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Record W2114786951 · doi:10.1093/irap/lcr018

Rising States, Rising Institutions: Challenges for Global Governance

2011· article· en· W2114786951 on OpenAlexaboutno aff
Isao Miyaoka

Bibliographic record

VenueInternational Relations of the Asia-Pacific · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMultilateralismGlobal governanceCorporate governancePolitical scienceGeneral partnershipInternational relationsPoliticsChinaPower (physics)Public administrationPolitical economyForeign policySociologyEconomicsLawManagement

Abstract

fetched live from OpenAlex

The global financial crisis of 2008 has strengthened the general impression that the decline of the United States and the rise of new powers such as China and India are simultaneously in progress. A shift in the balance of power must significantly affect the way of global governance. This is a subject of great importance in world politics. In the words of Robert Gilpin, ‘the fundamental problem of international relations in the contemporary world is the problem of peaceful adjustment to the consequences of the uneven growth of power among states’. Since around 2010, scholarly attention has been paid to the impact of emerging new powers on global governance. One of the very first books is the volume under this review, Rising States, Rising Institutions: Challenges for Global Governance. This edited volume is the second book that was produced by the collaborative work between the Center for International Governance Innovation (CIGI) – a Canadian think tank based in Waterloo, Ontario – and the Woodrow Wilson School of Public and International Affairs, Princeton University. (The first book from this partnership is Can the World Be Governed? Possibilities for Effective Multilateralism.)

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)0.008
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0070.044
Scholarly communication0.0210.020
Open science0.0010.008
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0050.001

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 head0.056
GPT teacher head0.322
Teacher spread0.266 · 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 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

Citations136
Published2011
Admission routes1
Has abstractyes

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