The Economic Impact of a U.S. Slowdown on the Americas
Bibliographic record
Abstract
This paper shows that the U.S.'s biggest trading partners in the Americas will likely see a significant loss in exports and GDP as the U.S. economy slows. Countries less reliant on the U.S. market will not be as negatively impacted. The paper makes two sets of projections for the decline in exports countries in the Americas may experience. The low-adjustment scenario assumes that the U.S. trade deficit falls from 5.2 percent of GDP in 2007 to 3.0 percent of GDP in 2010. The high adjustment scenario assumes that the U.S. trade deficit falls back to 1.0 percent of GDP by 2010. The paper finds that the countries that will likely suffer most as the result of a reduction in U.S. imports are the same countries with which the United States has implemented “free trade” agreements in recent decades, including the North American Free Trade Agreement (NAFTA) between the United States, Canada, and Mexico, and the Dominican Republic-Central America Free Trade Agreement (DR-CAFTA), which includes the United States along with Guatemala, El Salvador, Costa Rica, Nicaragua, Honduras, and the Dominican Republic. Meanwhile, countries that are less dependent on the United States, or more reliant on domestic demand, will see smaller impacts of the U.S. recession on their exports and national GDP.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".