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Record W2063688925 · doi:10.1080/09585190110111477

Paths into the economy: structural barriers and the job hunt for skilled PRC migrants in Canada

2002· article· en· W2063688925 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Journal of Human Resource Management · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
FundersAsia UniversityUniversity of Hong Kong
KeywordsHuman capitalCertificationLabour economicsConstruct (python library)Face (sociological concept)Social capitalQualitative researchBusinessHuman resource managementDemographic economicsSociologyEconomicsEconomic growthManagement

Abstract

fetched live from OpenAlex

Abstract Well-educated and trained Chinese professionals immigrating to Canada face barriers in finding jobs. To understand this wastage of human capital, we see entry to the professions as mediated by frameworks. The social construction of careers influences the demand for labour. Human capital is a social construct defined by certification procedures in Canada and by the way Canadian employers perceive appropriate matches of jobs and job applicants. Their demand for people with 'Canadian experience' blocks entry into higher-level jobs. The study interviewed thirty-two couples in 1999-2001 using qualitative methods to learn about their experiences finding jobs in Toronto. Keywords: ChinaHuman CapitalInternational MigrationSocial CapitalSocial Construction

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.255
Teacher spread0.243 · 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