Managing migration in the <scp>G</scp>reater <scp>M</scp>ekong <scp>S</scp>ubregion: Regulation, extra‐legal relation and extortion
Bibliographic record
Abstract
One major aim of the G reater M ekong S ubregion ( GMS ) integration programme, supported by the A sian D evelopment B ank ( ADB ), is to foster regional ‘community’ for sharing resources, people and financial flows. This ‘community’ is the target of both economic growth and poverty reduction. The emphasis on ‘community’ in the ADB 's mushrooming quantity of documents raises important questions about what kinds of people are included, in what roles and with what kinds of support and protection. This paper explores these questions in relation to the political economy of regulating ethnic migrants from M yanmar working in T hailand. This paper argues that extra‐legal relations between migrants and state/para‐state agents constitute a crucial part of regulation. In transferring the regulation of migration to the national scale, the ADB inadvertently reinforces national differences between Thais and cross‐border people. Additionally, the complicated and fluctuating implementation of national regulations in both countries leaves migrants subject to violence and extortion from state and quasi‐state agents in T hailand. This paper shows that the dynamics of global capitalism require ‘deportable labour’ supplied by ethnic migrants who are included in the GMS community as the most invisible, vulnerable and exploited members.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".