Bibliographic record
Abstract
Between 1933 and 1945, the UK took in numerous biologists displaced by Nazism, Italian fascism and the Second World War. While stellar biochemists such as Hans Krebs and Max Perutz are rightly celebrated, a diverse spectrum of other refugee biologists settled in the UK, from field naturalists to molecular biologists1. Support from British scientists was crucial. The Society for Protection of Science and Learning (SPSL) was founded in 1933 (originally as the Academic Assistance Council) in response to the first wave of dismissals by the Nazis1. Now known as the Council for At Risk Academics (CARA), the SPSL took a key mediating role for biologists as well as physical scientists and other academics. Supporters included J B S Haldane at University College London; Dr Julian Huxley at King’s College London and academics at London Zoo, who were hospitable in training a younger generation of specialised research workers. The SPSL assisted refugees with entry to the UK, finding laboratory space and – for some – getting onward visas to the US. When it came to internment, the SPSL and physiologist and Nobel laureate A V Hill secured scientists’ release or, as with Perutz, repatriation from Canada. Academic refugees also had a vigorous parliamentary voice through Hill, who was not only the Biological Secretary of the Royal Society, but MP for Cambridge University. He helped make the case that the refugees’ expertise could assist the war effort. The SPSL helped displaced academics adapt to their new homeland by offering grants to cover living expenses, interceding with the Home Office and putting individual refugees in touch with British academics. Often the first step was for them to complete a second PhD, which served both to confirm scientific competence and to socialise the researcher. Remarkably, SPSL funds for the refugees’ living expenses primarily came from academics at UK universities1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".