MétaCan
Menu
Back to cohort

Nazi Medical Research in Neuroscience: Medical Procedures, Victims, and Perpetrators

2016· article· en· W2531206297 on OpenAlexafffundvenue
Aleksandra Loewenau, Paul Weindling

Bibliographic record

VenueCanadian Journal of Health History · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsUniversity of Calgary
FundersUniversity of TorontoEberhard Karls Universität Tübingen
KeywordsNazismDocumentationNationalityWorld War IICriminologyPsychologyPolitical scienceWar crimeLawPsychiatrySociologyInternational lawImmigration

Abstract

fetched live from OpenAlex

Issues relating to the euthanasia killings of the mentally ill, the medical research conducted on collected body parts, and the clinical investigations on living victims under National Socialism are among the best-known abuses in medical history. But to date, there have been no statistics compiled regarding the extent and number of the victims and perpetrators, or regarding their identities in terms of age, nationality, and gender. "Victims of Unethical Human Experiments and Coerced Research under National Socialism," a research project based at Oxford Brookes University, has established an evidence-based documentation of the overall numbers of victims and perpetrators through specific record linkages of the evidence from the period of National Socialism, as well as from post-WWII trials and other records. This article examines the level and extent of these unethical medical procedures as they relate to the field of neuroscience. It presents statistical information regarding the victims, as well as detailing the involvement of the perpetrators and Nazi physicians with respect to their post-war activities and subsequent court trials.

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 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)0.010
metaresearch head score (Gemma)0.004
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.709
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.151
GPT teacher head0.354
Teacher spread0.203 · 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 teacher head, 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

Citations6
Published2016
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Health HistorySame topicMedical History and ResearchFrench-language works237,207