Exploring Changes in the Emotional Classification of Music between Eras
Bibliographic record
Abstract
Prior work has noted changes in musical cue use between the Classical and Romantic periods. Here we complement and extend musicological findings by blending score-based analyses with perceptual evaluations to provide new insight into this important issue. Participants listened to excerpts from either Bach’s The Well-Tempered Clavier or Chopin’s 24 Preludes – historically important sets drawn from distinct musical eras, with 12 major and 12 minor key pieces each. Participants selected one of five categories for each piece, adapted from previous musical analyses exploring historical changes in music’s cues. Combining participant classifications with score-extracted cues offers a useful way to complement and extend previous work exploring changes in the function of mode across musical eras based only on notational information. In doing so, we find evidence that changing associations of cues in the Romantic era influence judgments of affective meaning. This study provides a useful step toward bridging the divide between traditional approaches to musicology, music theory, and music perception by combining perceptual evaluations with cues extracted from musical scores to shed light on changes in musical emotion across eras.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".