Bibliographic record
Abstract
INTRODUCTION Monetary policy is the most flexible economic policy tool of government, and possibly its most potent one as well. Nevertheless, as World War II ended, the experience of the 1920s and 1930s revealed a deep mistrust of monetary policy, and perhaps to a greater extent, of central bankers. Governments yearned for some form of stability, after decades of large fluctuations in the price level and in other major macroeconomic aggregates. Policy coordination failed and there was a strong undercurrent of desire for countries to find their own destiny, as it were, in economic terms. While fiscal policy would dominate the scene as the principal tool of policy, three concurrent forces lead to a shift back to the view that the central bank must occupy a central place in the implementation of economic policy. First, exchange rate stability is an illusion and must of necessity come in conflict with domestic objectives that diverge across countries. Second, the growth of trade and of capital mobility leads to international imbalances that are exacerbated by artificial attempts to maintain exchange rate regimes ill suited to such an environment. Third, fiscal policy is slow to act and is increasingly an inept instrument for attaining particular economic objectives. This is especially true in a world of high-frequency data. The impression is sometimes given that what has changed, in the 1990s especially, is the greater recognition of the importance of price stability. Nothing could be further from the truth. Economists and policy makers long ago felt that monetary policy was about delivering low and stable inflation rates.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".