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Record W2155759977 · doi:10.1353/gsp.2011.0030

Value Hierarchies of Holocaust Rescuers and Resistance Fighters

2008· article· en· W2155759977 on OpenAlexafffundvenue
Peter Suedfeld, Stefanie de Best

Bibliographic record

VenueGenocide Studies and Prevention · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsThe HolocaustResistance (ecology)NazismMemoirOpposition (politics)Openness to experienceValue (mathematics)SociologySocial psychologyPsychologyLawPolitical science

Abstract

fetched live from OpenAlex

There has been considerable theorizing and research on the motivations of individuals who rescued Jews from the Nazi Holocaust. Participants in armed resistance movements, the other major form of active opposition within Nazi-dominated Europe, have attracted less scientific attention. The study reported here compared members of these two groups using a quantitative measure applied to their own post-war memoirs and interviews. Thematic content analysis was used to score the relative strengths of eleven major value categories in materials produced by forty-seven members of resistance movements and fifty Holocaust rescuers. Benevolence, Universalism, and Spirituality were significantly higher among rescuers than among resistance fighters, with the opposite pattern for Security. There were some gender differences, but no differences based on country of residence. Comparisons with Schwartz's international norm group results are also presented, and the implications of this research with respect to altruism in extreme circumstances are discussed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.067
GPT teacher head0.372
Teacher spread0.305 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2008
Admission routes3
Has abstractyes

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