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Record W2086058572 · doi:10.1177/000271620257900112

International Financial Architecture and International Financial Standards

2002· article· en· W2086058572 on OpenAlexaff
Michele Fratianni, John C. Pattison

Bibliographic record

VenueThe Annals of the American Academy of Political and Social Science · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsCanadian Imperial Bank of Commerce (Canada)
Fundersnot available
KeywordsFinanceBusinessSystemic riskInternational financeFinancial regulationBest practiceSpillover effectFinancial marketArchitectureWork (physics)Financial crisisAccountingEconomicsEngineeringManagement

Abstract

fetched live from OpenAlex

The international financial architecture literature is concerned with a set of best principles and practices that may lower the risk of financial crises and spillover effects. The financial world has grown enormously more complicated since the end of Bretton Woods. The valuable work of several standard-setting institutions must be judged as minimum requirements for good practice, which are below the perceived needs of the leading financial centers. The paper proposes a "portal" solution, in which the two most important financial centers, the United States and the United Kingdom, set best practices on international financial standards. Since these two centers control access to international markets, and thus, are the conduit of systemic risk, they can establish both the rules for market access and the core regulatory and supervisory framework to deal with international systemic issues. The regulators of the two portals therefore play the fundamental international regulatory role.

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)0.007
metaresearch head score (Gemma)0.015
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: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0030.019
Scholarly communication0.0130.011
Open science0.0010.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.330
Teacher spread0.274 · 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
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
Published2002
Admission routes1
Has abstractyes

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