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Record W3021285749 · doi:10.1558/rsth.40909

Minyan in Daniel Deronda

2020· article· en· W3021285749 on OpenAlexaff
Michael Greenstein

Bibliographic record

VenueReligious Studies and Theology · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsJudaismPlot (graphics)PortraitFreudian slipLiteratureJewish identityDiasporaVariety (cybernetics)Identity (music)HistoryGeorge (robot)Jewish studiesPhilosophyArtArt historyAestheticsPsychoanalysisTheologyArchaeology

Abstract

fetched live from OpenAlex

George Eliot’s final novel, Daniel Deronda (1876), is arguably her finest achievement. Deftly combining the plot of Gwendolen Harleth’s provincial English life with the Jewish plot involving Deronda’s hidden identity, Eliot’s fiction advances in new directions. After studying Jewish history and philosophy for a number of years, Eliot turned to “the other” in her writing, reaching out to a Jewish minority in the Diaspora, which was trying to finds its place in modern European society. Her multiple portraits of Jews across Europe are realistic and idealistic, extending back to the past and projecting to the future. Challenging Victorian taboos, Eliot’s novel is both proto-Zionist and proto-Freudian. Exposing her nineteenth-century readers to a variety of Jewish characters, she paves the way for twentieth-century writers to explore further the nuances of Jews and Judaism. Her radical and experimental techniques, hidden within traditional prose, continue to resonate in the twenty-first century, with its greater understanding of double plots.

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 score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.004
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.041
GPT teacher head0.311
Teacher spread0.270 · 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
Published2020
Admission routes1
Has abstractyes

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