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Record W7019536502

Guerra comercial entre ee.uu. y china: su impacto en la seguridad internacional

2020· article· en· W7019536502 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicExtractivism and Socioeconomic Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMultilateralismProtectionismChinaSloganEconomic nationalismHegemonyLatin AmericansNationalismTrade warWorld economyCold war
DOInot available

Abstract

fetched live from OpenAlex

The two economic superpowers: USA and China are immersed in a trade war that threatens the stability and growth not only of their economies, but the rest of the countries that occupy our planet. On the one hand, the United States with its nationalist and protectionist eagerness demonstrating its hegemonic ideas, starting from the slogan "america first"; China is committed to multilateralism from various global and regional platforms. North American companies operating in China would lose up to 12% of their profits. The trade war affects several countries, world growth is threatened and uncertainty reigns in international companies. US markets drop their products due to the rise in Chinese tariffs, the confrontation between the two nations can become an economic crisis that drags the US. and the world to a recession. Beijín argues that the only way out of the conflict is the talks, insists Washington to reconsider its hostile stance which will have dire consequences for the world economy. Latin American currencies weaken against the dollar, investors are more cautious to this joins the increase in the value of raw materials. North American farmers lose sales. Europe's economy is weakening, as is Germany's. Third countries benefit such as: Japan, Canada, Mexico. The supremacy in the technological area is at stake for the Americans. Cooperation and dialogue are better than friction and confrontation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.279
Teacher spread0.269 · 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.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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