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Record W2522496805 · doi:10.1177/0047244116664646

Beyond and behind the Iron Curtain: Sándor Márai crossing the borders between 1946 and 1948

2016· article· en· W2522496805 on OpenAlexaboutno aff
Judit Papp

Bibliographic record

VenueJournal of European Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsIron CurtainOpposition (politics)Western europeHistoryPerspective (graphical)Berlin wallEconomic historyArt historyDemographyMedia studiesPolitical scienceSociologyCold warLawArtVisual artsEconomicsInternational trade

Abstract

fetched live from OpenAlex

The time Sándor Márai (1900–89) spent in Switzerland, France and Italy in the winter of 1946–7 gave him the opportunity to observe and note the differences existing in ‘frozen, destitute Europe’ between East and West, Easterners and Westerners. The diary that Márai had already started to keep in 1943, Föld, föld!…, first published in Hungarian in 1972 in Toronto, and Európa elrablása (1947) represent interesting sources to reconstruct his experiences and thought about a Europe bisected by the Iron Curtain from the perspective of a ‘traveller venturing forth from the ruins of Eastern Europe’. In these works, he shares with us his impressions and depicts Western Europe, as represented by neutral Switzerland, France and a ‘defeated Italy’ in opposition to and in comparison with the East, represented by a ‘dismembered Hungary’. In analysing Márai’s account, the article focuses on the differences he perceived, on the way he reports them and also on how the West and Westerners viewed the East and the Easterners.

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: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.092

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 studies0.0130.008
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.003
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 head0.036
GPT teacher head0.339
Teacher spread0.303 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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