Understanding the Great Depression in the United States versus Canada
Bibliographic record
Abstract
It is now recognized that the Great Depression should be viewed as a global phenomenon with its roots in the gold standard so arduously restored in Great Britain in 1925. Temin (1989) and Eichengreen (1992) provide arguably the best recent accounts of the Great Depression. Not surprisingly, it has generated a vast literature, and continues to this day to fascinate economists and social scientists more generally. Unlike Friedman and Schwartz (1963, 1982), whose masterful works documented the role of monetary policy in explaining both the depth of the US Depression and its propagation outside the United States, Temin (1989) stresses the influence of a large ‘economic’ shock which was then magnified by an almost slavish adherence to the gold standard. Eichengreen (1992) would not disagree but would emphasize the breakdown in international cooperation among government and central bank officials. Others, such as Kindleberger (1986), might argue instead that the collapse of the post First World War monetary order produced financial chaos which, like the now much discussed ‘Asian flu’ of the late 1990s, caught on across much of the world. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".