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Record W7161034029 · doi:10.1017/s0026749x25101236

The making of transnational Islamic networks in early Cold War South Korea

2025· article· en· W7161034029 on OpenAlexaff
Janice Hyeju Jeong

Bibliographic record

VenueModern Asian Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicChina's Ethnic Minorities and Relations
Canadian institutionsSimon Fraser University
FundersHarvard University
KeywordsIslamMuslim communityContext (archaeology)ChinaGovernment (linguistics)CivilizationPeninsulaNarrative

Abstract

fetched live from OpenAlex

Abstract The Korean Peninsula is often neglected in investigations on Islam in East Asia. The region already occupies the conceptual peripheries of studies on Muslim societies. During the two decades after the Korean War (1950–1953), however, Seoul hosted a small yet active community of Korean Muslim converts and visitors from places such as Malaysia/Singapore, Pakistan, Turkey, and Saudi Arabia. The early Korean Muslim leaders, some of whom first encountered Islam in Japanese-occupied Manchuria, attempted to plug themselves into transnational Islamic networks and politics in the transformed context of the Cold War. Internally, Korean Muslim leaders advocated for the utility of Islam as a diplomatic resource for the South Korean government in the struggle against communism, thereby reformulating pre-war articulations of Islam policy that had circulated across China and Japan, as well as narratives on unified Islamic civilization with an inherent cultural essence. Externally, they forged educational and philanthropic networks by connecting with Muslim diasporic figures in the East and Southeast Asian sphere, such as Ibrahim Omar al-Saqqāf, the Hadrami Arab consul of the Saudi consulate in Singapore and an agent of the World Muslim League in Mecca. By situating the emergent Korean Muslim community in Seoul within a regional and trans-regional religio-political nexus, this article repositions it as having formed through encounters with modern state(s) and power, and through interactions with Muslim diasporic agents who (re-)directed post-war mobility channels.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.026
GPT teacher head0.322
Teacher spread0.295 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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