Social and Cultural Evolution Working Group, University of Pennsylvania.
Department of Biology, University of Pennsylvania.
Cogn Sci. 2022 Sep;46(9):e13197. doi: 10.1111/cogs.13197.
Over half a century ago, George Zipf observed that more frequent words tend to be older. Corpus studies since then have confirmed this pattern, with more frequent words being replaced and regularized less often than less frequent words. Two main hypotheses have been proposed to explain this: that frequent words change less because selection against innovation is stronger at higher frequencies, or that they change less because stochastic drift is stronger at lower frequencies. Here, we report the first experimental test of these hypotheses. Participants were tasked with learning a miniature language consisting of two nouns and two plural markers. Nouns occurred at different frequencies and were subjected to treatments that varied drift and selection. Using a model that accounts for participant heterogeneity, we measured the rate of noun regularization, the strength of selection, and the strength of drift in participant responses. Results suggest that drift alone is sufficient to generate the elevated rate of regularization we observed in low-frequency nouns, adding to a growing body of evidence that drift may be a major driver of language change.
半个多世纪前，乔治·齐普夫（George Zipf）观察到，更频繁出现的词往往更古老。从那时起，语料库研究证实了这一模式，即更频繁出现的词比不那么频繁出现的词被替换和规范化的频率更低。为了解释这一现象，提出了两个主要假说：一是由于高频词的创新受到更强的选择压力，因此变化较少；二是由于低频词的随机漂移更强，因此变化较少。在这里，我们首次对这些假说进行了实验检验。参与者的任务是学习一种由两个名词和两个复数标记组成的微型语言。名词的出现频率不同，并接受了不同的漂移和选择处理。我们使用一个能够解释参与者异质性的模型，测量了名词规范化的速度、选择的强度和参与者反应中的漂移强度。结果表明，漂移本身足以产生我们在低频名词中观察到的更高的规范化速度，这增加了越来越多的证据表明，漂移可能是语言变化的主要驱动力。
