Individual Differences in Music-Perceived Emotions
Why this work is in the frame
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Bibliographic record
Abstract
Previous music and emotion research suggests that individual differences in empathy, alexithymia, personality traits, and musical expertise might play a role in music-perceived emotions. In this study, we investigated the relationship between these individual characteristics and the ability of participants to recognize five basic emotions (happiness, sadness, tenderness, fear, and anger) conveyed by validated excerpts of film music. One hundred and twenty participants were recruited through an online platform and completed an emotion recognition task as well as the IRI (Interpersonal Reactivity Index), TAS-20 (Toronto Alexithymia Scale), BFI (Big Five Inventory), and Gold-MSI (Goldsmiths Musical Sophistication Index). While participants recognized the emotions depicted by the music at levels that were better than chance, their performance accuracy was negatively associated with the externally oriented thinking subscale from the TAS-20. Our results suggest that alexithymia, previously linked to a deficit in perception of facial and vocal expressions of emotion, is also associated with difficulties in perception of emotions conveyed by music.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it