Reserve funds of federal subjects: A comparative analysis of nature and practice in Russia and the U.S.
Why this work is in the frame
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Bibliographic record
Abstract
Subject. The article reviews four main types of budget reserves of the constituent entities of the Russian Federation, the USA and Canada, i.e. reserve funds of constituent entities of the Russian Federation, reserve funds of supreme executive authorities of the constituent entities of the Russian Federation, Rainy Day Funds and Contingency Reserve Funds of the US and Canadian provinces. Objectives. In Russia, the greatest attention is paid to the budget reserve of the Federal budget, while the budget reserves at the level of subjects of the Federation are underexplored and require close scientific understanding, as they bear the greatest social burden. Methods. The fundamental research method is a comparative analysis of the theoretical representation of scientific articles, statutory documents of the subjects of the Federation and annual reports on reserve funds of the USA and Canada. Results. The results of the analysis of reserve funds of the constituent entities of the Russian Federation, reserve funds of supreme executive authorities of the constituent entities of the Russian Federation, Rainy Day Funds and Contingency Reserve Funds of the USA and Canadian provinces are presented in the form of a matrix-characteristic of these four types of funds by eleven criteria. Conclusions. The performed theoretical and practical analysis of the four types of budget reserves is generalized in the form of directions for improving the Methodological Recommendations for subjects of the Russian Federation regarding the formation and use of regional funds of financial reserves of the Ministry of Finance of the Russian Federation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it