggest that education about the consent to sexual activity is a significant area of need for all participants, and has implications in terms of the social context for participants. Emerging findings will be discussed in terms of participants’ expressed needs, such as a greater emphasis on consent, using all venues to discuss consent and relationships, and the importance of social identity of educators matching that of participants.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".