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Record W4401368472 · doi:10.4324/9781003353485-3

Institutions

2024· book-chapter· en· W4401368472 on OpenAlexaboutno aff
Andrew J. Williams

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Regulation and Crises
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

The twentieth century has often been termed ‘the American century’ and, until recently, the twenty-first century had seemingly continued the trend of US dominance in formal global institutions like the United Nations (UN) and ad-hoc institutions like the ‘G7’ economic grouping of developed countries. States like India, and particularly China, are growing in influence and economic might, but they have yet to eclipse the United States, and neither has the European Union (EU). One reason is that the only really conceivable economic or political blocs to emerge in recent times as competitors to the West have far too many internal disagreements. Jim O’Neil, the former Goldman Sachs economist and the inventor of the term ‘BRICS’ in 2001, Brazil, Russia, India, China and South Africa is dismissive of these countries ever being able to form a common currency or a central bank. He called it ‘ridiculous … embarrassing almost’ and added that they had ‘never achieved anything since they first started meeting’. He did agree that ‘the global financial system [is] not beneficial for emerging countries’ because the US Federal Reserve works ‘in the interests of the US’ ( O&s;Neil 2023 ). But many observers disagree. The narrative of global power and influence is visibly shifting from a unilateral to a multilateral one. Meetings where China, Russia and India, all BRIC nations, sit down to discuss world affairs are as followed in the international press as much as are G7 or G20 developed nations (Canada, France, Germany, Italy, Japan, the United States, with the EU in attendance). Russia was expelled in 2014 over its invasion of Crimea, a stance strengthened at the G7 Summit in Hiroshima, Japan, in 2023 ( Al Jazeera 2023 ).

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)0.003
metaresearch head score (Gemma)0.009
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: Other · Consensus signal: Other
Teacher disagreement score0.164
Threshold uncertainty score0.548

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0060.006
Scholarly communication0.0150.009
Open science0.0020.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1640.057

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 head0.083
GPT teacher head0.244
Teacher spread0.161 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

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