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Record W2088788300 · doi:10.1177/0888325411398910

Polish-Ukrainian Relations during World War II

2012· article· en· W2088788300 on OpenAlexaff
Piotr Wróbel

Bibliographic record

VenueEast European Politics and Societies and Cultures · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicPolish Historical and Cultural Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsUkrainianWorld War IICommunismSpanish Civil WarPolitical scienceEconomic historyHistorySociologyLawPoliticsPhilosophy

Abstract

fetched live from OpenAlex

After the fall of communism in 1989–1991, Poland and Ukraine could have become partners in international, economic, and cultural fields. Yet despite many positive achievements, the contemporary Polish-Ukrainian cooperation did not fully develop. Among many reasons that slow down the Polish-Ukrainian rapprochement, historical memories seem to be especially detrimental. The remembrances of World War II are the most destructive. Both Poles and Ukrainians understand that the only way to change this situation is to study and discuss the common history. A list of works on Polish-Ukrainian relations during World War II is long. Yet most of these publications offer broad pictures and present Polish-Ukrainian relations in general or in particular regions, such as Volhynia (Wołyń) or Eastern Galicia. This microstudy, devoted to the town of Boryslav (Borysław) in the years 1939 to 1945, tries to show how the conflicts were born, how they became embedded in human memory, and, finally, how they were transformed into historical stereotypes. The text concentrates on the crucial moments of World War II in Boryslav and describes how Poles and Ukrainians reacted differently to the consecutive challenges and how these various reactions shaped their relationship. The article ends with a conclusion that the five years of the war tore apart the Poles and Ukrainians of Boryslav and the post-1945 iron Polish-Soviet border divided the both sides and created a situation in which World War II attitudes froze for a long time.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.801
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.253
Teacher spread0.234 · 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.

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
Published2012
Admission routes1
Has abstractyes

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