Eliciting awe in the spectator: The case of a Dhrupad-based dance performance
Bibliographic record
Abstract
This paper describes “Kalos, eîdos, skopeîn,” an immersive Dhrupad-based dance installation designed to elicit feelings of awe in the spectators, in a real-life artistic context. This study used a mixed-methods approach in order to explore spectators’ awe experience (N=45), using specific scales and interpretative phenomenological analysis. Results suggested that “Kalos, eîdos, skopeîn,” with its combination of nature motifs and the slow dance-walk associated with the Dhrupad music in the choreography, was able to produce awe-related moments in some spectators and inspire a degree of positive emotions. Our qualitative results viewed awe explicitly as a positive emotion and showed that generally the spectator narratives, involving the whole performance, were based on modified states of consciousness. Three themes emerged: the main theme is “A rich experience of modified states of consciousness” involving the whole performance, and two interconnected sub-themes “Captivated by the slowness of the dancers” associated with the slow movement and “I can still hear the mantra in my head” in rapport with Dhrupad music. This study was carried out as part of the Canadian FRQSC/FCI Project (2019-RC2-260306).
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".