<i>In-Between World</i>and<i>Worlds Within</i>: Reading Diasporic Return in Vassanji and Bissoondath
Bibliographic record
Abstract
The return journey has long been recognized as a central feature of diaspora, yet contemporary diaspora studies have conventionally understood it in stubbornly mythological terms. This paper looks to foster discussion about physical diasporic return journeys by juxtaposing M. G. Vassanji’s The In-Between World of Vikram Lall (2003) and Neil Bissoondath’s The Worlds Within Her (1998). Although the two novels overlap in their exploration of the Indian diaspora against the backdrop of racially volatile independence movements in former British colonies, they offer starkly different renderings of diasporic return that are reflected in their engagements with diasporic history. The paper closes with a consideration of the critical assumptions that have allowed the return journey to be overlooked in diaspora literary studies to date, suggesting that its absence may reflect the methodological nationalism of the field.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".