Conceptualizing Youth Participation in Children’s Health Research: Insights from a Youth-Driven Process for Developing a Youth Advisory Council
Bibliographic record
Abstract
Given the power asymmetries between adults and young people, youth involvement in research is often at risk of tokenism. While many disciplines have seen a shift from conducting research on youth to conducting research with and for youth, engaging children and teens in research remains fraught with conceptual, methodological, and practical challenges. Arnstein's foundational Ladder of Participation has been adapted in novel ways in youth research, but in this paper, we present a new rendering: a 'rope ladder.' This concept came out of our youth-driven planning process to develop a Youth Advisory Council for the Human Environments Analysis Laboratory, an interdisciplinary research laboratory focused on developing healthy communities for young people. As opposed to a traditional ladder, composed of rigid material and maintaining a static position, the key innovation of our concept is that it integrates a greater degree of flexibility and mobility by allowing dynamic movement beyond a 2D vertical plane. At the same time, the pliable nature of the rope makes it both responsive and susceptible to exogenous forces. We argue that involving youth in the design of their own participatory framework reveals dimensions of participation that are important to youth, which may not be captured by the existing participatory models.
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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 | 0.103 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.016 | 0.056 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".