Keys to the Future: A Study of Undergraduate Piano Education
Bibliographic record
Abstract
abstract: Classical pianists have struggled to reconcile personal artistic growth with the economic and cultural realities of a career as a musician. This paper explores the existing structure of North American undergraduate piano education and its development alongside sociological and cultural changes in the twentieth century. Through document study and interviews, I look at three different models of undergraduate piano curricula. Chapters One and Two explore the issues and history surrounding the traditional piano curriculum. Chapters Three and Four draw on interviews to study two different North American undergraduate curricula: a piano curriculum within a liberal arts environment of an American Conservatory-College, and a piano curriculum within a Canadian University Faculty of Music. Chapter Five concludes with a summary of these findings and potential recommendations for implementation. In this study, I suggest that changes to piano curricula were made because of a differing approach, one in which music is seen as an entrepreneurial vocation. These changes point to a discrepancy between what is being provided in the curriculum, and the actual skills that are needed in order to thrive in today's economy. Awareness of the constant flux of the current professional climate is necessary in order for pianists to channel their skills into the world. I theorize that changes in curricula were made in order to provide a better bridge for students to meet realistic demands in their career and increase their ability to impact the community.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".