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Analytics, Policy, and Governance
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Edited by:
Jennifer Bachner
Language:
English
Published/Copyright:
2017
About this book
The first available textbook on the rapidly growing and increasingly important field of government analytics
This first textbook on the increasingly important field of government analytics provides invaluable knowledge and training for students of government in the synthesis, interpretation, and communication of “big data,” which is now an integral part of governance and policy making. Integrating all the major components of this rapidly growing field, this invaluable text explores the intricate relationship of data analytics to governance while providing innovative strategies for the retrieval and management of information.
This first textbook on the increasingly important field of government analytics provides invaluable knowledge and training for students of government in the synthesis, interpretation, and communication of “big data,” which is now an integral part of governance and policy making. Integrating all the major components of this rapidly growing field, this invaluable text explores the intricate relationship of data analytics to governance while providing innovative strategies for the retrieval and management of information.
Author / Editor information
Jennifer Bachner is director of the Master of Science in Government Analytics at Johns Hopkins. Benjamin Ginsberg is David Bernstein Professor of Political Science and chair of Governmental Studies at Johns Hopkins. Kathryn Wagner Hill is director of the Center for Advanced Governmental Studies at Johns Hopkins.
Topics
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Frontmatter
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Contents
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Introduction
1 - I. ENGAGING THE DATA
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CHAPTER ONE. Measuring Political and Policy Preferences Using Item Response Scaling
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CHAPTER TWO. Causal Inference with Observational Data
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CHAPTER THREE. Causal Inference with Experimental Data
67 - II. EMERGING DATA SOURCES AND TECHNIQUES
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CHAPTER FOUR. Descriptive Network Analysis
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CHAPTER FIVE. Learning from Place in the Era of Geolocation
118 -
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CHAPTER SIX. Text Analysis
137 -
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CHAPTER SEVEN. Machine Learning and Governance
160 - III. IMPLICATIONS FOR GOVERNANCE
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CHAPTER EIGHT. Governing a Data-Driven Society
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CHAPTER NINE. Big Data and Privacy
204 -
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CHAPTER TEN. Reflections on Analytics
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Contributors
245 -
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Index
249
Publishing information
Pages and Images/Illustrations in book
eBook published on:
January 10, 2017
eBook ISBN:
9780300225174
Pages and Images/Illustrations in book
Main content:
256
Other:
33 b-w illus.
