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Record W2992278608 · doi:10.5539/res.v11n4p78

The Securitization of the European Migrant Crisis - Evidence From Bulgaria and Hungary (2015-2017)

2019· article· en· W2992278608 on OpenAlexvenueno aff
Tatiana P. Rizova

Bibliographic record

VenueReview of European Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Security and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsEuropean unionPolitical scienceBulgarianGovernment (linguistics)RefugeeRhetoricLawEconomicsEconomic policy

Abstract

fetched live from OpenAlex

Conflicts in Afghanistan, Iraq, and Syria over the past fifteen years have produced the largest waves of displaced people and refugees since World War II. As European Union (EU) leaders braced for an influx of thousands of people fleeing from these conflicts, they faced pressures to revisit and modify legal rules that left countries in Southeastern Europe and the Mediterranean unable to cope with a crisis of unprecedented proportions in the twenty-first century. While the logistical challenges of this humanitarian disaster threatened to undermine Southeastern and Mediterranean states’ capacity, multiple terrorist attacks across Europe magnified the security concerns of EU leaders. This paper compares how two of the European Union’s newest member states – Bulgaria and Hungary – have tackled the migrant crisis and assesses the impact of security concerns on their refugee policies. Some of the responses of these countries’ governments were similar – both governments mandated the erection or extension of physical barriers to impede migrants’ entry on their countries’ territory. While the Bulgarian government took cues from the rhetoric and actions of key EU leaders such as Angela Merkel, the Hungarian government continuously antagonized EU leaders and declined to cooperate with their proposed multi-lateral strategies of handling the migrant crisis. Decisions taken by the two governments were, to some extent, dictated by security concerns. The rhetoric of the Hungarian government, however, contained stronger nationalist overtones than that of the Bulgarian government. Hungary’s Prime Minister Viktor Orbán and his right-wing government led an anti-migrant and anti-refugee campaign that sought to exclude foreign nationals due to the patent incompatibility of their cultural values with those of Hungary’s nationals. On the other hand, the rhetoric of Bulgaria’s Prime Minister – Boiko Borisov – was more dualistic and contradictory. His policy statements to the foreign press or at EU summits reflected the general sentiment of the top EU brass, whereas statements made to the Bulgarian media focused more specifically on security concerns and were far more critical of the foreign nationals attempting to enter Bulgaria’s territory. Moreover, the security-focused rhetoric and actions of the government became more strident immediately before and after the Bulgarian presidential elections of November 2016, which led to the resignation of Borisov’s cabinet. Political parties in Bulgaria, including Borisov’s GERB party have increasingly become critical of refugees living in Bulgaria’s admission centers. Borisov’s government even extradited a group of Afghan asylum seekers due to their involvement in a riot at one of the refugee admission centers. This study is based on a content analysis of statements made by Bulgarian and Hungarian government officials and media coverage in several Bulgarian and Hungarian news publications between 2015 and 2017.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.055
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0040.002
Open science0.0010.004
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 head0.049
GPT teacher head0.354
Teacher spread0.305 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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