FROM MYSHKIN TO MARXISM: THE ROLE OF DOSTOEVSKY RECEPTION IN LUKÁCS'S REVOLUTIONARY ETHICS
Bibliographic record
Abstract
For European literati of the early twentieth century, Fyodor Dostoevsky represented a mythically Russian spirituality in contrast to a soulless, rationalized West. One such enthusiast was Georg Lukács, who in 1915 began a never-completed book about Dostoevsky's work, a model of spiritual community that could redeem a fallen world. Though framing his analysis in the language and themes of broader Dostoevsky reception, Lukács used this idiom innovatively to go beyond the reactionary implications this model might connote. Highlighting similarities with Max Weber's account of political ethics, I argue that Lukács developed an ethic derived from his reading of Dostoevsky, which focused on the idea of a hero defined by an ability to resolve the specific ethical dilemma of adherence to duty and moral law on the one hand, and, on the other, the need to restore spontaneous human community at a time when the social institutions embodying such laws had fallen into decay. Crucially, he deployed the same framework after his conversion to Marxism to justify revolutionary terror. However different his position from Dostoevsky's, it was through engagement with these novels that Lukács not only clarified his thought but also came to identify Lenin as a Dostoevskyan hero figure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.041 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".