The Bank of Canada and the Modern View of Central Banking
Bibliographic record
Abstract
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.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".