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Record W4396888406 · doi:10.1080/10971475.2024.2350125

China-Mexico Economic Relationship in the Context of China’s Penetration in Latin America

2024· article· en· W4396888406 on OpenAlexaboutno aff
Nathalie Aminian, Cuauhtémoc Calderón Villarreal

Bibliographic record

VenueChinese Economy · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
Fundersnot available
KeywordsChinaLatin AmericansContext (archaeology)Penetration (warfare)GeographyPolitical scienceDevelopment economicsEconomyEconomicsArchaeologyManagement

Abstract

fetched live from OpenAlex

China’s relationship with Latin America countries experienced a process of significant expansion over the past two decades. Even though Latin America was not considered as part of the BRI when it was first established, China designed its economic strategy toward the region by emphasizing investment, financial and industrial capacity cooperation, besides trade. Afterwards, China invited Latin American countries to participate in the BRI at the China–Community of Latin American and Caribbean States (CELAC) Ministerial Forum in Santiago in January 2018. Twenty-one Latin American and Caribbean (LAC) countries have signed up to the BRI. However, there are few LAC countries that have not done so, among them the region’s largest economies such as Brazil, Mexico and Colombia, although Brazil is with full AIIB membership. This paper focuses on the specific economic relations between China and Mexico, as far as Mexico is the less involved LA country into the BRI, and Mexico’s position toward China is more aligned with that of its North American partners than to the Latin American countries. This article analyzes the specific situation of Mexico, characterized by its deep integration and dependency on the US market and examines the current economic relations of China and Mexico, considering the impact of the United States–Mexico–Canada Agreement on the bilateral economic relations. The structure of bilateral trade between Mexico and China is also examined, using the Grubel-Lloyd Index (GLI).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.293
Teacher spread0.276 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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