Effects of metrical dissonance and expertise on perceived emotion in Schumann’s <i>Carnaval</i>
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Bibliographic record
Abstract
Numerous studies have investigated the effects of pitch structures on perceived emotion in music, but the emotional effects of rhythm and meter have received far less attention. In the experiment reported here, we manipulated the metrical framework of music by Robert Schumann and asked participants to judge perceived emotion in the resulting excerpts. The distinction between metrical dissonance and consonance offered by Harald Krebs (1999) was the theoretical basis of this study. Stimuli were 10 metrically dissonant excerpts from Schumann’s Carnaval and 10 metrically consonant recompositions of these excerpts. Recompositions maintained original tempi, global meters, and harmonic frameworks. Participants—graduate-level pianists and non-musicians—heard all 20 excerpts in randomized order. On each trial, they chose a cluster of emotion words, based on Schubert (2003), that best described the excerpt, a cluster that worst described the excerpt, and rated their level of interest. Results indicate significant effects of both metrical character and expertise on perceived emotion. There were also significant differences in the likelihood of participants changing their responses between metrically dissonant and consonant versions as a function of musical excerpt. This last finding leads to suggestions for future investigations on degrees of metrical dissonance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it