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Record W3125739589

Restoring Trade's Social Contract

2017· article· en· W3125739589 on OpenAlexaboutno aff
Frank J. García, Timothy Meyer

Bibliographic record

VenueeYLS (Yale Law School) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsFree tradeRevenueTrade barrierInternational tradeInternational free trade agreementEconomicsMandateTax revenueBusinessGovernment (linguistics)CurrencyInternational economicsFinancePolitical science
DOInot available

Abstract

fetched live from OpenAlex

As we write, the United States, Canada, and Mexico are meeting in Washington, D.C. to renegotiate the North American Free Trade Agreement (NAFTA). These talks—and their possible failure—represent the biggest shift in U.S. economic policy in a generation. Since NAFTA came into force in 1994, it has transformed the North American economy. NAFTA has made possible continent-wide supply chains, in industries like the auto sector, that have reduced costs and allowed American automakers to remain competitive; it has opened markets for American agriculture; it has greatly increased the standard of living in Mexico; and it has reduced consumer prices across the continent. Despite these gains, President Trump has repeatedly threatened to pull the United States out of NAFTA if he cannot get a deal that is “fair” for American workers. These repeated threats, coupled with aggressive U.S. government proposals to roll back liberalization in NAFTA 2.0, have sent the Canadian and Mexican governments and the U.S. business community searching for new policy ideas to save free trade.\nRestoring Trade’s Social Contract answers this call by proposing a financial transaction tax (FTT) in NAFTA and future trade agreements. The tax, no more than .1% of the value of securities or currency sales within the free trade area, would raise revenue to fund an expansion of adjustment assistance for workers who are displaced due to trade liberalization. An Economic Development Chapter in NAFTA and future trade agreements would mandate that this revenue be spent on expanded domestic trade adjustment assistance programs, such retraining, relocation assistance, and infrastructure investment.\nOur proposed tax would thus directly harness the wealth-creating potential of trade agreements and explicitly tie funding for adjustment assistance to major financial institutions, the parties benefitting the most from trade agreements. In so doing, it would restore what we term the social contract of trade—a bargain whereby trade liberalization occurs in a way that ensures that the least well off among us are, at a minimum, not harmed. Despite its huge contributions to poverty reduction and increased human welfare since World War II, trade liberalization has contributed to significant job losses, leading to economic calamity and social disruption in industrial heartlands from the mid-Western United States to Manchester, England and Wallonia, Belgium. These economic losses, in turn, have spurred the political backlash that now threatens the international economic order. Securing the long-term benefits of trade liberalization for ourselves and our fellow citizens—making free trade politically sustainable—thus requires including in trade law itself measures to address these significant costs. With NAFTA talks ongoing and the United States debating tax reform, the time is right for an FTT dedicated to expanded adjustment assistance.

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)0.011
metaresearch head score (Gemma)0.025
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: Other · Consensus signal: Other
Teacher disagreement score0.979
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0140.023
Scholarly communication0.0170.012
Open science0.0020.011
Research integrity0.0100.013
Insufficient payload (model declined to judge)0.0200.004

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 head0.034
GPT teacher head0.313
Teacher spread0.279 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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