“I think it made me a better person”: fostering personal-social development among immigrant youth through the SExT theatre programme
Bibliographic record
Abstract
Purpose Immigrant youth face both unique and disproportionate barriers to sexual health. Targeted sexual health education to redress these disparities requires creative and inclusive approaches that consider personal and community challenges and strengths. This study piloted a novel intervention: SExT: Sex Education by Theatre, a theatre-based, culturally-relevant, participatory action research programme delivered in an immigration destination neighbourhood in Toronto, Canada. Design/methodology/approach Nineteen youth were trained as peer educators. They participated in theatre-based workshops on sexual health topics which culminated in a performance for local peers. Mixed methods evaluation included surveys which investigated changes in personal and social development over three time-points (pre, post, 4-month follow-up). The impact of the intervention on peer educators was explored in greater depth using qualitative peer interviews and focus groups. Findings Quantitative study findings indicated that peer educators experienced significant improvements in personal growth, social inclusion and social engagement after participating in SExT and these improvements were maintained at follow-up. Thematic qualitative analysis further indicates that meaningful involvement in a sex education theatre intervention may protect against adverse outcomes and promote self-actualization, connection and active citizenship. Originality/value This research stands out for its innovative approach to addressing sexual health disparities among immigrant youth in Toronto using culturally relevant theatre-based peer education. SExT may serve as a model for sexual health interventions for newcomer youth and other priority groups in diverse contexts.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".