Methods for Characterizing Participants' Nonmainstream Dialect Use in Child Language Research

Abstract

Three different approaches to the characterization of research participants' nonmainstream dialect use can be found in the literature. They include listener judgment ratings, type-based counts of nonmainstream pattern use, and token-based counts. In this paper, we examined these three approaches, as well as shortcuts to these methods, using language samples from 93 children previously described in J. Oetting and J. McDonald (2001). Nonmainstream dialects represented in the samples included rural Louisiana versions of Southern White English (SWE) and Southern African American English (SAAE). Depending on the method and shortcut used, correct dialect classifications (SWE or SAAE) were made for 88% to 97% of the participants; however, regression algorithms had to be applied to the type- and token-based results to achieve these outcomes. For characterizing the rate at which the participants produced the nonmainstream patterns, the token-based methods were found to be superior to the others, but estimates from all approaches were moderately to highly correlated with each other. When type- and/or token-based methods were used to characterize participants' dialect type and rate, the number of patterns included in the analyses could be substantially reduced without significantly affecting the validity of the outcomes. These findings have important implications for future child language studies that are done within the context of dialect diversity.