'Being Chinese' in Mauritius and Madagascar: Comparing Chinese diasporic communities in the western Indian Ocean
Bibliographic record
Abstract
Chinese migration to the Western Indian Ocean since the 1800s was part of an earlier historical trend that saw European colonial powers setting up plantation economies that required foreign laborers. Migrants from Southern China arrived in Mauritius and Madagascar first as indentured laborers, and later as free merchants. Despite many similarities between the two diasporas, they differed in terms of their cultural and linguistic propensities. Furthermore, since the 1990s, both Mauritius and Madagascar have been experiencing rising influences of Mandarin-speaking Chinese immigrants working in infrastructure construction, commercial and educational sectors. Based on ethnographic fieldwork conducted in these two Western Indian Ocean countries between 2015 and 2020, this paper applies the theoretical lens of ‘diaspora-for-others,’ featured in this special issue, to explore the similarities and differences between Chinese migration trajectories to Mauritius and Madagascar, and their respective diasporic identity formations. Local socio-historical contexts in Mauritius, Madagascar, and China influence the transnational experiences of Mauritian and Malagasy Chinese communities, which further contributes to their heterogeneous, fluid and changing cultural identities. In addition, the People’s Republic of China’s increasing engagement in Western Indian Ocean countries as a gateway to Africa in the past two decades has also created more nuances in the distinguishable boundaries within the Chinese diaspora communities in the region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".