Learning soft skills the hard way: Historiographical considerations on the cultural adjustment process of German-speaking émigré neuroscientists in Canada, 1933 to 1963
Bibliographic record
Abstract
This article is a historiographical exploration of the special forms of knowledge generation and knowledge transmission that occur along local cultural boundaries in the modern neurosciences. Following the inauguration of the so-called "Law on the Re-Establishment of a Professional Civil Service" in Nazi Germany on April 7, 1933, hundreds of Jewish and oppositional neurologists, neuropathologists, and psychiatrists were forced out of their academic positions, having to leave their home countries and local knowledge economies and traditions for Canada and the United States. A closer analysis of their living and working conditions will create an understanding of some of the elements and factors that determined the international forced migration waves of physicians and clinical neuroscientists in the twentieth century from a historiographical perspective. While I am particularly looking here at new case examples regarding the forced migration during the National Socialist period in Germany, the analysis follows German-speaking émigré neurologists and psychiatrists who found refuge and settled in Canada. These individuals form an understudied group of refugee medical professionals, despite the fact that the subsegments of refugee neurologists and clinical psychoanalysts in the United States, for example, have been a fairly well-investigated population, as the works of Grob (1983), Lunbeck (1995), or Ash and Soellner (1996) have shown. This article is primarily an exploration of the adjustment and acculturation processes of several highly versatile and well-rounded German-speaking physicians, who had received their prior education in neurology, psychiatry, and basic brain research. They were forced out of their academic home institutions and had to leave their clinical research fields as well as their disciplinary self-understanding behind on the other side of the Atlantic.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.027 | 0.022 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".