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The victims of unethical human experiments and coerced research under National Socialism

2015· article· en· W2220896837 on OpenAlexaff
Paul Weindling, Anna von Villiez, Aleksandra Loewenau, Nichola Farron

Bibliographic record

VenueEndeavour · 2015
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of Calgary
FundersArts and Humanities Research CouncilWellcome TrustWellcome
KeywordsNazismGermanPsychologyPoint (geometry)CriminologyPolitical scienceLawHistoryMathematicsArchaeology

Abstract

fetched live from OpenAlex

There has been no full evaluation of the numbers of victims of Nazi research, who the victims were, and of the frequency and types of experiments and research. This paper gives the first results of a comprehensive evidence-based evaluation of the different categories of victims. Human experiments were more extensive than often assumed with a minimum of 15,754 documented victims. Experiments rapidly increased from 1942, reaching a high point in 1943. The experiments remained at a high level of intensity despite imminent German defeat in 1945. There were more victims who survived than were killed as part of or as a result of the experiments, and the survivors often had severe injuries.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.125
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.125
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0050.019
Scholarly communication0.0050.007
Open science0.0010.006
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.703
GPT teacher head0.707
Teacher spread0.004 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations105
Published2015
Admission routes1
Has abstractyes

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