Bibliographic record
Abstract
"Canada plans to adopt a retail payment system to allow Canadians to pay in real time (or near real time) 24 hours a day, 7 days a week. However, the traditional model for setting the overnight interest rate does not operate 24/7. In this paper, we adapt the traditional model to include paying after hours when participants do not have access to central bank lending and deposit facilities. If they do not have access to the central bank, they cannot send a payment after hours unless they have the funds available. This leads to what is called a “precautionary demand” for more funds to reduce the chance that payments cannot take place. This precautionary demand can cause the overnight interest rate to go up. This upward pressure depends on two aspects of the framework for implementing monetary policy: If uncertainty about the flow of after-hours payment is fairly low, allowing payments to be made 24/7 will cause only a small amount of pressure for the overnight interest rate to go up. If the framework naturally has a large level of settlement balances (deposits at the central bank), the upward pressure will also be minimal. Here are two contrasting examples: Floor systems (where the overnight rate trades near the central bank deposit rate) already have a large level of settlement balances. Corridor systems (where the market rate is set within a certain range, called a corridor) that do not have a required level of settlement balances (that is, there is no reserve requirement) are more likely to experience upward pressure on overnight interest rates with 24/7 settlement compared with rates without 24/7 settlement."
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 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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".