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Artificial Intelligence and Evaluation
Artificial Intelligence and Evaluation: Emerging Technologies and Their Implications for Evaluation is a groundbreaking exploration of how the landscape of program evaluation will be redefined by artificial intelligence and other emerging digital technologies. In an era where digital technologies and artificial intelligence (AI) are rapidly evolving, this book presents a pivotal resource for evaluators navigating the transformative intersection of their practice and cutting-edge technology. Addressing the dual dimensions of how evaluations are conducted and what is evaluated, a roster of distinguished contributors illuminate the impact of AI on program evaluation methodologies. Offering a di...
Towards Sustainable Futures
Towards Sustainable Futures serves as a guide to better understand what roles evaluation can play in sustainability. Rather than proposing a single definition of sustainability or methodological approach, this book gives us the tools to improve the quality and relevance of evaluation of sustainability. Divided into two parts, the first part introduces the reader to key debates and challenges related to evaluation of sustainability. Part Two provides examples of methods and applications. By combining a stellar line up of specialists, theorists, and practitioners in the field of development evaluation with expert, accessible and engaged analysis of key issues, Towards Sustainable Futures is a must-read source for re-tooling and re-focussing evaluation towards the green transition imperative. It should be essential reading for scholars and practitioners of evaluation. Chapters 1, 4, 6 and 15 of this book are freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons [Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND)] 4.0 license.
Data Science and Social Research
This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and ...
Statistical Learning of Complex Data
This book of peer-reviewed contributions presents the latest findings in classification, statistical learning, data analysis and related areas, including supervised and unsupervised classification, clustering, statistical analysis of mixed-type data, big data analysis, statistical modeling, graphical models and social networks. It covers both methodological aspects as well as applications to a wide range of fields such as economics, architecture, medicine, data management, consumer behavior and the gender gap. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field of data analysis and classification. It gathers selected and peer-reviewed contributions presented at the 11th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2017), held in Milan, Italy, on September 13–15, 2017.
Decision-Making Support Systems: Achievements and Challenges for the New Decade
Annotation The book presents state-of-the-art knowledge about decision-making support systems (DMSS). Its main goals are to provide a compendium of quality chapters on decision-making support systems that help diffuse scarce knowledge about effective methods and strategies for successfully designing, developing, implementing, and evaluating decision-making support systems, and to create an awareness among readers about the relevance of decision-making support systems in the current complex and dynamic management environment.
Machine Learning, Optimization, and Data Science
This two-volume set, LNCS 13163-13164, constitutes the refereed proceedings of the 7th International Conference on Machine Learning, Optimization, and Data Science, LOD 2021, together with the first edition of the Symposium on Artificial Intelligence and Neuroscience, ACAIN 2021. The total of 86 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 215 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Changing Bureaucracies
In Changing Bureaucracies, international experts provide an unparalleled look at how public sector bureaucracies can better adapt to the reality of unprecedented levels of uncertainty and complexity, and how they can better respond to the emerging needs and demands of citizens and beneficiaries. In particular, they discuss in detail how evaluation can play an important role in aiding bureaucracies in adapting, while noting that the value of evaluation is not at all automatic. Written in a clear and accessible prose, the contributors identify stability as a strength of bureaucratic structures, although adaptability is required in order to remain relevant. They also emphasize the need for bure...
The Realpolitik of Evaluation
The Realpolitik of Evaluation shines a light on the divergent demands for evaluation. But what explains the "gap" between what those on the "demand" side expect in terms of evaluation results, and the "supply" of information provided by evaluators? Can anything be done to narrow this gap? What works and what does not work? Examining these questions from both the demand and the supply side, experts describe ten different global examples of the gap between demand and supply of evaluation information in different contexts. In an attempt to bridge that gap, they effectively reveal the biases behind supposedly sources of evaluation information and highlight the pros and cons of attempts to bridge the gap through the use of third parties, enhanced stakeholder involvement, and the incorporation of social science models to strengthen Theories of Change (ToC). The Realpolitik of Evaluation is an important book that poses questions at multiple levels of thinking. It will be of great interest to policymakers, program implementers, and project managers.
Cyber Society, Big Data, and Evaluation
We are living in a cyber society. Mobile devices, social media, the Internet, crime cameras, and other diverse sources can be pulled together to form massive datasets, known as big data, which make it possible to learn things we could not begin to comprehend otherwise. While private companies are using this macroscopic tool, policy-makers and evaluators have been slower to adopt big data to make and evaluate public policy. Cyber Society, Big Data, and Evaluation shows ways big data is now being used in policy evaluation and discusses how it will transform the role of evaluators in the future. Arguing that big data will play a permanent and growing role in policy evaluation, especially since ...
