Marketing strategies for electroacoustics and computer music
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article explores possible strategies for appraising electroacoustic and computer music to enhance ‘marketability’. It is proposed that the specific aesthetics, characteristics and function of a work may be more salient features than those of the medium of composition (e.g. computer) to many listeners. It is suggested that the common practice of focusing on chronology, geography and specific schools is becoming less relevant due to a proliferation of home studios, the internet, and an increasing saturation of electronic sounds in new media contexts. On the other hand, aspects of form, mood, timbral palette, rhythmic complexity, etc., may become very useful bases for choosing works for a compilation CD or concert programme. The inadequacies of musicians' discourse for describing such attributes leads to the incorporation of analogies from visual and performing arts as well as a discussion of other possible approaches to ‘labelling’ and the inherent dangers in such a task. In conclusion, it is proposed that the time is ripe for shuffling the categories and regrouping composers' works according to aesthetic preferences, regardless of the percentage of electronic/computer content.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it