Youth-led community arts hubs: Self-determined learning in an out-of-school time (OST) program
Bibliographic record
Abstract
This article reports findings from qualitative case studies of three youth-led community arts hubs, a program that is rooted in, and utilizes a self-determined learning approach. Qualitative case studies of three program sites sought to generate meaningful data that could lead to rapid ongoing program development and inform the development and delivery of new program sites. Multiple lines of inquiry were utilized, including observations, and focus groups at all three program sites were designed to gather outcomes and demographic data from participating youth, as well as interviews with program staff. Findings indicate that the program is more successful engaging youth when using primarily self-directed and youth-led approaches to learning and program delivery when compared to adult-driven and more structured activities. The findings of these qualitative case studies also hint at the program having a positive impact on participating youth, helping them build confidence, and strengthening their artistic abilities. Recommendations include promoting informal peer learning and mentoring to further self-directed learning opportunities, as well as operating the hubs during the summer months.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".