A Regime Analysis: Evidence from Sri Lankan Migrant Domestic Workers’ Journeys to Saudi Arabia
Bibliographic record
Abstract
In this article, I use qualitative methods to examine the concept of a regime for migrant care based on Sri Lankan women’s transnational mobility as migrant domestic workers to Saudi Arabia. My work thus contributes to the growing body of literature on migrant care regimes from a Global South perspective, which to date has still received insufficient scholarly attention. The Sri Lanka–Saudi migrant care regime, shaped by a transnational consciousness of the possibilities for accumulation and production through reproductive labour, is located at a convergence of “translocal” gender, care, employment and migration systems. The regime is (re)produced through the relations and tensions between the family, the state and the market in an interchange of the dynamics of capitalist market forces and structural relations on various levels. The colour “brown” has emerged as a new racial classification in the global domestic sector, where power and subjectivity are constantly evolving. I argue that domestic work, which continues to be constructed as “women’s work”, represents an embodiment both of the subordination of women and of their personal autonomy. This, in turn, has broader implications for the meaning of feminine/masculine, motherhood/fatherhood, home and work. KEYWORDS: paid domestic labour; migrant domestic workers; care regime; Saudi Arabia; Sri Lanka
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".