The migrant in the market: Care penalties and immigration in eight liberal welfare regimes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article disaggregates high- and low-status care work across eight liberal welfare regimes: Australia, Canada, Iceland, Ireland, Israel, Switzerland, the United Kingdom and the United States. Using Luxembourg Income Study data, descriptive and multivariate analyses provide support for a ‘migrant in the market’ model of employment, notwithstanding variation across countries. The data demonstrate a wage penalty in both high- and low-status care employment in several liberal welfare regimes, with the latter (service jobs in health, education and social work) more likely to be part-time and situated in the private sector. Migrant care workers are found to work disproportionately in low-status, low-wage types of care and, in some cases, to incur additional wage penalties compared to native-born care workers with equivalent human capital.
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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 | 0.002 | 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 it