Trade Liberalization Under NAFTA - Report Card on Agriculture
Bibliographic record
Abstract
NAFTA -Report Card on Agriculturethe NAFTA negotiations in agriculture was that Mexico, the United States and Canada are complementary to a large extent in overall agricultural production.He concluded that evidence after five years of implementation seems to confirm that.Thomas Hertel, a Purdue University trade analyst, presented results of a quantitative study that confirmed Rosenzweig's observation.He found a strong increase in the intensity of farm and food exports from the NAFTA member countries to NAFTA as a whole since the mid-1980s.This finding provides strong evidence of falling transactions costs and increasing integration within the North American market.The recent free trade agreements have most certainly played an important role in this process.Michele Veeman, a noted trade analyst from the University of Alberta, concluded that NAFTA has been very effective as a vehicle to promote trade liberalization and has contributed to reducing trade disputes.She summed up the NAFTA report card as making good progress but requiring extra effort to keep on working for even better achievements.A U.S.-Canadian team of government analysts, Mary Burfisher, Terry Norman and Renée Schwartz described the dispute resolution instruments that exist in the agri-food industry.They concluded that informal linkages among participants in the NAFTA countries offer the greatest opportunity to prevent misunderstandings from occurring and developing into sensitive, high-level disputes that require formal settings to be resolved.They observed that by fostering greater communication among parties engaged in trade, informal mechanisms might help prevent trade disputes from occurring.Informal discussions of the type represented by these workshops were concluded to be critically important to both preventing and settling disputes.When they work, they are more effective and less costly than formal government settlement mechanisms.Julian Alston and Daniel Sumner from UC-Davis, and Richard Gray from the University of Saskatchewan, noted that when U.S. farmers look North, they cannot help but suspect some trade effects of the Canadian Wheat Board (CWB).They also observed a growing awareness that termination of the CWB's monopoly position might increase, rather than reduce, grain flows into the United States.This is what happened when Canada's western grain transportation sub-vii tions was the path breaking agreement on sanitary and phytosanitary measures, which provided a blueprint for the Uruguay Round and NAFTA agreements on this issue.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".