Abstract
Using data from a 100-million-word representative corpus and a large-scale acceptability survey, we have investigated the relationship between corpus data and acceptability judgments. We conclude that the relative proportions of morphosyntactic variants in a corpus are the most significant predictor of a variant's acceptability to native speakers, and that in particular high relative proportions of one variant in a corpus are reliable indicators of high acceptability to native speakers. At the same time we note the limits of this predictability: low-frequency items, as noted elsewhere in the literature, often enjoy high levels of acceptability. Statistical preemption thus appears as a more limited phenomenon than had heretofore been posited.
About the authors
Neil Bermel is Professor of Russian and Slavonic Studies at the University of Sheffield.
Luděk Knittl is Tutor in Czech at the University of Sheffield.
©[2012] by Walter de Gruyter Berlin Boston
