Comparative characteristics of the tax system of Russia and foreign countries
Bibliographic record
Abstract
В статье исследуется опыт налогового администрирования в странах с различными экономическими системами (Канада, Швейцария, Южная Корея и Российская Федерация). Сравнивается налоговая система, состоящая из схожих элементов и принципов налогообложения в дневнике, и определяются наиболее общие тенденции и различия. Этот анализ может быть использован в дальнейшем для определения направления совместного расчета налоговой системы Российской Федерации. Россия -федеративное государство с большой территорией, поэтому налоговая система состоит из использования трех уровней: федерального, регионального и местного. The article examines the experience of tax administration in countries with different economic systems (Canada, Switzerland, South Korea and the Russian Federation). The tax system consisting of similar elements and principles of taxation in the diary is compared, and the most general trends and differences are determined. This analysis can be used in the future to determine the direction of the joint calculation of the tax system of the Russian Federation. ... Russia is a federal state with a large territory, so the tax system consists of using three levels: federal, regional and local.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".