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Record W4394909143 · doi:10.32370/ia_2024_01_10

Two Axioms of European Classical Music and Maximum Number of Polytonalities in Music

2024· article· en· W4394909143 on OpenAlexvenueno aff
Mark Zilberman

Bibliographic record

VenueIntellectual Archive · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMathematicsAxiomClassical musicArtLiteratureGeometryMusical

Abstract

fetched live from OpenAlex

Article formulates two axioms of European classical music “Every musical piece should be within 24 tonalities, specifically 12 major and 12 minor tonalities, with some temporary slight variations allowed” and "Every musical piece should be written so that all instruments play in the same tonality at any given moment." These axioms stayed unchallenged until the approximately end of 19th century. First axiom was challenged by impressionists’ composers Claude Debussy, Maurice Ravel and other at the end of 19 century and later in the first half of 20 century by atonal, twelve-tone and other kinds of musical systems created by Arnold Schoenberg, Alban Berg, Anton Webern and other. The second axiom was challenged by creation of polytonal music. One of the early examples of polytonality can be found in the ballet of Igor Stravinsky "The Rite of Spring" (1913), where different instruments play in different keys simultaneously. Another influential figure in the development of polytonality was the French composer Charles Ives. The use of polytonal technique raised the theoretical question of how rich a contemporary composer's palette can be when the single-tonality axiom is set aside. In other words, what is the theoretical maximum number of tonalities that a composer can explore within a polytonality approach? Simple calculations show that total palette of polytonal music contains 24*23*22*21*…*1=24! (twenty-four factorial) or 620,448,401,733,239,439,360,000 of theoretically available combinations of tonalities. While obviously most of these combinations will result in cacophony, some tonal combinations have the potential to yield fresh and pleasant impressions that have not been explored in the past. If we consider the complete list of 9 modes per note (Major, Natural Minor, Harmonic Minor, Melodic Minor, Dorian mode, Phrygian mode, Lydian mode, Mixolydian mode, Locrian mode), we obtain 12 notes * 9 modes = 108 base tonalities/modes. Correspondingly in that case use of polytonalities produces 108! (108 factorial) combinations of tonalities/modes. This number appears as the theoretical upper limit of tonal palette in polytonality approach.

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 score0.456
Threshold uncertainty score0.989

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.041
GPT teacher head0.257
Teacher spread0.216 · 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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