The adoption of evolutionary approaches to study language change as a type of non-biological evolution has gained increasing interest and introduced a variety of quantitative tools to linguistics. The focus has thus far mainly been on language families, or ‘linguistic macroevolution,’ and taken the shape of linguistic phylogenetics. Here we explore whether evolutionary methods could be applicable for studying intra-lingual variation (‘linguistic microevolution’) by testing a population genetic clustering method for analyzing the ‘population structure’ of Finnish dialects. We compare the results with traditional dialect divisions established in the literature and with K-medoids clustering, which is free from biological assumptions. The results are encouragingly similar to each other and agree with traditional views, suggesting that population genetic tools could be a useful addition to the dialectological toolkit. We also show how the results of the model-based clustering could serve as a basis for further study.
Purchase
Buy instant access (PDF download and unlimited online access):
Institutional Login
Log in with Open Athens, Shibboleth, or your institutional credentials
Personal login
Log in with your brill.com account
Most of these maps can be found in Wiik (2004).
All Time | Past Year | Past 30 Days | |
---|---|---|---|
Abstract Views | 969 | 206 | 25 |
Full Text Views | 255 | 31 | 0 |
PDF Views & Downloads | 166 | 54 | 0 |
The adoption of evolutionary approaches to study language change as a type of non-biological evolution has gained increasing interest and introduced a variety of quantitative tools to linguistics. The focus has thus far mainly been on language families, or ‘linguistic macroevolution,’ and taken the shape of linguistic phylogenetics. Here we explore whether evolutionary methods could be applicable for studying intra-lingual variation (‘linguistic microevolution’) by testing a population genetic clustering method for analyzing the ‘population structure’ of Finnish dialects. We compare the results with traditional dialect divisions established in the literature and with K-medoids clustering, which is free from biological assumptions. The results are encouragingly similar to each other and agree with traditional views, suggesting that population genetic tools could be a useful addition to the dialectological toolkit. We also show how the results of the model-based clustering could serve as a basis for further study.
All Time | Past Year | Past 30 Days | |
---|---|---|---|
Abstract Views | 969 | 206 | 25 |
Full Text Views | 255 | 31 | 0 |
PDF Views & Downloads | 166 | 54 | 0 |