Внешнее восприятие научно-технологического комплекса России на примере докладов ОЭСР
This article analyses the perception of the Russian science and technology complex in the OECD reports for 2014 and for 2016. According to the OECD indicators of scientific and innovative development the Russian S&T complex shows a considerable improvement. However, the OECD indicators do not take into account the scale and effectiveness of S&T complexes, which leads to a high degree of abstractness of cross-country comparison. In addition, a number of indicators do not have a transparent calculation base or do not correspond to the Federal State Statistics Service data. It is also shown that in the foreign perception of national science and technology complexes great importance is attached to the public sector of science and the role of the government funding in it. The public sector of science is the main driver of innovative development, ensuring the growth of new knowledge and know-how, which then act as a trigger for the development of new technologies. It is considered to be the norm if the national public sector of science is 90% financed from public funds, although it is expected that in the future the share of non-budgetary sources will increase.The foreign concept of the public sector of science is a great methodological problem for any comparison of the Russian science and technology complex with foreign analogues, because despite the widespread use in foreign sources, the use of this term has not developed in the Russian state statistics. The article demonstrates that the translations of public research as ‘‘state research'', as well as other derivative interpretations with the word state, are incorrect. It is concluded that the statistical data on the parameters of foreign science and technology complexes should be used with great caution in reasoning and decision-making in the Russian national science and technology policy.
The global economic and political landscape is undergoing profound changes as the world enters a period of rapid transformation development strategies or adjusting their existing ones with greater prominence given to the role of innovation in the leading and underpinning development to strengthen their strategic arrangements for innovation⁃driven development, in a bid to improve their international competitiveness and seize the initiative in global competition Science, technology and innovation (STI) are recognized as the golden key to the door to growth In this trend of the times, the BRICS countries are spearheading the development of developing countries and attracting international attention with their highly innovative and distinctive development strategies Meanwhile, the BRICS as a bloc has become an exemplar of STI cooperation of developing countries.
As the rotating chair of BRICS in 2017, China will host the 9th BRICS Summit in Xiamen in September In the lead⁃up to the summit, the Ministry of Science and Technology of China (MOST) hosted the 5th BRICS Science, Technology and Innovation Ministerial Meeting in Hangzhou in July, where BRICS STI ministers had in⁃depth discussions and reached wide consensus on topics including STI policy, cooperation in priority areas, and co-funding for multilateral research projects The BRICS Action Plan for Innovation Cooperation and the Hangzhou Declaration
To support the work relating to BRICS STI cooperation under the Chinese presidency, China Science and Technology Exchange Center (CSTEC), as entrusted by MOST, established a High Level Expert Group of leading professionals The High⁃level Expert Group complied theBRICS Innovative Competitiveness Report 2017, in collaboration with the science and technology sections of Chinese embassies in other BRICS countries and STI think tanks in other BRICS countries Based on the latest available data, the Report of the BRICS STI cooperation, and presents country and thematic studies on the STI development of BRICS countries.
The Report consists of four parts, with a total of 12 sub⁃reports Part I two general sub⁃reports: an analysis report which evaluates and forecasts the national innovation competitiveness of BRICS countries and their STI cooperation and strategic priorities; and a research report on the priority areas BRICS STI cooperation for win⁃win results This part evaluates the comprehensive national innovative competitiveness of the BRICS countries since 2001 and forecast their innovative competitiveness in the next five years It also assesses the current status and progress of China's STI cooperation with other BRICS countries, and identifies priority areas of BRICS STI cooperation, support for BRICS countries to strengthen their national innovation competitiveness Part Ⅱ presents six country reports, which evaluate, analyze and forecast of the national innovation competitiveness of the BRICS countries and studies of their STI cooperation within the BRICS framework Part Ⅲ presents four thematic reports, which focus on the four thematic areas to STI, including digital economy, inclusive finance, energy, and agriculture, elaborate the STI development and potential of the individual BRICS countries in those areas, and provide valuable inputs for the BRICS countries' national innovation competitiveness Part IV contains appendixes, including an introduction to the related indicator system BRICS STI cooperation.
The ISSI 2017 Conferences provide an International forum for scientists, research managers and administrators, as well as other professionals related to information and communication science to share research and debate the new advancements of Informetrics and Scientometrics theories and applications. The theme of the 16th International Society of Scientometrics and Informetrics Conference is the theory, method as well as principle of five metrices science concepts including Bibliometrics, Informetrics, Scientometrics, Webometrics and Knowledgometrics.
Tech Mining, a special form of “Big Data” analytics, aims to generate Competitive Technical Intelligence (CTI) using bibliometric and text-mining software (e.g., VantagePoint, TDA) as well as other analytical & visualization applications for analyses of Science, Technology & Innovation (ST&I) information resources. The goal of the conference is to ENGAGE cross-disciplinary networks of analysts, software specialists, researchers, policymakers, and managers toADVANCE the use of textual information in multiple science, technology, and business development fields. The conference program will address key CHALLENGES in:
DataSourcing, preparing, and interpreting data sources including patents, publications, webscraping, and other novel data sources
Text-mining tools and methodsBest practices in software-based topic modeling, clumping, association rules, term manipulation, text manipulation, etc. Visualization
Applied researchFuture-Oriented Technology Analysis (FTA) Intelligence gathering to support decision-making in the private sector (e.g., Management of Technology)
This conference is intended for researchers and students across multiple fields, especially Scientometrics, Public Policy, Management of Technology and Information Science.
The paper examines a changing audience present at the major academic conventions in the Russian Empire in the second half of the 19th century – the congresses of Russian naturalists and physicians. Like similar national academic congresses in other European countries of the same age, the congresses of Russian naturalists and physicians served as important sites of academic socialisation, exchange and public dissemination of knowledge. The paper provides a detailed analysis of the dynamics of gender, regional and professional background, and institutional affiliation of registered participants. In this way it is able to demonstrate social and geographic expansion of public science in the late imperial Russia, and the role of the imperial universities, as the principal organisers of the conventions, in the process. In particular the paper focuses on the geography of science in the Russian empire, by tracing and analysing the involvement of different regions of the country, with their varied ethno-cultural background and traditions of scholarship, in the events.
The paper analyzes the contents and objectives of ‘public social science’, the relationship between scholarly and popular knowledge, conventions governing the representation of scientific knowledge outside the academic context, and the transfer of scholarly knowledge from academic to media environment. Public science is treated as a specific type of judgment and practice, thus the analysis of ‘public science’ cover cognitive aspects as well as social ones.
Research evaluation recently became a widely disseminated exercise aimed in the end of the day at improving the cost efficiency of public funding of national R&D sectors. In November 2013, the Government of the Russian Federation initiated a national evaluation exercise of public research institutions (PRIs) to provide information basis for development of S&T policies aimed at increasing effectiveness and strengthening the role of R&D performing institutions in economic and social development. The aim of this paper is that of providing an approach for multidimensional assessment of R&D performance based on quantitative data derived from the national evaluation exercise, specifically looking at its applicability and limitations for further analysis and preliminary differentiation of PRIs as well as for use in policymaking.
This paper considers how to analyze the performance indicators of universities. The data of this study comes from Russian National Research Universities' statements that are available in open access on official web sites. The main purpose of this study is to define via factor analysis the most important indicators for ranking and performance auditing behind the constellations of performance measures. For this purposes Statistical Package for the Social Sciences (SPSS) was used. Then we conducted factor analysis by using the extraction method with principal component analysis to choose the main factors for rating and performance auditing. We suggest using the factor analysis result for evaluation of an auditee.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.