Migrants’ care work in private households, or the strength of bilocal and transnational ties as a last(ing) resource in global migration
Bibliographic record
Abstract
All over the globe, women and men with middle and high incomes hire migrant workers in the private sphere of care. Women from Mexico and Central America leave to work for double-income families in the US; Indonesian women leave for economically more prosperous regions in Asia and the Arab countries; women from Sri Lanka migrate to Greece and Southern Europe, where quota systems have been introduced, especially for care workers. Women from Eastern Europe migrate to Germany, France, Italy, the US and Canada. The Philippines systematically developed the export of care and domestic workers. Here a substantial part of the country's migration industry focuses on often well-educated women leaving for care and domestic work abroad. The country, some call it a migrant nursery, ‘supplies’ about 160 countries all over the world with domestic workers (see Aguilar Jr, 2002). In Asia, Indonesia and Sri Lanka are also considered to be ‘supply’ countries. High and middle-income states in Asia, including Hong Kong, Singapore, Taiwan, China and Malaysia, as well as the Gulf states, employ thousands of women migrants as domestic workers (Parrenas, 2003). In Europe, too, care work is increasingly migrant work. There are differences in government policies toward women going abroad to work as domestic workers, ranging from liberal or encouraging systems (Philippines) to systems banning the outmigration of female workers (Bangladesh and Pakistan). Within Europe a variety of regulations concerning migrant work exists among the various countries. This chapter asks why care work is rapidly becoming migrant work in Europe, too – irrespective of different national labour market regulations and care arrangements in the individual countries. It is argued that global migrations follow existing regional hierarchies. Migrations further depend on regulations at extremely different geographic scales. Two intertwined trends add to the increase of migrant workers in the field of care and domestic work. First is the growing feminisation of migration on the global scale. The first part of this chapter presents the salient features in this respect by giving a rough overview of numbers and by presenting in a nutshell the existing theoretical lines of thinking on the impact of gender in the migration debate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".