Towards a Taxonomy of Musical Metacreation: Reflections on the First Musical Metacreation Weekend
Bibliographic record
Abstract
The Musical Metacreation Weekend (MuMeWe), a series of four concerts presenting works of metacreation, was held in June 2013. These concerts offered an opportunity to review how different composers and system designers are approaching generative practices. We propose a taxonomy of musical metacreation, with specific reference to works and systems presented at MuMeWe, in an effort to begin a discussion of methods of measuring metacreative musical works. The seven stages of this taxonomy are loosely based upon the autonomy of the system, specifically in its ability to make high-level musical decisions during the course of the composition and/or performance. We conclude with a discussion of how these levels could be interpreted, and the potential difficulties involved in their specification and terminology.
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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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.011 | 0.041 |
| Scholarly communication | 0.022 | 0.036 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".