The Lives and Deaths of a Soviet Saint in the Post-Soviet Period: The Case of Zoia Kosmodem'ianskaia
Bibliographic record
Abstract
This article analyzes the popular response to Soviet myths in the post-Soviet period through the lens of the complicated treatment of Zoia Kosmodem'ianskaia. As arguably the most famous Soviet World War II martyr, Kosmodem'ianskaia’s image splintered after glasnost' and has been located at the nexus of debate in various media since 1991. This paper poses questions about the fracturing of national memory when a nation has undergone upheaval: about the stability of heroes, about citizens’ responses to them, and about heroes’ transformation in the new regime. Catriona Kelly has demonstrated that the treatment of a national hero can illuminate the circumstances that produced the hero and the cultural climate of subsequent decades. Building on her work, this article asks “Why and how has the image of Kosmodem'ianskaia remained relevant while other Soviet heroes have been neglected since 1991?” This article posits that Kosmodem'ianskaia’s continued significance lies above all in the flexibility of her image and the transitional aspects of her body. Her depictions in various contexts represent prominent responses to the authoritarian regime which gave birth to both Kosmodem'ianskaia and her legacy. The variety of her images demonstrates the continued relevance of this figure two decades after the collapse of the USSR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.027 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".