Experiences of Time and Timelessness in Electroacoustic Music
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".