Quintessence and imperatives of strengthening the financial security of the country in the conditions of the digital economy
Bibliographic record
Abstract
The paper addresses the issues of strengthening Ukraine's financial security in the context of the formation of the digital economy. An overview of the main scientific approaches to interpreting the concept of 'National Financial Security' was conducted, and the author proposed a definition. The paper primarily focuses on the quintessence of strengthening the financial security of the country as a set of fundamental principles and approaches that should be implemented to ensure the stability and reliability of the domestic financial system, the creation of favorable conditions for economic development, and the protection of the country's financial interests. The imperatives of strengthening the financial security of the country in the context of digitalization were systematized, aiming to minimize threats such as cyber-attacks, financial fraud, and external risks. To mitigate these risks, the authors propose implementing measures such as the development of effective information protection technologies in the financial sphere and the introduction of a financial monitoring system to enhance the transparency of financial transactions. It has been demonstrated that the financial security of the country is a key element of its economic security, as it ensures the reliability and stability of the financial system and safeguards the financial interests of the country and its citizens. The paper also presents a set of proposals to enhance domestic financial security by enhancing the resilience of the financial system to new risks and threats associated with the digitalization of the domestic economy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".