US NonProliferation Policies and Canada’s Medical Isotopes Industry: A Case Study in Nuclear Ambivalence
Bibliographic record
Abstract
This paper analyzes how US nonproliferation policies that sought to curtail US exports of highly enriched uranium (HEU) affected Canada’s medical-isotope industry and, more particularly, the Canadian MAPLE reactors project. US HEU-export policies set between 1978 and 2012 highlight the “nuclear ambivalence” of the Canadian isotope industry’s flagship product, molybdenum-99 (Mo-99)—a life-saving commodity widely used by US hospitals but also a material whose production process, based on HEU, came to be perceived as a potential threat to US and world security. The ambivalent status of Mo-99 production was reinforced by a state of mutual dependence between the two countries: on the one hand, Canada depended entirely on US HEU exports to maintain its dominant position on the Mo-99 world market and could not turn to other sources of HEU supply. On the other hand, US hospitals relied mainly on Mo-99 of Canadian origin, which limited the US government’s ability to enforce its policy by suspending its HEU exports to Canada. As a result, US and Canadian efforts to convert the Canadian isotope facilities to low-enriched uranium (LEU) were thwarted by tensions between global security, public health, and commercial stakes, which led ultimately to ending Canada’s Mo-99 production.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.047 | 0.019 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".