Hormones and the Bolsheviks: From Organotherapy to Experimental Endocrinology, 1918–1929
Bibliographic record
Abstract
The discipline of endocrinology emerged over roughly the same period in Britain, France, Germany, Russia, the United States, and elsewhere, and its practitioners across the world shared research practices and agendas to a considerable degree. Yet the discipline's institutions, networks, and social practices were firmly embedded in the particular social fabric of concrete locales, and they were built on specific local traditions, resources, and patronage. Through analysis of the origins and early progress of Soviet endocrinology, this essay uncovers numerous factors and multiple actors involved with the institutional development of the discipline in the first decade of Bolshevik rule. As elsewhere in the world, the medicinal use of animal tissue extracts--organotherapy--paved the way for wide acceptance of the ideas of the nascent science of endocrinology by both the Soviet medical community and the general public. Organotherapy also supplied the new discipline with "seed" institutions, technologies, and personnel--the veterinarian Iakov Tobolkin and the therapist Vasilii Shervinskii. But the specific institutional, political, economic, and ideological landscape of Soviet Russia shaped the discipline in a particular way.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.041 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".