The<i>Mujahideen</i>in Bosnia: the foreign fighter as cosmopolitan citizen and/or terrorist
Bibliographic record
Abstract
This article explores the idea of the Mujahideen in Bosnia as ‘cosmopolitan citizens’. During the Balkan War in the early 1990s, these foreign fighters flocked to Bosnia in order to take up arms alongside those whom they understood to be their besieged Muslim brethren. Although this act of transborder mobilization can be framed as an act of cosmopolitan citizenship, the subsequent ‘problem’ of the Mujahideen in a post-9/11 context destabilized their original cosmopolitan act through a re-enactment of borders and the revocation of their (literal) citizenship. Within the larger post-9/11 narrative, where the Mujahideen must necessarily be understood as terrorists/potential terrorists, they are an interesting point of study in an examination of what can be seen as the sinister side of transnational citizenship, and they expose what Appadurai (A. Appadurai, 2006. Fear of small numbers: an essay on the geography of anger. Durham: Duke University Press.) calls our ‘fear of small numbers’. Particularly compelling is that the post-9/11 Mujahid is an unsympathetic figure, and is always already a questionable candidate for ‘citizenship’ as it is commonly understood. Furthermore, his (sic) original ‘cosmopolitan’ act suggests that, although the ‘cosmopolitan ideal’ is the achievement of a citizenship that transcends or escapes borders, the cosmopolitical must nevertheless be assigned value in order to be ethically intelligible.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.016 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".