Musical genres exhibit distinct sociophonetic targets: An analysis of Quebec French
Bibliographic record
Abstract
Genres such as indie (Beal 2009) and hip-hop (Eberhardt & Freeman 2015) feature dialectal traits in English, but whether genres form targets distinct from speech remains unclear. We examine genre effects on phonetic variation in Quebec French music by probing the role of genres (pop, country, alternative, and indie) on laxing and diphthongization, processes characteristic of Quebec French (Walker 1984). Stigma facing formal varieties of Quebec French has vanished within dialect (Kircher 2012), yet remains for processes that vary regionally or socioeconomically (Côté 2012; Côté & Lancien, 2019). Whereas laxing is categorical and non-stigmatized (Côté 2012; Paradis & Dolbec, 1998), diphthongization is variable and stigmatized (Côté 2012). We use a novel corpus of ten Québécois singers who released multiple albums from 2011-2021 (29 albums; 326 songs). We find the emergence of genre-specific linguistic norms distinct from speech and argue that genres in music parallel sociolects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".