Breaking with common practice: Exploring modernist musical emotion
Bibliographic record
Abstract
Experimental research on musical emotion has identified clear links between specific aspects of musical structure and emotional responses. However, growing recognition of changes in the affective meaning of specific cues over time raises intriguing questions about the degree to which these links hold across historical eras. In particular, the traditional focus on compositional principles from common-practice period music (ca. 1600-1900) might not capture how emotion is perceived in later compositions. Here we explore perceived emotion ratings in a set of 24 preludes by Dmitri Shostakovich (Op. 34), comparing the effects of cues in his preludes vs. those by Bach and Chopin. We find that prosodic cues (i.e., pitch height, timing) play a stronger role than mode in these pieces. Because music theorists widely recognize Shostakovich's music as tonal, this result reflects not his abandonment of mode, but rather his decision to use it differently than his predecessors. This provides an important perspective complementing a growing body of research using score-based analyses to explore historical changes in the "meaning" of specific cues. Our findings illustrate how modern compositions can provide novel insight into cues' historically changing roles in emotional communication.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".