Depiction of Anti-Semitism in the Fictional Works of Russian Emigrant Author Ellen Litman
Bibliographic record
Abstract
Ellen Litman is one of the foremost writers of the fourth wave of Russian emigration. Her fictional works The Last Chicken in America (2007) and Mannequin Girl (2014) raise a strong voice against anti-Semitism. Anti-Semitism was a severe socio-cultural and political issue experienced by the Soviet Jews during the final years of the Soviet Union. It became one of the major driving forces that compelled the Soviet Jews to quit the homeland and take residence in countries like the USA, Israel, Canada and Germany. Settled in the USA, Litman addresses the issue of anti-Semitism in both her fictional works. The present research paper attempts to discuss the nature of anti-Semitism that traumatized the Soviet Jews inside and outside the homeland. It will also focus on the precarious state of the Soviet Jews as well as Jewish emigrants in America on account of anti-Semitism. How American Jews treated the Soviet Jews and the reciprocal attitude of the Soviet Jews towards their American counterparts will also be discussed in this paper. As Litman herself is a Jewish emigrant writer, it will be interesting to see how see tackles the issues of anti-Semitism in her works.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".