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Record W4405412697 · doi:10.1080/17459737.2024.2404420

An exercise in formalizing jazz leadsheet structures

2024· article· en· W4405412697 on OpenAlexaff
Graeme Dyck

Bibliographic record

VenueJournal of Mathematics and Music · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsJazzComputer scienceProgramming languageVisual artsArt

Abstract

fetched live from OpenAlex

To analyze traditional jazz music in a way that attends to its idiom and performance practices, I develop two formalizations of jazz leadsheets, while also considering the relationship between sound and algebraic theory it initiates. First, I represent leadsheets as digraphs of chordal movement and articulate a digraph category. Second, I represent leadsheets as strings of chords and develop quotient semigroups on these strings using equivalence relations based on jazz performance practice. I produce a metric for leadsheets from these quotients. Then I apply the two formalizations to a set of twenty jazz standards and consider how the results compare with a listener's experience. I also include two original leadsheets composed to test the formalizations. Though they are grounded in jazz conventions, I conclude these formalizations often do not agree with a listener's perception; I consider what this implies about their construction and the general project of music algebra.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.040
GPT teacher head0.263
Teacher spread0.223 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2024
Admission routes1
Has abstractyes

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