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Record W2026929525 · doi:10.1111/1468-2435.00242

Migration of Highly Skilled Chinese to Europe: Trends and Perspective

2003· article· en· W2026929525 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

VenueInternational Migration · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsChinaPopulationInvestment (military)Economic growthPolitical scienceDevelopment economicsDemographic economicsEconomicsSociologyDemography

Abstract

fetched live from OpenAlex

Abstract Since China's economic opening and reforms in 1978, the country has broadened and deepened its exchanges and relations with other countries. This has contributed to the increase in the scale of international migration of highly skilled Chinese abroad. The impact of the migration of highly skilled Chinese on China and the relevant nations particularly deserve attention and study. Following the earlier migration flows mainly to the United States, Japan, Canada, Australia, and New Zealand, the migration of highly skilled Chinese to Europe has become a notable new trend. Currently, the flow of international migration of highly skilled Chinese personnel is mainly oriented toward Europe and the United States. While studying abroad has been the main form of migration of the skilled, this has now been joined by the migration of technical and professional staff, and the trend is increasing. The main country of destination for Chinese students is the United States, which absorbs more than half of the total, while Australia and Canada receive the largest number of skilled Chinese manpower. The United States also receives a large number of Chinese technical personnel, but its proportion has declined, while the flow to Europe has sharply increased. This development may be attributed to the global expansion of economic, scientific and technological, as well as cultural and educational exchanges and cooperation. But it is also the result of an increase in the educational investment made by the Chinese people following the continuous increase in China's economic strength and the population's personal income. Of greater importance are the gaps between China and Europe at the scientific, technological, and educational levels and the research and marketing environment. The intervening changes in labour market and immigration policies in European and American countries accelerate the trend further. For all of these and other reasons, the spatial distribution of Chinese students will become more balanced and play a positive role in the promotion of mutually beneficial exchanges between China and other countries.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.309
Teacher spread0.297 · 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