PROJECTS OF INTERREGIONAL COOPERATION IN COMPENSATION STRATEGIES FOR REGIONAL DEVELOPMENT
Bibliographic record
Abstract
The article investigates the practice of implementing interregional cooperation projects in compensatory strategies for the development of regions and generalizes the priority directions of interregional cooperation. The authors specify the tasks of compensatory policy of regional attractiveness and mechanisms that underlie compensatory strategies for the development of regional economic space. It is noted that compensatory strategies for the development of regional economic space increase the attractiveness of the most problematic regions through the mechanisms of integration with the most developed regions. The attention is focused on interregional projects that promote additional expansion of regional markets by creating the conditions (production, infrastructural, economic, financial, personnel, marketing ones) for the development of products and services markets. The experience of implementing the partnership at regional and interregional level of Austria, Israel is generalized. The mechanisms of implementation of regional compensation policy at the state level of Canada, France, and the Netherlands are analyzed. The approaches to organizational support of the realization of regional attractiveness policy through the creation of so-called interregional and regional institutes-organizations are considered. The necessity of active use in the processes of interregional cooperation of such an organizational form of territorial marketing as promotional agencies is noted. The application of compensatory regional policy of attractiveness, in our opinion, will allow to intensify the transboundary potential of Ukrainian regions both in relations with other regions of the country, and in relations with neighboring territories of friendly countries. As priority areas and mechanisms of interregional cooperation it is expedient to consider: interregional projects that promote additional expansion of regional markets.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".