The Effects of NAFTA On U.S.-Mexican Trade and GDP
Bibliographic record
Abstract
The North American Free Trade Agreement (NAFTA) went into effect on January 1 1994, creating a free trade area encompassing the United States, Canada, and Mexico Since then, agreements have been proposed-and, in some cases, negotiations begun or even completed-for a Free Trade area of the Americas and free trade areas with a number of other countries of varying degrees of development Consequently, assessing the effects of NAFTA is relevant to current debates about trade policy. This Congressional Budget Office (CBO) paper prepared at the request of the Chairman of the Senate Committee on Finance-examines aggregate U.S.-Mexican trade in goods in the first eight years after NAFTA went into effect and how it has been affected by the agreement and by other favors. The paper provides quantitative estimates of the effects of NAFTA on that trade and of the resulting effects on U.S. gross domestic product. (The paper focuses on U.S. trade with Mexico because U.S. trade with Canada had already been substantially liberalized in accordance with the Canada-United States Free Trade Agreement before NAFTA went into effect).
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".