Landscape, home, & nation: Chinatown identities in urban Southeast Asia
Bibliographic record
Abstract
Existing research on Chinatowns have focused largely on the development of the ethnic community, and racial and ethnic discourses in the context of urban spatialities in the form of enclaves, as well as economic networks. Migration and issues related to transnationalism and the Chinese diaspora are accompanying themes. More significantly, the majority of studies on Chinatowns have been situated in the 'Western Hemisphere', notably in North America and Europe. The purpose of this dissertation is to stimulate conversation on Chinatowns in Southeast Asia. It also proposes to explore the idea of Chinatown vis-a-vis concepts of heritage landscapes, diaspora and home, and national identities. Focusing on the cities of Bangkok, Ho Chi Minh City, Rangoon, and Singapore, this dissertation draws on theories of place to consider three themes and objectives. \n \nFirst, the research explores the processes that shape the urban and imaginative landscapes of Chinatown and the functions that Chinatown plays in the city. This theme examines the idea of Chinatown and its sources, investigating images drawn from concepts of heritage to produce a recognisable space. Second, in conjunction with the concept of diaspora, it explores the potential inherent in the idea of Chinatown as home to the Chinese population and a place of the Chinese diaspora. It also considers the multiple homes that diasporic and migrant communities tend to sustain. The third objective of the study examines the role and place of Chinatown in the context of the nation, and how particularly ethnic and multicultural identities are negotiated in this space. At the same time, this theme explores the complex globalities that Chinatowns involve with the nation and the city. Using a postcolonial framework to address these themes, the research analyses the negotiation of place and identity in its interaction with concepts of orientalism. \n \nThis research shows that Chinatown identities are produced in and through their landscapes which are shaped by imaginations of diasporic Chinese heritage. It also reveals that these diasporic identities help produce global impacts on their national contexts. It is at the intersection of these themes that Chinatown identities are realised as complex and plural, not arising simply from connections between China and present places of settlement, but also from the networks comprising other Chinatowns.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".