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History of the Jews in Modern Times

2000· book· en· W4388377032 on OpenAlexaboutno aff
Lloyd P. Gartner

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsJudaismEnlightenmentEmancipationHistorySubject (documents)TerminologyQuarter (Canadian coin)Jewish historyClassicsLiteratureAncient historyArtPoliticsJewish studiesLawPhilosophyPolitical scienceTheologyArchaeologyLibrary science

Abstract

fetched live from OpenAlex

Abstract Lloyd Gartner presents, in chronologically-arranged chapters, the story of the changing fortunes of the Jewish communities of the Old World (in Europe and the Middle East and beyond) and their gradual expansion into the New World of the Americas. The book starts in 1650, when there were no more than one and a quarter million Jews in the world (less than a sixth of the number at the start of the Christian era). Gartner leads us through the traditions, religious laws, communities and their interactions with their neighbours, through the Enlightenment, the French Revolution, and into Emancipation, the dark shadows of anti-Semitism, the impact of World War II, bringing us up to the twentieth century through Zionism, and the foundation of Israel. Throughout, the story is powerful and engrossing - enlivened by curious detail and vivid insights. Gartner, an expert guide and scholar on the subject, writing from within the Jewish community, remains objective and effective whilst being careful to introduce and explain Jewish terminology and Jewish institutions as they appear in the text. This is a superb introductory account - authoritative, in control, lively of the central threads in one of the greatest historical tapestries of modern times.

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)0.001
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 score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.006
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.031
GPT teacher head0.247
Teacher spread0.216 · 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

Citations22
Published2000
Admission routes1
Has abstractyes

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