Becoming a Migrant: Vietnamese Emigration to East Asia
Bibliographic record
Abstract
Since the early 1990s several million men and women from Southeast Asia's lower socioeconomic classes have migrated to East Asia with a temporary worker visa or a spousal visa. This article is based on five years of ongoing fieldwork in migrants' communities of origin in rural Vietnam and in places of destination in Taiwan, South Korea and Japan. The authors make three contributions: first, they argue that the categorization of migrants as either “workers” or “wives” in research obscures the complex trajectories and motives involved in the process of “becoming a migrant.” Second, they challenge studies that unquestioningly invoke social network approaches to migration. Instead, social networks should be regarded as a double-edged sword for emigrants because personal networks are embedded in a powerful migration industry. Third, they contend that migration outcomes and levels of success are, in part, influenced by processes taking place before departure. This article sheds light on the tension between migrants' agency and the structural constraints faced by candidates seeking to migrate from Vietnam, and from Southeast Asia more broadly.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".