Journal of Logic, Language and Information

, Volume 20, Issue 3, pp 385–396 | Cite as

A Mathematical Model of Prediction-Driven Instability: How Social Structure Can Drive Language Change

Article

Abstract

I discuss a stochastic model of language learning and change. During a syntactic change, each speaker makes use of constructions from two different idealized grammars at variable rates. The model incorporates regularization in that speakers have a slight preference for using the dominant idealized grammar. It also includes incrementation: The population is divided into two interacting generations. Children can detect correlations between age and speech. They then predict where the population’s language is moving and speak according to that prediction, which represents a social force encouraging children not to sound out-dated. Both regularization and incrementation turn out to be necessary for spontaneous language change to occur on a reasonable time scale and run to completion monotonically. Chance correlation between age and speech may be amplified by these social forces, eventually leading to a syntactic change through prediction-driven instability.

Keywords

Language variation Language change Incrementation Mathematical model Social structure Prediction-driven instability 

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Department of MathematicsCollege of CharlestonCharlestonUSA

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