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Record W1989070510 · doi:10.3200/symp.62.3.193-206

Irène Némirovsky's<i>David Golder</i>and the Myth of the Jew

2008· article· fr· W1989070510 on OpenAlexaff
Michael Tritt

Bibliographic record

VenueSymposium A Quarterly Journal in Modern Literatures · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicGerman legal, social, and political studies
Canadian institutionsMarianopolis College
Fundersnot available
KeywordsMythologyCharacter (mathematics)JudaismCredibilityCharacter traitsReligious studiesLiteratureArtArt historyHistoryPhilosophyTheologyPsychologySocial psychologyEpistemology

Abstract

fetched live from OpenAlex

The extent to which Irène Némirovsky's David Golder incorporates specific and, in some instances, centuries-old Jewish stereotypes has not been acknowledged. Although the title character is, at times, more realistically depicted than the rapacious money-man of myth, his credibility is irremediably undermined by the myriad stereotypical traits attributed to him. Golder's portrayal and that of the many other Jewish characters in the novel, who are even less well developed than he, reinforce and perpetuate the myth of the Jew that has evolved in literature and art through the ages.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.010
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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 designNot applicable
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

Citations0
Published2008
Admission routes1
Has abstractyes

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Same venueSymposium A Quarterly Journal in Modern LiteraturesSame topicGerman legal, social, and political studiesFrench-language works237,207