Bibliographic record
Abstract
This article applies agenre levelapproach to the tangled discourse surrounding the points of convergence between avant-garde electronica and electroacoustic music. More specifically the article addresses related experimental practices in these distinct yet related fields of electronic music-making. The democratisation of music technology continues to expand into an increasingly diverse set of musical fields, destabilising established power dynamics. A flexible, structured approach to the analysis of these relationships facilitates the navigation of crumbling boundaries and shifting relationships. Contemporary electronic music’s overlapping networks encompass varying forms of capital, aesthetics, technology, ideology, tools and techniques. These areas offer interesting points of convergence. As the discourse surrounding electronic music expands, so must the vocabulary and conceptual models used to describe and discuss new areas of converging artistic practice.Genre leveldiagrams selectively collapse, expand and arrange artistic fields, facilitating concrete, coherent arguments and the examination of patterns and relationships. Through thegenre leveldiagram’s establishment of distinct yet flexible boundaries, electronic music’s sprawling discourse can be cordoned off, expanded or contracted to suit structured analyses. In this way, this approach clarifies scope and facilitates simultaneous examination from a variety of perspectives.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".