Bibliographic record
Abstract
What precisely were the causes and consequences of the trade wars in the 1930s?Were there perhaps deeper forces at work in reorienting global trade prior to the outbreak of World War II?And what lessons may this particular historical episode provide for the present day?To answer these questions, we distinguish between long-run secular trends in the period from 1920 to 1939 related to the formation of trade blocs (in particular, the British Commonwealth) and short-run disruptions associated with the trade wars of the 1930s (in particular, large and widespread declines in bilateral trade, the narrowing of trade imbalances, and sharp drops in average traded distances).We argue that the trade wars mainly served to intensify pre-existing efforts towards the formation of trade blocs which dated from at least 1920.More speculatively, we argue that the trade wars of the present day may serve a similar purpose as those in the 1930s, that is, the intensification of China-and UScentric trade blocs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".