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Record W2069946595 · doi:10.1080/1462169x.2012.729978

Jewish Enlightenment (almost) without Haskalah: the Dutch example

2012· article· en· W2069946595 on OpenAlexaboutno aff
Irene Zwiep

Bibliographic record

VenueJewish Culture and History · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHaskalahEnlightenmentJewish identityGermanJudaismHistoryAntisemitismQuarter (Canadian coin)ClassicsLiteratureSociologyJewish studiesPhilosophyTheologyArtArchaeology

Abstract

fetched live from OpenAlex

This contribution offers a comparative perspective on the Prague Haskalah as a movement in its own right, by briefly analysing another tradition that, like Prague, has often been presented as deeply indebted to the project of the Berlin Maskilim: the Dutch Jewish Enlightenment, which flourished during the first quarter of the nineteenth century. Contrary to common opinion, which has always emphasized the German origins of the ‘Dutch Haskalah’, this ‘Haskalah’ was not imported from Berlin but had been inspired first and foremost by contemporary Dutch (Christian) enlightened discourse. Of course one Jew’s Dutch Enlightenment was not the other Jew’s Dutch Enlightenment. To illustrate this, the article briefly compares four ‘enlightened’ publications, i.e. historical biographies, by four prominent Dutch-Jewish intellectuals who operated in the early decades of the nineteenth century. Their varying treatments of Judaism’s role in (universal) history serve to illustrate the complexity of enlightened experience in the Netherlands, where the Jews had received civic equality as early as 1796, thus facing the challenge of building new communal infrastructures and forging a new, at least partly Dutch identity.

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: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.086

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 studies0.0040.003
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.045
GPT teacher head0.264
Teacher spread0.219 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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