Kay Anderson, Ien Ang, Andrea Del Bono, Donald McNeill, and Alexandra Wong, Chinatown Unbound: Trans-Asian Urbanism in the Age of China
Bibliographic record
Abstract
In an era of Tiktok and Huawei, it can be easy to forget that until recently some of the most visible evidence of anything "Chinese" beyond the country's borders was to be found in the Chinatowns, which are a feature of many major global cities.In Sydney-where the book under review is rooted-London, Vancouver, and elsewhere, these circumscribed pockets of Chinese residence and business, often dominated by people from southern provinces such as Fujian and Guangdong, reflected an age of racialized marginalization.How then has the role of Chinatowns shifted in a twentyfirst century when the massively increased economic, political, and cultural weight of East Asia far exceeds the parameters of an "ethnic" enclave with its limited repertoire of foods, bilingual street signs, and swaying red lanterns?This, among others, is a question that preoccupies Kay Anderson, Ien Ang, Andrea Del Bono, Donald McNeill, and Alexandra Wong in their five-way co-authored book Chinatown Unbound.Drawing on a heterogenous collection of materials from census and other statistical data, surveys and focus groups, participant observation, and media analysis, as well as Del Bono's PhD dissertation, the authors take a multi-pronged approach to the shifting social, economic, and political currents of Chinatown in the Haymarket district of Sydney, Australia.The notion of "unboundedness" applies to more than simply the scope of the book's ambition (or its accommodation of coauthors), for this idea is a thematic and theoretical lens through which to understand how "Chinatown" conceptually speaks of transformations occurring on a multi-scalar global canvas.Having emerged from a 2012-15 research project, this avowedly expansive work strikingly rings today like an unwitting elegy to an era of connection and openness that has since given way to boundary-drawing, retrenchment, and exclusion.Following an introduction that sets the scene for the research that was carried out and fleshes out the idea of "unboundedness," Chinatown Haymarket is considered from multiple angles in chapters dealing with the area's past and present (chapter 2), its architecture and planning (chapter 3), demographics (chapter 4), "multi-Asian" diversity (chapter 5), business landscape (chapter 6), branding within Sydney and China
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".