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

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          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.

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                Author and article information

                Contributors
                Journal
                2397-1835
                Glossa: a journal of general linguistics
                Ubiquity Press
                2397-1835
                02 May 2018
                2018
                : 3
                : 1
                Affiliations
                [1 ]Leipzig University, IPF 141199, Nikolaistraße 6-10, 04109 Leipzig, DE
                Article
                10.5334/gjgl.294
                ddb63e62-a644-431e-a1b8-10c016fe05d9
                Copyright: © 2018 The Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.

                Categories
                Special collection: probabilistic grammars: syntactic variation in a comparative perspective

                General linguistics,Linguistics & Semiotics
                horror aequi,help,complexity,economy,Bayesian regression,iconicity

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