Making Music: Composing With Young Musicians Program Evaluation
Bibliographic record
Abstract
Making Music: Composing with Young Musicians is a research-commissioning project that involves a partnership between the Faculty of Education, University of Ottawa and Curriculum Services, Ottawa-Carleton District School Board (OCDSB). Over a three-year period, 18 new research-based compositions for students enrolled in school music programs were created, studied and premiered in local schools by teachers and their students. The purpose of this presentation is to provide the findings from three focus groups, each representing one of the three years of the Making Music Project. Overall, the participants indicated that the experience was very positive; they appreciated the opportunity for their students to connect with professional composers and they indicated an eagerness to participate in future projects. The major strength of the project was the opportunity for teachers and their students to collaborate with living composers in the creative process, and the major weakness was the composers’ lack of experience composing educational music (a wide-spread problem in Canada). Based on their experience in the project, the teachers indicated that they were more willing to teach music composition in their classes. They noted that the composers were far more involved in the students’ learning process than would normally occur with a standard commissioning program. The teachers also noted that their own involvement shifted towards a facilitating role rather than that of teacher-directed instruction. The project could be improved through better promotion to the schools and a prior meeting with the participants to articulate roles, responsibilities and process.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".