Expressive Timing or Thematic Transformation? Onset Displacement in Performances of Jazz Standard Melodies
Bibliographic record
Abstract
The rhythms of jazz standard melodies are inherently flexible prototypes that are brought to life by jazz musicians using a variety of expressive transformations. I argue that these transformations fall under two closely related categories. The first, expressive timing, involves displacements of onsets that are so small—usually in the order of milliseconds—that they do not constitute a change in metric-hierarchic position; they fall below the level of syntax. Conversely, thematic transformation often involves displacing notes to a different metric position. In this paper, I contend that expressive timing and thematic transformation represent interrelated improvisational processes that are coordinated in performances of jazz standards. I connect these techniques to recent work on jazz ontology and referents, arguing that the ambiguous relationships between these transformational categories is the result of the ontological flexibility of jazz tune melodies. I ultimately argue that both techniques become involved in an ongoing give-and-take as the improvisational process unfolds.
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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 | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".