From NAFTA to USMCA: Can a Good Idea that Came Too Late Be Born Again?
Bibliographic record
Abstract
This article analyzes from the trade perspective the lower-than-expected growth dividends of the export-led strategy adopted by Mexico in the 1990s. Particular attention is given to employment, labor productivity, and regional outcomes. The North American Free Trade Agreement (nafta) caused Mexican exports to skyrocket in the first years of its implementation. This initial lift was quickly sapped by China’s emergence after its entry into the World Trade Organization (wto) in 2001. Recent years witnessed a renewed dynamism of Mexican presence in the U.S. market. In an international context marked by deglobalization and decoupling, this rebound is expected to continue under the United States-Mexico-Canada Agreement (usmca). Yet, in order to deliver economic growth, Mexico needs to diversify the geographical location of its exporting industries. The analysis of Mexican exports shows also that idiosyncratic weaknesses, such as the low contribution of the business services sector or the deficient trade and transport infrastructure, must be addressed.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.010 | 0.023 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.015 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".