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Christopher, Nadezda (2018) Aspects of Information Structure in Kazakh : the Dynamic Syntax Approach. PhD thesis. SOAS University of London. DOI: https://doi.org/10.25501/SOAS.00032245

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Abstract

The Kazakh language is an under-researched Turkic language spoken in the Central Asian state of Kazakhstan and some neighbouring countries. While the grammar of this language is fairly well described, its information structural characteristics have not been examined in detail in the literature to date. This thesis aims to start filling this research gap by providing detailed descriptions of: the relation between information structure and word order; topic markers; and a pragmatically significant particle. Original, contextualised language examples are used to reject previous limited and rigid understanding of the relation between information structure and word order in Kazakh. It is shown that the information structural configurations of a Kazakh sentence are far more diverse than had been assumed. This conclusion is not only a revelation in its own right, but can also serve as a foundation for further research on the information structure of Kazakh, and other under-researched Turkic languages. This thesis also provides the first detailed descriptions of the three Kazakh topic markers. Numerous examples of their uses are presented in order to demonstrate the differences in these markers’ distribution and meaning. Several grammaticalisation processes related to these topic markers are revealed; it is proposed that these processes are currently at different stages of progress. Pragmatically significant particle ğoj is examined in detail for the first time: its distribution and meaning are illustrated with contextualised examples from various sources. It is posited that there are two syntactically diverse variants of this item which do, however, share the same existential semantics. The theoretical framework of Dynamic Syntax is employed throughout the thesis to underpin the first formal analyses of the phenomena under discussion.

Item Type: Theses (PhD)
SOAS Departments & Centres: SOAS Research Theses
Supervisors Name: Irina Nikolaeva
DOI (Digital Object Identifier): https://doi.org/10.25501/SOAS.00032245
Date Deposited: 30 Jan 2020 11:32
URI: https://eprints.soas.ac.uk/id/eprint/32245

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