Bibliographic record
Abstract
Presents current analytic views by established scholars of the traditional tonal repertoire, with essays on works by Bach, Handel, Haydn, Mozart, Beethoven, Schubert, Chopin, and Brahms. Outstanding Multi-Authored Collection Award from the Society for Music Theory Bach to Brahms presents current analytic views on the traditional tonal repertoire, with essays on works by Bach, Handel, Haydn, Mozart, Beethoven, Schubert, Chopin, and Brahms. The fifteen essays, written by well-established scholars of this repertoire, are divided into three groups, two of which focus primarily on elements of musical design (formal, metric, and tonal organization) and voice leading at multiple levels of structure. The third groupof essays focuses on musical motives from different perspectives. The result is a volume of integrated studies on the music of the common-practice period, a body of music that remains at the core of modern concert and classroom repertoire. Contributors: Eytan Agmon, David Beach, Charles Burkhart, L. Poundie Burstein, Yosef Goldenberg, Timothy L. Jackson, William Kinderman, Joel Lester, Boyd Pomeroy, John Rink, Frank Samarotto, Lauri Suurpää, Naphtali Wagner, Eric Wen, Channan Willner. David Beach is professor emeritus and former dean of the Faculty of Music, University of Toronto. Yosef Goldenberg teaches at the Hebrew University of Jerusalem and at the Jerusalem Academy of Music and Dance, where he also serves as head librarian.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.085 | 0.026 |
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".