3.2.1 A Simple Index of Quality of Scientific Output Based on the Publications in Major Journals

Includes bibliographical references and index

Preface; Contents; Part I Science and Society. Research Organizations and Assessment of Research; 1 Science and Society. Assessment of Research; 1.1 Introductory Remarks; 1.2 Science, Technology, and Society; 1.3 Remarks on Dissipativity and the Structure of Science Systems; 1.3.1 Financial, Material, and Human Resource Flows Keep Science in an Organized State; 1.3.2 Levels, Characteristic Features, and Evolution of Scientific Structures; 1.4 Triple Helix Model of the Knowledge-Based Economy; 1.5 Scientific Competition Among Nations: The Academic Diamond

2.5.7 h-Like Indexes and Indexes Complementary to the Hirsch Index2.6 The g-Index of Egghe; 2.7 The in-Index; 2.8 p-Index. IQp-Index; 2.9 A-Index and R-Index; 2.10 More Indexes for Quantification of Research Production; 2.10.1 Indexes Based on Normalization Mechanisms; 2.10.2 PI-Indexes; 2.10.3 Indexes for Personal Success of a Researcher; 2.10.4 Indexes for Characterization of Research Networks; 2.11 Concluding Remarks; References; 3 Additional Indexes and Indicators for Assessment of Research Production; 3.1 Introductory Remarks; 3.2 Simple Indexes

2 Commonly Used Indexes for Assessment of Research Production2.1 Introductory Remarks; 2.2 Peer Review and Assessment by Indicators and Indexes; 2.3 Several General Remarks About Indicators and Indexes; 2.4 Additional Discussion on Citations as a Measure of Reception, Impact, and Quality of Research; 2.5 The h-Index of Hirsch; 2.5.1 Advantages and Disadvantages of the h-Index; 2.5.2 Normalized h-Index; 2.5.3 Tapered h-Index; 2.5.4 Temporally Bounded h-Index. Age-Dependent h-Index; 2.5.5 The Problem of Multiple Authorship. overlineh-Index of Hirsch and gh-Index of Galam; 2.5.6 The m-Index

1.12 Notes on the Methods of Research Assessment1.12.1 Method of Expert Evaluation; 1.12.2 Assessment of Basic Research; 1.12.3 Evaluation of Research Organizations and Groups of Research Organizations; 1.13 Mathematics and Quantification of Research Performance; 1.13.1 Weighting Without Accounting for the Current Performance; 1.13.2 Weighting with Accounting for the Current Performance ; 1.13.3 How to Determine the Values of Parameters; 1.14 Concluding Remarks; References; Part II Indicators and Indexes for Assessment of Research Production

1.6 Assessment of Research: The Role of Research Publications1.7 Quality and Performance: Processes and Process Indicators; 1.8 Latent Variables, Measurement Scales, and Kinds of Measurements; 1.9 Notes on Differences in Statistical Characteristics; 1.10 Several Notes on Scientometrics, Bibliometrics, Webometrics, and Informetrics; 1.10.1 Examples of Quantities that May Be Analyzed in the Process of the Study of Research Dynamics; 1.10.2 Inequality of Scientific Achievements; 1.10.3 Knowledge Landscapes; 1.11 Notes on Research Production and Research Productivity

Available to OhioLINK libraries

This book deals with methods to evaluate scientific productivity. In the book statistical methods, deterministic and stochastic models and numerous indexes are discussed that will help the reader to understand the nonlinear science dynamics and to be able to develop or construct systems for appropriate evaluation of research productivity and management of research groups and organizations. The dynamics of science structures and systems is complex, and the evaluation of research productivity requires a combination of qualitative and quantitative methods and measures. The book has three parts. The first part is devoted to mathematical models describing the importance of science for economic growth and systems for the evaluation of research organizations of different size. The second part contains descriptions and discussions of numerous indexes for the evaluation of the productivity of researchers and groups of researchers of different size (up to the comparison of research productivities of research communities of nations). Part three contains discussions of non-Gaussian laws connected to scientific productivity and presents various deterministic and stochastic models of science dynamics and research productivity. The book shows that many famous fat tail distributions as well as many deterministic and stochastic models and processes, which are well known from physics, theory of extreme events or population dynamics, occur also in the description of dynamics of scientific systems and in the description of the characteristics of research productivity. This is not a surprise as scientific systems are nonlinear, open and dissipative