At the Cross-Roads of US and Canadian Trade Controls: The Cuba Conflict
Bibliographic record
Abstract
Canada and the United States are each other’s best trading partners. Our supply chains are deeply integrated. Corporate ownership criss-crosses the border many times over. In the context of foreign policy, although we have differed from time to time in the past, we generally target the same list of ‘bad actors’ – Iran, North Korea, Myanmar among them. Indeed, many of our sanctions programmes have been adopted pursuant to the same United Nations Security Council resolutions that are applied in similar fashion by UN member countries. Our controls on the export of goods and transfer of technology arise from our common commitments under the 1996 Wassenaar Arrangement on Export Controls for Conventional Arms, Dual-use Goods, Technology and other international agreements. It should come as no surprise therefore that in this environment many companies impose a single set of rules or principles regarding export controls and doing business with sanctioned countries. Under the assumption that Canadian and US laws are similar and, that any differences arise from more restrictive elements of US policy, a common default approach is for US companies to graft their US-based export control, economic sanctions policies, and procedures on to their Canadian operations; even some Canadian-based companies doing business in the United States will follow this approach. This is problematic for a number of reasons. Contrary to popular belief, Canadian export controls and economic sanctions can be more restrictive than those of the United States – aspects of the control regime for cryptographic goods and technology and the rules governing trade with and investment in Myanmar are two such examples. More importantly, there are instances in which there is direct conflict between Canadian and US law – that is, compliance with the requirements of one nation’s laws results in contravention of the laws of the other. Two examples of such conflict arise with US military controls under the International Traffic in Arms Regulations and Canadian human rights legislation and with Cuban trade and investment. The latter conflict is the focus of this article.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".