RURAL TERRITORIES DEVELOPMENT THROUGH THE GOVERMENT SUPPORT OF BIOENERGY
Bibliographic record
Abstract
Introduction. Sustainable economic development of rural territories, especially remote areas development, is one of the priorities in government management in many countries in the world. The basis of sustainable development is the renewable energy. The paper looks at the relevant issues related to the rural areas’ development under government policy in the field of sustainable development and bioenergy. The study investigates the issue through the case study of Russia. The paper looks at the relevant issues related to the rural areas’ development under the alternative energy and bioenergy. The study presents an overview of scientific research in government policy instruments for bioenergy under in the frame of sustainable development and economic aspects. The most relevant issue for the rural territories - the implementation of small energy generation based on biofuel – should be dealt with comprehensively and viewed from economic to socio-environmental prospective. The role of government is to provide government support for such projects at the state level. Aims. The main aim of this article is to investigate the theoretical base of the government policy in the field of government support of bioenergy. Also the article looks at how the problem of energy supply for remote rural areas in Russia can be settled successfully by developing the network of small bioenergy plants, which are quickly growing in rural forested areas. Bioenergy development in the rural territories also will allow starting new high-tech production in remote and northern regions, providing them with an autonomous energy sources. The methods of theoretical research (systems analysis, abstraction and concretization, idealization, etc.), as well as the methods of empirical research (method of expert assessment, comparison, analogy, and generalization) are applied in the study. Results. Theoretical and practical solution of the research task will allow to complete and develop the domestic and world scientific knowledge in the field of alternative ecologically safe energy, to promote the development of mono-economy regions and to stimulate economic development and growth of the bioenergy capacity in the largest forested regions of Russia (with the possible establishment of export-oriented industries). The results that will be obtained during the project implementation are of high scientific and practical value for popularization of the green economy concept based on renewable energy, for its development in Russia and in countries with similar economic and climatic conditions, such as Canada, Finland, Norway, Switzerland and others. Conclusion. The research shows how the usage of local fuel solves the problem of providing electricity and heating to the remote settlements regardless of their remoteness and availability of transportation routes. Besides, the implementation of a small boiler operating on wood chips will help to create employment of local population, which has a very positive social
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".