Championing Ethical Engagement of Youth in Healthcare: A Reflective Commentary
Bibliographic record
Abstract
Engaging youth as advisors in health research and service delivery is a rapidly growing practice, yet there are no consistent frameworks or ethical guidelines available to ensure the protection of this vulnerable population from unintended harm. This commentary aims to bring awareness to 3 ethical complexities observed in the authors' own participation within the field of youth engagement in health research and service delivery: (1) a lack of standardized safeguards for youth advisors, (2) a lack of accountability for the safety of youth advisors, and (3) the need to cater engagement activities to the development and well-being of youth. Further, recommendations for meaningfully engaging youth advisors are proposed with the aim of ensuring their safety and enabling opportunities to drive impactful outcomes in health care.
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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 | 0.076 | 0.303 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.037 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.040 | 0.058 |
| Insufficient payload (model declined to judge) | 0.002 | 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".