La chanson populaire francophone : airs et ondes entre le Canada et la France
Bibliographic record
Abstract
Ce numéro thématique de la revue est porté par deux spécialistes de la chanson, l’un français et l’autre franco-ontarienne : Stéphane Hirschi de l’Université Polytechnique Hauts-de-France et Johanne Melançon de l’Université d’Ottawa. Il propose quelques regards sur les phénomènes de rencontre entre la France et le Canada francophone, à travers le medium de la chanson, dans ses paroles, sa musique et son interprétation… S’y croisent les champs disciplinaires : sociologie, études littéraires, cantologie, perspectives historiques ; et les répertoires : des styles populaires de variété jusqu’aux expressions contemporaines du rap, de chanteurs médiatisés à artistes confidentiels. C’est la notion de croisement qui a présidé à ce numéro : pluralité des approches, des univers artistiques, des époques, et bien sûr des continents d’origine, avec un seul fil conducteur : la dynamique des échanges.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.022 | 0.016 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".