Gogol'’s “Portrait” Repainted: On Gary Shteyngart’s “Shylock on the Neva”
Bibliographic record
Abstract
The Russian-American novelist Gary Shteyngart has frequently been called a “Gogolian” writer, usually in an attempt to explain the pedigree of his grotesque humour. This article focuses on Shteyngart’s story “Shylock on the Neva” (2002), which is a modern-day rewriting of Gogol'’s tale “Portret” [“The Portrait”]. A close analysis of Shteyngart’s text and comparison to its Gogolian model reveals a complex relation that is not necessarily centered on Gogol'’s humour. In his rewriting of “The Portrait,” Shteyngart emphasizes the inherent venality and vulgarity of Gogol'’s characters, who turn into grotesque caricatures of their prototypes. In doing so, he seems to “Gogolize” Gogol'’s tale by adding some of the absurd humour that critics have found to be lacking in “The Portrait.” By making a painting the focus of their stories, both Gogol' and Shteyngart engage in a self-reflective comment about art and the role of the creative artist. Similar to the clichéd hack-paintings of Gogol'’s painter Chartkov, artistic creation has been reduced in “Shylock on the Neva” to the production of postmodern simulacra based on stereotypes and cultural myths.
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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 | 0.000 | 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 | 0.003 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".