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Record W6986251619

The Pacific Alliance's Relationships with its Future Associate Members: A Multidimensional View from the Perspective of Trade, Investment and Economic Cooperation

2021· article· en· W6986251619 on OpenAlexaboutno aff

Bibliographic record

VenueEl Repositorio Institucional de la Universidad EAFIT (Universidad EAFIT) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIsland Studies and Pacific Affairs
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationAllianceInvestment (military)Perspective (graphical)Asia pacific
DOInot available

Abstract

fetched live from OpenAlex

The Pacific Alliance emerged with the objective of serving as a platform for articulating the efforts of its members in matters involving trade, investment and cooperation with the Asia Pacific region. The Pacific Alliance's projection towards this region has currently become impending as it has entered negotiations with Australia, Canada, New Zealand and Singapore to become Associate members. Since these negotiations will involve the establishment of new generation economic agreements between the Pacific Alliance as a bloc and these countries, it important to study the relations with this group of countries from a multidimensional perspective, as well as to address some of the main opportunities and challenges that may arise within the framework of this process. The study concludes that there is great potential for the strengthening of commercial relations with the Associate members in the food (especially products of animal origin, dairy products, and food processing) textiles and apparel sectors, which are among the most protected. Foreign investment and economic cooperation must be channeled towards the productive sectors that have the greatest capacity to generate value chains.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.012
Scholarly communication0.0140.008
Open science0.0010.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEl Repositorio Institucional de la Universidad EAFIT (Universidad EAFIT)Same topicIsland Studies and Pacific AffairsFrench-language works237,207