Bibliographic record
Abstract
This book examines why the economic decline in Canada in the early 1930s was so severe and the recovery to 1937 so incomplete, both absolutely and relative to our main trading partners.There are several reasons why its re-issue at this time is appropriate.First, there is an intrinsic and growing interest in the Great Depression of the 1930s.In the two-hundred-year recorded history of business fluctuations, no other depression, with the possible exception of one in the late nineteenth century, was as severe or had so many lasting consequences.There has been a surge of publications on the thirties, both popular and academic, in recent decades.In part this interest reflects increasing recognition of the links between business cycles and many developments in macroeconomics and economic growth.There are competing schools of thought in this literature that reflect very different views on the reasons for fluctuations in output and employment.This edition includes an addition to the 1959 bibliography that lists some of the more recent literature for Canada and internationally.From my perspective, particularly significant additions include Bernanke (2000), Betts et.al. (1996), Friedman and Schwartz (1963), Kindleberger (1986), and Temin (1988).Gordon (1990) is an excellent example of the many contributions by the National Bureau of Economic Research.There is also a short summary of work on business cycles generally in Romer (2008).Second, despite all this publication, no other broad study of the Canadian experience, with a focus also on developments in key sectors, has appeared in all these years.Fifty years after its original publication, professors of history and economic history as well as specialists in business cycles, among others, continue to cite it in their research and refer their students to it.Since 1987 the federal Public Lending Right Commission has surveyed annually a number of public and, until recently, university libraries as a basis for compensating Canadian writers for the use of their books in Canada's libraries.This book has always been in all of the libraries surveyed.Third, the underlying theoretical, historical, and quantitative approach of this study seems to have some lasting merit as shown in the conclusions of a very careful theoretical and empirical test of various explanations of the onset, depth and duration of output collapse in Canada and the United States in the 1930s (Betts et.al., 1996).The authors report that "results are consistent with hypotheses such as those of Fisher (1933), Bernstein (1987) and Safarían (1959), that emphasize secular factors in explaining the Depression" (p.35).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.375 | 0.202 |
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".