School-Based Research With Youth: When Protection Leads to Disconnection
Bibliographic record
Abstract
Abstract We explore the relationship between ideal research design and ethical review policies, focusing on how the disconnect between these two integral parts of conducting research impact research in practice. Throughout the process of developing a youth-informed substance resource to be used in public schools in Ontario, Canada, several key themes around ethical considerations emerged. Drawing on research with youth aged 14–18 in Ontario, Canada, as an example, we argue that existing ethics review processes creates barriers to conducting school-based participatory research with youth and adds to the inherent challenge of striking a reasonable balance between protection and participation of children and youth in research. Our experience highlights three key themes surrounding how the ethical approval process distances student contributors from engaging in research: (1) the dual ethics approval processes at researcher institutions and school boards creates substantial delays, (2) existing ethics review processes limit the ability to build and maintain relationships with student contributors and (3) disconnected ethics reviews between researcher institutions and school boards can lead to reshaping of research projects in an effort to continue on with the research for student benefit. Finally, we explore potential avenues for facilitating timely, effective and relevant ethics decisions in this context.
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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 | 0.077 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.040 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".