Recently, the public sector has given an increasing amount of national and international attention to electronic government systems. Therefore, it is inevitable that the theoretical implications and intersections between information technology and governmental matters are more widely discussed. Public Information Management and E-Government: Policy and Issues offers a fresh, comprehensive dialogue on issues that occur between the public management and information technology domains. With its focus on political issues and their effects on the larger public sector, this book is valuable for administrators, researchers, students, and educators who wish to gain foundational and theoretical knowledge on e-government policies.
Describes the quantitative research process--framing analytical questions, developing a comprehensive outline, providing a roadmap for the reader, and accessing indispensable computer and program tools. Supplies end-of-chapter checklists, extensive examples, and biobliographies.
This book provides the first accessible introduction to neural network analysis as a methodological strategy for social scientists. The author details numerous studies and examples which illustrate the advantages of neural network analysis over other quantitative and modelling methods in widespread use. Methods are presented in an accessible style for readers who do not have a background in computer science. The book provides a history of neural network methods, a substantial review of the literature, detailed applications, coverage of the most common alternative models and examples of two leading software packages for neural network analysis.
This book provides a brief, easy-to-read guide to implementing hierarchical linear modeling using three leading software platforms, followed by a set of original how-to applications articles following a standardard instructional format. The "guide" portion consists of five chapters by the editor, providing an overview of HLM, discussion of methodological assumptions, and parallel worked model examples in SPSS, SAS, and HLM software. The "applications" portion consists of ten contributions in which authors provide step by step presentations of how HLM is implemented and reported for introductory to intermediate applications.
Multilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R & HLMTM provides a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multiple software resources for their students and an applications-based foundation for teaching multilevel modeling in the social sciences. Author G. David Garson’s step-by-step instructions for software walk readers through each package. The instructions for the different platforms allow students to get a running start using the package with which they are most familiar while the instructor can start teaching the concepts of multilevel modeling right away. Instructors will find this text serves as both a comprehensive resource for their students and a foundation for their teaching alike.
Written by a leading scholar of public information systems, Public Information Technology and E-Governance is a comprehensive, well-balanced and up-to-date resource on public information technology and e-government. Based on thousands of academic and practitioner studies and reports, this book provides policy information on e-democracy, access issues, privacy, security, regulatory, enforcement and taxation issues, as well as management information on business plans, public-private partnerships, strategic planning, project management, implementation factors, and evaluation. An excellent text or reference, this book features several chapter case studies, a glossary, discussion questions, and chapter summaries to maximize comprehension of the subject.
This book provides the first accessible introduction to neural network analysis as a methodological strategy for social scientists. The author details numerous studies and examples which illustrate the advantages of neural network analysis over other quantitative and modelling methods in widespread use. Methods are presented in an accessible style for readers who do not have a background in computer science. The book provides a history of neural network methods, a substantial review of the literature, detailed applications, coverage of the most common alternative models and examples of two leading software packages for neural network analysis.
The techniques of analytic mapping and of geographic information systems (GIS) have become increasingly important tools for analysing census, crime, environmental and consumer data. The authors discuss data access, transformation and preparation issues, and how to select the appropriate analytic graphics techniques.
This lucid resource guide discusses the appropriate applications of microcomputing in university curricula. Academics and administrators can benefit from a wide variety of computer software applications, computer-based data sources and other computer resources. Garson lists typical `toolkits' for scholars and administrators, focusing on generic needs and the leading products in use today.
Factor Analysis and Dimension Reduction in R provides coverage, with worked examples, of a large number of dimension reduction procedures along with model performance metrics to compare them. Factor analysis in the form of principal components analysis (PCA) or principal factor analysis (PFA) is familiar to most social scientists. However, what is less familiar is understanding that factor analysis is a subset of the more general statistical family of dimension reduction methods. The social scientist's toolkit for factor analysis problems can be expanded to include the range of solutions this book presents. In addition to covering FA and PCA with orthogonal and oblique rotation, this book’s coverage includes higher-order factor models, bifactor models, models based on binary and ordinal data, models based on mixed data, generalized low-rank models, cluster analysis with GLRM, models involving supplemental variables or observations, Bayesian factor analysis, regularized factor analysis, testing for unidimensionality, and prediction with factor scores. The second half of the book deals with other procedures for dimension reduction. These include coverage of kernel PCA, factor analysis with multidimensional scaling, locally linear embedding models, Laplacian eigenmaps, diffusion maps, force directed methods, t-distributed stochastic neighbor embedding, independent component analysis (ICA), dimensionality reduction via regression (DRR), non-negative matrix factorization (NNMF), Isomap, Autoencoder, uniform manifold approximation and projection (UMAP) models, neural network models, and longitudinal factor analysis models. In addition, a special chapter covers metrics for comparing model performance. Features of this book include: Numerous worked examples with replicable R code Explicit comprehensive coverage of data assumptions Adaptation of factor methods to binary, ordinal, and categorical data Residual and outlier analysis Visualization of factor results Final chapters that treat integration of factor analysis with neural network and time series methods Presented in color with R code and introduction to R and RStudio, this book will be suitable for graduate-level and optional module courses for social scientists, and on quantitative methods and multivariate statistics courses.
Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers. The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling. Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis.
