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Record W3114862850 · doi:10.32796/cice.2020.100.7120

American Tariffs and their Impact in the EU and Spain

2020· article· en· W3114862850 on OpenAlexaff
Fátima El Khatabi, Carlos Llano, Federico Steinberg

Bibliographic record

VenueCuadernos Económicos de ICE · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsImpact
Fundersnot available
KeywordsProtectionismInternational tradeSustainabilityInternational economicsEconomicsGlobalizationValue (mathematics)BusinessMarket economy

Abstract

fetched live from OpenAlex

Donald Trump´s so called trade wars and the COVID-19 pandemic are likely to have a substantial impact on international trade flows and would probably reshape globalization. As trade is restricted by tariffs, global value chains are shortened and international cooperation becomes more difficult, there is a chance that environmental sustainability will increase due to lower and shorter trade flows. This paper tackles this issue by exploring the impact that recent American tariffs have had on the EU with a special focus in Spain. Using the SMART simulation model developed by the World Bank and the UNCTAD, we estimate the impact of the new tariffs applied to iron, steel and aluminum, the products included in the list of products affected by the Airbus dispute, as well as the potential new tariffs to the automotive sector. We end with a discussion on the effects of this new wave of protectionism on sustainability.

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)0.000
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 score0.112
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.029
GPT teacher head0.242
Teacher spread0.213 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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