Global Experience in Improving Multi-Level Coordination of the Management of Public Investments to Ensure Their Efficiency
Bibliographic record
Abstract
The issue of improving the multi-level coordination of the management of public investments to ensure their efficiency is especially relevant for Ukraine, as its effective mechanisms maximize the return on investment for regional development. Ukraine will need significant public investment to recover from the destruction caused during the Russian-Ukrainian war, and these investments are (and will be) the driving force behind the recovery of the domestic economy. In conditions when investment opportunities and investment funds are limited, the question arises of their rational use and direction to achieve prioritized tasks. Taking into account the fact that the implementation of public investments is a long process with a wide range of persons involved, the issue of the efficiency of multi-level coordination of public investment management becomes especially acute. The experience of different countries, and especially the members of the Organization for Economic Cooperation and Development (OECD) in the field of establishing effective multi-level coordination of authorities at different levels, needs to be highlighted and taken into account in domestic practice. The theoretical and methodological basis of the study is a number of OECD materials, as well as scientific works of foreign and Ukrainian scholars. The article summarizes the experience of OECD member countries (both positive and negative) in the field of multilevel management. Emphasis is placed on the first pillar of the OECD Recommendation and the three principles it incorporates, in particular, the use of an integrated strategy adapted to local characteristics, the introduction of effective coordination instruments and horizontal coordination. Among the best implementation practices are the examples of the European Union, Japan, New Zealand, Australia, Austria, Canada, France, the United Kingdom, Turkey, Luxembourg and Switzerland. A number of steps towards improving the multi-level coordination of the management of public investments in Ukraine to ensure their efficiency have been proposed.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".