Public Management of SMART Specialization of Sustainable Development of the Region in the System of Ensuring Innovation Security
Bibliographic record
Abstract
The main purpose of the study is to model the prospects for sustainable development of the region due to smart specialization in the system of ensuring innovative security.The methodology includes a diverse number of techniques that contributed to the achievement of the desired result.In particular, general theoretical methods of analysis, the method of comparing the key characteristics of the studied regions, the method of correlation and regression analysis were used.As a result of the study, the density of the influence of various factors (characteristics of the functioning of the educational and scientific components, indicators of the innovative activity of the business environment of the region) on the dynamics of changes over time in the performance indicators of a particular region was studied.According to the authors, this study can become a guide for regional authorities in developing an implementation plan and relevant roadmaps for the implementation of practical strategies for sustainable development of the region.The study has limitations and they relate to the inability to cover an indicative number of regions.Each region is individual and requires a separate approach.The practical value of the calculations carried out lies in the disclosure of those components and characteristics of the educational, scientific, and industrial activities of the region, the direction of efforts and resources for the activation of which will allow the region to get a guaranteed positive result through the growth of the gross regional product and the available income of the region due to an indicative increase in innovation security.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".