Socialism, Aestheticized Bodies, and International Circuits of Gender: Soviet Female Film Stars in the People’s Republic of China, 1949–1969*
Bibliographic record
Abstract
This paper analyses the importance of love relations and sexuality in Soviet film for Chinese socialism in the 1950s and 1960s. By looking at the movement of Soviet women across the Sino-Soviet border — in films and as part of film delegations — I highlight the international circuits of gender that shaped socialist womanhood in China. I examine Chinese discussion of Soviet film stars including Marina Ladynina, Vera Maretskaia, and Marina Kovaleva. I locate the movement away from 'fun-loving post-revolutionary' womanhood associated with Ladynina to socialist womanhood located in struggle and partisanship within the larger context of Maoist theory and Sino-Soviet relations. In my examination of debates over which female film stars were appropriate for China I draw out celebrated and sanctioned couplings of Chinese and Soviet film heroines, such as the links made between Zoya and Zhao Yiman. By looking at how Soviet film stars became part of Chinese political aesthetics, sexuality and love emerge as more important to our understanding of womanhood in Maoist China than has been recognized by most scholars of gender in China. This approach therefore offers a new perspective on Maoist ideologies of gender with its emphasis on non-Chinese bodies as constitutive of gender subjectivities in Maoist China. I argue that while gender in Maoist China was primarily enacted on a national level, internationalism and international circuits of gender were central to its articulation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".