Social Stratification in Science

This study analyses the research performance of National Institutes of Technology (NITs) of India during 2001-2010 on several parameters including NITs overall contribution, its growth pattern, citation impact, the share of international collaboration, identification of significant participating countries in NITs international collaboration, contribution and impact by different subject areas, identification of weak and strong subject areas, productivity and impact of prolific authors, pattern of communication of NITs output in most productive journals and characteristics of high cited papers of NITs. The Scopus Citation Database has been used to retrieve the data for 10 years (2001-10).

Research Performance of National Institutes of Technology (NITS) of India During 2001-2010: A Bibliometric Analysis

The Saha Institute of Nuclear Physics (SINP) is one of the prestigious autonomous research institutes under the Department of Atomic Energy, Govt. of India. The present study is carried out to identify the research performance of the scientists of SINP during 2005-2016. For this purpose, a total number of 3694 articles as reflected in Web of Science (WoS) database have been retrieved and evaluated on the basis of year, authorship, publication pattern, source journal, impact factor, collaborating institution, country, research area and citation. Out of total publications, the international collaborative research output constitute 41.20% share and western developed nations i.e. USA, Germany, Italy have been found as the most favoured countries for collaborations. The institute has produced significant number of research articles participating with international collaboration experimental groups or consortia like ALISC, CMS, MAGIC and PICASSO. The scientists of SINP also select some foreign reputed journals to publish their maximum research findings and of these, Physics Letters B journal has been found as the most preferred source journal.

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Research Productivity of Saha Institute of Nuclear physics (SINP), India with special reference to International Collaborative Experimental Consortia

This paper studies the transdisciplinary impact of scientific publications with a longitudinal, comprehensive, and large-scale analysis on the Microsoft Academic Graph (MAG) dataset. More specifically, this paper aims to understand to what extent publications in discipline A have impact on discipline B. To this end, we propose a novel method to characterize the degree to which a publication impacts another discipline instead of its original discipline. We consider the ratio of the number of citations in a certain discipline and that in the original discipline. We also adopt an OLS regression to identify the equation between the ratio and the affinity of discipline pair and find a clear positive relation. This inspires us to categorize a publication's degree of transdisciplinarity by setting up two thresholds, the top 95% and the bottom 95% confident interval curve (of the fitted line). Publications above the top 95% curve is categorized as transdisciplinary ones, those below the bottom 95% curve as domain-specific ones, and those between the two curve as normal publications. This categorization does not require any pre-defined framework for transdisciplinarity and offers an automatic way of definition by data distribution itself. We find that sociology, mathematics, physics, and chemistry account for a great proportion of transdisciplinary publications that influence other domains, and that medicine, biology, economics, and geology have the greatest proportion of domain-specific publications that show impact in the original discipline. Moreover, we observe a negative relation between the number of citations and the proportion of transdisciplinary publications. A longitudinal analysis presents that the proportion of transdisciplinary publications shows a slightly increase trend for years. 

Towards transdisciplinary impact of scientific publications: A longitudinal, comprehensive, and large-scale analysis on Microsoft Academic Graph

India is perhaps unique amongst developing countries in having established a distinct science identity since last few centuries The Council of Scientific and Industrial Research (CSIR) is an autonomous body established in 1942 with the aim of providing strong S&T base for the industry, strategic sectors and advancement of fundamental knowledge The present study is to understand the quality and quantity of research output and current state-of-the-art of CSIR laboratories using publications output data as reflected in Web of Science and Scopus The study points out that during 2010 to 2015, although the yearly output has increased from 3940 papers to 5531 papers, the growth rate is neither linear nor exponential The scientists of the laboratory attach more weight to foreign journals rather than Indian journals having SCI impact factor within the range of 20 to 40 The authorship trend is completely slanted towards co-authorship and CSIR is assisting considerable financial support for conducting research The citation analysis of CSIR publications reveals that, a total of 30011 articles published during 2010-2015, received 251212 citations during 2010-2016 with an average rate of 7 citations per article Almost 10% articles did not receive any citation and 62% articles received citation in the range of 1 to 10

Research in Indian CSIR Laboratories:A Bibliometric Study

The quantification of scholarly performance has become an obvious necessity in many academic pursuits. Evaluation of research output is, therefore, an integral element of R&D institutions worldwide. This paper critically scrutinizes the literature on research productivity concerning scientific institutions (include universities and departments) in an informational context. It provides a thorough review to map the quantum of knowledge relating to ‘institutional research productivity’ correlating the Indian vista. The paper also offers a few recommendations to undertake evaluative studies with caution. Thus it shows a coherent picture of this emerging area in the sociology of science.

Evaluation of Institutional Research Productivity

The combination of a variety of inputs (both tangible and intangible) enables the numerous outputs in varying degrees to realize the research productivity. To select appropriate metrics and translate into the practical situation through empirical design is a cumbersome task. A single indicator cannot work well in different situations, but selecting the 'most suitable' one from dozens of indicators is very confusing. Nevertheless, establishing benchmarks in research evaluation and implementing all-factor productivity is almost impossible. Understanding research productivity is, therefore, a quintessential need for performance evaluations in the realm of evaluative scientometrics. Many enterprises evaluate the research performance with little understanding of the dynamics of research and its counterparts. Evaluative scientometrics endorses the measures that emerge during the decision-making process through relevant metrics and indicators expressing the organizational dynamics. Evaluation processes governed by counting, weighting, normalizing, and then comparing seem trustworthy.

Soumitra Sarkar

Papers

Evaluation of Institutional Research Productivity

Understanding research productivity in the realm of evaluative scientometrics