Brides, Maids, and Prostitutes: Reflections on the Study of 'Trafficked' Women
Bibliographic record
Abstract
This essay critically examines the blurred boundaries – or the analytical shadow lines – in scholarly and popular conceptualizations of Asian women migrants. I ask what women who migrate from the global South to the North as maids, brides, or sex workers have in common? How important are the commonalities and the distinctions between them? When are such blurs warranted, and what are the implications of such blurs for women’s self-perceptions and life experiences, for feminist scholarship, and for immigration policies? Drawing from ethnographic field research among Chinese and Filipina correspondence brides, Filipina domestic workers, and from the wider literature on sex workers, this essay considers some of the problems with a ‘trafficking’ framework, and considers the analytical and ethnographic possibilities that emerge with closer examination of the real and imagined shadow lines between sex workers, domestic workers, and migrant brides.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".