Credibility with Flexibility: The Evolution of Inflation-Targeting Regimes, 1990-2006
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Beginning with a review of the adoption of inflation targeting in a broad group of countries, Paulin focuses on changes in the design of inflation-targeting frameworks in light of fifteen years of accumulated experience. Included in the discussion are the use of numerical targets and ranges, the policy horizon, supporting institutional policy structures, and communication, including the publication of forecasts. A recurring theme is how much flexibility an inflation-targeting regime allows. The article concludes that the changes made to the frameworks have been relatively modest since their adoption, but in concert with the improved credibility that has resulted from central banks meeting their inflation-control targets, they have allowed an increasingly nuanced response to economic shocks.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it