The New Geopolitics of Globalization: Bulls, Pandas and the Road to Charlevoix
Bibliographic record
Abstract
Rising tensions in the Yellow Sea, a festering ‘Migrant Crisis’ in Europe and Africa and resurgent antagonisms in the Persian Gulf are further threatening the Post-War social contract bequeathed by President Truman, Gen. Marshall and Gen. Eisenhower: praetorian Midwestern pragmatists whose work underpinned political stability and economic prosperity globally for more than 70 years... A geoeconomic realignment seems to be under way: the Canadian Prime Minister has announced his intention to join the China-backed AIIB, thus becoming the first North American member of the institution, a bold political decision that aligns with the country’s thirst for overseas investments in infrastructure – an asset class where Canadian pension funds have become the world’s leading financial investors. Tellingly, Trudeau has traveled repeatedly to Beijing, discussing the future of free trade, international monetary policy coordination, infrastructure investment, climate change and global labor law norms, thus giving the Chinese leadership a high-level ‘sneak preview’ of the upcoming G7 Summit (Charlevoix, June 2018), a gathering founded by the United States, of which China isn’t even a member.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".