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Record W2046529433 · doi:10.1002/ijpg.310

Gendered structural barriers to job attainment for skilled Chinese emigrants in Canada

2003· article· en· W2046529433 on OpenAlexaffabout
Janet W. Salaff, Arent Greve

Bibliographic record

VenueInternational Journal of Population Geography · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHuman capitalImmigrationUnemploymentHuman capital theoryChinaDemographic economicsEducational attainmentContext (archaeology)Social capitalEmigrationLabour economicsSociologyEconomicsPolitical scienceEconomic growthSocial scienceGeographyLaw

Abstract

fetched live from OpenAlex

Abstract Our study examines the career achievements of 50 professional couples that immigrated from China to Canada. We compare their job attainment when they left China with that years after immigration. We apply concepts of human capital and institutional theory to understand why the job status of the majority drops after immigrating. Human capital concepts account for most career advancement in China. Human capital theory falls short in explaining the structural barriers to achievement that affect those in the controlled professions, and especially women, in Canada. The institutional framework views immigrants' unemployment and a drop in job levels and wages as a status change. Structural concepts handle job deterioration, and in particular women's loss of status, in terms of social recognition of career paths. Structural concepts explain why immigrants' past career paths are poorly understood or are blocked in a new context. We conclude that institutional theory is more widely applicable than human capital theory for understanding the loss of job status for our sample of skilled immigrants from China. Copyright © 2003 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.096
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.010
GPT teacher head0.299
Teacher spread0.289 · 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

Citations80
Published2003
Admission routes2
Has abstractyes

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