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Record W2335003418 · doi:10.1177/011719680301200303

Chinese Business Migration to Australia, Canada and the United States: State Policy and the Global Immigration Marketplace

2003· article· en· W2335003418 on OpenAlexaffabout
Lloyd Wong

Bibliographic record

VenueAsian and Pacific migration journal · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsImmigrationCompetition (biology)ChinaCompetitor analysisImmigration policyPoliticsState (computer science)Political scienceEconomicsDevelopment economicsEconomic growthEconomyBusinessMarketing

Abstract

fetched live from OpenAlex

This paper examines business migration to Australia, Canada and the United States by integrating the concepts of a global immigration marketplace and the commodification of citizenship into global political economy theory. It finds that state business migration policies constitute “offers” to potential businesspersons, in a discourse of “competition” and simultaneously regulate the process. In the sorting process of potential migrants across countries many businesspersons have a rational “choice” of the country they want to emigrate to. This competition and choice provide evidence of a global immigration marketplace and data show that only Australia and Canada are active competitors with Canada having an advantage. An analysis of Chinese business migration from China, Hong Kong, Macao, Taiwan, Malaysia and Singapore indicate substantial numbers in the tens of thousands in the early 1990s but this has decreased in recent years due to several economic and political factors. Currently there are moderate levels of Chinese business migration with China now as the major source country. Since businesspersons are not a homogenous group the paper concludes with some suggested policy changes to make business migration more accessible and transformative.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.010
GPT teacher head0.270
Teacher spread0.260 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations34
Published2003
Admission routes2
Has abstractyes

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