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            Конструкции с опорным глаголом в русском и итальянском языках / Support Verb Constructions. A Russian-Italian Contrastive Analysis

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            Author(s)
            MAIKO, TATSIANA
            Language
            Russian
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            Abstract
            The monograph focuses on a special type of collocations–Support, or Light, Verb Constructions (SVCs). SVCs consist of a semantically reduced verb together with a noun (as the direct object or embedded in a prepositional phrase) that conveys core lexical meaning to the combination. SVCs often vary cross-linguistically, with languages using different strategies to conceptualize the same denotative situations. This study in line with the principles of the Integrated Contrastive Model, aims firstly to offer a corpus-driven contrastive cognitive-semantic description of SVCs in Russian and Italian based on the Construction Grammar model; and secondly to conduct a Contrastive Interlanguage Analysis of the use of Russian SVCs by Italian-speaking students. The findings of this study, in addition to its theoretical significance, may be useful in teaching Russian as a foreign language and could be of interest for lexicography.
            URI
            https://doab-dev.siscern.org/handle/20.500.12854/181671
            Keywords
            Support Verb Constructions; Light Verb Constructions; Contrastive Interlanguage Analysis; Russian; Italian; thema EDItEUR::N History and Archaeology::NH History
            DOI
            10.36253/978-88-9273-983-3
            ISBN
            9788892739833, 9788892739826, 9788892739840
            Publisher
            Firenze University Press
            Publisher website
            www.fupress.com/
            Publication date and place
            Florence, 2022
            Series
            Biblioteca di Studi Slavistici,
            Pages
            226
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            Credits


            • logo Investir l'avenirInvestir l'avenir
            • logo MESRIMESRI
            • logo EUEuropean Union
              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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