Building Bridges through Music: A Recording and Performance Collaboration with Adult Composers, Young Soloists, and Collegiate Band Accompaniment
Bibliographic record
Abstract
abstract: Although music is regarded as a universal language, it is rare to find musicians of different ages, ability levels, and backgrounds interacting with each other in collaborative performances. There is a dearth of mixed-ability-level wind band and string orchestra repertoire, and the few pieces that exist fail to celebrate the talents of the youngest and least-experienced performers. Composers writing music for school-age ensembles have also been excluded from the collaborative process, rarely communicating with the young musicians for whom they are writing. \n\nThis project introduced twenty-nine compositions into the wind band and string orchestra repertoire via a collaboration that engaged multiple constituencies. Students of wind and string instruments from Phoenix’s El Sistema-inspired Harmony Project and the Tijuana-based Niños de La Guadalupana Villa Del Campo worked together with students at Arizona State University and composers from Canada, Finland, and across the United States to learn and record concertos for novice-level soloists with intermediate-level accompaniment ensembles. \n\nThis project was influenced by the intergenerational ensembles common in Finnish music institutes. The author provides a document which includes a survey of the existing concerto repertoire for wind bands and previous intergenerational and multicultural studies in the field of music. The author then presents each of the mixed-ability concertos created and recorded in this project and offers biographical information on the composers. Finally, the author reflects upon qualitative surveys completed by the project’s participants. \n\nMost the new concertos are available to the public. This music can be useful in the development and implementation of similar collaborations of musicians of all ages and abilities.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".