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Record W2607163840 · doi:10.1080/13576275.2017.1310093

Reassessing the pauper burial: the disposal of corpses in nineteenth-century Brussels

2017· article· en· W2607163840 on OpenAlexfundno aff
Jolien Gijbels

Bibliographic record

VenueMortality · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsnot available
FundersFonds Wetenschappelijk OnderzoekUniversity of WaterlooUniversity of Alabama Health Services Foundation P.C.
KeywordsIdeologyLawSociologyDead bodyHistoryAncient historyArchaeologyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

In this article, I examine the changing disposal of pauper corpses in the nineteenth-century hospitals of Brussels. I argue that the end of the century witnessed a growing focus on the individuality of the pauper corpse. Research into hospital records has revealed the significance of the ideological struggles between Catholics, liberals and socialists from the 1860s onwards, as a result of which the indifferent attitude of hospital administrators regarding dead patients and relatives was increasingly contested. Acts and complaints by the local authorities, mutualist burial societies and relatives brought about improvements in the material conditions of the pauper burial. My analysis of this debate shows that the ideological conflicts regarding Catholic and civil burials, as well as the introduction of new burial standards within hospitals, led to a greater emphasis on the burial desires of the dead. Yet, I argue that this attention towards the individual pauper corpse was only deemed necessary if close family members or burial societies stood up for the fulfilment of the dying wishes of the dead. Poor hospital patients without such social relationships could not prevent an anonymous anatomy burial.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0150.020
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0020.003
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 head0.060
GPT teacher head0.284
Teacher spread0.224 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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