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Record W3124039744

International Organizations in a World of Regional Trade Agreements: Lessons from Club Theory

2007· article· en· W3124039744 on OpenAlexaff
Michele Fratianni, John C. Pattison

Bibliographic record

VenueSSRN Electronic Journal · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsCanadian Imperial Bank of Commerce (Canada)
Fundersnot available
KeywordsClubWorld tradeInternational tradeBusinessProcess (computing)Face (sociological concept)International economicsEconomicsSociologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

This essay deals with the challenge that international organizations face at the turn of the millennium. The basic insight from the theory of clubs and information theory is that coordination and cooperation require dominant providers. Cooperation becomes more difficult as players become more equal in economic size. Today's environment is less conducive to cooperation than the environment after World War II. By extension, club theory suggests that Regional Trade Agreements are not flukes. They have proliferated because cooperation is feasible in smaller groups with a few larger players. There is a significant risk, however, that regional blocs may replace the multilateral cooperative process. To reduce this risk we propose the creation of an inter-bloc international organization dedicated to reduce blocs' barriers to trade and finance.

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)0.008
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 score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.012
Scholarly communication0.0080.012
Open science0.0010.005
Research integrity0.0040.003
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 head0.031
GPT teacher head0.239
Teacher spread0.209 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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