Nanc-in-a-Can Canon Generator. SuperCollider code capable of generating and visualizing temporal canons critically and algorithmically
Bibliographic record
Abstract
In the present paper a SuperCollider library designed to produce temporal canons, like the ones proposed by Conlon Nancarrow, is explored in order to create new temporal conceptions within the field of live coding. We will define temporal canon as a composition strategy that allows a poly-temporal audition by expressing a single musical idea at different speeds simultaneously. Likewise, our intention is to socialise the work of Nancarrow, often captured by a reduced academic niche, so it may be integrated into a broader and more diverse context. In this paper a broad introduction to the library is provided that emphasises some of its salient aspects that overlap with specific interests of live coders. By de-canonising the ideas of Nancarrow and approaching them from a heterodox and unconventional perspective we attempt to unravel understandings of time and rhythm beyond the scope of the music of Conlon Nancarrow as well as the practices of Mexican and international live coding communities.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".