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Record W2376784907 · doi:10.7227/hrv.2.1.3

Symbolically burying the six million: post-war soap burial in Romania, Bulgaria and Brazil

2016· article· en· W2376784907 on OpenAlexfundno aff
Joachim Neander

Bibliographic record

VenueHuman Remains and Violence An Interdisciplinary Journal · 2016
Typearticle
Languageen
FieldPsychology
TopicMemory, Trauma, and Commemoration
Canadian institutionsnot available
FundersYork University
KeywordsLegendJudaismSOAPThe HolocaustAncient historyHistoryWorld War IIArtArt historyLawArchaeologyPolitical science

Abstract

fetched live from OpenAlex

During the Second World War and its aftermath, the legend was spread that the Germans turned the bodies of Holocaust victims into soap stamped with the initials RIF, falsely interpreted as made from pure Jewish fat. In the years following liberation, RIF soap was solemnly buried in cemeteries all over the world and came to symbolise the six million killed in the Shoah, publicly showing the determination of Jewry to never forget the victims. This article will examine the funerals that started in Bulgaria and then attracted several thousand mourners in Brazil and Romania, attended by prominent public personalities and receiving widespread media coverage at home and abroad. In 1990 Yad Vashem laid the Jewish soap legend to rest, and today tombstones over soap graves are falling into decay with new ones avoiding the word soap. RIF soap, however, is alive in the virtual world of the Internet and remains fiercely disputed between believers and deniers.

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)0.003
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 score0.094
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0080.011
Scholarly communication0.0030.001
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.348
Teacher spread0.324 · 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
Published2016
Admission routes1
Has abstractyes

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