PROCESSED FOOD TRADE AND FOREIGN DIRECT INVESTMENT UNDER NAFTA
Bibliographic record
Abstract
Trade in processed food products is rapidly growing. Trade with Canada and Mexico has especially been growing since free trade agreements have been implemented. The U.S. presence in the processed food industry in other countries through foreign direct investment (FDI) is also large and has been expanding. The relationship between trade and FDI is uncertain and subject to much debate. Japan and Canada are the largest importers of processed foods from the United States, followed by Mexico and Korea. Canada is the leading exporter of food products to the United States, followed by France, Mexico, and Italy. Canada and Mexico have, in recent years, become increasingly important trading partners in processed foods. Results from this study do not conclusively indicate any type of relationship between FDI and trade. Trade in processed foods also appears to be mostly insensitive to the exchange rate. Some of the increase in trade flows can be explained by growth in real GDP. Trade liberalization may also explain the increase in trade flows. Free trade agreements have positively influenced U.S. FDI in Canada and Mexico. Labor cost and inflation in the host country also influences U.S. FDI.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".