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Record W3014540490 · doi:10.29173/psur131

China’s Challenge to the Institutions of Global Governance and US Soft Power

2020· article· en· W3014540490 on OpenAlexaffvenue
Evan Oddleifson

Bibliographic record

VenuePolitical Science Undergraduate Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChinaCorporate governanceGlobal governanceSoft powerPoliticsDeveloping countryPolitical scienceIdeologyOrder (exchange)Political economyPower (physics)EconomicsInternational tradeDevelopment economicsEconomic growthLawFinance

Abstract

fetched live from OpenAlex

China stands on the brink of surpassing the US in material capability and is pushing the world towards an increasingly multipolar order. This paper assesses the constraints on the growth of China's non-coercive influence in global politics. However, the constitutional groundings of global economic governance in US ideology and their institutional stickiness make China’s prospects of altering the mandates and structures of the IMF, WB, and WTO highly unlikely. Furthermore, by examining the outcomes of China's lending strategies in developing countries using Angola as a case study, this paper highlights China's inability to supplant growing IMF and WB agreements in developing countries and their failure to institutionalize their influence in partner countries. In sum, this paper concludes that liberal values, and by extension the non-coercive influence of the US, are likely to be upheld during China's rise by the institutions of global governance, namely the International Monetary Fund, World Bank, and World Trade Organisation.

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)0.002
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 score0.979
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.050
GPT teacher head0.362
Teacher spread0.311 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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