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Record W2125049430 · doi:10.1017/mdh.2014.68

The Strength of a Loosely Defined Movement: Eugenics and Medicine in Imperial Russia

2014· article· en· W2125049430 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMedical History · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEugenicsComputer scienceData scienceWorld Wide WebBiologyGenetics

Abstract

fetched live from OpenAlex

This essay examines the 'infiltration' of eugenics into Russian medical discourse during the formation of the eugenics movement in western Europe and North America in 1900-17. It describes the efforts of two Russian physicians, the bacteriologist and hygienist Nikolai Gamaleia (1859-1949) and the psychiatrist Tikhon Iudin (1879-1949), to introduce eugenics to the Russian medical community, analysing in detail what attracted these representatives of two different medical specialties to eugenic ideas, ideals, and policies advocated by their western colleagues. On the basis of a close examination of the similarities and differences in Gamaleia's and Iudin's attitudes to eugenics, the essay argues that lack of cohesiveness gave the early eugenics movement a unique strength. The loose mix of widely varying ideas, ideals, methods, policies, activities and proposals covered by the umbrella of eugenics offered to a variety of educated professionals in Russia and elsewhere the possibility of choosing, adopting and adapting particular elements to their own national, professional, institutional and disciplinary contexts, interests and agendas.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.889
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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.

Opus teacher head0.026
GPT teacher head0.242
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it