Bibliographic record
Abstract
Arguing for more conceptual specificity regarding the term “Muslim diaspora,” this article identifies two conflation problems in the scholarship on Muslim immigrants. First, the immigrants’ “Muslimness,” which refers to the signifiers, thought-processes, discourses, and actions that others perceive to be associated with Islam, is often conflated with the immigrants being “Muslims”—i.e., members of a discrete, bounded group supposedly different from non-Muslims. Second, Muslims’ transnational engagements—meaning, their cross-border ties between exclusively the sending and receiving countries—are often conflated as being diasporic—connections targeted towards other Muslims abroad motivated by a sense of religious solidarity. Consequently, researchers have been largely unable to distinguish Muslims’ religious performance from an ethnic one and have taken Muslims’ immigrant transnationalism as evidence of an emerging “Muslim” “diasporic” consciousness. This article parses existing scholarship on Muslim immigrants in the West and offers a new way of conceptualizing “Muslim diaspora” to move past these ambiguities. It offers the concept of “heartland”—distinct from immigrants’ “homeland”—to better distinguish Muslims’ religion-based diasporic expressions from their ethnicity based transnational ones.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".