Actual Issues of Planning of Well-Balanced Development of Innovative & Investment Activities
Bibliographic record
Abstract
The modern factors of development of the country’s economy require interdetermination and interdependence of the study of issues of planning of balance of innovative and investment activities, which has a very important meaning for economic systems and determines the scientific interest in this topic. The purpose of this article is the study of theoretical and methodological aspects of planning of well-balanced development of innovative and investment activities and development of practical recommendations, aimed at the increase of efficiency of economic systems. In order to achieve this purpose, the authors used economic and statistical methods of research and methods of economic & comparative analysis. Methodological and practical development was based on the following approaches: process, program-oriented, complex and structural & logical, and methods of comparison and modeling. The authors distinguish the determinants of planning of well-balanced development of innovative and investment activities of economic systems, which, unlike the existing approaches, allowed forming the system of targeted landmarks and limitations which guaranteed the optimal conditions for effective functioning and development of economy of macro-, meso- and micro-levels; the authors offer a program-oriented approach to the well-balanced development of innovative and investment activities of economic systems, the novelty of which consists in the fact that it is used as a modern technology of planning which facilitates solving tasks of limited and creative type, which, in its turn, creates possibilities for creation and support for balance between the volume of investments and development of investment activity. Besides, these recommendations as to formation of balance of investments for the purpose of increase of efficiency of innovative activity contain methods and means for solving problems of well-balanced development and allow implementing analytical, synthetic, and practical interests of all economic subjects in the process of systemic adaptation to the changes of external conditions. The recommendations, formulated in the research, may be used in the work of federal and regional authorities; in the process of improvement of innovative and investment activities of economic subjects of micro-level.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".