Regularization of nouns due to drift, not selection: An artificial-language experiment
Corpus data suggests that frequent words have lower rates of replacement and regularization. It is not clear, however, whether this holds due to stronger selection against innovation among high-frequency words or due to weaker drift at high frequencies. Here, we report two experiments designed to probe this question. Participants were tasked with learning a simple miniature language consisting of two nouns and two plural markers. After exposing plural markers to drift and selection of varying strengths, we tracked noun regularization. Regularization was greater for low- than for high-frequency nouns, with no detectable effect of selection. Our results therefore suggest that lower rates of regularization of more frequent words may be due to drift alone.