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Record W582199029

The control of acoustic intensity during jazz and free improvisation performance : possible transcultural implications for social discourse and community

2010· article· en· W582199029 on OpenAlexvenueno aff
Roger T. Dean, Freya Bailes

Bibliographic record

VenueCritical Studies in Improvisation / Études critiques en improvisation · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsnot available
Fundersnot available
KeywordsImprovisationSound intensityIntensity (physics)JazzRange (aeronautics)AcousticsLinguisticsPsychologyEngineeringPhysicsSound (geography)Philosophy
DOInot available

Abstract

fetched live from OpenAlex

This paper demonstrates the predominance of a pattern of acoustic intensity change in recorded improvisations in which intensity rises are shorter than falls and in which the rate of intensity change is greater in the rises than in the falls. A wide range of improvised music from the USA, Europe, and Australasia is studied, and the analyses are conducted by measuring intensity in moving windows across each piece. The windows used are 0.04 sec, 0.5 sec, 5 sec, and 10 sec, chosen to sample a range of important musical structures such as patterns, phrases, and phrase groups. In addition, a comparative analysis uses detected rhythmic beats as the window, with slightly variable lengths. The recurrent pattern is interpreted in terms of a hypothesised Force-Effort-Energy-Loudness-Affect (FEELA) chain, linking improviser with listeners and with other improvisers. Partial experimental investigation of this chain in other work has been consistent with the theory in supporting a major role of acoustic intensity in the perception of both musical change and affect. It seems that improvisers share this patterning of acoustic intensity with interpreters of classical music, and composers of electroacoustic music. Thus we suggest that music made with non-acoustic instruments—that is those for which physical effort of performers does not provide the energy comprised in a sound— has developed the same pattern because composers and improvisers recognise its expressive power as a statistical archetype. Improvisers are particularly salient to this argument because they are not necessarily constrained by any of the prior conventions of music. It remains to be seen whether this statistical feature could have been assimilated from environmental and/or speech sounds. Given that the studied music flows within both the Afro-logic and Eurologic discourses delineated by George Lewis, we discuss the possible trans-cultural implications of our observations for social discourse and community.

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)0.001
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.084
GPT teacher head0.393
Teacher spread0.309 · 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 designBench or experimental
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

Citations3
Published2010
Admission routes1
Has abstractyes

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