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RURAL TERRITORIES DEVELOPMENT THROUGH THE GOVERMENT SUPPORT OF BIOENERGY

2018· article· ru· W3049044764 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueARS ADMINISTRANDI (Искусство управления) · 2018
Typearticle
Languageru
FieldBusiness, Management and Accounting
TopicDigitalization and Economic Development in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)BioenergySustainable developmentRenewable energyBusinessRural areaEnvironmental planningEconomic growthNatural resource economicsEnvironmental resource managementEconomicsPolitical scienceGeographyEngineering

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.016
GPT teacher head0.224
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it