JOURNAL ARTICLE
ALWAYS ALMOST: NINA AGADZHANOVA AND THE AMBIVALENT ARCHIVE OF EARLY SOVIET CINEMA.
Published In: Slavic & East European Journal, 2025, v. 69, n. 3. P. 336 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Kendall, Matthew 3 of 3
Abstract
Although the film Battleship Potemkin is often singularly linked with the auteur figure of Sergei Eisenstein, it is rarely mentioned that the film's screenplay was written by Nina Agadzhanova-Shutko (1889-1974). This article suggests that the dilapidated state of Agadzhanova's archive at the Russian State Historical Museum (GARF) can help explain why her efforts in this film and others have gone mostly unnoticed, mostly unnoted, and mostly forgotten. By making use of what I call the ambivalence of archive, I suggest that an important question for research on Soviet women's cinema practitioners asks not only what we lose when figures like Agadzhanova are eclipsed, but why it happens in the first place, and what it tells us about the writing of film history both inside of the Soviet Union and outside of it. I do this both by reinvestigating and reconsidering how Agadzhanova's labor for Potemkin was perceived over time, and by reconsidering her work as co-director of the understudied 1929 film, The Two Buldis. Constantly repressed but never entirely forgotten, the ambivalence of Agadzhanova's archive can direct us to a unique form of cinematic labor that typical methods of film historiography have frequently eclipsed. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Slavic & East European Journal. 2025/09, Vol. 69, Issue 3, p336
- Document Type:Article
- Subject Area:Film
- Publication Date:2025
- ISSN:0037-6752
- Accession Number:190815184
- 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.)
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