Bibliographic record
Abstract
This chronological survey of English translations of Notes from Underground covering the years 1913–2014 evaluates the treatment of the text from various, often contradictory, perspectives. Well-known and unknown translators and editors offer sometimes opposing versions of the text aided by various ancillary materials which range from biographical information to a detailed chronology of Dostoevsky’s life plus excerpts from contemporary documents and modern critical evaluations. A number of the translations are designed expressly for students, others for those with limited or no knowledge of Dostoevsky, Russian history or the Russian language. No single introduction or translation emerges as the most insightful or accurate, although those of the last two decades are more idiomatic. Influencing this is often the background of the editor or translator. American editors focus on the context of Dostoevsky’s creation, English or Russian editors concentrate on the core elements that emphasize either the Russian literary tradition or late 19th century Russian politics and its importance for Dostoevsky’s conception of the story. Almost all editors consider the narrative experimentation of the work and the structural differences between Parts I and II. A number of the editors also address the Existential quality of the text, while translators confront the difficulties of capturing Dostoevsky’s sometime idiosyncratic prose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".