Our ability to observe and forecast severe weather events has improved markedly over the past few decades. Forecasts of snow and ice storms, hurricanes and storm surge, extreme heat, and other severe weather events are made with greater accuracy, geographic specificity, and lead time to allow people and communities to take appropriate protective measures. Yet hazardous weather continues to cause loss of life and result in other preventable social costs. There is growing recognition that a host of social and behavioral factors affect how we prepare for, observe, predict, respond to, and are impacted by weather hazards. For example, an individual's response to a severe weather event may depend on their understanding of the forecast, prior experience with severe weather, concerns about their other family members or property, their capacity to take the recommended protective actions, and numerous other factors. Indeed, it is these factors that can determine whether or not a potential hazard becomes an actual disaster. Thus, it is essential to bring to bear expertise in the social and behavioral sciences (SBS)â€"including disciplines such as anthropology, communication, demography, economics, geography, political science, psychology, and sociologyâ€"to understand how people's knowledge, experiences, perceptions, and attitudes shape their responses to weather risks and to understand how human cognitive and social dynamics affect the forecast process itself. Integrating Social and Behavioral Sciences Within the Weather Enterprise explores and provides guidance on the challenges of integrating social and behavioral sciences within the weather enterprise. It assesses current SBS activities, describes the potential value of improved integration of SBS and barriers that impede this integration, develops a research agenda, and identifies infrastructural and institutional arrangements for successfully pursuing SBS-weather research and the transfer of relevant findings to operational settings.

Presents papers which were discussed at the Arden House Conference—a conference held to establish a working relationship between sociologists at the Russell Sage Foundation and journalists of the Graduate School of Journalism of Columbia University. Both behavioral science and journalism have for a long time been concerned with some of the same major national social problems—juvenile delinquency, urban problems, race and minority group relations, international tensions, and labor relations. These papers touch on some of the barriers to communication and point to possible ways of breaking through those barriers.

This collection of essays was the first major attempt to apply game theory, linear programming, and graph theory to anthropological data. Contributors: John Atkins; Ira B. Buchler; Albert M. Chammah; Luke Curtis; Walter Goldschmidt; Hans Hoffman; Robert Kozelka; Bernhardt Lieberman; Frank B. Livingstone; R. Michael McKinlay; Anatol Rapoport; Richard F. Salisbury; T. C. Schelling; M. Shubik; and Martin Southwold.

The Second Edition of the award-winning Research Methods for the Behavioral Sciences employs a problem-focused approach that fully integrates the decision tree—from choosing a research design to conducting statistical analysis and communicating results. With a conversational, student-friendly writing style, Gregory J. Privitera shows how methods and analysis work together and enable the testing of hypotheses through use of the scientific method. Outstanding pedagogy, current examples, and robust resources empower students to approach their study and application of research methods with confidence.

Highly accessible A-Z of the major terms in the social and behavioural sciences, spanning anthropology, communication and media studies, criminal justice, economics, education, geography, human services, management, political science, psychology and sociology.

This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different combinations of variables in large data sets. Methodological findings and conceptual models that explain reliable EDM techniques for predicting and understanding various risk mechanisms are integrated throughout. Numerous examples illustrate the use of these techniques in practice. Contributors provide insight through hands-on experiences with their own use of EDM techniques in various settings. Readers are also introduced to the most popular EDM software programs. A related website at http://mephisto.unige.ch/pub/edm-book-supplement/offers color versions of the book’s figures, a supplemental paper to chapter 3, and R commands for some chapters. The results of EDM analyses can be perilous – they are often taken as predictions with little regard for cross-validating the results. This carelessness can be catastrophic in terms of money lost or patients misdiagnosed. This book addresses these concerns and advocates for the development of checks and balances for EDM analyses. Both the promises and the perils of EDM are addressed. Editors McArdle and Ritschard taught the "Exploratory Data Mining" Advanced Training Institute of the American Psychological Association (APA). All contributors are top researchers from the US and Europe. Organized into two parts--methodology and applications, the techniques covered include decision, regression, and SEM tree models, growth mixture modeling, and time based categorical sequential analysis. Some of the applications of EDM (and the corresponding data) explored include: selection to college based on risky prior academic profiles the decline of cognitive abilities in older persons global perceptions of stress in adulthood predicting mortality from demographics and cognitive abilities risk factors during pregnancy and the impact on neonatal development Intended as a reference for researchers, methodologists, and advanced students in the social and behavioral sciences including psychology, sociology, business, econometrics, and medicine, interested in learning to apply the latest exploratory data mining techniques. Prerequisites include a basic class in statistics.

The success of nearly all public- and private- sector policies hinges on the behavior of individuals, groups, and organizations. Today, such behaviors are better understood than ever, thanks to a growing body of practical behavioral science research. However, policymakers often are unaware of behavioral science findings that may help them craft and execute more effective and efficient policies. The pages of this new journal will become a meeting ground: a place where scientists and non-scientists can encounter clearly described behavioral research that can be put into action. By design, the scope of BSP is broad, with topics spanning health care, financial decisionmaking, energy and the environment, education and culture, justice and ethics, and work place practices. Contributions will be made by researchers with expertise in psychology, sociology, law, behavioral economics, organization science, decision science, and marketing. The journal is a key offering of the Behavioral Science & Policy Association in partnership with the Brookings Institution. The mission of BSPA is to foster dialog between social scientists, policymakers, and other practitioners in order to promote the application of rigorous empirical behavioral science in ways that serve the public interest. BSPA does not advance a particular agenda or political perspective. The first issue’s contents follow. Behavioral Science & Policy, vol. 1, no. 2 Extending the reach of behavioral policy Editors’ note: Craig R. Fox & Sim B. Sitkin 1. Belonging nowhere: Marginalization and radicalization risk among Muslim immigrants, Sarah Lyons-Padilla, Michele J. Gelfand, Hedieh Mirahmadi, Mehreen Farooq, & Marieke van Egmond 2. New directions for policies aimed at strengthening low-income couples, Justin A. Lavner, Benjamin R. Karney, & Thomas N. Bradbury 3. A personal touch in text messaging can improve loan repayment, Dean Karlan, Melanie Morten, & Jonathan Zinman 4. Beyond good intentions: Prompting people to make plans improves follow-through on important tasks, Todd Rogers, Katherine L. Milkman, Leslie K. John, & Michael I. Norton 5. Improving the communication of uncertainty in climate science and intelligence analysis, Emily H. Ho, David V. Budescu, Mandeep K. Dhami, & David R. Mandel 6. Moving citizens online: Using salience and message framing to motivate behavior change, Noah Castelo, Elizabeth Hardy, Julian House, Nina Mazar, Claire Tsai, & Min Zhao 7. Blinding prosecutors to defendants’ race: A policy proposal to reduce unconscious bias in the criminal justice system, Sunita Sah, Christopher T. Robertson, & Shima B. Baughman 8. The White House social and behavioral sciences team: Lessons Learned from Year One, William J. Congdon & Maya Shankar