Music as Environment: Biological and Ecological Constraints on Coping with the Sounds
Bibliographic record
Abstract
This paper deals with musical sense-making in a real-time listening situation. Revolving around the ecological conception of organism-environment interaction, it elaborates on the interactions between the listener as an organism and the music as environment. The listener, in this view, can be described in terms of coping behavior that is shaped by biological and ecological constraints. Relying on the seminal work by von Uexküll and Gibson in the fields of biosemiotics and ecology, with a special emphasis on the concepts of functional tone and affordance, listeners are defined as organisms that actively seek for information by carrying out physical and epistemic interactions on the sonic environment. As such, they construct an inner model of the sonic world as the sum total of subjective meanings that are assigned to those elements that receive semantic weight. By stressing the role of functional significance and interactions, this approach is on a continuum with the biosemiotic claims that music knowledge must be generated as a tool for adaptation to the sonic world. Musical sense-making, in this view, relies on several levels of processing, going from low-level reactivity to higher-level processing by the brain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".