Tasting Physical Expression: A Sensorial and Cultural Analysis of the Notion of Rasa in Classical Indian Dance
Bibliographic record
Abstract
This dissertation is a detailed study of the notion of “rasa,” a Sanskrit term that translates as “juice,” “essence,” or, in the performing arts, “aesthetic delight.” The research has two goals: (1) to determine what rasa means within Indian neo-classical dance, especially in Eastern Canada (Quebec and Ontario), by contrasting the classical theory of rasa to its present actualization in the performing arts through foundational moods and emotions (erotic love, mirth, repugnance, terror and so on); (2) to provide a more complex understanding of the senses and emotions in Indian society and beyond through a sensory and affective anthropological analysis of rasa. Data for this project was collected from interviews with Montreal- and Toronto-based professional Bharatanatyam and Odissi dancers as well as participant sensation in India and Canada. The data was complemented by the study of (translated) Sanskrit theory on rasa (Natyashastra, Abhinaya Darpana, works of theorists Anandavardhana, Abhinavagupta, Bhojaraja, Rupa and Jiva Goswamin, etc.). \n \nThe research shows that rasa, understood as an experience in the viewer, is not limited to the expert spectator (rasika) as classical theory would have it, but rather expands to the performer and emerges out of the relationship that is built between dancer and audience (including uninitiated spectators). Rasa, in fact, is an aesthetic experience that can be learned by performers and spectators—a process coined as “rasik literacy.” Spectators develop their rasik literacy through the exposure to the aesthetics of Indian performing arts via visual, imaginative, aural and aesthetic savouring. In addition to these, dancers acquire theirs through internal perception such as kinaesthesia, proprioception, equilibroception, (embodied) rhythm and flow, thus forming body memories that are eventually associated with the emotional hues of rasa. Hence, rasa is a rich emotional, sensorial and aesthetic concept that greatly enriches the field of sensory anthropology and demonstrates the inadequacy of the mind-body opposition in the study of cultures. As an “embodied thought” (Michelle Z. Rosaldo), this concept also expands the understanding of the aesthetics reception of emotions in the performing arts by inviting spectators and artists to taste performances, rather than just looking or listening to them.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".