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Record W7128235504 · doi:10.1111/sena.70001

Sylheti Diaspora in the United Kingdom: Exceptionalism or Contested Nationalism?

2025· article· en· W7128235504 on OpenAlexaff
A. K. M. Ahsan Ullah, Anabelle Ragsag

Bibliographic record

VenueStudies in Ethnicity and Nationalism · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicBangladesh Politics, Society, and Development
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDiasporaExceptionalismMainstreamNationalismIdentity (music)MulticulturalismContext (archaeology)EthnographyNarrative

Abstract

fetched live from OpenAlex

ABSTRACT This study looks at the Sylheti diaspora in the United Kingdom and examines whether their identity reflects a form of cultural exceptionalism or a contested nationalism. Originating from the Sylhet region of Bangladesh, the Sylheti community has a distinct dialect, customs and heritage that often sets them apart from other Bangladeshi communities. Through qualitative interviews and ethnographic research, we explore the complex narratives surrounding Sylheti identity. Participants revealed a sense of belonging to their Sylheti roots that sometimes contrasts with the broader Bangladeshi identity. This unique perspective can lead to a sense of cultural distinctiveness, even in the context of Bangladesh itself, where Sylheti identity may not always align with the mainstream national narrative. Our findings suggest that the Sylheti diaspora in the United Kingdom embodies a dual identity, with people often identifying as either Sylheti or British, or a combination of both, rather than having a broader Bangladeshi identity. This complex interplay between cultural heritage and national identity leads to an understanding of how diasporic communities manage their identity in a multicultural environment. This research contributes to the wider discourse on diaspora, cultural identity and nationalism and offers insights into the unique experiences of the Sylheti community in the United Kingdom.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.211
GPT teacher head0.449
Teacher spread0.238 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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