Fiscal realities and changing social priorities are requiring a dramatic shift in the way that benefits are selected and awarded to employees, especially in the public sector. This means that public administrators and policy researchers must consider new parameters and contingencies, both financial and social, when evaluating choices and making pol
Americans have long prided themselves on living in a country that serves as a beacon of democracy to the world, but from the time of the founding they have also engaged in debates over what the criteria for democracy are as they seek to validate their faith in the United States as a democratic regime. In this book John Gunnell shows how the academic discipline of political science has contributed in a major way to this ongoing dialogue, thereby playing a significant role in political education and the formulation of popular conceptions of American democracy. Using the distinctive “internalist” approach he has developed for writing intellectual history, Gunnell traces the dynamics of conceptual change and continuity as American political science evolved from a focus in the nineteenth century on the idea of the state, through the emergence of a pluralist theory of democracy in the 1920s and its transfiguration into liberalism in the mid-1930s, up to the rearticulation of pluralist theory in the 1950s and its resurgence, yet again, in the 1990s. Along the way he explores how political scientists have grappled with a fundamental question about popular sovereignty: Does democracy require a people and a national democratic community, or can the requisites of democracy be achieved through fortuitous social configurations coupled with the design of certain institutional mechanisms?
Recently, the public sector has given an increasing amount of national and international attention to electronic government systems. Therefore, it is inevitable that the theoretical implications and intersections between information technology and governmental matters are more widely discussed. Public Information Management and E-Government: Policy and Issues offers a fresh, comprehensive dialogue on issues that occur between the public management and information technology domains. With its focus on political issues and their effects on the larger public sector, this book is valuable for administrators, researchers, students, and educators who wish to gain foundational and theoretical knowledge on e-government policies.
Statistical Graphics for Univariate and Bivariate Data focuses on graphical displays that researchers can employ as an integral part of the data analysis process, and provides strategies for examining data more effectively.
Examines the life of education activist Audrey Cohen and her founding of Metropolitan College of New York. In 1964 educational activist Audrey Cohen and her colleagues developed a unique curricular structure that enables urban college students to integrate their academic studies with meaningful work in community settings. Creating a College That Works chronicles Cohens efforts to create an innovative educational model that began with the Womens Talent Corps, evolved into the College for Human Services, and finally became, in 2002, what is now Metropolitan College of New York (MCNY), a fully accredited institution of higher education that offers bachelors and masters degrees. Focusing her attention on the major players in the development of MCNY, Grace G. Roosevelt provides a ringside seat during the years of turbulence, hope, and innovation in the 1960s and 70s. She captures the life of a visionary educational leader while situating Cohens ideas within the history of progressive education. Cohen and her colleagues, facing great opposition, petitioned and marched, and were harassed and rebuffed. But they persevered, and today the college they founded continues to graduate hundreds of students dedicated to improving their communities, workplaces, and schools in the New York metropolitan area. Woven throughout the narrative are the changing dynamics of the civil rights movement, questions about womens leadership roles, and stories of how adults have transformed their lives through Cohens innovative educational model.
Americans have long prided themselves on living in a country that serves as a beacon of democracy to the world, but from the time of the founding they have also engaged in debates over what the criteria for democracy are as they seek to validate their faith in the United States as a democratic regime. In this book John Gunnell shows how the academic discipline of political science has contributed in a major way to this ongoing dialogue, thereby playing a significant role in political education and the formulation of popular conceptions of American democracy. Gunnell traces the dynamics of conceptual change and continuity as American political science evolved from a focus in the nineteenth century on the idea of the state, through the emergence of a pluralist theory of democracy in the 1920s and its transfiguration into liberalism in the mid- 1930s, up to the rearticulation of pluralist theory in the 1950s and its resurgence, yet again, in the 1990s. Along the way he explores how political scientists have grappled with a fundamental question about popular sovereignty: Does democracy require a people and a national democratic community, or can the requisites of democracy be achieved through fortuitous social configurations coupled with the design of certain institutional mechanisms?
Why are some territorial partitions accepted as the appropriate borders of a nation's homeland, whereas in other places conflict continues despite or even because of division of territory? In Homelands, Nadav G. Shelef develops a theory of what homelands are that acknowledges both their importance in domestic and international politics and their change over time. These changes, he argues, driven by domestic political competition and help explain the variation in whether partitions resolve conflict. Homelands also provides systematic, comparable data about the homeland status of lost territory over time that allow it to bridge the persistent gap between constructivist theories of nationalism and positivist empirical analyses of international relations.
In this dramatic story of the making and unmaking of Portugal's agrarian reform, Nancy Bermeo probes the origins and effects of the workers' actions. Originally published in 1986. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
The techniques of analytic mapping and of geographic information systems (GIS) have become increasingly important tools for analysing census, crime, environmental and consumer data. The authors discuss data access, transformation and preparation issues, and how to select the appropriate analytic graphics techniques.
Written by a leading scholar of public information systems, Public Information Technology and E-Governance is a comprehensive, well-balanced and up-to-date resource on public information technology and e-government. Based on thousands of academic and practitioner studies and reports, this book provides policy information on e-democracy, access issues, privacy, security, regulatory, enforcement and taxation issues, as well as management information on business plans, public-private partnerships, strategic planning, project management, implementation factors, and evaluation. An excellent text or reference, this book features several chapter case studies, a glossary, discussion questions, and chapter summaries to maximize comprehension of the subject.
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