Understanding Human Emotion: An Intervention of Anger through Raudra Rasa in Dina Mehta’s Drama Brides Are Not for Burning
Bibliographic record
Abstract
Anger is the main propaganda of this study. This study aims to explore the intervention of anger through the aesthetic concept of Raudra rasa in Dina Mehta's drama, "Brides Are Not for Burning." Emotions play a significant role in human experiences, and anger, in particular, has been the subject of extensive research. Drawing upon traditional Indian aesthetics and performing arts, Raudra rasa represents a complex emotional state of anger, rage, or ferocity. By examining its portrayal and impact in Mehta's drama, this study seeks to enhance our understanding of the role of Raudra rasa in evoking and managing anger. Utilizing a descriptive qualitative method, this study employs how Raudra rasa is embodied and expressed by the character. By delving into the intervention of anger through Raudra rasa in the play, this study contributes to the existing knowledge on the interplay between emotions, art, and human experiences.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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 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".