Sectoral Orientedness of Public-Private Partnership in Ukraine: The Problems and Prospects
Bibliographic record
Abstract
The article is aimed at identifying the priority directions of public-private partnership in Ukraine on the basis of research of world experience and peculiarities of implementation of public-private partnership projects in Ukraine. The article provides statistics on the distribution of public-private partnership agreements by areas of implementation and volume of investment in both the developed European countries and the developing countries, as well as statistics on the distribution of investments under public-private partnership agreements by areas of implementation in Ukraine. It is concluded that it is characteristic of public-private partnership projects that the number of concluded agreements does not necessarily have to coincide with the amount of investment. The analysis of the world experience in the use of public-private partnership mechanisms in the countries that have reached the highest stage of development as to the considered matter (these include the UK, France, Spain, the USA and Canada), helped to identify the most successful directions of its implementation. Thus, one of the most important directions of public-private partnership, which is defined by the mentioned countries as priorities, are the construction of highways and social infrastructure objects. The analysis of the current legislation of Ukraine proved absence of a government administration of the sectoral orientedness of public-private partnership, which confirms the inability of the State to solve the problems of socioeconomic development with the use of this instrumentarium. The analysis of each of the priority directions of public-private partnership, the importance of which has already been proved on the example of developed countries of the world, demonstrates the presence of obstacles, primarily of a legislative nature, that entail other problems
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".