Cheap Labour Reserves & the Growth of Cities: Undocumented Indonesian Workers in Macau
Bibliographic record
Abstract
This paper presents new research findings on undocumented Indonesian migrant workers in Macau, \nabout whom no previous study exists. Critical analysis explicates the dovetailing arrangements \nbetween public and private sector interests that are systemically creating undocumented labour \nmigration flows and shows how these arrangements are structurally inherent in the mutual \ncompetitiveness of globalising nodes of wealth creation. Undocumented migration cheapens \nproduction costs and results in a flexible black market of vulnerable, right-less and exploited \nworkers. Contrary to illusions of an urbanizing Asia with expanding spaces for civil liberties, the \ndevelopment of globally competitive mega-cities, built and supported by low-skilled migrant \nworkers, rests on a global underclass of transient workers, who bear the human costs of transience \nand labour flexibility, enabling mega-cities to externalise such costs and enhancing their global \ncompetitiveness. \nIn this paper we analyse the vulnerabilities of undocumented Indonesian workers in the context of \nMacau‘s rapid economic development as an aspiring mega-city. The Macau government‘s laissezfaire \ntolerance of such workers is grounded in the need for a particular type of human labour, that \nis abundant, cheap, marginal and disposable, fuelling rapid growth. Furthermore, the outflow of \nIndonesian migrant workers to Macau is linked to Hong Kong‘s exclusionary Immigration policies, \nwhich aim at extricating surplus migrant labour. Meanwhile, the Indonesian government refuses \nresponsibility for its migrant workers in Macau on the grounds that Macau is not recognised as an \nofficial destination, thereby denying its own role as a structural producer of such labour. The paper \nshows how public and private interests motivate increasing numbers of migrants to become \nundocumented overstayers in Macau, as they try to avoid oppressive practices in labour migration \nfrom Indonesia and the exclusionary policies of Hong Kong.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".