Bibliographic record
Abstract
About half of the Jewish survivors (120,000) interned in Displaced Persons camps in Germany, Austria, and Italy after the liberation emigrated to Palestine, which was to become Israel in May 1948; another 80,000 to 90,000 of those interned went to the United States. After the war, approximately 140,000 survivors fled to the United States while nearly 350,000 embarked for Palestine. A large majority of the remaining Jews, which represented a small portion of the total number of survivors, emigrated to Canada, Australia, South Africa, or Argentina. Most survivors suffered from depression and anxiety, as well as various psychological and psychosomatic disorders resulting from the traumas associated with the Holocaust–a subject that will be examined in chapter 12. This chapter will focus on the plays that probe the difficulties that survivors had in adjusting to their new lives in the United States (Barbara Lebow's A Shayna Maidel) and the problems that Sabra Jews (native-born Israelis) had in accepting Old World Diaspora Jews into Israeli culture (Leah Goldberg's Lady of the Castle and Ben-Zion Tomer's Children of the Shadows ). Survivors who emigrated to the United States, many of them suffering from severe psychological trauma, had to accommodate to a much more complex lifestyle, learn a foreign language, adapt to new laws and customs, and build a new support structure. English, in particular, exacerbated problems for survivors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".