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Metrical Displacement and Group Interaction in ‘Evidence’ by the Thelonious Monk Quartet

2021· book-chapter· en· W4200458817 on OpenAlexaff
Ryan D. W. Bruce

Bibliographic record

VenueOxford University Press eBooks · 2021
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsDisplacement (psychology)Group (periodic table)MathematicsPhysicsPsychologyPsychoanalysisQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract Jazz pianist Thelonious Monk is known for his rhythmically complex compositions and improvisations. His typical 32-bar AABA form pieces provide a framework of musical norms in terms of harmonic movement, and thus a point of reference for the harmonic rhythm to be displaced. ‘Evidence’ is exemplary of Monk’s displaced rhythms, which creates a sense of metrical shifts during the head arrangement. Composed c.1948 and a frequent piece of Monk’s performance repertoire into the 1970s, a transcription and analysis of the recording from Thelonious Monk Quartet Plus Two at the Blackhawk demonstrates a conflicting sense of metre between band members of the quartet. This chapter investigates how the musicians negotiated metrical discrepancies in the composed section and the saxophone solo in terms of group interaction. A mediation of time is demonstrated by a displaced metre in the drums and each musician’s performative response to the discrepancy by providing musical signals during the course of performance. Through analysis of this performance, the chapter examines the way in which the musicians arbitrated a decisive point of reference within a confounding performance of overturning the beat. This chapter contributes to understanding rhythm and metre through improvisatory processes, augmenting scholarship on jazz through its analysis of the temporal constituents of group interaction.

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)0.002
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.014
Scholarly communication0.0060.003
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.049
GPT teacher head0.218
Teacher spread0.169 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueOxford University Press eBooksSame topicMusicology and Musical AnalysisFrench-language works237,207