Bibliographic record
Abstract
The confluence of composition and performance is a compelling phenomenon which confronts many 21st century electronic music artists, brought about primarily through an independent “DiY” ethos to creativity and the ubiquity of advanced musical, and non-musical, technology. Techniques of software programming, improvisation, reconstitution of electric and acoustic instruments, sampling, and manipulation of audio in a live setting (to name a few) may all find a place in an artist’s methodology regardless of style. It may be even be said that the techniques employed by an artist delineate the style itself, e.g. “controllerism,” “turntablism,” “live PA,” etc. The following paper offers an in-depth structural analysis of the composition and performance fundamentals of BlipVert, a pseudonym under which I have been presenting electronic music to the general public for almost two decades. The BlipVert composition “New Choomish,” from BlipVert’s 2010 release “Quantumbuster Now” (Eat Concrete Records, NL), is examined as a construct which manifests an expressive faculty in both live and studio environments, consequently demonstrating a profoundly synthesized framework of sonic and gestural principles. Keywords: composition, performance, improvisation, movement, building-blocks, Northlich, BlipVert, New Choomish
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.104 | 0.033 |
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".