Toward a Useful Synthesis of Deweyan Pragmatism\nand Music Education
Bibliographic record
Abstract
The purpose of this work is to explore the possibility of incorporating pragmatism into music education. The paper discusses John Dewey’s pragmatism and analyzes the interpretations and influences of Deweyan pragmatism in music education with the help of interview responses of scholars worldwide. Finally, it seeks specific answers as to how Deweyan pragmatism can help the transformation of music education, particularly of music teacher education. The historical information was obtained through a close analysis and reviewing of Dewey’s writings, as well as other educational scholars’ writings on Dewey’s pragmatism. After gaining a personal insight and understanding how much Dewey’s pragmatism and specific notions (such as experience and democracy) have influenced the field of education and music education, several well-known music professors and philosophical scholars in the field of music education and philosophy from the United States, Canada, and Finland were asked to respond to interview questions. As the review of literature and interview analysis showed, current music educators, writers, and thinkers have not exhausted the study of pragmatism. Dewey’s ideas offer great potential to expand the abilities and possibilities of music education for social change. They can also be used as a guide to understand the complexity of postmodern society and its institutions. A more comprehensive construction of a Deweyan music education might be proposed to further philosophical studies.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.019 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".