Then—and now: Sino–American Relations in World War II and the 2020s
Bibliographic record
Abstract
During the current period of Sino-American tensions, historians should contribute to policy-making deliberations. The rich literature on US-China relations during World War II offers a suggestive test case that demonstrates the rewards of comparative and multi-disciplinary analysis–and highlights complexities too easily obscured by the fog of current war talk. In particular, the bilateral dynamics of 1940–1945 and the 2020s reveal two countries weighing powerfully countervailing calculations of security, economic, and psychological concerns. Then and now, this produces a context within which China and the US might be seen as balancing on the edge of a volcano–though it is important to recognize that the balancing is as important as the potential for eruption. Here, a Chinese historian and a Canadian-American historian collaborate to suggest the broad relevance of historical sensitivity to contemporary policy analysis–and the particular value of scholarly cooperation across fraught national boundaries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".