The experience of youth-participatory action research in a social innovation lab: A methodological and organizational approach
Bibliographic record
Abstract
Based on the theory and quality criteria of Youth-Participatory Action Research (Y-PAR), youth and adult co-researchers at a social innovation lab in Ontario, Canada, have undertaken various knowledge generation and action activities for the purpose of supporting youth mental health and wellbeing among transitional-age youth (ages 16–25). We describe the methodological and organizational approach employed in this undertaking, including aspects of the social innovation model to support the action components of Y-PAR. We draw on Bradbury-Huang’s (2010) seven choice points for quality in action research to structure this collective reflection. Our experiences illustrate the tensions and opportunities arising from housing a Y-PAR project within a large health services institution. We also note how social innovation lab processes can support the emancipatory aims of participatory research. Implications for using Y-PAR in other areas are included.
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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 | 0.122 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.032 | 0.071 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.005 | 0.032 |
| Research integrity | 0.005 | 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".