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Record W4386981862 · doi:10.1016/j.ibusrev.2023.102195

The Tech Cold War, the multipolarization of the world economy, and IB research

2023· article· en· W4386981862 on OpenAlexaff
Rosalie L. Tung, Ivo Zander, Tony Fang

Bibliographic record

VenueInternational Business Review · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRivalryChinaGeopoliticsCold warContext (archaeology)Political scienceEconomyWorld economyGovernment (linguistics)International tradeEconomicsGeographyPolitics

Abstract

fetched live from OpenAlex

This paper first traces the evolution of the Tech Cold War to multipolarization in the context of major developments in the global economy, i.e. the ascent of China in the 21st century, antagonistic rivalry for technological supremacy between the United States and China, and the impending bifurcation of the world economy and its consequences. The paper then discusses the implications of the aforementioned developments for international business (IB) research and practice. Research topics include the Global North-South divide, nonmarket influences, government-MNE relationships, industrial policy and techno-nationalism, innovation in a multipolar world economy, the rise of middle powers, and innovation under geopolitical pressure.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.048
GPT teacher head0.323
Teacher spread0.276 · 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.

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

Citations95
Published2023
Admission routes1
Has abstractyes

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