David Zimmerman, <i>Ensnared between Hitler and Stalin: Refugee Scientists in the USSR</i> Toronto: University of Toronto Press, 2023. Pp. 376. ISBN 978-1-4875-4365-5. $85.00 (hardcover).
Bibliographic record
Abstract
Among those displaced by the two world wars, intellectuals generally and scientists in particular have received no small share of historians' attention.Charles Weiner's 'New site for the seminar' (1969) set the scene historiographically for physicist refugees to America, and much scholarship since has documented the exodus of scientists from Central Europe.That the Soviet Union was either destination or (more often) forced detour for a sizeable cohort of Central European scientists is well known, and scholarship on their plight has expanded greatly since 1991.David Zimmermann aims for a fresh view of these peregrinations, shifting the focus from the more famous figures who went directly to 'the West' and treating a more academically diverse cohort whose members did not generally achieve the fame of a Hans Bethe or an Edward Teller.The outcome is a pleasing synthesis of an impressive body of literature, demonstrating admirable empathy for its protagonists, but it holds few revelations for anyone closely acquainted with Russian and Ukrainian history of science.Zimmermann follows thirty-six scholars, mostly natural scientists, including the odd philosopher or musicologist who caught his interest.The value lies in the sociological breadth, however, ranging from German physical chemist Hans Hellmann (executed by the Soviets in 1938) to Russian mathematician Michael Sadowsky, who trained in Germany and eventually wound up in the United States.'Surprisingly', writes Zimmermann, 'only a minority of the refugee academics in this study (fourteen out of thirty-four whose birthplace is known) were born in Germany' (p.26).Yet in an important sense this is not surprising at all, since many of the scientists whom he characterizes throughout as 'the Ensnared' were children of empires, not aboriginally 'German' despite their immersion in German-speaking academia.Zimmermann duly invokes the dissolution of empires (sensibly citing Peter Gatrell's seminal work) and the ambiguity of nationality in the new passport regimes after 1918, but his narrative too strongly anticipates Hitler's rise to power in 1933, even though the vulnerabilities that would plague his protagonists (some Jewish, some married to Jews, some leftist in their politics) were already becoming apparent after 1918 and beyond German borders.Unfamiliarity with Russian imperial heritage does not help.For example, in Sadowsky's brief biography we learn, 'After the Russian Revolution, Dorpat became Tartu' (p.28); the ethnically Russian Sadowsky family, stranded in Finland, was unwelcome in newly independent Estonia, nor did they want to migrate to the Soviet Union.German Dorpat (town and university) had in fact become 'Iuriev' as part of the Russification of the Baltic in 1893.Michael's father, the physicist Aleksandr Ivanovich Sadovskii, began
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.018 |
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".