THE POWER OF POWERLESS WORDS: HOW CAN RUSSOPHONE POETRY RESIST THE AGGRESSIVE WAR (2022-2023)?

  • Published In: Slavic & East European Journal, 2025, v. 69, n. 1. P. 20 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Kukulin, Ilya 3 of 3

Abstract

Between 2022 and 2023, a significant body of anti-war poetry emerged in Russian literature, including works by authors residing in Russia and those who had recently emigrated. These poems represent diverse artistic movements. This article proposes a comprehensive theoretical framework for analyzing contemporary anti-war poetry and examining its genealogy. Rather than employing the term "anti-war poetry," this study introduces the concept of "anti-aggression poetry," as these works specifically critique the contemporary Kremlin regime's aggression toward Ukraine and its suppression of Russian civil society, rather than war in general. Two aesthetic and political movements chronologically and thematically preceded contemporary antiaggression poetry: critical poetry from the Russian-Chechen wars (1994-2000) and poetry from the 2010s that criticized societal violence and presented history through the lens of violence (primarily in works by Irina Kotova and Gala Pushkarenko). Beyond political interpretations, anti-aggression poetry can be most effectively analyzed through the theoretical framework of Czech dissident philosopher Jan Patocka, who conceptualized the "solidarity of the shaken" as fundamental to resisting the normalization of aggression. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Slavic & East European Journal. 2025/03, Vol. 69, Issue 1, p20
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2025
  • ISSN:0037-6752
  • Accession Number:186125802
  • Copyright Statement:Copyright of Slavic & East European Journal is the property of American Association of Teachers of Slavic & East European Languages and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.