SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, United Kingdom.
Department of Linguistics, University of New Mexico, Albuquerque, New Mexico, United States of America.
PLoS One. 2021 Jun 2;16(6):e0252582. doi: 10.1371/journal.pone.0252582. eCollection 2021.
Languages emerge and change over time at the population level though interactions between individual speakers. It is, however, hard to directly observe how a single speaker's linguistic innovation precipitates a population-wide change in the language, and many theoretical proposals exist. We introduce a very general mathematical model that encompasses a wide variety of individual-level linguistic behaviours and provides statistical predictions for the population-level changes that result from them. This model allows us to compare the likelihood of empirically-attested changes in definite and indefinite articles in multiple languages under different assumptions on the way in which individuals learn and use language. We find that accounts of language change that appeal primarily to errors in childhood language acquisition are very weakly supported by the historical data, whereas those that allow speakers to change incrementally across the lifespan are more plausible, particularly when combined with social network effects.
语言会在个体使用者的相互作用下随着时间的推移在群体层面上产生和演变。然而,很难直接观察到单个说话者的语言创新如何引发语言在整个群体中的变化,因此存在许多理论假设。我们引入了一个非常通用的数学模型,它包含了各种个体层面的语言行为,并为这些行为导致的群体层面变化提供了统计预测。该模型使我们能够根据个体学习和使用语言的方式的不同假设,比较多种语言中定冠词和不定冠词的经验性变化的可能性。我们发现,那些主要依赖于儿童语言习得错误的语言变化解释,在历史数据中得到的支持非常微弱,而那些允许说话者在整个生命周期中逐步变化的解释则更合理,尤其是当与社交网络效应结合时。