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Record W3156787403 · doi:10.26443/jiows.v4i2.81

An Imagined Diaspora: The making of Shi'i Muslim ethnicity in Sri Lanka

2021· article· en· W3156787403 on OpenAlexvenueno aff
Harun Rasiah

Bibliographic record

VenueThe Journal of Indian Ocean World Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Geopolitics and Ethnography
Canadian institutionsnot available
Fundersnot available
KeywordsDiasporaHomelandSolidarityIslamPoliticsEthnic groupMuslim communityGender studiesSri lankaConsciousnessSociologySouth asiaGeographyPolitical scienceEthnologyAnthropologyLawArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

The contemporary formation of a community of Shi’i Muslims provides a window into the making and unmaking of ethnicity in Sri Lanka. Originating in solidarity with the Islamic revolution of Iran, Sunni activists formed a political network which has evolved into an autonomous Shi’i religious community. Members studied the traditional Islamic disciplines in the institution of learning (hawza ‘ilmiyya) in Qom alongside students who had undergone a similar transformation, fortifying an internationalist outlook. With associates in the Indian Ocean region, particularly the Gulf states, the transregional community is bound by the common thread of Shi’ism and focuses on Iran and the ‘Atabat of Iraq as spiritual homeland. Exploring the “diasporic consciousness” of the community, this article focuses on the transmission of ideas in time and space. Temporally, it emphasizes claims to local Muslim heritage in variant readings of the Sri Lankan past. Spatially, their cartography provides an alternative account of the sacred landscape based on scholarly practice, devotional activity and political contestation. By recounting the history and mapping the geography of the Shi’i Muslim community, this article investigates how Shi’ism influences the configuration of a diasporic field.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.025
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.048
GPT teacher head0.377
Teacher spread0.329 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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