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Record W2936670558 · doi:10.5744/bi.2019.1002

Equality after Death: The Dissection of the Female Body for Anatomical Education in Nineteenth-Century England

2019· article· en· W2936670558 on OpenAlexaff
Jenna M. Dittmar, Piers D. Mitchell

Bibliographic record

VenueBioarchaeology International · 2019
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsArthur B. McDonald-Canadian Astroparticle Physics Research Institute
Fundersnot available
KeywordsDissection (medical)Dead bodyHistoryMedicineGender studiesAnatomySociologyAutopsyPathology

Abstract

fetched live from OpenAlex

Since the medieval period, anatomical dissection has been considered a cornerstone of medical education. In recent decades, several archaeological excavations have uncovered evidence of this practice in the form of tool marks on human skeletal remains. At the majority of sites where dissected individuals were uncovered, remains of men considerably outnumbered those of women. The aim of this research is to investigate how postmortem treatment of medicalized bodies differed according to sex during the nineteenth century. To assess differences in treatment, the skeletal remains of dissected adult male (n = 74) and female (n = 25) individuals from the Royal London Hospital and the University of Cambridge were analyzed both macro-and microscopically. The location and orientation of the tool marks were recorded, and silicone molds (n = 41) of selected tool marks were analyzed using scanning electron microscopy. The assessment of the tool marks revealed no differences in how the bodies of men and women were dissected, nor were there any differences in the tools used. This finding suggests that the sociopolitical status of women, which necessitated their protected treatment during life, shifted drastically after death. Rather than a preference to dissect male bodies, the sex disparity in the archaeological record can be explained by the social roles of women, which made it less likely that they would die in hospitals or remain unclaimed from workhouses. However, the bodies of women that were dissected were not viewed as fragile or afforded protected status by anatomists, as they were dissected in the same manner as the bodies of men. Depuis la période médiévale, la dissection anatomique a été considérée comme un des fondements de l’éducation en médecine. Durant les dernières décennies, un nombre d’excavations archéologiques a mis en évidence cette pratique sous forme de marques laissées par les instruments sur les restes de squelettes humains. Sur la plupart des sites où l’on a découvert des individus ayant été disséqués, les hommes étaient considérablement plus nombreux que les femmes. Le but de cette recherche est d’examiner la façon dont le traitement post-mortem des corps médicalisés différait selon leur genre durant le XIXe siècle. Pour évaluer les différences de traitement, les restes de squelettes disséqués d’individus masculins (n = 74) et féminins (n = 25) du Royal London Hospital et de l’Université de Cambridge ont été analysés de façon micro et macroscopique. L’endroit et l’orientation des marques laissées par les instruments ont été enregistrés et les moulages en silicone (n = 41) des marques d’instrument sélectionnés ont été analysés en utilisant un microscope électronique à balayage. L’examen des marques laissées par les instruments (tool marks) n’a révélé aucune différence dans la façon dont les corps masculins et féminins étaient disséqués. Aucune différence d’instruments utilisés pour ces dissections n’a été constatée. Cela suggère que le statut socio-politique des femmes, qui nécessitait un traitement de protection durant leur vie, changeait radicalement après la mort. Plutôt qu’une préférence pour la dissection des corps masculins, la disparité des genres dans les archives archéologiques peut être expliquée par les rôles sociaux des femmes, qui rendaient moins probable le fait de mourir à l’hôpital ou de demeurer non réclamées aux hospices. Cependant, les corps de femme qui étaient disséqués n’étaient pas vus comme fragiles ou ne se voyaient pas accorder un statut de protection par les anatomistes, puisqu’ils les disséquaient de la même manière que les corps d’hommes.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.332
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2019
Admission routes1
Has abstractyes

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