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Record W3121185995

No Refuge: Hungarian Romani Refugee Claimants in Canada

2016· article· en· W3121185995 on OpenAlexaffabout
Julianna Beaudoin, Jennifer Danch, Sean Rehaag

Bibliographic record

VenueeYLS (Yale Law School) · 2016
Typearticle
Languageen
FieldHealth Professions
TopicRomani and Gypsy Studies
Canadian institutionsYork University
Fundersnot available
KeywordsRefugeePersecutionContext (archaeology)Political sciencePolitical rhetoricPoliticsRhetoricCriminologyGender studiesSociologyLawHistoryTheologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

From 2008 to 2012, large numbers of Hungarian Romani refugee claimants came to Canada. Their arrival was controversial. Some political actors suggested that their claims were unfounded and amounted to abuse of Canada’s refugee processes -- abuse which could only be prevented through wide-scale reforms to the refugee determination system. Many advocates for refugees, by contrast, argued that persecution against Roma was rampant in Hungary and noted that hundreds of Hungarians had been recognized as refugees in Canada. Some went further and contended that Romani refugee claimants fled persecution in Hungary only to be confronted with similar mistreatment in Canada. Unfortunately, much of the debate about Hungarian Romani refugee claims in Canada has occurred in an evidentiary vacuum. The purpose of this article is to fill this vacuum by setting out the results of a quantitative and qualitative empirical study of Hungarian Romani refugee claims. The article begins by discussing the context of the study, offering an overview of the historic and contemporary experience of Roma in Hungary and outlining the history of Hungarian Romani migration to Canada, including two recent streams of migration by Hungarian Romani refugee claimants and Canada’s response to these claimants. The article then moves on to an empirical study about the experience of Hungarian Romani with Canada’s refugee determination system between 2008 and 2012. Finally, the article offers concluding remarks, focusing on several particularly troubling findings from the study, including the impact of anti-refugee rhetoric, concerns about institutional bias and inconsistent decision making at the Immigration and Refugee Board, and problems related to quality of counsel.

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)0.005
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 score0.059
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0440.015
Scholarly communication0.0080.002
Open science0.0030.008
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.318
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

Citations10
Published2016
Admission routes2
Has abstractyes

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