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Record W2279128177

Current Federal Reserve Policy Under the Lens of Economic History

2015· preprint· en· W2279128177 on OpenAlexaboutno aff
Owen F. Humpage

Bibliographic record

VenueRePEc: Research Papers in Economics · 2015
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Theory and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCentennialMonetary policyContext (archaeology)EconomicsMonetary reformInflation targetingMacroeconomicsHistory
DOInot available

Abstract

fetched live from OpenAlex

In December 2012, as a kick-off to the Federal Reserve System's centennial, the Federal Reserve Bank of Cleveland asked leading monetary historians and macroeconomic economists to address current and recurring economic concerns that confront central banks from a historical perspective. The resulting papers, published in this volume, cover a wide range of issues, including the meaning of central-bank independence, the role of communications and rules in fostering credibility, the evolution of the lender-of-last-resort function, the mechanism through which banks transmit economic shocks, and prospects for a European monetary union. A retrospective on the Federal Reserve, this book contains essays by some of the world's most prominent financial historians and provides a thorough overview of the evolution of the monetary standard over the past two centuries. Offering historical context as a complement to economic theory and empiricism, these papers investigate how financial infrastructure shapes economic outcomes through comparisons of Canada and the United States. Suggested citation: Humpage, Owen F., ed., 2015. Current Federal Reserve Policy Under the Lens of Economic History: Essays to Commemorate the Federal Reserve System's Centennial. New York: Cambridge University Press.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0030.005
Scholarly communication0.0100.006
Open science0.0010.001
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0110.003

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.

Opus teacher head0.126
GPT teacher head0.345
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicEconomic Theory and PolicyFrench-language works237,207