Article published in:Language Typology and Historical Contingency: In honor of Johanna Nichols
Edited by Balthasar Bickel, Lenore A. Grenoble, David A. Peterson and Alan Timberlake
[Typological Studies in Language 104] 2013
► pp. 195–216
Capturing diversity in language acquisition research
In order to understand how children cope with the enormous variation in structures worldwide, developmental paths need to be studied in a sufficiently varied sample of languages. Because each study requires very large and expensive longitudinal corpora (about one million words, five to seven years of development), the relevant sample must be chosen strategically. We propose to base the choice on the results of a clustering algorithm (fuzzy clustering) applied to typological databases. The algorithm establishes a sample that maximizes the typological differences between languages. As a case study, we apply the algorithm to a dozen typological variables known to have an impact on acquisition, concerning such issues as the presence and nature of agreement and case marking, word order, degrees of synthesis, polyexponence and inflectional compactness of categories, syncretism, the existence of inflectional classes etc. The results allow deriving small samples that are maximally diverse. As a side result, we also note that while the clustering algorithm allows maximization of diversity for sampling purposes, the resulting clusters themselves are far from being discrete and therefore do not reflect a natural partition into basic language types.
Published online: 13 December 2013
Cited by 3 other publications
This list is based on CrossRef data as of 02 may 2021. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.