Writing Class with Mr. Khan: No Luncheon at Longchamps for the Jumbie Bird
Bibliographic record
Abstract
Almost forty years ago, Ismith Khan (1925-2002), taught a writing class at the University of California, Berkeley. The dynamics of that class raise larger issues about Khan’s work, and about Indian diasporic writings before the term existed. By the winter of 1971, when Khan faced the class, the writer had made a mark with two novels: The Jumbie Bird and The Obeah Man. But difficulties Khan encountered throughout his career were already apparent. Khan’s output would be slender and he would not attract a wide readership. Khan sensed a kind of marginalization. He was obsessed with The New Yorker’s refusal to publish his story, ‘Luncheon at Longchamps’. He critiqued one student’s work, set in Iran, as a ‘travelogue’. His struggles with a Vietnam veteran’s writings as well as with a student’s story about boar hunting in Yugoslavia betrayed other tensions. The class members spoke in a cacophony of cultures, all expressing themselves in traditionally-constructed short stories in English. And always in front of the class was Khan’s sad, intelligent face: Male, Black, Muslim, Indian, Trinidadian, Pathan. This paper explores Khan’s legacy by looking at issues that arose in the class and that we are only able to name and critically understand years later—issues of location, marginalization, time and identity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.029 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.033 | 0.007 |
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".