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Record W2043135795 · doi:10.1080/09692290.2013.824912

Turning point: International money and finance in Chinese IPE

2013· article· en· W2043135795 on OpenAlexaff
Xin Wang, Gregory Chin

Bibliographic record

VenueReview of International Political Economy · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsYork University
Fundersnot available
KeywordsEconomicsPoint (geometry)Turning pointInternational financeKeynesian economicsMacroeconomicsPhilosophy

Abstract

fetched live from OpenAlex

Unlike the depth of international political economy (IPE) research on finance and money in North America and Britain/Europe, or the amount of work that has been done inside China on the IPE of international trade, the IPE of global finance and money is still at a nascent stage inside China. The paper examines the evolution of Chinese IPE research on global finance and money and suggests that research in these issue areas appears to be reaching a turning point. The main empirical finding is that this shift in knowledge production has been induced principally by China's emergence as a financial force and the national developmental concerns this entails, as well as by the onset of the 2008–09 global financial crisis and the rise of the emerging economies’ grouping. The growing Chinese scholarship on the IPE of finance and money is adding analytical depth and broadening Chinese IPE, particularly on the impact of financial globalization on developing and emerging economies. While such research will likely contribute to Chinese policymaking in the future, the scholarly test for Chinese IPE is whether and how it will contribute to filling the global knowledge gaps on the determinants of financial and monetary policy, and whether it will give rise to new understandings on global finance and money, especially the causes of international financial crises. Heretofore, much of the literature has been heavily policy-oriented and normative.

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 categoriesInsufficient payload (model declined to judge)
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 score0.824
Threshold uncertainty score1.000

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)0.0010.000

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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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.

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

Citations9
Published2013
Admission routes1
Has abstractyes

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