The Future of Canadian Trade Policy: Three Symposia on Canada’s Most Pressing Trade Policy Challenges
Bibliographic record
Abstract
The global economy has gone through dramatic and rapid changes over the past 20 years and the current environment is a challenging and evolving landscape for practitioners to manage. Meanwhile, economic research on international trade is also evolving with theory and empirical evidence on a rapidly changing global economy and policy space. What are the key challenges and opportunities facing Canada in a rapidly changing global economy and what are the most important and relevant international policy directions being developed? To examine these and related questions, leading institutions and scholars organized three events where they discussed the direction of Canadian trade policy and trade policy research. The University of Calgary’s School of Public Policy, the University of Ottawa’s CN-Paul M. Tellier Chair on Business and Public Policy in the Graduate School of Public and International Affairs, the Centre for International Governance Innovation, and Global Affairs Canada partnered to bring together leading scholars, stakeholders and trade policy experts to address Canada’s most pressing trade policy issues. Topics included the effect of new technology on trade, progressive trade policy, the rise of protectionism, changes in global supply chains, and the role of academia in the formulation of trade policy, among others. The result was the development of new directions for the study and practice of trade policy in Canada. This report summarizes the findings of these meetings to make them accessible to scholars and policymakers. The programs for each of the three symposia are provided as an appendix. The three symposia were developed by a research planning team that included Eugene Beaulieu, Shenjie Chen, John Curtis, Judit Fabian, Patrick Leblond, Meredith Lilly, and Marie-France Paquet.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.027 | 0.006 |
| Scholarly communication | 0.022 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".