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Record W2890608473 · doi:10.12794/metadc1157533

Traditional Korean Music in Contemporary Context: A Performance Guide to Gideon Gee Bum Kim's Kangkangsullae

2018· dissertation· en· W2890608473 on OpenAlexaboutno aff
Hyejin Lee

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicAsian Culture and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeeContext (archaeology)HistoryArtSociologyVisual artsMathematicsArchaeologyStatisticsGeneralized estimating equation

Abstract

fetched live from OpenAlex

Gideon Gee Bum Kim is an internationally-acclaimed contemporary Korean-Canadian composer. Kim has utilized traditional Korean music with Western composition techniques in some of his works. Kim created his own style by incorporating traditional Korean musical elements such as the scale, rhythmic diversity, syncopation, variation, ornamentation, and the progression of melody into a body of music that is otherwise contemporary and Western. The purpose of this study is to develop a performance guide for Gideon Gee Bum Kim's Kangkangsullae for string trio. Kangkangsullae trio is based on Korean historical, cultural and musical influences. I give a detailed historical and cultural background for this work and demonstrate how Kim integrated Western compositional techniques with traditional Korean music. My emphasis is on defining specific characteristics of traditional Korean music which will provide several points toward understanding Kim's compositional style.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.003

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.

Opus teacher head0.066
GPT teacher head0.327
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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