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Record W2530146815 · doi:10.5195/ahea.2016.263

Hungarian Martyrs, Refugees, and the Politics of Anticommunism in Salazar’s Portugal, 1956–1957

2016· article· en· W2530146815 on OpenAlexaff
Steven Jobbitt

Bibliographic record

VenueHungarian Cultural Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geopolitical and Social Dynamics
Canadian institutionsLakehead University
Fundersnot available
KeywordsRefugeeCommunismBarbarismPoliticsHypocrisyState (computer science)Political scienceIdeologyAuthoritarianismLawPolitical economyEconomic historySociologyHistoryDemocracy

Abstract

fetched live from OpenAlex

This article summarizes the findings of Jobbitt’s early research into the experiences of Hungarian migrants in Portugal after World War II, and the way in which the Hungarian Revolution and its suppression in 1956 was politicized by Prime Minister António de Oliveira Salazar’s Estado Novo [‘New State’]. Recognizing the propagandistic value of the 1956 Revolution and the refugee crisis that it created, the Salazar government celebrated Hungary’s freedom fighters as martyrs while simultaneously painting an idealized and simplistic picture of an honorable Christian nation locked in a fundamentally moral struggle against the civilizational threat posed by Soviet barbarism and communist terror. However, in attempting to align its own political and ideological message with the actions of Hungary’s revolutionaries and the suffering of its refugees, the Salazar regime ran the very real risk of highlighting the numerous contradictions, shortcomings, and injustices that defined the Estado Novo. Ultimately the Salazar regime’s propagandistic support of the Revolution betrayed the hypocrisy of an authoritarian, clerico-fascist state, one that was not only unwilling to accept Hungarian refugees on a long-term basis, but also guilty of suppressing its own people and its non-European colonial subjects.

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.054

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 studies0.0090.010
Scholarly communication0.0040.001
Open science0.0000.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.329
Teacher spread0.293 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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