To be presented at Plenary Session A of the Economic History Association Annual Meeting,
Bibliographic record
Abstract
extensive comments and suggestions. I suspect that like many visitors to this library, I find much to admire in the Johnson administration: its commitment to civil rights, the war on poverty, the expansion of the social safety net. The theme of my talk, however, will be that its conduct of macroeconomic policy was not one of them. Indeed, I will argue that far from being the high point of economic policymaking in the postwar era, the 1960s represented the beginning of a long dark period for macroeconomic policy. Both monetary and fiscal policy actions were seriously misguided in the 1960s, and led to undesirable economic outcomes. In my view, macroeconomic policies of the 1960s were not the result of a change in the goals of policy or the effectiveness of economists. Policymakers at least since World War II had been committed to short-run stabilization, and economic models, if not actual economists, had been influential from the 1920s on. Rather, the revolution of the 1960s was a revolution in economic ideas. The model that policymakers used to understand the economy changed in dramatic ways. This led them to make radically different policy recommendations. The resulting policy outcomes had two effects on the economy. One was to generate inflation and short-run instability. The second was to end the historical norm of long-run budget
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.440 | 0.189 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".