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Record W4220780976 · doi:10.33423/jabe.v24i2.5098

Japanese Economic Engagement With the EU: Geopolitics Meets Business

2022· article· en· W4220780976 on OpenAlexvenueno aff
Hiroki Nakamura, Patrik Ström, Claes G. Alvstam

Bibliographic record

VenueJournal of Applied Business and Economics · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsGeopoliticsPoliticsInvestment (military)Economic systemEconomic geographyInternational tradeEconomicsGlobalizationEconomyPolitical scienceMarket economy

Abstract

fetched live from OpenAlex

During the recent years the world has experienced a shift towards complex relations being formed in the growing interlacing between geoeconomics and geopolitics. This paper aims at bringing geoeconomics and geopolitics on the macroeconomic level together with the potential implications for Japanese firms operating in Europe and more specifically within the EU Single Market. The paper grounds the analysis within international political economy, international business and economic geography. This broad, eclectic theoretical foundation enables the analysis to contribute to a deeper understanding of how firms respond to and potentially drive the political development of trade and investment relations. Hence, the paper strives to examine how geopolitics alter the flows of trade and investments, but also to map a new configuration taking place in parallel on the firm level of industrial dynamics and economic geographical footprint.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0040.004
Scholarly communication0.0070.004
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.183
Teacher spread0.153 · 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 designObservational
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

Citations2
Published2022
Admission routes1
Has abstractyes

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