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Record W2038787965 · doi:10.1515/asch.2006.103

Vilna on the Spree: Yiddish in Weimar Berlin

2007· article· en· W2038787965 on OpenAlexaboutno aff
Gennady Estraikh

Bibliographic record

VenueAschkenas · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean history and politics
Canadian institutionsnot available
Fundersnot available
KeywordsJudaismGermanProletariatQuarter (Canadian coin)Ancient historyYiddishHistoryEconomic historyEthnologySociologyPolitical scienceLawArchaeologyPolitics

Abstract

fetched live from OpenAlex

Yiddish-speakers, or Ostjuden (Eastern [European] Jews), who built a visible minority in the-turn-of-the-twentieth-century Berlin, usually migrated to the Kaiserreich capital from the then German territory of Posen (Poznan) as well as from Russian and Austro-Hungarian Poland. In Berlin, they would settle in the proletarian East of the city, most notably in the Scheunenviertel (Barn Quarter), the slum quarter »a few blocks northeast of Alexanderplatz, bounded by Linienstrasse to the north, Oranienburgerstrasse to the west and south and Landsberger Allee to the east.« The Scheunenviertel, however, never became a Jewish ghetto in the true sense of the word, because Ostjuden lived there together with other outsiders twice over – non-German and foreign-born. In addition, absorption of Jewish newcomers usually faced less problems in Berlin than, for example, in Vienna. Although thousands of full-bearded »caftan Jews« and their families never acquired assets for social mobility and stayed put in the Alexanderplatz area, many others would work their way up from the lowest rung on the social ladder and move to more elegant districts, including Charlottenburg, merging there with »real« Western Jews.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.948
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.034
GPT teacher head0.305
Teacher spread0.272 · 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 teacher head, 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

Citations3
Published2007
Admission routes1
Has abstractyes

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