A Poetics of Chaos: Spatial Metaphors in Leila Aboulela’s The Translator and Minaret
Bibliographic record
Abstract
While contemporary culture seems to valorize unbounded mobility as the cornerstone of a transnational and borderless world, both social and individual experience continue to be dominated by the impulse for borders and restrictions. Leila Aboulela explores this discrepancy by interrogating the spatial organization of social reality both to show the prevalence of border logic and to suggest pathways for resurgence. This paper examines how the deployment of spatial tropes in Aboulela’s early novels The Translator (1999) and Minaret (2006) is aimed at demonstrating that conceptions of space as orderly and static often serve to maintain certain power configurations. At the same time, these tropes counter the discursive drive for order by tapping into the potential for resistance that inhabits these hegemonic narratives of space. I argue that by mobilizing such tropes as border-crossing, journeying, and carnivalesque chaos, the texts in question advocate a more fluid and chaotic notion of space.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".