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Are reports of the death of conventional fieldwork in anthropology greatly exaggerated? This book takes a critical look at the latest developments and key issues in fieldwork. The nature of 'locality' itself is problematic for both research subjects and fieldworkers, on the grounds that it must now be maintained and represented in relation to widening (and fragmenting) social frames and networks. Such developments have raised questions concerning the nature of ethnographic presence and scales of comparison. From the social space of a cybercafe to cities in India, the UK and South Africa among others, this book features a wide range of ethnographic studies that provide new ways of looking at the concepts of 'locality' and 'site'. It shows that rather than taking key fieldwork processes such as globalization and mobility for granted, anthropologists are well-placed to examine and critique the totalizing assumptions behind these notions.
"A vitally important contribution to anthropology. . . . Most importantly, although the critique is sharply directed, the tone of the volume is constructive rather than destructive—or deconstructive."—Joan Vincent, Barnard College "A rich, thought-provoking, and highly original collection. . . . The research presented is new and the perspectives original. This collection of essays casts significant new light on phenomena and practices which have long been central to anthropology, while at the same time introducing new substantive materials."—Don Brenneis, University of California, Santa Cruz
A revealing look at the common causes of failures in randomized control experiments during field reseach—and how to avoid them All across the social sciences, from development economics to political science, researchers are going into the field to collect data and learn about the world. Successful randomized controlled trials have brought about enormous gains, but less is learned when projects fail. In Failing in the Field, Dean Karlan and Jacob Appel examine the taboo subject of failure in field research so that researchers might avoid the same pitfalls in future work. Drawing on the experiences of top social scientists working in developing countries, this book describes five common categories of failures, reviews six case studies in detail, and concludes with reflections on best (and worst) practices for designing and running field projects, with an emphasis on randomized controlled trials. Failing in the Field is an invaluable “how-not-to” guide to conducting fieldwork and running randomized controlled trials in development settings.
This comprehensive and clearly structured book presents essential information on modern Location Science. The book is divided into three parts: basic concepts, advanced concepts and applications. Written by the most respected specialists in the field and thoroughly reviewed by the editors, it first lays out the fundamental problems in Location Science and provides the reader with basic background information on location theory. Part II covers advanced models and concepts, broadening and expanding on the content presented in Part I. It provides the reader with important tools to help them understand and solve real-world location problems. Part III is dedicated to linking Location Science with other areas like GIS, telecommunications, healthcare, rapid transit networks, districting problems and disaster events, presenting a wide range of applications. This part enables the reader to understand the role of facility location in such areas, as well as to learn how to handle realistic location problems. The book is intended for researchers working on theory and applications involving location problems and models. It is also suitable as a textbook for graduate courses on facility location.
This book constitutes the refereed proceedings of the 9th International Conference on Ubiquitous Computing, UbiComp 2007. It covers all current issues in ubiquitous, pervasive and handheld computing systems and their applications, including tools and techniques for designing, implementing, and evaluating ubiquitous computing systems; mobile, wireless, and ad hoc networking infrastructures for ubiquitous computing; privacy, security, and trust in ubiquitous and pervasive systems.
This guide offers practical tips on science writing - from investigative reporting to pitching ideas to magazine editors. Some of the best known science witers in the US share their hard earned knowledge on how they do their job.
From research preparations to post-research debriefing, this book covers every stage of the social research process, outlining how to undertake fieldwork as safely as possible.
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.
The substantially updated and revised Fifth Edition of The SAGE Handbook of Qualitative Research by editors Norman K. Denzin and Yvonna S. Lincoln presents the state-of-the-art theory and practice of qualitative inquiry. Representing top scholars from around the world, the editors and contributors continue the tradition of synthesizing existing literature, defining the present, and shaping the future of qualitative research. The Fifth Edition contains 19 new chapters, with 16 revised—making it virtually a new volume—while retaining six classic chapters from previous editions. New contributors to this edition include Jamel K. Donnor and Gloria Ladson-Billings; Margaret Kovach; Paula Saukko; Bryant Keith Alexander; Thomas A. Schwandt and Emily F. Gates; Johnny Saldaña; Uwe Flick; Mirka Koro-Ljungberg, Maggie MacLure, and Jasmine Ulmer; Maria Elena Torre, Brett G. Stoudt, Einat Manoff, and Michelle Fine; Jack Bratich; Svend Brinkmann; Eric Margolis and Renu Zunjarwad; Annette N. Markham; Alecia Y. Jackson and Lisa A. Mazzei; Jonathan Wyatt, Ken Gale, Susanne Gannon, and Bronwyn Davies; Janice Morse; Peter Dahler-Larsen; Mark Spooner; and David A. Westbrook.