Comparison of Gains for LICs and HICs under the WTO Framework Within the NAFTA Context
Bibliographic record
Abstract
Since the 1990s, the global trade system has been shaped by two major institutions: the World Trade Organization (WTO) and the North American Free Trade Agreement (NAFTA). The WTO, established in 1995, aims to stabilize global trade through multilateral agreements and structured dispute resolution. NAFTA, launched in 1994, created a regional trade bloc comprising the United States, Canada, and Mexico, aiming to promote economic integration by reducing tariffs and non-tariff barriers.This article explores the differential gains achieved by high-income countries (HICs) and low-income countries (LICs) within the WTO framework in the context of NAFTA. While all three NAFTA members—the United States, Canada, and Mexico—benefited from WTO membership, the nature and extent of their gains vary. Using a comparative analysis of institutional influence, trade structure, and dispute participation, the study reveals that HICs enjoy broader rule-shaping advantages, while LIC-like members, such as Mexico, face structural and policy constraints that limit their ability to gain. The findings highlight that WTO participation reinforces existing hierarchies in global trade unless accompanied by targeted domestic upgrading.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
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".