The Main Directions of the Bank of Russia’s Activity in the System of Integrated Financial Regulation
Bibliographic record
Abstract
Actuality : The transition to integrated financial regulation brought the issue on the central banks’ role in the new configuration of financial supervision; on the necessity of resistance to financial crises and systemic risks; on overcoming of sectoral fragmentation in the area of regulation and supervisory activities’ standardization based on best supervisory practices. Novelty : The regulatory and supervisory function has evolved into a critical factor in management of the financial system stability. Rethinking of the essence of the financial integral regulation has allowed distinguishing three separate directions: ensuring of financial stability, macroprudential oversight and regulation of moral hazard risk in the banking sector, financial institutions’ business behavior and limitation of the intention to establish the regulatory arbitrage. Practical Value : In countries, that have adopted the integral regulation of the financial market, in relation to all its sectors, the authors propose to develop and apply standards of the moral hazard risk regulation in the banking sphere and the business behavior of financial institutions; universal standards and technologies of regulation and supervision in order to limit the establishment of regulatory arbitrage; leveling of systemic risks of financially-credit sphere.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".