Probabilistic grammar and constructional predictability: Bayesian generalized additive models of help + (to) Infinitive in varieties of web-based English

Abstract

The present study investigates the construction with help followed by the bare or to -infinitive in seven varieties of web-based English from Australia, Ghana, Great Britain, Hong Kong, India, Jamaica and the USA. In addition to various factors known from the literature, such as register, minimization of cognitive complexity and avoidance of identity ( horror aequi ), it studies the effect of predictability of the infinitive given help and the other way round on the language user’s choice between the constructional variants. These probabilistic constraints are tested in a series of Bayesian generalized additive mixed-effects regression models. The results demonstrate that the to -infinitive is particularly frequent in contexts with low predictability, or, in information-theoretic terms, with high information content. This tendency is interpreted as communicatively efficient behaviour, when more predictable units of discourse get less formal marking, and less predictable ones get more formal marking. However, the strength, shape and directionality of predictability effects exhibit variation across the countries, which demonstrates the importance of the cross-lectal perspective in research on communicative efficiency and other universal functional principles.