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Record W2066802070 · doi:10.2753/ijp0891-1916350103

The Bank of Canada and the Modern View of Central Banking

2006· article· en· W2066802070 on OpenAlexaffabout
Marc Lavoie, Mario Seccareccia

Bibliographic record

VenueInternational Journal of Political Economy · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMonetary policyTransparency (behavior)Inflation targetingEconomicsCentral bankInflation (cosmology)Interest rateBank rateMonetary reformRelevance (law)FaithOfficial cash rateMonetary economicsPolitical scienceLaw

Abstract

fetched live from OpenAlex

Many observers of the art of central banking would probably argue that the most significant change in the behavior of central banks over the past fifteen years has been the adoption of inflation targeting. Beginning in 1991, Canada was one of the first countries, after New Zealand, to adopt explicit inflation rate targets. While this may be of some interest to policy analysts, we wish to argue that the Bank of Canada has introduced many more innovations in the conduct of monetary policy over the past fifteen years and that these innovations have just as much importance, and possibly more relevance, than explicit inflation targeting. In particular, the new procedures followed by the Bank of Canada take away the veil that has traditionally shrouded monetary theory and policy. With the new procedures, tied to additional transparency a key word now in central banking lingo it is possible to have a better understanding of the actual process of monetary creation/ destruction in contemporary monetary economies like that of Canada. In addition to the new procedures, monetary policy as such has gradually changed, and we wish to record these changes, emphasizing both what has changed and what have remained articles of faith at the Bank of Canada. In other words, while new wine has been added, some of it still remains sitting in old bottles.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.212
Teacher spread0.192 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations16
Published2006
Admission routes2
Has abstractyes

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