<i>Ambiguous Devices</i>: Improvisation, agency, touch and feedthrough in distributed music performance
Bibliographic record
Abstract
This article documents the processes behind our distributed musical instrument,Ambiguous Devices. The project is motivated by our mutual desire to explore disruptive forms of networked musical interactions in an attempt to challenge and extend our practices as improvisers and instrument makers. We begin by describing the early design stage of our performance ecosystem, followed by a technical description of how the system functions with examples from our public performances and installations. We then situate our work within a genealogy of human–machine improvisation, while highlighting specific values that continue to motivate our artistic approach. These practical accounts inform our discussion of tactility, proximity, effort, friction and other attributes that have shaped our strategies for designing musical interactions. The positive role of ambiguity is elaborated in relation to distributed agency. Finally, we employ the concept of ‘feedthrough’ as a way of understanding the co-constitutive behaviour of communication networks, assemblages and performers.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".