Principles of free trade agreements, from GATT 1947 through NAFTA Re-Negotiated 2018
Bibliographic record
Abstract
Free trade agreements (FTAs) have dominated global trade for over a decade. This dominance is likely to continue for many years on every continent. Already, more than half of all international trade takes place under FTAs. Principles of Free Trade Agreements, from GATT 1947 through NAFTA Re-Negotiated 2018 examines the origins of free trade agreements (FTAs) and customs unions (CUs) in Article 24 of the GATT 1947 agreement. Article 24 permits but attempts to regulate their creation, an effort that failed early on. A sleeping giant for decades, FTAs were re-awakened by the path-breaking Canada-U.S. FTA of 1989. In 1994, NAFTA triggered an onslaught of hundreds of FTAs around the globe, overwhelming the impact of the establishment of the World Trade Organization in 1995. The coverage, trade rules and trade remedies of the world's FTAs are remarkably and complexly diverse. Perhaps surprisingly, the hostility of President Trump to multilateral trade agreements like TPP-12, the WTO, the EU and NAFTA 1994, caused the number of FTAs to increase. America's trade partners and competitors rushed to secure trade deals not involving the USA. TPP-11, the Japan-EU FTA, the expanded Mexico-EU FTA, and the China-driven RCEP provide excellent examples. Meanwhile, despite being characterized by President Trump as the worst trade deal ever, the United States, Canada and Mexico completed re-negotiation of NAFTA in 2018. All of this, and more, is covered in this book. Designed for students, lawyers, government officials and people in business, the author addresses the interests not only of Americans, but also those located outside the USA who are concerned about the law and economics of free trade agreements. Active links for the e-book and downloadable versions of this Concise Hornbook are provided throughout.--Publisher website.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".