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Record W4230332257 · doi:10.1017/9781108877015

Clash of Powers

2020· book· en· W4230332257 on OpenAlexaff
Kristen Hopewell

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChinaInternational tradeGlobal governanceRivalryTrade warCorporate governanceOrder (exchange)Political scienceEconomicsPolitical economyLawManagement

Abstract

fetched live from OpenAlex

The US-China trade war instigated by President Trump has thrown the multilateral trading system into a crisis. Drawing on vast interview and documentary materials, Hopewell shows how US-China conflict had already paralyzed the system of international rules and institutions governing trade. The China Paradox – the fact that China is both a developing country and an economic powerhouse – creates significant challenges for global trade governance and rule-making. While China demands exemptions from global trade disciplines as a developing country, the US refuses to extend special treatment to its rival. The implications of this conflict extend far beyond trade, impeding pro-development and pro-environment reforms of the global trading system. As one of the first analyses of the implications of US-China rivalry for the governance of global trade, this book is crucial to our understanding of China's impact on the global trading system and on the liberal international economic order.

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)0.004
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: Other · Consensus signal: Other
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.015
Scholarly communication0.0090.009
Open science0.0010.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0310.005

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 head0.023
GPT teacher head0.227
Teacher spread0.204 · 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
GenreOther

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

Citations90
Published2020
Admission routes1
Has abstractyes

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