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        The Mehweb language

        Essays on phonology, morphology and syntax

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        Contributor(s)
        Daniel, Michael (editor)
        Dobrushina, Nina (editor)
        Ganenkov, Dmitry (editor)
        Collection
        Knowledge Unlatched (KU); Language Science Press 2018-2020
        Number
        104952
        Language
        English
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        Abstract
        This book is an investigation into the grammar of Mehweb (Dargwa, East Caucasian also known as Nakh-Daghestanian) based on several years of team fieldwork. Mehweb is spoken in one village community in Daghestan, Russia, with a population of some 800 people, In many ways, Mehweb is a typical East Caucasian language: it has a rich inventory of consonants; an extensive system of spatial forms in nouns and converbs and volitional forms in verbs; pervasive gender-number agreement; and ergative alignment in case marking and in gender agreement. It is also a typical language of the Dargwa branch, with symmetrical verb inflection in the imperfective and perfective paradigm and extensive use of spatial encoding for experiencers. Although Mehweb is clearly close to the northern varieties of Dargwa, it has been long isolated from the main body of Dargwa varieties by speakers of Avar and Lak.
        URI
        http://library.oapen.org/handle/20.500.12657/23417
        Keywords
        Linguistics
        DOI
        10.5281/zenodo.3374730
        ISBN
        9783961102082
        Publisher
        Language Science Press
        Publisher website
        https://langsci-press.org/
        Publication date and place
        Berlin, 2019-10-23
        Grantor
        • Knowledge Unlatched - 104952 - Language Science Press 2018 - 2020
        Classification
        Linguistics
        Rights
        https://creativecommons.org/licenses/by/4.0/legalcode
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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