Capturing diversity in language acquisition research

Abstract

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 Show more