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Record W2485338994 · doi:10.1057/9781403937339_9

The Renascence of Hebrew and Jewish Nationalism in the Tsarist Empire 1881–1917

2003· book-chapter· en· W2485338994 on OpenAlexaff
David Aberbach

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2003
Typebook-chapter
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsHaskalahEmpireNationalismReactionaryJudaismHebrewEmancipationPolitical scienceEnlightenmentJewish literatureHistoryReligious studiesPoliticsJewish studiesClassicsLawPhilosophyTheology

Abstract

fetched live from OpenAlex

In previous chapters, we have explored the secularization of Hebrew in a long-term framework including medieval Spain and the French Enlightenment. This chapter considers in greater detail a narrower and in some ways more striking change: the point at which modern Hebrew literature emerged as art, between the outbreak of the pogroms in 1881 and the 1917 revolution. This renascence is arguably the most important development in Jewish culture since the Bible. Hebrew literature was the main cultural spur to the rise of modern Jewish nationalism. The Russian Jewish population prior to 1881 had been moving toward increased acculturation within the Tsarist empire and had hopes of emancipation and civil rights. They were deeply wounded, psychologically as well as economically, by Russian government policies legislated in a futile reactionary struggle to adapt to major changes in socio-economic conditions and the international balance of power. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.274
Teacher spread0.243 · 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
GenreOther

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
Published2003
Admission routes1
Has abstractyes

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