Analyses et comparaisons des techniques répétitives utilisées dans les oeuvres séculaires et sacrées de Loyset Compère
Bibliographic record
Abstract
This study is the first step toward a better understanding of the introduction of pervasive imitation at the end of the fifteenth century. The focus is on selected works of Loyset Compère: the ténor motet Omnium bonorum plena, two motetti missales cycles and twenty chansons. Four types of repetition have been identified in these works: imitation, free repetition, repeated modules and doubling. The main analysis is based on the statistical frequency of the different types of repetition. Percentage tables allow us to observe stylistic changes between early and late chansons and also underline some resemblances between late chansons and motetti missales. Different types of repetition tend to vary in length; imitation generally uses longer melodic lines than other types of repetition. I also studied pitch intervals of repetition used by Compère. I have noticed that unlike some composers of the time, Compère used pitch intervais other than the octave and unison, mainly the fifth and principally in his late chansons. Finally, I have constructed a System of modular classification which allowed me to identify unifying devices used by Compère in his motetti missales. The results presented in this thesis suggest that Loyset Compère was a major contributor to the evolution of pervasive imitation.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".