Converging economies of care? Immigrant women workers across 17 countries and four care regimes
Bibliographic record
Abstract
This study analyses 17 care economies using 2016 Luxembourg Income Study data to contribute to extant debate regarding the ongoing utility of care regimes as a classificatory schema for cross-national comparison. Examining similarities and differences in the provision of low-status work in health, education, social work, and domestic services - the 'care economy' - the data reveal devaluation of the labour done by immigrant women care workers, net of national and regime-level variation. In addition, numerous similarities across liberal, corporatist, social democratic, and central and eastern European care regimes emerge, in terms of the overrepresentation of immigrant women in low status care work, and the disproportionate financial penalties these workers incur. Together, findings suggest that notwithstanding national and policy-specific differences, there has been considerable convergence across economies of care towards a 'migrant in the market' model of employment. Such large-scale evidence of this trend calls into question the ongoing efficacy of care regimes for national comparisons of migrant care work under conditions of neoliberal globalization.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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".