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Record W2103086183 · doi:10.1093/qje/qjr018

Social Structure and Development: A Legacy of the Holocaust in Russia

2011· article· en· W2103086183 on OpenAlexaff
Daron Acemoğlu, Tarek A. Hassan, James A. Robinson

Bibliographic record

VenueThe Quarterly Journal of Economics · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsBooth University College
Fundersnot available
KeywordsThe HolocaustPersecutionNazismPoliticsWorld War IISoviet unionHolocaust survivorsPolitical scienceEuropean unionDevelopment economicsPolitical economyEconomyEconomic historyGeographyEconomicsLawEconomic policy

Abstract

fetched live from OpenAlex

We document a statistical association between the severity of the persecution, displacement and mass murder of Jews by the Nazis during World War II and long-run economic and political outcomes within Russia. Cities that experienced the Holocaust most intensely have grown less, and both cities and administrative districts (oblasts) where the Holocaust had the largest impact have worse economic and political outcomes since the collapse of the Soviet Union. We provide evidence that the lasting impact of the Holocaust may be attributable to a permanent change it induced in the social structure across different regions of Russia.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.260
Teacher spread0.203 · 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 designObservational
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

Citations268
Published2011
Admission routes1
Has abstractyes

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