<i>From the Vilna Ghetto to Nuremberg: Memoir and Testimony</i>. Abraham Sutzkever
Bibliographic record
Abstract
Abraham (Avrom) Sutzkever (1913–2010) was among the most remarkable poets of the twentieth century. Though he left Vilna in 1946, he remained inextricably linked with the city as well as the Yiddish language. Although Vilna had only a fraction of the Jewish population of such larger cities as Warsaw, it was a cultural center and a beacon of Jewish pride and creativity in the Diaspora. Jews had a special name for Vilna: Yerushalayim d’Lite (The Jerusalem of Lithuania). Alongside this legacy, what mattered most to Sutzkever and many of his young friends in prewar Vilna was the special place of Yiddish. At a time when Yiddish was in decline elsewhere, it still flourished in Vilna. Before the war, the young Sutzkever was an up-and-coming Yiddish poet; however, his beautifully crafted verse—with its exquisite evocations of Siberian forests and Vilna’s landscape—made him an outlier in the Yiddish literary scene, which demanded protest and social engagement in response to fascism, poverty and growing antisemitism. On June 24, 1941, the Nazis seized Vilna. Sutzkever and his young wife attempted to escape, but were forced back into the city. Between June 1941 and January 1942, the Germans and their Lithuanian helpers murdered two thirds of Vilna’s Jews. Of an original Jewish population of seventy thousand (counting refugees) in June 1941, only twenty thousand remained in the Vilna ghetto, which the Germans finally liquidated in September 1943.
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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 | 0.006 |
| 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 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.063 | 0.030 |
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".