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Record W4283164944 · doi:10.33137/wij.v18i1.38910

Women and Witnesses Twice Silenced: Giving a Voice to Holocaust Complicity and Resistance

2022· article· en· W4283164944 on OpenAlexvenueno aff
Ann Lazarsfeld-Jensen

Bibliographic record

VenueWomen in Judaism A Multidisciplinary e-Journal · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicCatholicism and Religious Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSilenceThe HolocaustPersecutionComplicityInjusticeResistance (ecology)ShameCrueltyHistoryLawSociologyGender studiesReligious studiesCriminologyPolitical scienceArtAestheticsPhilosophy

Abstract

fetched live from OpenAlex

Women’s voices had no place in the Third Reich, and the Christian churches agreed: a woman’s place was in the kitchen. After the war, women’s voices frankly discussed the churches’ shame. Some Christians had colluded, others stood silently by, and some of those who resisted the persecution of Jewish converts did not fully understand the injustice and cruelty of socially normalised anti-Semitism. Theologically trained female vicars who had never been permitted to serve the church, stepped into pastoral duties when men were imprisoned, executed, or sent to the front. They took risks to bring spiritual hope to villagers who were fearful, confused, and appalled, by war. Victoria Barnett worked as a journalist in Germany in the 1970s and collected the accounts of Confessing Church members who resisted Hitler, to help expose the moral failures of the holocaust for the evangelical church. When Barnett returned to the US, she began her life’s work in the reconciliation of Christians and Jews. Her books analyse the silence and complicity of ordinary people during the holocaust. They are not easy reading, but her work is important in an age where people still face discrimination, repression and persecution, and institutional silence.

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)0.006
metaresearch head score (Gemma)0.019
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 score0.023
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0230.022
Scholarly communication0.0110.008
Open science0.0020.010
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0050.001

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 head0.021
GPT teacher head0.247
Teacher spread0.226 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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