Bibliographic record
Abstract
Canada has long been subject to the powerful cross-pressures of geopolitics and global demand for its bountiful natural resources. Looking ahead over the next quarter century, I expect that the most important impact on Canada's relations with the world will stem from geopolitical developments in the United States and Asia. Not only will demand for natural resources and commercial products from these two parts of the world exert an ineluctable influence over Canada's economic development, but so too will the fallout generated by the politics of China's rise and America's response to this new force. We might call this the shadow of geopolitics. As Canada attempts to diversify its economy away from an overreliance on the American market, rising Sino-American tensions will effectively shrink geopolitical space in the most important new market for Canadian trade and investment. The paradox is that as Canada is drawn into economic flows connected to Asia's political economy, it will also slide into the crosshairs of rising Sino-American geopolitical tensions. In other words, to the extent that Canada reduces its economic vulnerability to the United States, it will become more susceptible to geopolitical vulnerabilities in Asia. Ironically, over the next 25 years or so, economic diversification may well generate geopolitical vulnerability for Canada in its global relations.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.025 | 0.022 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".