Bibliographic record
Abstract
Abstract Following a confused encounter with a music manuscript, the author explores the underpinnings of that experience, to understand the nature and structure of music notations as drawing systems. A music notation is an almost-impossibly complicated bit of drawing. Calling it a map does not quite do the trick, even if the page somehow works like a map. Labelling it a diagram, typically a didactic visual tool, is off the mark as well. Furthermore, the traditional western staff notation, as an example with historical authority, happens to be a richly developed system for reading and writing, for composition. This mixed bag of structure and function makes the staff notation a persistently vital teaching tool, even in our vexing era of computational solutions. In its hybrid display, a music notation gives its many user-communities a strategic, two-dimensional mechanism for cross-modal analysis and annotation, and ultimately performance of its content, in higher dimensions. How does a music drawing relate to other drawing systems? And how is it that we are enabled to fix and re-fix the multi-dimensional complexes of musical performance onto a page?
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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".