Bibliographic record
Abstract
In the wake of civil protest in Seattle during the 1999 World Trade Organization meeting, many issues raised by globalization and increasingly free trade have been in the forefront of the news. But these issues are not necessarily new. Taking Trade to the Streets describes how so many individuals and nongovernmental organizations came over time to see trade agreements as threatening national systems of social and environmental regulations. Using the United States as a case study, Susan Ariel Aaronson examines the history of trade agreement critics, focusing particular attention on NAFTA (the North American Free Trade Agreement between Canada, Mexico, and the United States) and the Tokyo and Uruguay Rounds of trade liberalization under the GATT. She also considers the question of whether such trade agreement critics are truly protectionist. The book explores how trade agreement critics built a fluid global movement to redefine the terms of trade agreements (the international system of rules governing trade) and to redefine how citizens talk about trade. (The "terms of trade" is a relationship between the prices of exports and of imports.) That movement, which has been growing since the 1980s, transcends borders as well as longstanding views about the role of government in the economy. While many trade agreement critics on the left say they want government policies to make markets more equitable, they find themselves allied with activists on the right who want to reduce the role of government in the economy. Aaronson highlights three hot-button social issues--food safety, the environment, and labor standards--to illustrate how conflicts arise between trade and other types of regulation. And finally she calls for a careful evaluation of the terms of trade from which an honest debate over regulating the global economy might emerge. Ultimately, this book links the history of trade policy to the history of social regulation. It is a social, political, and economic history that will be of interest to policymakers and students of history, economics, political science, government, trade, sociology, and international affairs. Susan Ariel Aaronson is Senior Fellow at the National Policy Institute and occasional commentator on National Public Radio's "Morning Edition."
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.010 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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.
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".