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A necessary exploration into the mechanics of data privacy protections within empirical social science research.

The explosion of computational power and data availability has revolutionized empirical social science research, but it has also created unprecedented challenges for protecting the privacy of individuals and businesses. As computational tools make it increasingly possible to breach data anonymity in government surveys by combining the survey data with additional information from external sources, statistical agencies face mounting pressure to develop new privacy protection methods while maintaining data quality essential for research and policymaking. This volume explores how innovations in data privacy protection, including differential privacy and synthetic data methods, affect the conduct of empirical analysis in economics, computer science, and statistics. Contributors explore critical questions about the trade-offs between privacy and data usability: How do new protection methods impact statistical inference and parameter estimation? What standards should data providers adopt? The chapters examine frameworks for characterizing privacy protection, disclosure limitation challenges for survey data, methodological innovations for privacy-preserving statistical analysis, regulatory considerations in modern data governance, and strategies for balancing confidentiality with research access.

This volume provides researchers, statistical agencies, and policymakers with essential guidance for navigating the complex landscape where data protection meets scientific inquiry.

Randomized experiments—often referred to as the gold standard of research design—are generally accepted as the type of studies that provide the strongest evidence about cause and effect. There has been a wide adoption of experimental methods in agriculture, medicine, industrial design, and laboratory social sciences, such as experimental psychology, where conditions can be controlled. Since then, there has been an increase in the use of field experiments to provide evidence of cause and effect beyond the laboratory. However, the social settings in which these studies take place complicate the design and evaluation of experiments because their social contexts must be taken into account in order for the experiment to provide useful and unambiguous results. In Designing Experiments in Education and the Social Sciences, statistician Larry V. Hedges details how to design educational and social science field experiments that are sensitive enough to provide clear-cut evidence on the effects of social interventions.

Hedges draws on one hundred years of statistical theory and classic experimental design in Designing Experiments in Education and the Social Sciences. Highlighting the social-structural information embedded in field experiments, he links this history with contemporary statistical methods in the social sciences to explain how to design social experiments that are adequately sensitive to determine the influence of an intervention. He covers the four basic research designs—and 39 elaborations of those designs—that are used most often in social experiments while also introducing additional, more complex, designs. He brings together, in the same notation, work on experimental design, design sensitivity, and optimal design of experiments for the most frequently used research designs in education and the social sciences, emphasizing their conceptual consistency. Hedges also discusses the practical problems of how to recruit and maintain a sample throughout the duration of an experiment.

Designing Experiments in Education and the Social Sciences is an essential resource for researchers planning educational and social field experiments and graduate students.

Digital ethnography can be understood as a method for representing real-life cultures through storytelling in digital media. Enabling audiences to go beyond absorbing facts, computer-based storytelling allows for immersion in the experience of another culture. A guide for anyone in the social sciences who seeks to enrich ethnographic techniques, Digital Ethnography offers a groundbreaking approach that utilizes interactive components to simulate cultural narratives.

Integrating insights from cultural anthropology, folklore, digital humanities, and digital heritage studies, this work brims with case studies that provide in-depth discussions of applied projects. Web links to multimedia examples are included as well, including projects, design documents, and other relevant materials related to the planning and execution of digital ethnography projects. In addition, new media tools such as database development and XML coding are explored and explained, bridging the literature on cyber-ethnography with inspiring examples such as blending cultural heritage with computer games.

One of the few books in its field to address the digital divide among researchers, Digital Ethnography guides readers through the extraordinary potential for enrichment offered by technological resources, far from restricting research to quantitative methods usually associated with technology. The authors powerfully remind us that the study of culture is as much about affective traits of feeling and sensing as it is about cognition—an approach facilitated (not hindered) by the digital age.

In the seventeenth century, a map of the plague suggested a radical idea—that the disease was carried and spread by humans. In the nineteenth century, maps of cholera cases were used to prove its waterborne nature. More recently, maps charting the swine flu pandemic caused worldwide panic and sent shockwaves through the medical community. In Disease Maps, Tom Koch contends that to understand epidemics and their history we need to think about maps of varying scale, from the individual body to shared symptoms evidenced across cities, nations, and the world.  

Disease Maps begins with a brief review of epidemic mapping today and a detailed example of its power. Koch then traces the early history of medical cartography, including pandemics such as European plague and yellow fever, and the advancements in anatomy, printing, and world atlases that paved the way for their mapping. Moving on to the scourge of the nineteenth century—cholera—Koch considers the many choleras argued into existence by the maps of the day, including a new perspective on John Snow’s science and legacy. Finally, Koch addresses contemporary outbreaks such as AIDS, cancer, and H1N1, and reaches into the future, toward the coming epidemics. Ultimately, Disease Maps redefines conventional medical history with new surgical precision, revealing that only in maps do patterns emerge that allow disease theories to be proposed, hypotheses tested, and treatments advanced.