Impacts of U.S. Sugar Policy and the North American Free Trade Agreement in North American Sugar Containing Products
Bibliographic record
Abstract
Sugar is one of the most protected agricultural commodities in the United States and other countries around the world through the use of production allotments, preferential marketing agreements, and tariffs. These protectionist measures lead to increased input costs for manufacturers of candies and soft drinks. The North American Free Trade Agreement (NAFTA) has in part altered the nature of sugar trade throughout the North American continent. This paper presents a game theoretical Cournot model which illustrates how trade in sugar containing products and the location of sugar containing product manufacturers in North America is likely to be impacted by the combined effects of U.S. sugar policy and NAFTA. Current international agreements which affect sugar confectioners are incorporated in the Cournot model such as NAFTA along with U.S. and Mexican re-export programs. Preliminary results indicate that domestic firms are at a cost disadvantage to firms that export into the domestic market due to current international agreements and domestic policy. Furthermore, due to the nature of policy in Canada, Mexico and the U.S., firms are implicitly given an incentive to locate in another country and export to Mexico or the U.S. The nature of current policy affects the amount of sugar trade between North American countries as firms seek to gain an advantage in the cost of inputs as well as the volume of finished goods traded between countries.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".