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  • Author or Editor: P. Nagpaul x
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Abstract  

This study analyzes the pattern of transnational linkages of Indian science in eleven scientific fields (Mathematics, Physics, Chemistry, Biology, Earth & Space Science, Agriculture, Clinical Medicine, Biomedical Research, Engineering & Technology, Computer Science, and Materials Science) during the five-year period: 1990–1994. The following indicators are constructed to examine inter-field and inter-country differences in India’s transnational linkages: Internationalization index, Cooperation index, Cooperation extensiveness index and Affinity index. A four-category typology is proposed to classify the fields according to their propensities for attracting bilateral and multilateral cooperation with foreign countries. The structure of multidimensional system of relationships between India’s thirty-five most significant partner countries and eleven scientific fields is analyzed through correspondence analysis. A series of correspondence analyses are carried out on subsets of the multidimensional data to reveal the fine-grained structure of India’s cooperation links in clusters of specific fields and with clusters of specific countries.

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This paper reports the results of an empirical study on the impact of three proximity measures: geographical distance, thematic distance and socio-economic distance among the set of 45 scientifically most advanced countries on their cooperation network. In network data, individuals (viz. countries) are linked to one another and the relationships are nested and embedded in groups, with the result that statistical assumptions of independence underlying ordinary least squares regression are systematically violated. Hence, we have used a non-parametric regression procedure, Quadratic Assignment Procedure (QAP), for regressing the matrix of transnational cooperation on the matrices of three proximity measures: geographic proximity, thematic proximity and socio-economic proximity. The results indicate that all the three proximity measures have the expected negative effect on transnational cooperation. Geographic proximity has greater impact than the other proximity measures.

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This paper examines the contribution of Indian universities to the mainstream scientific literature during 1987–1989 along two distinct, but inter-related dimensions of quantity and quality of research output. The quantity of output is assessed through the number of articles published in journals covered byScience Citation Index, while the quality of output is assessed through the impact factors of journals in which the articles are published. The impact factors are normalized to eliminate the confounding effects of their covariates,viz. the subject field and the nature of journal. A number of relative indicators are constructed for inter-field and inter-institution comparisons,viz. publication effectiveness index,1 relative quality index,2 activity index3 and citability index4. Inter-field comparisons are made at the level of eight macrofields: Mathematics, Physics, Chemistry, Biology, Earth & Space Sciences, Agriculture, Medical Sciences and Engineering & Technology. Inter-institution comparisons cover thirty three institutions which had published at least 150 articles in three years. The structure of correlations of these institutions with eight macrofields is analyzed through correspondence analysis of the matrices of activity and citability profiles. Correspondence analysis yields a mapping of institutions which reveals the structure of science as determined by the cumulative effect of resource allocation decisions taken in the past for different fields and institutions i.e. the effect of national science policy.

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This paper argues that research performance is essentially a multidimensional concept which cannot be encapsulated into a single universal criterion. Various indicators used in quantitative studies on research performance at micro or meso-levels can be classified into two broad categories: (i) objective or quantitative indicators (e.g. counts of publications, patents, algorithms or other artifacts of research output) and (ii) subjective or qualitative indicators which represent evaluative judgement of peers, usually measured on Likert or semantic differential scales. Because of their weak measurement properties, subjective indicators can also be designated as quasi-quantitative measures. This paper is concerned with the factorial structure and construct validity of quasi-quantitative measures of research performance used in a large-scale empirical study carried out in India. In this study, a reflective measurement model incorporating four latent variables (R & D effectiveness, Recognition, User-oriented effectiveness and Administrative effectiveness) is assumed. The latent variables are operationalized through thirteen indicators measured on 5-point semantic differential scales. Convergent validity, discriminant validity and reliability of the measurement model are tested through LISREL procedure.

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This paper seeks to examine the characteristics and quality of research planning at the level of microcosm of the research unit in six countries — Argentina, Egypt, India, Republic of Korea, Poland and USSR. It is concerned basically with the following aspects: (i) differences in the characteristics and quality of research planning in research units in different countries and institutional settings; (ii)pattern of relationships between the indices of planning and three measures of effectiveness—scientific, user-oriented and administrative; and (iii) stability in the pattern of relationships across countries and measures of performance. As a result of analysis, a few universal indices have been identified that have consistent relationships across countries. It is concluded that the determinants of effectiveness of research planning depend upon the criteria used for measuring the performance of the research unit. Besides specificity of research goals, the most important predictors of performance are: conceptual challenge of the research programme and external linkages of the research group—linkages with scientific peers and potential users of research results.

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This paper examines the following basic issues of leadership in research units: (1) characteristics of the leader and the functions performed by him that predict the image of his quality; and (2) the role of leadership in enhancing the performance of the research unit. Analysis is based on data collected on 1460 research units in six countries for the second round of International Comparative Study on Organization and Performance of Research Units. Variations in the characteristics and role of leadership in different institutional settings and countries are analyzed through POSCOR (ranking programme based on partially ordered sets). Stepwise multiple regression analysis was used to examine the common pattern of relationship of various indices of leadership with the image of leader's quality and three measures of effectiveness — scientific, user-oriented and administrative. Analysis was repeated for each country to explore the stability in the pattern of relationships and to identify universal indices that have consistent relationships across countries. Implications of the results are discussed.

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In this study, the specialization profiles of eleven countries are compared along two interconnected but distinct dimensions of research, viz. publication output and citation impact in nine subfields of chemistry. The data for comparative analysis were taken from Scientometric Datafiles.1Since raw counts of publications and citations are confounded by the size of the countries and the size of subject fields, cross-national comparison is made, using relative indicators—activity index and attractivity index. The subfields of relative strength and weakness for these countries are identified from the values of these indicators. The similarity structure of specialization profiles of the eleven countries is mapped, using hierarchical cluster analysis and multidimensional scaling. This mapping leads to the representation of chemistry as it is structured by the dynamics of national science policies of these countries.

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This paper focuses on the dichotomy between the multifaceted and multidimensional nature of contemporary R&D activity and unidimensional approaches to the measurement of its performance. While publications in refereed journals and citations are the most preferred indicators of research performance, there are also other indicators such as chapters in edited books, research reports, patents, algorithms, prototypes and designs, etc., which cannot be overlooked. Even when multiple indicators are used, they are used in isolation with the result that one gets only partial views of a multidimensional manifold. Here, a major problem is how to construct a composite measure of research performance, without assigning arbitrary weights to different measures of research output. This problem is particularly important for cross-institutional and cross-national comparisons of research performance. In this paper we have demonstrated the feasibility of constructing a multi-objective measure of research performance using Partial Order Scoring (POSCOR) algorithm developed by Hunya (1976). The algorithm is briefly described and applied to the empirical data on research outputs of 1460 research units in different socio-cultural, institutional and disciplinary settings. The potentialities and limitations of using POSCOR algorithm in scientometric analysis are briefly discussed.

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This paper seeks to compare the research priorities of thirty three countries in five macrofields (Physics, Chemistry, Biology, Mathematics and Engineering & Technology) in two time spans: 1980–1984 and 1985–1989. Comparative analysis is based on the distribution of publications in different fields. Since the raw counts of publications are confounded by the size of the countries and the size of the subject fields, a relative index — Research Priority Index (PI) — is computed for cross-national comparisons. Correspondence analysis is applied to the asymmetrical matrices of priority profiles to reveal the structure of multivariate relationships between countries and fields. The configurations for the two time-spans, obtained through correspondence analysis, are compared to reveal the dynamics of research priorities of these countries.

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