Bibliographic record
Abstract
Most of us can recall chuckling, or even laughing out loud, at a humorous musical passage and perhaps recalling how much that experience increased our enjoyment of the music. This article focuses on musical humor in passages from instrumental works by Joseph Haydn, Michael Haydn, and Mozart. In the most general sense, musical humor arises when composers play with established conventions of musical discourse by writing something incongruous according to the stylistic context. I begin by briefly discussing the role of contrast in establishing musical humor in both historical and modern writings. I then introduce a strategy by which Classical composers created musical humor. I call this strategy “script opposition,” following linguistic theories of verbal humor. In my analytical discussion, I explain how “valence shifts” between implications of “high” and “low” create script oppositions, and demonstrate how these valence shifts are produced primarily by musical topics, but are bolstered by formal functions and cues in other musical parameters. My analytical and theoretical approach to musical humor draws on recent studies of musical topics, form, and communication in the Classical style, as well as concepts from recent linguistic theories of verbal humor.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".