Diversity Sells: Uzma Jalaluddin’s Muslim Adaptation of<i>Pride and Prejudice</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pride and Prejudice (1813) is transposed onto an Indian-origin Muslim community in modern-day Toronto in Uzma Jamaluddin’s Ayesha at Last (2019), and the novel is as much about being Muslim in the West as it is about being an Austen adaptation. These creative departures from the Austen hypotext contribute to the novel’s positive reception, which can be gauged from the 4.4 stars rating by 1184 users on Amazon. Ronald Robertson (1995) argues that “diversity sells,” and this article examines Amazon user reviews to demonstrate how Jalaluddin’s Muslim glocalization of Pride and Prejudice makes her novel a success and reveals the market for such diverse stories. She makes a commendable effort to make space for practicing Muslim protagonists in the Austen oeuvre and succeeds in providing realistic depictions of many aspects of the Muslim community. However, the novel’s unfortunate surrender to Western stereotypes of the “terrorist” Muslim male to appeal to the implicit white reader ultimately undermines its authenticity and does not fully represent the breadth of Muslim experience, thereby demonstrating that continued effort is required to overhaul the publishing industry’s employee and audience base to enable the inclusion of more equitably drawn minority characters.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it