Mode and tempo relative contributions to “happy-sad” judgements in equitone melodies
Bibliographic record
Abstract
Judgement of emotion conveyed by music is determined notably by mode (major-minor) and tempo (fast-slow). This suggestion was examined using the same set of equitone melodies, in two experiments. Melodies were presented to nonmusicians who were required to judge whether the melodies sounded "happy" or "sad" on a 10-point scale. In order to assess the specific and relative contributions of mode and tempo to these emotional judgements, the melodies were manipulated so that the only verying characteristic was either the mode or the tempo in two "isolated" conditions. In two further conditions, mode and tempo manipulations were combined so that mode and tempo either converged towards the same emotion (Convergent condition) or suggested opposite emotions (Divergent condition). The results confirm that both mode and tempo determine the "happy-sad" judgements in isolation, with the tempo being more salient, even when tempo salience was adjusted. The findings further support the view that, in music, structural features that are emotionally meaningful are easy to isolate, and that music is an effective and reliable medium to study emotions.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".