MétaCan
Menu
Back to cohort
Record W2786983957 · doi:10.15544/rd.2017.054

OPTIMIZATION OF THE MANAGEMENT MECHANISM FOR THE INNOVATIVE DEVELOPMENT OF THE REGION’S AGRICULTURAL SECTOR

2018· article· en· W2786983957 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

VenueProccedings of International Scientific Conference "RURAL DEVELOPMENT 2017" · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicDigitalization and Economic Development in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsAgrarian societyLaggingAgricultureContext (archaeology)BusinessProductivityEuropean unionEconomic systemAgrarian systemTechnological changeAgricultural productivityPopulationEconomicsEconomic policyNatural resource economicsIndustrial organizationEconomic growth

Abstract

fetched live from OpenAlex

The current trends in the development of innovative activities in Russia are far from fully meeting the expectations associated with improving the competitiveness of products and the quality of life of the population, with the provision of dynamic sustainable growth, and the formation of the innovative economy. The mixed nature of the Russian economy, the fundamentally different technological level and institutional conditions for the development of various sectors exclude the possibility of defining a single model of innovative development that is universal for all sectors. In the current conditions, the technical and technological level of the agrarian sector of the country's economy is the most catastrophically lagging behind the world's leading producers of agricultural products. Domestic agrarian production is 5 times more energy intensive and 4 times more metal consuming, and labor productivity is 8-10 times lower than in the USA, in the leading countries of the European Union and Canada. Not having eliminated this techno-technological backlog, without implementing the advanced development of certain specific areas of scientific research and technological developments in the field of agriculture, Russia's agrarian sector will finally lose its competitiveness and will not be able to ensure the country's food security. Thus, the need for a scientific justification of the theory, methodology and practice of the innovative development management of the agrarian sector of the regional economy in the context of large-scale economic and institutional transformations determines the urgency of the issue. Currently, most of the works of domestic researchers put emphasis on the problems of knowledge transfer, at the same time, the methodology for creating and commercializing competitive scientific knowledge through the formation of innovative agricultural clusters is beyond the scope of scientific research, and its management and economic mechanism has not been developed yet. Thus, the aim of this research is to develop proposals for optimization of the management mechanism for the innovative development of the region's agricultural sector (by the example of the Samara Region of the Russian Federation). The research used a set of methods of scientific knowledge used at both theoretical and empirical levels (conceptual modeling, synthesis and analysis, tabular and graphical interpretation of theoretical information and empirical data).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.220
Teacher spread0.187 · 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