The “proletarian lord”: Leo Tolstoy's image during the Russian revolutionary period
Bibliographic record
Abstract
Too, those who are caught by Tolstoy's eyes, in the various portraits, room after room after room, are not unaffected by the experience. It is like, people say, committing a small crime and being discovered at it by your father, who stands in four doorways, looking at you. Barthelme, “At the Tolstoy Museum” Leo Tolstoy figured large in the deeply partisan and impassioned debates during the Russian revolutionary period (1917–24). In the uncharted social and political chaos of disappearing and emerging institutions, competing centers of authority vied for validation and credibility by reciting and creating stories about Tolstoy: how he foretold the Revolution, warned against it, or caused it; why he would have rejected or embraced it; what he would have said or done had he lived to see it. Regardless of political position, these commentators saw Tolstoy as the code that, when correctly interpreted, offered a truer understanding of the Revolution's cipher, because both Tolstoy and the Revolution were equally products of a uniquely Russian experience. An examination of the stories people told about Tolstoy in primary historical documents from the Russian and international press provides a fuller and more nuanced historical understanding of debates about the authenticity, inevitability, and justness of the Russian Revolution. While the storytellers intended only to influence the perception of the Revolution by invoking Tolstoy, making what was new and unfamiliar into something comprehensible by referencing something known, these stories nonetheless altered Tolstoy's image as well.
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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 | 0.001 |
| Science and technology studies | 0.016 | 0.019 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".