Musicologie et musique vocale : esquisse d’une méthodologie d’analyse texte-musique adaptée au répertoire du chansonnier Félix Leclerc
Bibliographic record
Abstract
Dans cet article, le corpus entier du chansonnier Félix Leclerc est prétexte à l’explication d’une méthode d’analyse « texte-accompagnement instrumental » adaptée à l’étude de la musique vocale. L’attention se porte d’abord sur l’analyse littéraire des paroles, et plus spécifiquement à partir de l’exemple de la chanson « Les Rogations » de Leclerc, sur la présence d’idées nationalistes dans les chansons avant 1970 (Monière 1977; Balthazar 1986; Dumont 1996). Par la suite, l’analyse musicale se concentre sur les relations entre les influences musicales du chansonnier et les techniques d’accompagnement à la guitare dans les chansons enregistrées (Green 2001; Tagg et Clarida 2003). Au final, la somme des étapes analytiques proposées remet en question deux conceptions répandues du style de Leclerc : la division de sa carrière en seulement deux périodes – avant et après la crise d’Octobre 1970; et la forte appartenance esthétique de son répertoire à la « grande chanson française ».
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".