A robust analysis of trade policy: the chicken and softwood lumber wars
Why this work is in the frame
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Bibliographic record
Abstract
Purpose The paper extends the robust political economy framework to analyze the impact of tariffs on the entrepreneurial market process. It proposes that the unintended consequences of using trade policy to bolster a nation's economy will inevitably prevent an economy from allocating its resources to their highest-valued use. The study aims to expand the robust political economy literature to international trade. Design/methodology/approach The paper develops a robust analysis of trade policy and illustrates it with two case studies of trade wars: The Chicken War (1963) and the US–Canada softwood lumber disputes (1982-present). Findings The paper provides theoretical insights into how the entrepreneurial market process is distorted by trade barriers. The case studies show that the theoretical insights have real-world implications that should not be ignored when planning trade policy. Originality/value This paper applies a robust political economy framework to international trade.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it