Bibliographic record
Abstract
Abstract This book is an original study of youth organizations in London, Toronto, and Vancouver that represent a burgeoning global sector of creative and cultural learning for socially marginalized young people. The book is also about a sector that is not recognized as such—organizations that do not like being institutionalized, forms of education that exist outside the mainstream, types of aesthetic expression that often go unrecognized, and opportunities for socially marginalized young people who are frequently denied them. Rooted in the history of community arts movements from the 1970s, YouthSites or the non-formal youth arts learning sector is now part of cities throughout the world. Technological change, shifts in educational discourses, changes in policy rhetorics, including a turn away from traditional public institutions, and a corresponding decline in confidence and funding of formal public schooling have all impacted the growth of youth arts organizations. Yet, there are currently no systematic studies of the history, structure, and development of this sector. This book fills this gap and is the first book to develop an internationally comparative, evidence-based, structural analysis of the development of the youth arts sector. Based on an original 4-year study examining the history, priorities, and tensions within this sector between 1995 and 2015, this book explores the new creative transition routes, organizations, and people who help young people become creators, citizens, or just themselves at a time when support for young people seems to be perilously fragile or at risk.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.203 | 0.058 |
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".