International Practice of Provision of Guarantees for Implementation of Investment Projects
Bibliographic record
Abstract
Subject. State support for the country's economy, especially the support for its high-tech sector, is of great importance during a crisis. State guarantees are also one of the key instruments of state support for investment activity in Russia. Significant successful practice of using this instrument has been accumulated in Canada, Spain, the Netherlands, the USA, Turkey, Sweden, and Chile. The world experience indicates that the implementation of projects as public-private partnerships (PPP) leads to the completion of the project on time and in accordance with its budget more often than when implementing the project based on public funding only. Goals. The study is aimed at analysis of the mechanism of state guarantees in foreign countries, the conditions and consequences of their provision. Methods. The research methods include a review of the scientific literature in this area, synthesis and analysis of the information obtained, as well as comparison, formalization, and specification. Results. The practical implementation of state guarantees in foreign countries has been analyzed in the study. The specifics and the possibility of applying the best practices in Russia have been revealed. Conclusion. The fiscal legislation of Russia includes a developed system for regulating the provision of guarantees and establishes the requirements for the application and accounting of state guarantees that are very conservative in accordance with international standards. The application of the world practice in the creation of guarantee agencies in order to support small and medium-sized enterprises can have a positive effect on business activities. The need to diversify directions for the provision of state guarantees with a view to balanced economic development must also be noted.
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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 | 0.066 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".