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Record W4378386914 · doi:10.5509/2023962229

Globalization of Arms Production and Hierarchical Market Economies: Explaining the Transformation of the South Korean Defense Industry

2023· article· en· W4378386914 on OpenAlexvenueno aff
Chonghyun Choi, Soul Park

Bibliographic record

VenuePacific Affairs · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGlobalizationInterdependenceConvergence (economics)East AsiaCompetition (biology)CapitalismScholarshipProduction (economics)Latin AmericansEconomic systemPolitical scienceInternational tradeEconomyMarket economyEconomicsPolitical economyEconomic geographyEconomic growthChina

Abstract

fetched live from OpenAlex

The global arms industry has experienced a major transformation in the post-Cold War era, with production becoming increasingly transnational and larger in scale. While many scholars and policymakers predicted the widespread adoption of market-enhancing reforms aimed at increasing domestic competition and attracting FDI, globalization of arms production has not led to a convergence of national defense industries into a liberal- market model. Drawing on the varieties of capitalism (VoC) literature, recent scholarship has demonstrated how an interdependent web of economic institutions has shaped each country's response in varied ways. This paper builds on the VoC literature and argues that the hierarchical market economy (HME) as a distinct variety serves as a better model for understanding the trajectory of defense industries in many second-tier producers that do not fit the existing categories of VoC. We conduct an in-depth case study of South Korea's defense-industry reform initiated in 2008 and the subsequent threefold increase in its arms exports. We show that the trajectory of South Korea's defense-industry reform can be seen as the result of an HME's attempt to adapt to the globalization of arms production in ways that preserve its distinct comparative advantage. As the HME model has broad applicability for many countries in Asia and Latin America, our findings have important implications for future developments in the global arms industry.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.219
Teacher spread0.192 · 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 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

Citations7
Published2023
Admission routes1
Has abstractyes

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