Сравнение методов

	Verbal-Guise Technique	Variationist Sociolinguistics
Область	Лингвистика	Лингвистика
Семейство	Process / pipeline	Process / pipeline
Год появления	2010	1972
Автор метода	Language-attitudes researchers (variant of Lambert's matched guise; synthesis by Peter Garrett)	William Labov
Тип	Indirect experimental measure of language attitudes	Quantitative field study of socially conditioned linguistic variation
Основополагающий источник	Garrett, P. (2010). Attitudes to Language. Cambridge University Press. ISBN: 9780521759175	Labov, W. (1972). Sociolinguistic Patterns. University of Pennsylvania Press. ISBN: 9780812210521
Другие названия	Verbal Guise Test, Speaker Evaluation Verbal Guise, Verbal-Guise Experiment	Variationist Analysis, Labovian Sociolinguistics, Quantitative Sociolinguistics
Связанные	3	4
Сводка	The verbal-guise technique is the naturalistic cousin of the matched-guise technique for measuring language attitudes. Instead of one bidialectal speaker producing every variety, different speakers each produce a single variety, and listeners rate each speaker on personality and status trait scales. This solves the matched-guise problem of finding speakers who can authentically and equivalently perform two or more varieties, and it uses genuine native voices for each variety — but at the cost of reintroducing speaker-to-speaker differences as a potential confound. It remains a core instrument in the speaker-evaluation paradigm for studying covert attitudes toward accents, dialects, and languages.	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.