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Syntactic change and syntactic borrowing in generative grammar

  • Claire Bowern
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Principles of Syntactic Reconstruction
This chapter is in the book Principles of Syntactic Reconstruction

Abstract

This paper explores three issues in the reconstruction of syntactic borrowing. First, I discuss the scholarly traditions which have shaped historical phonology and historical syntax. I point out some of the incompatible assumptions which the two fields make, and examine the role of speakers’ individual grammars in language change, along with the effects that traditions within generative syntax have had on framing historical syntactic questions. I then move to an investigation of calquing and the reconstruction of syntactic borrowing, and a discussion of the work of Minimalism in historical syntactic research (in particular, Longobardi (2003)). I argue that any detailed account of language change (no matter what the framework) must address the role of language contact. I argue that real progress in syntactic reconstruction requires a theory of borrowing that does not treat loan constructions as simply ‘noise’ in the data.

Abstract

This paper explores three issues in the reconstruction of syntactic borrowing. First, I discuss the scholarly traditions which have shaped historical phonology and historical syntax. I point out some of the incompatible assumptions which the two fields make, and examine the role of speakers’ individual grammars in language change, along with the effects that traditions within generative syntax have had on framing historical syntactic questions. I then move to an investigation of calquing and the reconstruction of syntactic borrowing, and a discussion of the work of Minimalism in historical syntactic research (in particular, Longobardi (2003)). I argue that any detailed account of language change (no matter what the framework) must address the role of language contact. I argue that real progress in syntactic reconstruction requires a theory of borrowing that does not treat loan constructions as simply ‘noise’ in the data.

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