Impact of the COVID-19 Pandemic on the Economy and the Banking Sector of Bulgaria
Bibliographic record
Abstract
The goal of the research is to analyze the consequences caused by the coronavirus pandemic COVID-19 on the economy and the banking sector of Bulgaria. In structural terms, the research consists of an introduction, presentation, conclusion and cited sources. The significance of the researched topic is brought out in the introduction. The presentation analyzes the consequences caused by the COVID-19 pandemic on the economy of Bulgaria. It also analyzes the effect of the impact of the unfavorable macroeconomic environment caused by the coronavirus pandemic on the banking sector in our country. As we know, the stability of the banking system in a country is of extreme importance, because due to its structure-determining position, the banking sector is a key contributor to the dynamics of the economic development of the EU, including Bulgaria. The presentation of the article also describes the economic measures that have been taken with a view to reducing the adverse consequences of the new coronavirus. In the conclusion, the main implications of the research are presented, and the possibilities of using different policies are considered, with a view to mitigating the negative impact on the economic measures in the last quarter of 2022.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".