El Foro China-CELAC en la disputa por la hegemonía económica global entre Estados Unidos y China, en América Latina y el Caribe
Bibliographic record
Abstract
The objective of this article is to analyze, based on international economics, the economic relationship between Latin America and the Caribbean (lac) with China in the first quarter of the 21st century, a period in which China consolidates itself as an economic power and emerges as an alter ego to the United States (USA) in the struggle for economic supremacy. Using the comparative method, the article describes the stages of the Sino-Latin American relationship, from the political and economic ties established by China with the Community of Latin American and Caribbean States (CELAC), an organization created in 2011 that later in 2015 created the China-CELAC Forum (Foro China-CELAC Forum or FCC), incorporating China as a partner. We have found that China is gaining ground over the USA in the Latin American region, which has only recently begun to implement some actions to counteract China’s presence in LAC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".