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Record W1991695039 · doi:10.7202/1014309ar

Learning the Koto

2013· article· en· W1991695039 on OpenAlexvenueno aff
Patrick Halliwell

Bibliographic record

VenueCanadian University Music Review · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsImitationMusicalInterpretation (philosophy)Musical notationRelation (database)Representation (politics)NotationPhraseLinguisticsTeaching methodMusic theoryMusic educationPsychologyCommunicationVisual artsComputer scienceArtMathematics educationPedagogySocial psychology

Abstract

fetched live from OpenAlex

This paper examines traditionally-oriented teaching and learning processes in Japanese koto music. Earlier evaluations (negative and positive) by Western scholars are introduced, together with a brief comparison to Western practices. A distinction is made between "inside" and "outside" students; the former have greater exposure to music and speech about music, and teaching methods also may differ. Traditional methods of learning through imitation are shown to have other musical goals besides the transmission of musical "text." Playing together is fundamental; teachers may use speech, shôga (oral representation of instrumental sound), or purely musical means to convey information to the student. Notation, often used nowadays, is nevertheless of relatively minor importance. The dominant values underlying traditional teaching methods are expressed through the phrase "if you can steal it, that's OK." Finally, concepts of "text" and "interpretation" are considered in relation to values concerning change in traditional koto music.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.338
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1080.008

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 head0.050
GPT teacher head0.188
Teacher spread0.138 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2013
Admission routes1
Has abstractyes

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