Aesthetic Expressions in Deudā Song Lyrics: An Analysis of Shreengār and Karuṇa Rasas
Bibliographic record
Abstract
In recent years, many authors have shed light on the hidden world of folklore, particularly on folk songs seeking to re-envision the practices of the traditional society. This research on a folk song of Far Western Nepal i.e. Ḍeuḍā holds special promise for analyzing it in the light of Rasa theory; a theory about aesthetic flavor in arts that evokes emotions and feelings of the readers. The study reflects upon the theory of rasa and attempts to make an assessment of it in relation to the Deudā song that adopts qualitative research method, using observations and interviews as data collections tools. The main intention of this study is to see how the song lets out the common emotions (rasas) of the people dwelling in Far Western Nepal. It examines how different forms of rasa function in various Deudā songs. A particular emphasis is placed on analyzing the songs in terms of Shreeṅgār and Karuṇa rasas. The findings of the study reveal that the Deudā song is loaded with the feeling of the throbbing hearts of the people of the region with their emotions of pain, pathos, suffering, misery, hardships, compassion, mercy, love and romance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".