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    Chapter Melancholic Humor, Skepticism and Reflective Nostalgia. Igor’ Guberman’s Poetics of Paradox

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    Author(s)
    Salmon, Laura
    Language
    English
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    Abstract
    The poetry of Israeli émigré Igor' Guberman, comprising thousands of quatrains (‘gariki’), represents a hybrid genre at the junction of Jewish aphoristic tradition, Russian oral folklore, and classical Russian poetry. The theme of toska, which is central to the gariki, may be sharply distinguished from the ‘restorative nostalgia’ theorized by Svetlana Boym (2001): Guberman's toska is a thoughtful, melancholic, and paradoxical feeling. It expresses a particular variety of skepticism that characterizes the paradoxical humor of the Ashkenazi, the purpose of which is not to ridicule others' shortcomings, but to gently make fun of the sadness and painful absurdity that impermeates human existence. Such melancholic and paradoxical humor permits Guberman to look at life, at himself, even at God, with an indulgent ‘smile of reason’ that is absolutely devoid of arrogance. A subtle melancholic and deep skeptic, Guberman "laughs through his tears", for this is what Russian-Jewish tradition teaches, a lesson that has penetrated deeply and more generally into Russian literature: when the soul is beset by excessive sadness, its has recourse only to laughter.
    URI
    https://library.oapen.org/handle/20.500.12657/55821
    Keywords
    Guberman; gariki; paradox; humor; nostalgia; Russian-Jewish literature
    DOI
    10.36253/978-88-6655-822-4.06
    ISBN
    9788866558224, 9788866558224
    Publisher
    Firenze University Press
    Publisher website
    https://www.fupress.com/
    Publication date and place
    Florence, 2015
    Series
    Biblioteca di Studi Slavistici, 28
    Pages
    41
    Rights
    https://creativecommons.org/licenses/by/4.0/
    • 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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