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Record W2102762447 · doi:10.60082/2817-5069.2955

No Refuge: Hungarian Romani Refugee Claimants in Canada

2016· article· en· W2102762447 on OpenAlexaffvenueabout
Sean Rehaag, Julianna Beaudoin, Jennifer Danch

Bibliographic record

VenueOsgoode Hall law journal · 2016
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsWestern UniversityYork University
Fundersnot available
KeywordsRefugeePersecutionContext (archaeology)Political sciencePolitical rhetoricPoliticsRhetoricCriminologyLawSociologyGender studiesHistoryTheologyArchaeology

Abstract

fetched live from OpenAlex

From 2008 to 2012, thousands of Hungarian Roma sought asylum in Canada. Some political actors suggested that their claims were unfounded and demonstrated that Canada’s refugee processes were vulnerable to abuse. In contrast, advocates for refugees argued that persecution against Roma was rampant in Hungary and noted that hundreds of Hungarian Roma were granted refugee status in Canada. Much of this debate has occurred in an evidentiary vacuum. This article fills this vacuum through a qualitative and quantitative study of Hungarian Romani refugee claims. First, the context of the study is discussed. Then, the article explores the experiences of Hungarian Roma within Canada’s refugee determination system between 2008 and 2012. The article ends with concluding remarks, focusing on particularly troubling findings from the study, including the impact of anti-refugee rhetoric, institutional bias, inconsistent decision making, 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)0.003
metaresearch head score (Gemma)0.008
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 score0.069
Threshold uncertainty score0.502

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0530.019
Scholarly communication0.0090.002
Open science0.0030.009
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0040.000

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 head0.038
GPT teacher head0.370
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

Citations29
Published2016
Admission routes3
Has abstractyes

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