Facing power: navigating power dynamics in a youth participatory action research project situated within a healthcare setting
Bibliographic record
Abstract
Youth Participatory Action Research (YPAR) is oftentimes cited as a method guided by social justice principles to uplift youth voice and pursue youth priorities in research. However, to uphold these principles, YPAR researchers must address how youth and adults alike negotiate power differentials to be equal partners in research and scholarship. We explore YPAR power sharing through a reflexive thematic analysis of in-depth, semi-structured interviews (n= 42) and focus groups (n=2) conducted at three timepoints (baseline, mid-point, and exit) with youth (n=8) and adult (n=6) researchers engaged in a YPAR exploring health equity at a large, safety-net hospital. Our analyses suggest that both youth and adult researchers negotiate power dynamics in a YPAR at every stage of the project. YPAR researchers made four recommendations to negotiate power: 1) preserve time for relationship building, 2) structure group expectations, 3) require training for adults working with youth of color, and 4) designate youth-only spaces. This study provides an in-depth analysis of youth and adult reflections on power across a YPAR project. Our findings indicate that YPAR requires significant investment in resources, including time to reflect on and process power, transparent and structured expectations, and ongoing training to uphold principles of YPAR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.065 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".