How individuals change language
This work addresses a fundamental challenge in linguistics by providing a framework to test theories of language change, though it is incremental as it builds on existing models and focuses on specific linguistic features.
The authors tackled the problem of understanding how individual linguistic innovations lead to population-level language changes by developing a general mathematical model that predicts such changes based on individual behaviors. They found that models assuming incremental changes across the lifespan, combined with social network effects, are more plausible than those based on childhood acquisition errors, as supported by historical data on definite and indefinite articles in multiple languages.
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.