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Record W2099887683 · doi:10.5539/res.v3n2p2

Roma Minorities in Post-Communist Bulgaria and the U.S. Visa Regime

2011· article· en· W2099887683 on OpenAlexvenueno aff
Rossen Petkov, Atanaska Mindevska

Bibliographic record

VenueReview of European Studies · 2011
Typearticle
Languageen
FieldHealth Professions
TopicRomani and Gypsy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCommunismPolitical sciencePolitical economyLawSociologyPolitics

Abstract

fetched live from OpenAlex

The inclusion in the Visa Waiver Programme (VWP) would mean more favourable development of the relationships between Bulgaria and the USA. It would also serve as recognition of the economic, political and social stability of the country. However, membership in the program is not automatic. In the past, Bulgaria has made significant progress, but there are still pending areas that hinder the finalization of the process. Specifically, Bulgaria is facing very difficult issues with its minority Roma population and its integration within its boundaries. In this paper, we will evaluate the Roma’s socio-economic difficulties that they have to deal with, specifically as workers in this region. In order to complete the task, we would evaluate the historical background of the Bulgarian Roma. Specifically, we would analyse the political movement post-communism as it relates to the VWP. We believe that Bulgaria needs to support its minority Roma population and such social reforms would help the country to establish itself and to help enter into the VWP list. Bulgaria could implement programs in relationships with the “other 3 EU Member omitted States” and together work towards the inclusion in the US Visa Waiver Programme and resolution of its population issues. We believe that a coordinated strategy would help all the member states and would solve the issue in the shortest possible time and help the country enter the VWP quicker.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.574
Threshold uncertainty score0.428

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.142
GPT teacher head0.407
Teacher spread0.266 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreReview

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
Published2011
Admission routes1
Has abstractyes

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