Trade Diversification Away from the U.S. or North American Customs Union? A Review of Canada's Trade Policy Options
Bibliographic record
Abstract
This study examines Canada’s key strategic trade policy options – whether pushing for further economic integration with the U.S., or diversifying to non-U.S. markets and reducing the degree to which Canada’s economy depends on the U.S. In particular, this study compares the economic benefits of implementing a North American customs union with the benefits of increasing Canada’s trade with either emerging countries (e.g., India, China, Brazil) or with advanced partners such as Europe and Japan. The main conclusion is that there may be considerable benefit to Canada of diversifying some of its trade away from the United States provided that countries with more youthful populations and rapid growth, such as India, are targeted. Diversification to older countries such as Europe and Japan would not be beneficial. The analysis is based on a series of recent policy-modeling studies by the authors examining the economic impacts of diverse trade policies options in global economy models, taking also into consideration an important feature of the 21st century, the demographic changes around the world that accompany the globalization process for goods and services, capital and labor. / Cette étude examine certaines options de politique commerciale pour le Canada, en particulier la question de savoir si le Canada devrait poursuivre encore plus son stade d’intégration économique avec les États-Unis, ou s’il devrait diversifier son commerce et réduire son degré de dépendance face aux États Unis. En particulier, l’étude compare les bénéfices d’une éventuelle Union Douanière avec les États-Unis par rapport à ceux d’un commerce croissant avec certains pays émergents (Inde, Chine, Brésil) ou avec l’Europe et le Japon, et conclue qu’il existe des bénéfices pour le Canada de diversifier une partie de son commerce en faveur de pays démographiquement plus jeunes et à croissance plus rapide – par exemple, l’Inde ou le Brésil, mais non en faveur de l’Europe ou du Japon. Cette étude se base sur les résultats d’études précédentes menées par les auteurs et qui examinent les impacts économiques de différentes options commerciales à l’aide de modèles d’équilibre général prenant en compte une caractéristique importante du 21ième siècle, les changements démographiques mondiaux qui accompagnent le processus de globalisation des biens et services, du capital, et du travail.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.015 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".