A performance guide: new cello compositions by Serra Miyeun Hwang
Bibliographic record
Abstract
Korean Canadian composer Serra Miyeun Hwang (1962-) has written three compositions for cello- Beckoning, Presence, and Hundredth View- inspired by Korean culture and traditional music. She infuses each piece with Korean elements, including special rhythmic patterns, text, and tone color, which are influenced and motivated by traditional Korean percussion music, religions, culture, combined with techniques of Western instrumental performance. The purpose of this study is to introduce Hwang’s music to other cellists and help them incorporate the historical and cultural aspects of Korean traditional music to their performance practices. By analyzing Hwang’s compositions in greater detail, this essay will provide cellists practice guidelines to achieve the desired tone and interpretive gestures of new cello repertoire.\nThis essay contains Hwang’s biography and her philosophy of music and a description of the Korean influences on her music, including the genres of traditional music in Korea, their cultural background, music in Shaman ceremonies, Buddhist music, and p’ungmul (folk drumming and dance). There is also a performance guide of Beckoning for Cello and two Korean Drums; Presence for Soprano, Cello, and Piano; and Hundredth View for Solo Cello with my own interpretation.\nLearning Hwang’s pieces will bring cellists new experiences that are a mixture of music, culture, thoughts, and methods from Western and Eastern influences.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".