Providing an introductory overview of the process of social research, and including classic readings in research methods that all students and researchers should be familiar with, this text offers a comprehensive introduction to key areas of quantitative and qualitative research.
Doing Performative Social Science: Creativity in Doing Research and Reaching Communities focuses, as the title suggests, on the actual act of doing research and creating research outputs through a number of creative and arts-led approaches. Performative Social Science (PSS) embraces the use of tools from the arts (e.g., photography, dance, drama, filmmaking, poetry, fiction, etc.) by expanding—even replacing—more traditional methods of research and diffusion of academic efforts. Ideally, it can include forming collaborations with artists themselves and creating a professional research, learning and/or dissemination experience. These efforts then include the wider community that has a meaningful investment in their projects and their outputs and outcomes. In this insightful volume, Kip Jones brings together a wide range of examples of how contributing authors from diverse disciplines have used the arts-led principles of PSS and its philosophy based in relational aesthetics in real-world projects. The chapters outline the methods and theory bases underlying creative approaches; show the aesthetic and relational constructs of research through these approaches; and show the real and meaningful community engagement that can result from projects such as these. This book will be of interest to all scholars of qualitative and arts-led research in the social sciences, communication and performance studies, as well as artist-scholars and those engaging in community-based research.
Recently, social science has had numerous episodes of influential research that was found invalid when placed under rigorous scrutiny. The growing sense that many published results are potentially erroneous has made those conducting social science research more determined to ensure the underlying research is sound. Transparent and Reproducible Social Science Research is the first book to summarize and synthesize new approaches to combat false positives and non-reproducible findings in social science research, document the underlying problems in research practices, and teach a new generation of students and scholars how to overcome them. Understanding that social science research has real consequences for individuals when used by professionals in public policy, health, law enforcement, and other fields, the book crystallizes new insights, practices, and methods that help ensure greater research transparency, openness, and reproducibility. Readers are guided through well-known problems and are encouraged to work through new solutions and practices to improve the openness of their research. Created with both experienced and novice researchers in mind, Transparent and Reproducible Social Science Research serves as an indispensable resource for the production of high quality social science research.
This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.
Computational approaches offer exciting opportunities for us to do social science differently. This beginner’s guide discusses a range of computational methods and how to use them to study the problems and questions you want to research. It assumes no knowledge of programming, offering step-by-step guidance for coding in Python and drawing on examples of real data analysis to demonstrate how you can apply each approach in any discipline. The book also: Considers important principles of social scientific computing, including transparency, accountability and reproducibility. Understands the realities of completing research projects and offers advice for dealing with issues such as messy or incomplete data and systematic biases. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed. For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.
Quantitative social science research has been expanding due to the ava- ability of computers and data over the past few decades. Yet the textbooks and supplements for researchers do not adequately highlight the revolution created by the R software [2] and graphics system. R is fast becoming the l- gua franca of quantitative research with some 2000 free specialized packages, where the latest versions can be downloaded in seconds. Many packages such as “car” [1] developed by social scientists are popular among all scientists. An early 2009 article [3] in the New York Times notes that statisticians, engineers and scientists without computer programming skills ?nd R “easy to use.” A common language R can readily promote deeper mutual respect and understanding of unique problems facing quantitative work in various social sciences. Often the solutions developed in one ?eld can be extended and used in many ?elds. This book promotes just such exchange of ideas across many social sciences. Since Springer has played a leadership role in promoting R, we are fortunate to have Springer publish this book. A Conference on Quantitative Social Science Research Using R was held in New York City at the Lincoln Center campus of Fordham University, June 18–19, 2009. This book contains selected papers presented at the conference, representing the “Proceedings” of the conference.
Unlike other athletes, the rock climber tends to disregard established norms of style and technique, doing whatever she needs to do to get to the next foothold. This figure provides an apt analogy for the scholar at the center of this unique book. In Rocking Qualitative Social Science, Ashley Rubin provides an entertaining treatise, corrective vision, and rigorously informative guidebook for qualitative research methods that have long been dismissed in deference to traditional scientific methods. Recognizing the steep challenges facing many, especially junior, social science scholars who struggle to adapt their research models to narrowly defined notions of "right," Rubin argues that properly nourished qualitative research can generate important, creative, and even paradigm-shifting insights. This book is designed to help people conduct good qualitative research, talk about their research, and evaluate other scholars' work. Drawing on her own experiences in research and life, Rubin provides tools for qualitative scholars, synthesizes the best advice, and addresses the ubiquitous problem of anxiety in academia. Ultimately, this book argues that rigorous research can be anything but rigid.
It seems like most of what we read about the academic social sciences in the mainstream media is negative. The field is facing mounting criticism, as canonical studies fail to replicate, questionable research practices abound, and researcher social and political biases come under fire. In response to these criticisms, Matt Grossmann, in How Social Science Got Better, provides a robust defense of the current state of the social sciences. Applying insights from the philosophy, history, and sociology of science and providing new data on research trends and scholarly views, he argues that, far from crisis, social science is undergoing an unparalleled renaissance of ever-broader understanding and application. According to Grossmann, social science research today has never been more relevant, rigorous, or self-reflective because scholars have a much better idea of their blind spots and biases. He highlights how scholars now closely analyze the impact of racial, gender, geographic, methodological, political, and ideological differences on research questions; how the incentives of academia influence our research practices; and how universal human desires to avoid uncomfortable truths and easily solve problems affect our conclusions. Though misaligned incentive structures of course remain, a messy, collective deliberation across the research community has shifted us into an unprecedented age of theoretical diversity, open and connected data, and public scholarship. Grossmann's wide-ranging account of current trends will necessarily force the academy's many critics to rethink their lazy critiques and instead acknowledge the path-breaking advances occurring in the social sciences today.
As data become ′big′, fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of - and control over - how these computing tools and algorithms are implemented. Programming with Python for Social Scientists offers a vital foundation to one of the most popular programming tools in computer science, specifically for social science researchers, assuming no prior coding knowledge. It guides you through the full research process, from question to publication, including: the fundamentals of why and how to do your own programming in social scientific research, questions of ethics and research design, a clear, easy to follow ′how-to′ guide to using Python, with a wide array of applications such as data visualisation, social media data research, social network analysis, and more. Accompanied by numerous code examples, screenshots, sample data sources, this is the textbook for social scientists looking for a complete introduction to programming with Python and incorporating it into their research design and analysis.
Doing a Literature Search provides a practical and comprehensive guide to searching the literature on any topic within the social sciences. The book will enable the reader to search the literature effectively, identifying useful books, articles, statistics and many other sources of information. The text will be an invaluable research tool for postgraduates and researchers across the social sciences.