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Record W2044579811 · doi:10.54648/trad2014040

When Chinas National Champions Go Global: Nothing to Fear but Fear Itself?

2014· article· en· W2044579811 on OpenAlexaboutno aff
Michael Du

Bibliographic record

VenueJournal of World Trade · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsChinaOpposition (politics)Foreign direct investmentNothingPolitical scienceFace (sociological concept)Mergers and acquisitionsPolitical economyDevelopment economicsMarket economyBusinessInternational tradeEconomicsLawSociologyPolitics

Abstract

fetched live from OpenAlex

Due to the success of the 'Go Global' policy, in recent years there has been a dramatic increase in overseas direct investment made by Chinese state-owned enterprises (SOEs). However, Chinese SOEs' overseas investment has been viewed with suspicion and several attempted acquisitions discontinued in the face of strong opposition from host countries. This article analyses the plausibility of some common fears about Chinese SOEs' overseas direct investment and evaluates critically the regulatory responses of the US, Canada, Australia and the European Union motivated by such fears. The article argues that though some fears are legitimate, they are grossly exaggerated in view of the SOE reforms in China over the past three decades. The policy implications of this finding for both host countries and China's ongoing SOE reforms are also explored.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.008
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.048
GPT teacher head0.237
Teacher spread0.189 · 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 designNot applicable
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

Citations5
Published2014
Admission routes1
Has abstractyes

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