Gambling on the Future: Casino Enclaves, Development, and Poverty Alleviation in Laos
Bibliographic record
Abstract
Following the extraordinary wealth generation of casinos in Macau and Singapore, governments and non-state actors across Southeast Asia have developed gambling establishments as a means to fast-track economic growth and stimulate national development. Yet, here and elsewhere, casinos have been heavily criticized for their association with immoral behaviour, problem gambling, corruption and organized crime. In this article I focus on two casinos in northern Laos to address two research questions. First, I consider how casinos have come to exist within the remote border regions of one of Asia’s least developed countries. Here, I discuss vice economies within the Golden Triangle region, multi-actor aspirations to boost transnational connectivity within continental Southeast Asia, strengthening political-economic relationships between Laos and China, and Government of Laos efforts to use foreign investment as a mechanism for increasing governance capacities in borderlands. Following this, I critically analyse how, in what ways, and for whom, casinos have brought development to Laos. Here, I focus specifically on the multifarious effects of casinos on the lives and livelihoods of local communities to argue that casino development has been informed by logics of expulsion and the establishment of new predatory formations. To make this argument, the article draws on four fieldwork visits to each of the casino sites between 2011 and 2015, desk-based research, and interviews with local residents, casino staff and members of the Government of Laos.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".