Youth Voices: Evaluation of Participatory Action Research
Bibliographic record
Abstract
Abstract: When conducted with sensitivity and reflexivity, participatory action research (PAR) can be an empowering process that is particularly relevant for engaging young people in reflection and dialogue for social change. As the theory and practice of PAR evolve, researchers have evaluated the experiences of community participants, using both qualitative and quantitative approaches. However, only a limited number of evaluations have focused on PAR processes undertaken with youth, and few published papers have reported on involving youth in the evaluation. This article addresses the process of enabling youth to participate to their fullest ability in an evaluation of a PAR project called Youth Voices. The analysis draws on feedback questionnaires from community evaluators, minutes and notes from team meetings, and the researchers’ experiences and observations. The authors reflect on lessons learned that can be helpful to others considering participatory evaluation research with youth. The study revealed limitations in employing participatory evaluation with at-risk youth, including challenges posed by their psychosocial development and maintaining participants’ engagement throughout the processes of participatory evaluation. These lessons shed light on key tensions in using participatory evaluation and challenge the implicit assumption that a higher level of participation is necessarily better when working with youth. A central question is posed: What level of participation is optimal to ensure authentic community decision-making in a PAR project without overwhelming youth participants?
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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 | 0.267 | 0.253 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".