Dancing to “groovy” music enhances the experience of flow
Bibliographic record
Abstract
We investigated whether dancing influences the emotional response to music, compared to when music is listened to in the absence of movement. Forty participants without previous dance training listened to "groovy" and "nongroovy" music excerpts while either dancing or refraining from movement. Participants were also tested while imitating their own dance movements, but in the absence of music as a control condition. Emotion ratings and ratings of flow were collected following each condition. Dance movements were recorded using motion capture. We found that the state of flow was increased specifically during spontaneous dance to groovy excerpts, compared with both still listening and motor imitation. Emotions in the realms of vitality (such as joy and power) and sublimity (such as wonder and nostalgia) were evoked by music in general, whether participants moved or not. Significant correlations were found between the emotional and flow responses to music and whole-body acceleration profiles. Thus, the results highlight a distinct state of flow when dancing, which may be of use to promote well-being and to address certain clinical conditions.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".