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Record W4409471496 · doi:10.4236/me.2025.164029

Why Americans Voted for Trade Protectionism Again: A Review of Political-Economic Models

2025· review· en· W4409471496 on OpenAlexaboutno aff
Karl Farmer

Bibliographic record

VenueModern Economy · 2025
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
Fundersnot available
KeywordsProtectionismEconomicsPoliticsInternational economicsInternational tradePolitical scienceLaw

Abstract

fetched live from OpenAlex

Since 2018, the USA has unilaterally imposed tariffs on imports of goods from abroad, especially from China. President Trump enacted since the inauguration for his second term further increases in tariffs, for imports from Mexico, Canada, China, und announced recently tariffs for imports from Europe. Why did a politician who explicitly advocated foreign trade protectionism become again president of the world’s most economically developed country? Why do US voters value the economic freedom of being able to buy cheaper foreign goods instead of more expensive domestic goods less than the rather dubious promise of making domestic industry great again? The paper answers these questions based on a review of political-economic models published since Trump’s first term as follows: Foreign trade protectionism has once again become politically powerful in the USA because, within the framework of international supply policy, US globalization losers could not be compensated, white lower middle-class men in the old industrial areas of the USA were tormented by status anxiety towards people of different colors and foreigners, about half of the US electorate no longer identified with the nation as a whole but only with their own social class, and after China joined the WTO, voters and party representatives who were in favor of free trade became nationalists and protectionist social conservatives. According to an economically liberal interpretation of natural law, however, free international trade does not contradict social conservatism.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.829
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.136
GPT teacher head0.292
Teacher spread0.156 · 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
GenreReview

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

Citations2
Published2025
Admission routes1
Has abstractyes

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