Instruments of Financial Legal Policy in the Countries of the European Union
Bibliographic record
Abstract
For the purpose of a more detailed analysis of the features of administrative regulation of fiscal policy, it is necessary to consider examples of fiscal regulation of business processes in individual foreign countries, as well as features of fiscal policy in the EU. For several decades in a row, the G7 countries – Great Britain, Italy, Germany, Canada, the USA, France, and Japan - determine world economic policy. Despite the periodic global economic crises, they are among the first to overcome their consequences and maintain a leading position in the global business environment. This happens due to a balanced fiscal regulation policy. Among their common features is that part of the GDP that they accumulate through leverage of fiscal regulation has a steady tendency for growth. Thus, over the past 40 years in France, this share has grown by 10.1%, and in Canada - by 10.9%. The paper shows that the theoretical basis of modern fiscal regulation in these countries is neo-conservatism, the basis of which is the importance of direct impact on production through targeted and large-scale tax cuts. The authors show that fiscal regulation in this case provides incentives for conservation and investment. Another important element is the reduction of government spending, mainly due to the implementation of targeted government programs. However, despite several common features, each country has certain features in the administrative and legal regulation of fiscal policy. The relevance of the study is determined by the fact that it is necessary to investigate these features in more detail through the lens the historical development of the administrative and legal regulation of fiscal policy in foreign countries.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".