PATRIOTIC AND HEROIC MOTIVES IN THE POETRY OF ALEXANDR TVARDOVSKY AND KEYSAR AMINPUR
Bibliographic record
Abstract
Connections and interrelations come up in the global literary process directly and indirectly. The present article is devoted to the literary parallels in the creative work of the famous Russian poet, a participant of the Second World War, chief editor of the literary magazine «Nowy Mir» Alexandr Tvardovsky and the popular Iran poet Keysar Aminpur. War and peace problems – are persistent in any national literature throughout the centuries. These problems have reflected in the life, fate and creative work of the Russian poet. They are also predominant in the poetry of K. Aminpur. Longing for home, dreams about piece in the world during ongoing military actions– are common concepts in the poetry of Tvardovsky and Aminpur, where people striving for peace have been drawn into the conflict. Patriotic and heroic motives in the poetry of the Russian and the Iran poets, ways of reflection in style, language and composition of the poems are different due to literary process particularities in the USSR and Iran in the last quarter of the XX-th century. At the same time, there are common points allowing us to compare poetry of A. Tvardovsky and K. Aminpur. Motives of patriotism and heroics are being analyzed from the prospective of nature. Homeland and smaller motherland landscape concepts are inseparable in the poetry of the both poets.
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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 | 0.004 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".