« Ousqu’on chill à soir? » Pratiques multilingues comme stratégies identitaires dans la communauté hip-hop montréalaise
Bibliographic record
Abstract
Dans ce bref portrait sociolinguistique de la culture hip-hop de Montréal, Mela Sarkar et son équipe de recherche de l’Université McGill confrontent les défenseurs de la « Québéquicité », c’est-à-dire être blanc et parler français avec l’accent approprié, aux pratiques multilingues qui caractérisent la communauté hip-hop montréalaise. En effet, les jeunes de la génération hip-hop au Québec inventent un nouveau langage hybride et mixte, né de l’amalgame des langues et cultures d’origines diverses que l’immigration et les politiques linguistiques ont introduites dans les écoles québécoises de langue française en milieu urbain. Les pratiques multilingues qu’ont créées les jeunes rappeurs québécois scolarisés en français en milieu multiethnique montréalais agissent comme des stratégies d’affirmation identitaire pour toute une génération.
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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 | 0.002 | 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 | 0.014 | 0.012 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".