Working<i>with</i>and engaging<i>in</i>recreation and sport research with youth who live on the margins
Bibliographic record
Abstract
Working collaboratively with youth who live on the margins in recreation and sport research provides unique opportunities and challenges for both participants and researchers. This paper aims to highlight methodological challenges from a recent collaborative sport and recreation research project with youth in a Western Canadian city. Guided by key principles of youth-led participatory action research (YPAR), we discuss challenges with (a) power-sharing and mutual respect, (b) development of meaningful connections, and (c) facilitating space for youth voice. Our intent is not to offer simple, all-encompassing solutions to such challenges, but to outline the processes of how our team negotiated such challenges. The insights gained through our work may provide practical tools for researchers and community members interested in working with and engaging in research with youth at risk to address social injustices.
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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 | 0.023 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.023 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.002 | 0.004 |
| 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".