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Shifting Grounds
"Shifting Grounds brings together the existing social constructivist research in International Relations (IR) and political geography, and examines the interactive relationship between territory and war from conceptual, theoretical, and historical perspectives. The central premise is the following: territory is what states and societies make of it. Put differently, states and societies have adhered to different forms of territoriality across time and space, and territory as well as territorial control meant different things in different time periods and regions. Shifting Grounds makes two claims. First, how state elites conceive territory within and beyond their domains affect their military...
Topics on Methodological and Applied Statistical Inference
This book brings together selected peer-reviewed contributions from various research fields in statistics, and highlights the diverse approaches and analyses related to real-life phenomena. Major topics covered in this volume include, but are not limited to, bayesian inference, likelihood approach, pseudo-likelihoods, regression, time series, and data analysis as well as applications in the life and social sciences. The software packages used in the papers are made available by the authors. This book is a result of the 47th Scientific Meeting of the Italian Statistical Society, held at the University of Cagliari, Italy, in 2014.
Data Science for Complex Systems
Many real-life systems are dynamic, evolving, and intertwined. Examples of such systems displaying 'complexity', can be found in a wide variety of contexts ranging from economics to biology, to the environmental and physical sciences. The study of complex systems involves analysis and interpretation of vast quantities of data, which necessitates the application of many classical and modern tools and techniques from statistics, network science, machine learning, and agent-based modelling. Drawing from the latest research, this self-contained and pedagogical text describes some of the most important and widely used methods, emphasising both empirical and theoretical approaches. More broadly, this book provides an accessible guide to a data-driven toolkit for scientists, engineers, and social scientists who require effective analysis of large quantities of data, whether that be related to social networks, financial markets, economies or other types of complex systems.
New Thinking in GIScience
This book is a collection of seminal position essays by leading researchers on new development in Geographic Information Sciences (GIScience), covering a wide range of topics and representing a variety of perspectives. The authors propose enrichments and extensions to the conceptual framework of GIScience; discuss a series of transformational methodologies and technologies for analysis and modeling; elaborate on key issues in innovative approaches to data acquisition and integration, across earth sensing to social sensing; and outline frontiers in application domains, spanning from natural science to humanities and social science, e.g., urban science, land use and planning, social governance, transportation, crime, and public health, just name a few. The book provides an overview of the strategic directions on GIScience research and development. It will benefit researchers and practitioners in the field who are seeking a high-level reference regarding those directions.
Statistical Modeling and Inference for Social Science
Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes the connection between statistical procedures and social science theory. Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables - the primary aim of social scientists - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students will also gain the ability to create, read and critique statistical applications in their fields of interest.
Data Science for Complex Systems
This book provides a guide to the analysis of complex systems through the lens of data science.
A First Course in Network Science
A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.
Understanding the Dynamics of Global Inequality
Despite the fact that the globalization process tends to reinforce existing inequality structures and generate new areas of inequality on multiple levels, systematic analyses on this very important field remain scarce. Hence, this book approaches the complex question of inequality not only from different regional perspectives, covering Africa, Asia, Europe, Latin and Northern America, but also from different disciplinary perspectives, namely cultural anthropology, economics, ethnology, geography, international relations, sociology, and political sciences. The contributions are subdivided into three essential fields of research: Part I analyzes the socio-economic dimension of global exclusion...
