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Record W4408301257 · doi:10.1002/ase.70001

From body to image—Pernkopf's anatomical gaze and eyewitness accounts on the process of creating images from Nazi victims' bodies

2025· article· en· W4408301257 on OpenAlexaff
Sabine Hildebrandt, Claudia Krebs

Bibliographic record

VenueAnatomical Sciences Education · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicMedical History and Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNazismGazePsychologySociologyVisual artsHistoryArtPsychoanalysisArchaeology

Abstract

fetched live from OpenAlex

The Pernkopf atlas is a well-known case study of anatomists' ethical transgressions in using bodies of Nazi victims for professional purposes and the relevance of this history for today. This study examines the likely sources from which Pernkopf developed his own anatomical gaze and pedagogical approach to depicting the human body. It also describes how he inserted himself in the process of creating images from human bodies, including those of executed Nazi victims. Eyewitness accounts allow a reconstruction of the workflow and an understanding of others involved, including morgue technicians, anatomists, work-study students, and illustrators. Also, it appears likely from these accounts that more bodies were needed than the number of 400 images created during the war years suggests, as often several copies of the same dissection, and thus several bodies, were needed for the painting of one image. An analysis of these processes is relevant as Pernkopf was not alone in his use of Nazi victims for anatomical representations. A study of his approach and processes may also shed light on the creation of other 20th century anatomical works from Nazi Germany and its annexed or occupied territories. Notably, the Spanner-Spalteholz atlas has a similar history of ethical transgressions, and the procedural steps identified here for the Pernkopf atlas may inform further studies of the Spanner-Spalteholz history. Going forward, these historical analyses can contribute to the development of history-informed and ethically grounded principles in the creation of innovative anatomical images, especially within emerging new technologies.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.337
Teacher spread0.318 · 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 designTheoretical or conceptual
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

Citations2
Published2025
Admission routes1
Has abstractyes

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