Bibliographic record
Abstract
Challenging the usual acceptance of electroacoustics as a distinct field of its own, this article leads the reader through a series of paths to show the extent to which concerns and techniques of electroacoustics are shared with other musical and artistic disciplines. It continues with a similar questioning of the usual interpretation of analysis by examining the variety of aims, methods, and characteristics of analytical methods, and encourages an increased awareness on the part of all analysts to appreciate where their own work is situated within the field. Typical concerns of electroacoustics, such as the design of timbral structures, gestures and textures are discussed within the realm of parametric analysis, but allusion is also made to other approaches which examine style and context. Disciplines from perception to semiotics are shown to have relevance for further development of adequate analytical tools. The author does not advocate one particular approach, but rather attempts to demonstrate the vastness and intricacy of the field. The conclusion is that analysis of electroacoustics could both contribute to, and benefit from, analysis in other areas of music and art.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.020 | 0.026 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.096 | 0.014 |
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".