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Regionalism and the Multilateral Trading System

2017· book-chapter· en· W2687983987 on OpenAlexaffabout
James Peter Murphy, Carolan McLarney

Bibliographic record

VenueAdvances in business strategy and competitive advantage book series · 2017
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsInternational tradeRegionalism (politics)Free tradeRegional tradeGlobalizationInternational economicsInternational free trade agreementWorld tradeLiberalizationTrade barrierEuropean unionEconomic integrationEconomicsPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Regionalism and the Multilateral Trading System: The Role of Regional Trade Agreements is a discussion about the new reality and the evolution of the reduction of international barriers to freer trade under the World Trade Organization (WTO) formerly the General Agreement on Trade and Tariffs (GATT). The chapter devotes time to the two largest regional trade agreements (RTAs), the European Union (EU) with 28 countries and North American Trading Agreement (NAFTA) with three countries account for half of all world trade (WTO, 2017a). The US set a course post World War II as the proponent of globalization and freer trade. RTAs at that time were failing or inconsequential. In response to the EU trading block, the US committed to a (Free Trade Area) FTA with Canada and subsequently the NAFTA with Canada and Mexico the rest of the world began to become concerned about being shut out of a preferential trade deal. The main theme of the chapter is that trade liberalization is moving forward because of Regional Trading agreements, not the WTO which is stalled and may never restart in its current form.

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)0.000
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.002

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 head0.029
GPT teacher head0.217
Teacher spread0.188 · 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
GenreReview

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

Citations7
Published2017
Admission routes2
Has abstractyes

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