The disconnected keyboard: Inclusive learning and musicking practice with modular synthesis
Bibliographic record
Abstract
Since the 1960s, electronic sound synthesis and the keyboard interface have been so closely associated that many young musicians have come to see them as inseparable components, if not interchangeable terms. In this article, we ‘disconnect the keyboard’ and explore an alternative history of electronic sound synthesis – modular synthesis – that has remained largely overshadowed by keyboard-based synthesizers since the Minimoog. Researchers in music education signal that Eurocentric aesthetic norms, ableist performance ideals and exclusionary practices are interwoven in keyboard technologies, creating barriers that extend into popular music education. Drawing upon critical discussions in music education and science and technology studies (STS), we examine the underexplored opportunities of using modular synthesizers for music learning. We examine how modular synthesis, liberated from the keyboard-controller, serves as a basis for exploring an alternative model for sound-based inquiry and for rethinking the possibilities of instrument design and ways of musiking that are more inclusive.
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 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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".