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Record W4293772908 · doi:10.5509/2022953595

Understanding Mistrust and Instability in East Asia

2022· article· en· W4293772908 on OpenAlexvenueno aff
Jahyun Chun

Bibliographic record

VenuePacific Affairs · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Zones and Regional Development
Canadian institutionsnot available
Fundersnot available
KeywordsEast AsiaChinaProsperityPolitical sciencePoliticsOrder (exchange)International relationsDevelopment economicsMiddle EastChina seaGeographyEconomyPolitical economySociologyLawEconomics

Abstract

fetched live from OpenAlex

In recent years, East Asian countries have faced numerous security threats, including territorial disputes in the East China Sea, the US-China conflict, and economic turmoil due to the COVID-19 pandemic. Under such circumstances, a stable regional order and economic prosperity are crucial. This essay reviews three recent books that attempt to identify the distinct features of East Asian international relations and the main causes of regional instability. The first part of this essay addresses the main themes and contributions of each book, and o ers an evaluation of their implications. The second section focuses on two key themes touched on in each of the books: "China and East Asian regional order" and "history still matters." The conclusion presents the challenges to, and provides recommendations for, peaceful coexistence in East Asia. This review elucidates not only the distinct features of current Sino-Japanese relations and East Asia's international politics but also addresses the future of the region.

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)0.003
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 score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.011
Scholarly communication0.0060.009
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.201
Teacher spread0.121 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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