Bibliographic record
Abstract
William Allaudin Mathieu (born in 1937) is a consummate musician, a pianist, composer, author, and teacher — and, in my view, one of the most influential musicians of his generation. In his early twenties he composed music for the Kenton and Ellington Big Bands, was the founding musical director of the famed Second City of Chicago (Improv Theater) and was a pioneer in the 1960s of the application of theater improvisation games into the musical sphere. He is the author of four influential books, including the best selling "The Listening Book" (1991). In a teaching career spanning more than fifty years, Mathieu has been an important influence and guide to many musicians worldwide. As I demonstrate throughout this essay, W.A. Mathieu reminds us that in highlighting the world of improvisation we must be careful not to romanticize spontaneity, for doing so might well involve our falling into the trap of dualistic thinking that separates if not excludes such activity from composition. Overall, Mathieu implores us to reflect deeply about false dichotomies as improvisation/composition, and by extension think more broadly about the perils of dualistic thinking in general. In exploring themes in discussion of improvisation, I highlight some of the ways in which we can begin to draw connections between Mathieu’s ideas and the usefulness of improvisation to pedagogy in music education and beyond.
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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 | 0.002 | 0.006 |
| 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 | 0.026 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".