Bibliographic record
Abstract
It is a common argument that one of the factors contributing to the decline of institutionalism as a movement within American economics was the arrival of Keynesian ideas and policies. That thesis is not disputed here. Keynesian economics, and the subsequent macroeconomic debates between Keynesians and monetarists, did displace the various institutionalist research programs on cycles and depressions and played a significant part in the marginalization of institutional economics in the post–World War II period. What will be disputed, however, is the common view that institutionalists were somehow left helpless by the phenomenon of the Great Depression, so that Keynesian economics was “welcomed with open arms by a younger generation of American economists desperate to understand the Great Depression, an event which inherited wisdom was utterly unable to explain, and for which it was equally unable to prescribe a cure” (Laidler 1999, p. 211). As work by William Barber (1988) and David Laidler (1999) has made clear, there is something very wrong with this story. In the 1920s, there was, as Laidler puts it, “a vigorous, diverse, and distinctly American literature dealing with monetary economics and the business cycle” – a literature that had a central concern with the operation of the monetary system, gave great attention to the accelerator relationship, and contained “widespread faith in the stabilizing powers of counter-cyclical public-works expenditures” (Laidler 1999, pp. 211–212).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.014 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".