The Prophecies of the Naysayers - Assessing the Vision of the Protectionists in the U.S.-Canada Debate on Agricultural Reciprocity, 1846-1854
Bibliographic record
Abstract
Debates over proposals to liberalise international trade are often heated and acrimonious. They are often argued, in part, on the basis of projections of market conditions after the proposed liberalisation. These argument are often important in influencing trade policy decisions, yet their accuracy is seldom assessed after liberalisation takes place. As a result, the projections may be more influential than they should be. This paper examines the projections of protectionists in the debate surrounding a proposed reciprocity agreement between the United States and British North America over the period 1846-1854 as a case study. The protectionist prophesies on both sides of the border were found not to be supported by the evidence from the subsequent period of reciprocity. A number of reasons for the inaccuracy of the projections are identified.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".