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Theoretical developments and the emergence of new epistemological insights are based on interactions between old problems and new methodologies (Courgeau, 2003). At least two methodologies have helped social scientists of the past two generations in overcoming the traditional divide between individualistic and holistic approaches in the social sciences: multilevel analysis and social network analysis. The purpose of this book is to provide an exploration of the diverse ways in which these two methodologies can be brought together in statistical approaches to multilevel network analysis, specifically their combination in the development of three areas: theory, techniques, and empirical applications in the social sciences. The combination of approaches opens up new avenues of research and improves the necessary management of so-called ‘ecological fallacies’ in complex systems of inequalities: for example, when looking at problems as different as school performance of pupils or career development in labor markets. With respect to theory, this book describes the development of multilevel network reasoning by showing how it can explain behavior by insisting on two different ways of contextualizing it. The first method consists of identifying levels of influence on behavior and identifying in sophisticated ways different aggregations of actors and behaviors as well as complex interactions between levels and therefore between context and behavior. A second, more recent method of contextualization, consists of identifying different systems of collective agency as distinct levels of analysis, differentiating for example among levels of collective action with different goals; specific resource interdependencies between members; and specific social processes that help members manage dilemmas of collective action at each level. The book also provides an overview of different methodologies contributing to this perspective and case studies and datasets that explore new avenues of theorizing and modeling. Each chapter contributes to the exploration of structure in multilevel network analysis, from descriptive and inductive techniques to stochastic models (from network autocorrelation models to p2 models to ERGMs), accounting for both horizontal and vertical interdependencies. Although heterogeneous with respect to units of analysis and methods, models of multilevel network analysis presented in this volume tend to take into account a variety of structural dependencies, both within and between levels. The conclusion extends theoretical, methodological and empirical results of this new epistemology by speculating on the insights provided on our knowledge of societies that have become “organizational” societies, i.e. rationalized, managerialized, and marketized.
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hal-01520949 , version 1 (11-05-2017)



Emmanuel Lazega, Tom Snijders. Introduction. Emmanuel Lazega; Tom Snijders. Multilevel Network Analysis: Theory, Methods and Applications, Springer, pp.1 - 12, 2016, 9783319245201. ⟨hal-01520949⟩
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