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Record W2806491966 · doi:10.1177/0958928718768337

The migrant in the market: Care penalties and immigration in eight liberal welfare regimes

2018· article· en· W2806491966 on OpenAlexaffabout
Naomi Lightman

Bibliographic record

VenueJournal of European Social Policy · 2018
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWelfareImmigrationWageCare workDemographic economicsLabour economicsWork (physics)EconomicsHealth careWelfare statePolitical scienceEconomic growthMarket economy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.029
GPT teacher head0.374
Teacher spread0.345 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations24
Published2018
Admission routes2
Has abstractyes

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