Bibliographic record
Abstract
This article examines Nabokov’s novel Pnin as a conscious response to, and “translation” of, elements from Pushkin’s Evgenii Onegin. Both novels experiment with and subvert literary conventions and corresponding reader expectations, a process that is called “translation” in this article. Evgenii Onegin is both a model of the technique and a crucial source text for Pnin. Perhaps most significantly, the intricate narrative stance in Nabokov’s novel owes much to its literary predecessor. In both novels, the narrators bear more than a passing resemblance to their authors. The narrators cannot be strictly identified with their creators, however, since they also function as fictional characters. As one delves further, the narrative structure appears still more complex and even paradoxical: despite their apparently fictional status, the narrators at times achieve standard narrative omniscience, with access to the inner lives of other characters.Both novels are concerned with the tension between fiction and the reader’s awareness of an author behind the text. While this tension is enhanced by the deliberate blurring of the lines between the author and the narrator of each text, a significant difference is also present. Nabokov revisits the territory of narrative inconsistency and contradiction that Pushkin explores in Evgenii Onegin and takes the problem one step further, by creating a narrator whose reliability must be called into question. In addition, Nabokov takes full advantage of the narrator’s role as participant in the action; it turns out that the narrator of Pnin is not simply a well-meaning and faithful observer, but a full participant in the drama, playing significant roles in two of the most emotionally charged events in Pnin’s life. Thus, Pnin is a demonstration of what happens to a text when its internal narrative contradictions are exposed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".