Bibliographic record
Abstract
M. G. Vassanji's The In-between World of Vikram Lall describes how the life of the eponymous protagonist, a third-generation Asian African, is affected by Kenya's independence struggle and its post-colonial aftermath. This essay analyses how this novel uses the motif of travel in order to explore the possibilities and difficulties for Asian Africans to make East Africa their true home. It is often through travel that the protagonist re-examines some facets of his ＂Kenyan＂ identity. This essay first explains how the novel reflects the historical particularities of Asian Africans in colonial East Africa, and how those particularities affect the protagonist's early life and his sense of belonging. It then discusses the significance of the trip his family takes when he is an eight-year-old boy, analysing how this journey allows him to bracket the instability of his identity and deepen his sense of geo-cultural belonging. Next, the journeys the adult protagonist undertakes in post-independent Kenya are examined. These trips function as occasions to reaffirm his sense of belonging to the country in spite of the deepening political corruption and his own involvement in it. Lastly, the essay explores the importance of Canada, where he hides himself after fleeing Kenya and writes the autobiography that constitutes most of the novel. The geo-cultural distance between Canada and Africa forces the protagonist to question his relationship with Kenya and ultimately makes him decide to go back to the country.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".