Bibliographic record
Abstract
Dans cet article, Philippe Leroux évoque sa rencontre avec Ivan Wyschnegradsky et ce qu’elle a apporté à sa vision de la composition. Pour cela, il explique – après les avoir décrits sommairement – en quoi les principales théories compositionnelles de Wyschnegradsky que sont les périodicités et les cycles non-octaviants ainsi que les échelles ultrachromatiques, se différenciaient des principes sériels, stochastiques ou d’objets sonores en vogue à Paris à la fin des années 1970. Il aborde ensuite l’influence qu’ont pu avoir ces théories sur sa musique, et comment elles ont joué pour lui un rôle libérateur en proposant une façon d’envisager le travail sur les hauteurs de note qui s’affranchit des visions motivique, aléatoire ou de timbre harmonique. Il évoque enfin comment il s’en est peu à peu affranchi, tout en reconnaissant en quoi ces théories ont fortement participé à sa conception de la notion de continuum perceptif.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".