Conundrum WEAK, HESITANT AND protracted recovery
Bibliographic record
Abstract
domestic product (GDP) did not regain its prerecession level until third quarter 1992, a year and a half after the recession’s trough. On the whole, however, incoming data were less negative during 1992 than in 1991 and the Federal Open Market Committee (FOMC) generally displayed more confidence that the economy was growing in 1992. ’ As concern about a further economic downturn receded, troubling aspects of the monetary aggregates ’ behavior became more prominent in FOMC deliberations. Since mid-1991, an unusual combination of very slow M2 growth and rapid growth of reserves and Ml has drawn considerable attention.’ The juxtaposition of fast Ml and reserve growth and slow M2 growth was an important conundrum for policymakers in 1992: Was slow M2 growth constricting economic recovery (though slowing inflation at the same time), or was rapid Ml growth a signal of future inflationary pressure (though perhaps supporting rapid recovery)? These worst-case interpretations highlight the range of uncertainty raised by anomalous behavior of an important set of indicators. The article begins with an outline of major economic developments in 1992 followed by an examination of the aforementioned monetary conundrum. These first two sections provide a backdrop for more detailed discussion in the third section of the eight FOMC meetings and policy actions taken between meetings. Because discussion of monetary policy often uses potentially ambiguous terms such as easing, I have included a shaded insert, “Translating the FOMC Policy Directives, ” which explains how some of these terms are used in FOMC directives and in discussions of monetary policy.
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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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".