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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Sociophonetic Analysis× | Variationist Sociolinguistics× | |
|---|---|---|
| Domaine | Linguistique | Linguistique |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 2006 | 1972 |
| Auteur d'origine≠ | Sociophoneticians (William Labov; Paul Foulkes; Erik R. Thomas) | William Labov |
| Type≠ | Workflow correlating acoustic phonetic measurement with social factors | Quantitative field study of socially conditioned linguistic variation |
| Source fondatrice≠ | Foulkes, P., Scobbie, J. M., & Watt, D. (2010). Sociophonetics. In W. J. Hardcastle, J. Laver, & F. E. Gibbon (Eds.), The Handbook of Phonetic Sciences (2nd ed., pp. 703–754). Wiley-Blackwell. ISBN: 9781405145909 | Labov, W. (1972). Sociolinguistic Patterns. University of Pennsylvania Press. ISBN: 9780812210521 |
| Alias | Sociophonetics, Sociophonetic Variation Analysis, Phonetic Variation Analysis | Variationist Analysis, Labovian Sociolinguistics, Quantitative Sociolinguistics |
| Apparentées | 4 | 4 |
| Résumé≠ | Sociophonetic analysis sits at the intersection of acoustic phonetics and variationist sociolinguistics. It applies the precise, quantitative measurement of phonetic variables — vowel formants, voice onset time (VOT), the spectral moments of /s/, and many others — to socially structured samples of speech, then correlates those measurements with social factors such as age, social class, gender, ethnicity, and region. The result is a fine-grained, statistically defensible account of how phonetic detail carries social meaning and how it patterns across communities and across time, increasingly built on large-scale, automated measurement. | Variationist sociolinguistics is the quantitative study of how linguistic variation is structured by social and linguistic factors. Pioneered by William Labov in the 1960s and 1970s, it treats alternative ways of saying the same thing — the 'linguistic variable' — as systematically conditioned by speaker characteristics (class, age, sex, ethnicity), stylistic context, and the surrounding linguistic environment, and it uses statistical modeling of natural speech to reveal the orderly heterogeneity beneath apparent randomness. |
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