Reimagining the Aapravasi Ghat: Khal Torabully's poetry and the indentured diaspora
Bibliographic record
Abstract
National narratives in Mauritius often affiliate the Indian diaspora with the experience of indentureship and the Aapravasi Ghat, a nineteenth century immigration depot classified in 2006 as a UNESCO World Heritage Site. This affiliation inevitably disregards the African, Malagasy, and Chinese laborers who also worked under the system of indenture in Mauritius during the nineteenth and twentieth centuries. In his 2013 collection of poetry, Voices from the Aapravasi Ghat: Indentured Imaginaries, Khal Torabully returns to the Aapravasi Ghat to recast the history of indentureship and highlight the various ethnicities of the indentured diaspora, their shared trauma, and displacement. This study contends that Torabully’s poetic engagement with the Aapravasi Ghat, as an historical site of indentureship and its overlooked diversity, challenges the perception of the Ghat as a representation of Indian indentured memory. It uses Torabully’s Coolitude poetics as a conceptual frame to consider the Aapravasi Ghat as an inaugural space that facilitated the creation of a complex, open-ended identity that aspires to promote a culture of diversity but not without its limitations and contradictions. Despite efforts to disrupt ethnic distinctiveness, Torabully reproduces Indo-centric perspectives expressed through the concept of kala pani and the fakir figure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.021 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".