North American Agricultural Market Integration And Its Impact On The Food And Fiber System
Bibliographic record
Abstract
Economic change and market dynamics have fundamentally altered the structure and performance of agricultural markets in the United States, Canada, and Mexico within the last 25 years. Many factors have helped shape the current North American food and fiber system, including technological change, domestic farm policies, international trade agreements, and the economic forces of supply and demand. Ratification of NAFTA, for example, helped integrate the North American market, sparking a surge in trade and investment among the United States, Canada, and Mexico. In recent years, efforts to further integrate the continental market seem to have slowed. Broadening the scope of NAFTA to include institutional reforms that lead to a more unified system of commercial law, the establishment of common antitrust and regulatory procedures, harmonization of product standards, and increased coordination of domestic farm, market, and macroeconomic policies would deepen market integration and enhance market efficiency and growth within North America.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".