Clusters as a Mechanism for Solving Socio-Economic Problems of Post-Conflict Ukraine
Bibliographic record
Abstract
The purpose of the article was to analyze the cluster strategy in various countries of the world and to highlight the legal instruments that can be used in the process of creation and operation of clusters in Ukraine, taking into account the existing post-conflict socio-economic problems. The research methods used were: analysis, synthesis, consistency, comparison, generalization and prognosis, etc. The main models of cluster development in the world practice are analyzed. The characteristics of the state strategy in the field of regional clustering in the USA, Canada, Italy, Germany, Austria, France, Finland, Japan and China are studied. The authors focused on the legal instruments used in the process of creation and operation of clusters in different countries of the world, which it is advisable to borrow and implement in the Ukrainian legislation. Finally, the following problems of cluster creation in Ukraine have been identified: the lack of a legislative framework; a state strategy to support clusters, as well as incentives for investors. It is concluded that clusters in a difficult socio-economic situation in Ukraine should help to attract investments and develop the economy of regions affected by hostilities.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.003 |
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 teacher head, 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".