“We no longer fear brides from afar”: Marriage markets and gendered mobilities in rural Vietnam
Bibliographic record
Abstract
Since the late 1990s, Vietnamese women’s participation in international marriage migration has garnered academic and media attention. In contrast, internal marriage migration, a key driver of overall internal migration flows, has received scant consideration. In this paper, we examine marriage and migration dynamics in four rural communes that have “lost” significant numbers of their single women to international marriage and gained brides through internal migration. Based on ethnographic fieldwork conducted in 2012 and 2013 in four villages and analysis of local marriage registration data and census data, this article examines internal and international marriage migration. We probed marriage migration vis-a-vis marriage markets, internal labor migration and gendered mobility patterns. The increased diversification of marriage with respect to spousal places of origin indicates a reconfiguration of marital norms and practices and changing social constructions of a desirable wife and daughter-in-law. Results underscore the role of labor migration and interprovincial networks in expanding mate-seeking circles among rural youth and in altering marital norms. Female international marriage migration is one piece of a larger puzzle whereby various forms of mobility are intertwined with changes in the realms of gender, family and marriage.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".