Classical Rondos and Sonatas as Stylistic Categories
Bibliographic record
Abstract
Sonata and rondo movements are often defined in terms of large-scale form, yet in the classical era, rondos were also identified according to their lively, cheerful character. We hypothesized that sonatas and rondos could be categorized based on stylistic features, and that rondos would involve more acoustic cues for happiness (e.g., higher average pitch height and higher average attack rate). In a corpus analysis, we examined paired movement openings from 180 instrumental works, composed between 1770 and 1799. Rondos had significantly higher pitch height and attack rate, as predicted, and there were also significant differences related to dynamics, meter, and cadences. We then conducted an experiment involving participants with at least 5 years of formal music training or less than 6 months of formal music training. Participants listened to 120 15-second audio clips, taken from the beginnings of movements in our corpus. After a training phase, they attempted to categorize the excerpts (2AFC task). D-prime scores were significantly higher than chance levels for both groups, and in post-experiment questionnaires, participants without music training reported that rondos sounded happier than sonatas. Overall, these results suggest that classical formal types have distinct stylistic and affective conventions.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".