Bibliographic record
Abstract
Defining the Kindertransport The Kindertransport was an international rescue effort that took place between 1938 and 1940. To escape the impact of Nazism, Jewish refugee children, or “Kinder” as they are collectively known today, fled their homelands (in Germany, Austria, Czechoslovakia, and Poland) to Britain, the Netherlands, France, Belgium, Norway, Sweden, and Switzerland. It was “conceived as a transmigratory scheme” with the idea that the children would be relocated beyond British shores at some point. But even in Britain itself the Kinder faced relocation several times over. They became “enemy aliens” and were interned in Britain, Canada, and Australia, or moved as emigrants to America and New Zealand. In the postwar period, many Kinder made yet further journeys to be reunited with surviving family members. Some went to Israel, setting up Moshavim and Kibbutzim such as Kibbutz Lavi. A few Kinder even returned to their former homelands. However, the Kindertransport did not always save the children. While many of those who found refuge in countries bordering Germany such as the Netherlands and France survived the war, others were caught up in deportations following the Nazi invasion and were murdered in the Holocaust. The following book sets out to study the way the Kindertransport has been represented in public memory in the English-speaking host nations and in Germany, the country from which most of the Kinder came. For reasons of space, we have not examined the extent to which the topic has been represented in Austria, Poland, or Czechoslovakia, although we do make occasional reference to memorials and exhibitions in these countries. We explore Kindertransport memorialization not least through the lens of the national memory frameworks obtaining in each country under discussion, at the same time highlighting through our comparative approach the way differences between these frameworks impacted on memorialization in each case. We focus mainly on memorials, exhibitions and commemorative events, asking also to what extent transnational memory trends have influenced these. Given that the Kindertransport was itself an international event—something that should not be overlooked despite Britain's central role—it would seem, ideally at least, to lend itself to a transnational optic. We have written this book because, to date, most studies of the Kindertransport, whether in English or German, focus rather on its history.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".