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Record W2948008542 · doi:10.5509/2019922211

The Richness of Financial Nationalism

2019· article· en· W2948008542 on OpenAlexvenueno aff
Eric Helleiner, Hongying Wang

Bibliographic record

VenuePacific Affairs · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsnot available
Fundersnot available
KeywordsNationalismChinaPolitical scienceEconomic systemBusinessEconomicsLaw

Abstract

fetched live from OpenAlex

Financial nationalism has received little attention in the literature on Chinese nationalism. Nor has China been a focus of the emerging literature on comparative financial nationalism. This is surprising as financial matters were central to modern Chinese nationalism when it began to take shape in the nineteenth and the twentieth centuries, and financial nationalism remains influential in contemporary China, which has undoubtedly become a major actor in the international financial system today. Our exploration of Chinese financial nationalism seeks to begin to fill this gap in both sets of literature. This article examines three areas of concern shared by Chinese financial nationalists past and present: currency, foreign financial institutions in China, and international borrowing/lending. We find that, as China’s position in the international power hierarchy has evolved, the nature of financial nationalism has changed, from a largely inward and defensive orientation to an increasingly outward orientation. Our study also reveals diverse strands of thinking among Chinese financial nationalists, both now and in the earlier historical era, according to whether they hold a zero-sum or positive-sum conception of international financial relations. The case of China shows the richness of financial nationalism and highlights the importance of a nuanced understanding of this phenomenon.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.001

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 head0.006
GPT teacher head0.186
Teacher spread0.179 · 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 designTheoretical or conceptual
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

Citations10
Published2019
Admission routes1
Has abstractyes

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