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Record W2758959039

The Prospects for U.S. Trade Policy under the Trump Administration

2017· article· en· W2758959039 on OpenAlexaboutno aff
Beata Słomińska, Marek Jan Wasiński

Bibliographic record

Venue˜The œPolish Quarterly of International Affairs · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Political and Economic Relations
Canadian institutionsnot available
Fundersnot available
KeywordsPledgeCommercial policyInternational tradeAdministration (probate law)Free tradeBalance of tradePolitical scienceInternational free trade agreementGeneral partnershipEconomicsPublic administrationLaw
DOInot available

Abstract

fetched live from OpenAlex

IntroductionAfter a long campaign, Donald Trump won the Republican Party presidential nomination in July 2016, and then on 8 November, defeated Democratic candidate Hillary Clinton in electoral votes, 306 to 232, despite lower popular support (63 million votes against 65 million cast for Clinton).1 One of Trump's major campaign rallying cries was the need to revise current U.S. trade policy, namely to re-negotiate the North American Free Trade Agreement (NAFTA) with Canada and Mexico; to withdraw the U.S. from the Transpacific Partnership (TPP); and to take retaliatory measures against trade partners engaging in unfair practices (with direct reference to China).2 Then, on 20 January 2017, in his Inaugural Address,3 the president reaffirmed the importance of trade policy to the agenda of the new U.S. administration, describing it as a priority area of his America First pledge and its principal goals, including the creation of 25 million new jobs.4 The new trade policy will rely chiefly on measures subject to his Buy American and Hire American5 principle and, on the one hand, promote businesses in the U.S. while, on the other, taxing U.S. production abroad, as well as targeting major trade partners to improve the trade balance.Trump's vision of trade policy diverges strongly from the Republicans' traditionally liberal course of expanding the free trade area, an integral component, based on bilateral, macro-regional (NAFTA, TTIP, TPP) and multilateral (World Trade Organisation, or WTO) agreements. It converges with the direction of a recent change in public perception of trade agreements. Pre-election polls reflected protectionist tendencies in American citizens' attitudes. A Politico-Harvard survey showed that 47% of the Republican electorate believed trade agreements entered into by the U.S. had adversely affected Americans' living standard in the past 10 years while 18% felt those treaties had contributed to an increase in welfare (among the Democratic electorate, the figures were 24% and 33%, respectively).6 An October 2016 Pew Research poll also confirmed the preponderance of anti-trade attitudes among the Republican electorate, with about 68% of these respondents stating free trade agreements were detrimental to the U.S. Scepticism about free trade ran the strongest amongst Trump supporters (67% in the primaries, according to polls conducted in March 20167 and 68% in August 20168 following Trump's nomination as the Republican candidate). This shiftin the preferences of the Republican electorate, a majority of whom as recently as in May 2015 had been in favour of entering into trade agreements with third countries (with barely 36% of respondents pronouncing such a policy unfavourable) was due, among other things, to the climate of opinion on trade agreements fostered by Trump as well as by Democratic candidates Bernie Sanders and Hillary Clinton. However, the split over trade policy in the Republican camp already was increasingly noticeable towards the end of the TPP negotiations.Trade to the U.S. EconomyIn 2015, the U.S. was the world's greatest trade power, accounting for 12% of global trade in goods and services, slightly ahead of China, which ranked first in global exchange of goods.9 In 2016, the value of U.S. trade stood at $4.9 trillion, with imports of $2.7 trillion in excess of exports of $2.2 trillion.10 At 28%, trade's share of U.S. GDP is well below the global average of 58% (compared to 83% for the EU, 73% for Mexico, 65% for Canada, 41% for China, 36% for Japan). This reflects the strength of the American domestic market as the foremost driver of the economy, with exports accounting for 13% of GDP, compared to the global average of 30% of GDP.11Despite the strong position of the U.S. economy on the global market, the asymmetry in U.S. trade with its chief partners remains a problem. In 2016, the U.S. had the largest nominal trade deficit in the world, of $500 billion.12 However, the U. …

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0110.006
Scholarly communication0.0170.006
Open science0.0010.004
Research integrity0.0210.013
Insufficient payload (model declined to judge)0.0190.006

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 head0.021
GPT teacher head0.321
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2017
Admission routes1
Has abstractyes

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