Application of Youth-Led Participatory Action Research to Examining Adolescent Sexual and Reproductive Health and Rights in Ontario: What Can We Learn?
Bibliographic record
Abstract
Engaging adolescents and young people as partners in research is increasingly acknowledged as a vital strategy to ensure diverse voices are heard and to catalyze social change. This article, coauthored by adolescent and adult researchers, presents the methodological approach and outcomes of a youth-led participatory action research (YPAR) study in which three teams of youth researchers developed and implemented projects examining equity-related factors affecting adolescent sexual and reproductive health and rights (ASRHR) in Ontario, Canada. Teams of four assigned-female youth researchers aged 16-19 years were recruited from three priority regions through purposive sampling. Selected youth completed a paid 5-day virtual YPAR training. Each youth team, supported by adult research mentors, identified key ASRHR issues in their region and developed a related research question. Each team then determined their study's design, obtained institutional ethics approval, and conducted data collection, analysis, and interpretation. Based on their findings, teams proposed potential solutions and communicated results to multiple stakeholders. Methodologically, the YPAR process amplified youth voices through a social justice-framed approach to examining ASRHR. Centering the perspectives, values, and experiences of youth positively impacted the youth researchers themselves, while yielding results that were relevant, meaningful, adolescent-responsive, and culturally informed. Results from the youth-led projects identified multiple barriers to accessing sexual and reproductive health services and products. Policy and practice implications encompassed concerns related to geographical accessibility, equity, service provider competence, and content of sexuality education curricula.
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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 | 0.031 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".