Solutions to the “Great Nineteenth-Century Rhythm Problem” in Horowitz’s Recording of the Theme from Schumann’s<i>Kreisleriana</i>, Op. 16, No. 2
Bibliographic record
Abstract
This case study on the interpretation of microtiming is framed by the hypothesis that the avoidance of monotony in the case of highly regular phrase/hypermetric structures was not only one of the great compositional problems of the nineteenth century, as William Rothstein has proposed, but also was and remains a problem for performers. This analytical strategy helps to organize and synthesize diverse observations about a complex set of subtle microtiming practices in the titular recording. It is shown that Horowitz introduces subtle variations when materials are repeated, and that he tends to bring out the most salient aspects of Schumann’s own solutions to the “rhythm problem” (metric tensions, contrasts in rhythmic shape), except in cases of phrase linkage. This study suggests that principles of phrase rhythm could make a valuable contribution to the analytical toolbox for performance studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".