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Record W3048362613 · doi:10.1017/s135577182000014x

Experiences of Time and Timelessness in Electroacoustic Music

2020· article· en· W3048362613 on OpenAlexaff
Jason Noble, Tanor Bonin, Stephen McAdams

Bibliographic record

VenueOrganised Sound · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcGill University
Fundersnot available
KeywordsElectroacoustic musicPerceptionMusicalTime perceptionActive listeningContext (archaeology)Cognitive psychologyPsychologyAestheticsCognitive scienceRepetition (rhetorical device)Duration (music)Computer scienceMusic psychologyCommunicationArtHistoryVisual artsLinguisticsLiteraturePhilosophyNeuroscience

Abstract

fetched live from OpenAlex

Electroacoustic music and its historical antecedents open up new ways of thinking about musical time. Whereas music performed by humans is necessarily constrained by certain temporal limits that define human information processing and embodiment, machines are capable of producing sound with scales and structures of time that reach potentially very far outside of these human limitations. But even musics produced with superhuman means are still subject to human constraints in music perception and cognition. Focusing on five principles of auditory perception – segmentation, grouping, pulse, metre and repetition – we hypothesise that musics that exceed or subvert the thresholds that define ‘human time’ are likely to be recognised by listeners as expressing timelessness. To support this hypothesis, we report an experiment in which a listening panel reviewed excerpts of electroacoustic music selected for their temporally subversive or excessive properties, and rated them (1) for the pace of time they express (normative, speeding up, or slowing down), and (2) for whether or not the music expresses ‘timelessness’. We find that while the specific musical parameters associated with temporal phenomenology vary from one musical context to the next, a general trend obtains across musical contexts through the excess or subversion of a particular perceptual constraint by a given musical parameter on the one hand, and the subjective experiences of time and timelessness on the other.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.030
GPT teacher head0.245
Teacher spread0.215 · 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 designQualitative
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

Citations14
Published2020
Admission routes1
Has abstractyes

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