Building favorable investment climate for economic development
Bibliographic record
Abstract
The research is devoted to the adaptation of theoretical and applied organizational grounds of favorable investment climate based on the establishment of an efficient mechanism of investment capacity increase in Ukraine. The main aim of the paper is to substantiate the mechanism of forming a favorable investment climate as the basis of investment capacity increase in Ukraine. The paper verifies the authors' hypothesis on the adequacy of the substantiation of the mechanism of favorable investment climate forming as the basis of investment capacity increase leading to the substantial improvement of Ukrainian positions in international rankings. The dependence of Ukraine's investment climate on the formed mechanism of its development is confirmed, and the necessity of its improvement is emphasized. The paper proves that forming of the favorable investment climate as the main precondition of boosted development, reproduction, and efficient use of investment climate at all levels is one of the most important strategic tasks that Ukraine faces. Economic, institutional-legal, and organizational-administrative mechanisms and implementation tools directed at improvement of the investment climate in Ukraine and the creation of conditions for investment capacity growth and its efficient transformation into an investment product are systematized.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".