The many ways of Puerto Rican community music
Bibliographic record
Abstract
For several decades, scholars in the field of community music have largely concentrated on community music practices in the Global North. Such interest has not been as prevalent in certain parts of the world, like the Caribbean. Consequently, this qualitative multiple case study focuses on three Puerto Rican community music initiatives that foster the country’s indigenous music: Bomba, Plena, and Música Campesina. Scholars have documented the evolution and characteristics of these musical traditions. In contrast, this article centers around the practices of Taller Tambuyé, a female-led Bomba organization, Decimanía, a national Música Campesina initiative that funds other community music projects, and La Junta, a community-based project tied to the sector of El Machuchal in the capital of Puerto Rico. This paper presents and analyzes their practices through the lens of Australia’s Sound Links project and its nine domains of community music. The multiple case study methodology’s cross-case analysis revealed notable divergences among the projects in terms of learning practices, promotion of the indigenous music tradition, and the connection between the musical initiative and their community. Additionally, researchers found the framework established by Sound Links to be a comprehensive tool to analyze community music practices outside of Australia.
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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 | 0.001 | 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 | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".