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Transpacific Integration and Open Regionalism: The Case of Singapore as Associated State of the Pacific Alliance

2024· article· en· W4405689658 on OpenAlexaboutno aff
Fabricio A. Fonseca

Bibliographic record

VenueThe Korean Journal of International Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsnot available
Fundersnot available
KeywordsAllianceRegionalism (politics)State (computer science)Political scienceInternational tradeEconomic geographyGeographyBusinessComputer science

Abstract

fetched live from OpenAlex

The Transpacific integration process is entering its third decade, and it encompasses a vast number of economic agreements and a wide range of actors on both sides of the Pacific. In the side of Latin America, the Pacific Alliance (PA) and its member states have been identified as using the concept of open regionalism to maximize their integration efforts, not only between themselves, but also with their counterparts in the Asia-Pacific. With the introduction of the category of Associated State, the PA founding members (Chile, Colombia, Mexico and Peru) have been able to add a new dimension to this Transpacific integration process. In 2022, Singapore was the first country to receive that category after finalizing negotiations for a free trade agreement with all the Alliance members. Other candidates are Australia, Canada, New Zealand, and more recently, South Korea. This article intends to trace the process of Singapore’s partnership with the PA, exploring the different motivations and features of economic ties between both sides of this new development. Therefore, through the observation of qualitative data and descriptive statistics, we suggest that it is possible to move beyond material incentives and drives, and emphasize elements such as shared values and ideas, in order to better comprehend the decision of those actors in coming together and continue promoting notions associated with a liberal and multilateral trading system, as a preferred model for Transpacific cooperation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.063
GPT teacher head0.368
Teacher spread0.305 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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