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Record W4400211880 · doi:10.14746/ssp.2024.1.11

Hungarian Refugees in the United Kingdom in the Context of the Domestic Policy (1956–1957)

2024· article· en· W4400211880 on OpenAlexaboutno aff
Tadeusz Kopyś

Bibliographic record

VenueŚrodkowoeuropejskie Studia Polityczne · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeContext (archaeology)Political scienceKingdomEconomic growthPoliticsEconomic shortageDisplaced personDevelopment economicsGeographyLawEconomicsGovernment (linguistics)

Abstract

fetched live from OpenAlex

After the suppression of the 1956 uprising in Hungary, a large group of political refugees, most of them young and often highly skilled professionals, left for the West. Most of the refugees fled to Austria. Austria immediately called on countries to help both financially and physically by resettling the refugees. Most of the refugees were very quickly resettled in other countries. These facts stand in stark contrast to contemporary resettlement practice, which is characterized by a shortage of resettlement sites and a small number of resettlement countries. The scarcity of jobs and the peculiarities of the migration policies of some countries (e.g., the United Kingdom) meant that some refugees could not find a long-term place in European countries and therefore sought refuge overseas. In 1956 and 1957, Canada took in more than 37,500 Hungarian refugees. The United States was also a more common c Hungarian Refugees in the United Kingdom in the Context hoice for refugees than the United Kingdom, for example.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.536

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 studies0.0030.002
Scholarly communication0.0030.001
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.050
GPT teacher head0.382
Teacher spread0.332 · 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 designQualitative
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
Published2024
Admission routes1
Has abstractyes

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