Instrumental Agency and the Co-Production of Sound: From South Asian Instruments to Interactive Systems
Bibliographic record
Abstract
In this paper, we will look at sympathetic resonance as seen in South Asian instruments as a source of complex performer-instrument interaction. In particular, we will compare this rich tradition to the various types of human/machine interactions that arise in digital instruments endowed with computational agency. In reflecting on the spectrum of agency that exists between the extremes of instrumental performance and machine partnership, we will arrive at two concepts to help frame our study of complex interactions in acoustic instruments: the co-production of sound and material agency. As a case study, we asked musicians of these South Asian instruments questions about their perceived relationship with their sympathetic strings. Building upon this, we designed and created an interactive system that models the phenomenon of performing with sympathetic strings. We then asked musicians to interact with this new system and answer questions based on this experience. The results of these sessions were examined both to uncover any similarities between the two sets of interviews,and to situate this entangled performer-instrument interaction with respect to markers of perceived control, influence, co-creation, and agency.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".