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Record W4402892874 · doi:10.1002/waf2.12043

Exclusion and persecution: The Rohingya crisis through the lens of nationalism, statelessness, and violence

2024· article· en· W4402892874 on OpenAlexaff
Rifat Darina Kamal, Z. R. M. Abdullah Kaiser, Kad Mariano

Bibliographic record

VenueWorld Affairs · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsYork University
Fundersnot available
KeywordsPersecutionStatelessnessNationalismPolitical scienceRefugeeBandicootCriminologySociologyLawBiologyImmigrationNationality

Abstract

fetched live from OpenAlex

Abstract The brutal military crackdown in Myanmar's Rakhine state caused more than 1 million Rohingya refugees to flee to Bangladesh. By analyzing the tripartite relationship between nationalism, violence, and statelessness, this commentary examines how Myanmar's political exclusion of the Rohingya contributed to their stateless condition and led to an ongoing humanitarian crisis in the region. The study argues that the Rohingya are stateless because of Myanmar's state‐sanctioned ethnic discrimination premised on nationalist conceptions of the country as a uniquely Burmese and Buddhist nation‐state. The state systematically justifies the Rohingya's precarity within Myanmar society to promote an imagined national homogeneity.

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)0.001
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 score0.013
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.028
Scholarly communication0.0070.006
Open science0.0010.006
Research integrity0.0030.004
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 head0.018
GPT teacher head0.296
Teacher spread0.278 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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