Bibliographic record
Abstract
Abstract Recent Canadian preferential trade agreements (PTAs) include increased market access for imports of supply‐managed products (dairy and poultry). Such agreements are typically expected to create trade flows and increase supply of relatively low‐priced products in Canada. Industry groups representing Canadian producers and processors of supply‐managed products negotiated to receive approximately C$5 billion in payments from the federal government as compensation for the prospects of facing more international competition and reduced domestic sales. We discuss partial‐equilibrium simulation models that are commonly used by academics and governments to project market effects of new trade agreements, and conceptually illustrate how different assumptions about import supply conditions generate different projected market outcomes. We focus on the quota fill rates of new access commitments—most studies, including those used to inform government policies on compensation payments, assume imports increase in an amount equal to new commitments. This is often not the case, including with recent Canadian trade agreements. We apply a conceptual framework to Canada's supply‐management industry by re‐simulating a quantitative model of the Canadian dairy industry with updated information on implementation and quota fill rates. Projected market effects of trade agreements under the assumption of full import quotas are markedly different from projections that account for unfilled quotas. We discuss the political economy and welfare implications of compensation payments in light of our analysis.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".