“Showy”, “Music-hall” America: To the Centenary of Sergey Esenin’s Essay Iron Mirgorod
Bibliographic record
Abstract
The article analyzes the image of America created by S.A. Esenin after his trip to the West with I. Duncan in the essay “Iron Mirgorod” (1923) and offers a comprehensive analysis of the poetics and the main sources of his text. Esenin was the first Soviet poet to visit America and create an essay about it, taking into account the rich literary tradition and his own vivid impressions. During his four month stay in America the poet lived in the New York City and visited 14 cities, in 11 states: Baltimore, Boston, Detroit, Indianapolis, Kansas City, St. Louis, Cleveland, Toledo, Toronto, Louisville, Memphis, Milwaukee, Philadelphia, Chicago. In connection with the history of the creation and publication of the essay, the article pays attention to the ambiguous semantics of its title, its connection with reality and literary sources — the cycle of essays by M. Gorky’s In America (1906) and N.V. Gogol’s works, including the collection of novellas Mirgorod (1835). The researcher analyzes the multilevel content, the correlation between the external and internal dialogue and the creation of a complex and contradictory image, in which the showy, festive, carrying the “banner of industrial culture” is contrasted with the “music hall” America. The article reveals Esenin’s polemics with the poem 150 000 000 writen by Mayakovsky “on the basis of pictures” taken from old magazines, “translating Whitman” (most of Esenin‘s attacks against Mayakovsky were not published) and his controversy with Russian urbanists (those from “Kuznitsa,” “LEF”). Esenin’s deep concern for the problems of modern spirituality and culture was expressed in categorical and sometimes shocking tone of his assessments and judgments, oddity of style and the pecularity of genre — the essay is written in an ironic manner balancing between satire and grotesque. Carrying on a dialogue with Gogol, Esenin extremely sharpens the contradictions of real America and warns against choosing the American path of development with its exceptionalism, false pride of being “cultured”, “immersion in business” and “the power of dollar.”
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".