Bibliographic record
Abstract
In White Teeth (2000), Zadie Smith uses the phrase original to capture the sense of unbelonging and uprootedness experienced by those involved in the mass migrations of the twentieth century. Taking this phrase as its thematic cue, this paper seeks to investigate migrant identity in two novels written by and about contemporary British Muslim women – Monica Ali's Brick Lane (2003) and Leila Aboulela's Minaret (2005). Drawing on trauma studies and theories of narrative and identity, it attempts critically to revisit the notion of hybrid selfhood that is central to postcolonial criticism. Each novel centres on a love affair between the female protagonist and a younger, politically radical and/or staunchly religious man. At first glance, the texts seem to suggest gender-specific coping mechanisms in response to the traumatic experience of migration: the radical answers provided by the male figures are countered with a feminine strategy of compromise, negotiation and pragmatism. This neat division along gender lines is complicated, however, by the fact that the female figures initially fall prey to the allure and seduction of the extreme; moreover, the pragmatic stance that they eventually settle for is far from straightforward; it is painful and defies closure. Tracing characters' attempts to reintegrate their traumatic experience into a coherent narrative, both texts question the very possibility of a narrative reconstruction of the traumatized self and imply that the quest for coherent subjectivity is a flawed one. What the novels suggest, then, is that trauma refuses narrative integration – in fact, the very attempt is destructive in itself. Far from creating alluringly hybrid identities that flexibly respond to varying global contexts, the original of the migrant experience repeats itself in a fundamental sense, creating new traumas even as older ones are being worked through.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.021 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".