Research Ethics

The Handbook of Social Research Ethics by Donna M. Mertens; Pauline E. Ginsberg The Handbook of Social Research Ethics is the first comprehensive volume of its kind to offer a deeper understanding of the history, theory, philosophy, and#65533;implementation of applied social research ethics. Much of the literature surrounding research ethics originates from or focuses on medical or related health science issues involving human subject research. Yet, the intricacies of social research often raises ethical concerns and issues that are unique to or requiring further contextualization to general research ethics topics, guidelines, and practices. This volume brings together eminent, international scholars across the social and behavioral sciences and education to address those ethical issues that arise in the theory and practice of research within the technologically advancing and culturally complex world in which we live. In addition, ethical dilemmas that arise in the relationship between research practice and social justice issues are examined. The guiding themes used throughout the volume include: Defining and exploring the role(s) of ethics in research from a multi-disciplinary perspective; Making explicit the differing ethical emphases entailed by differing research traditions; Locating ethical concerns within research practice; Elucidating how each of the above influences the relationship between good ethical practice and good research practice. This reference is an invaluable resource to graduate students, professors, researchers, and practitioners of various kinds of social and behavioral research.

Quantifying Research Integrity by Michael Seadle; Gary Marchionini (Editor) Institutions typically treat research integrity violations as black and white, right or wrong. The result is that the wide range of grayscale nuances that separate accident, carelessness and bad practice from deliberate fraud and malpractice often get lost. This lecture looks at how to quantify the grayscale range in three kinds of research integrity violations: plagiarism, data falsification, and image manipulation. Quantification works best with plagiarism, because the essential one-to one matching algorithms are well known and established tools for detecting when matches exist. Questions remain, however, how many matching words of what kind in what location in which discipline constitute reasonable suspicion of fraudulent intent. Different disciplines take different perspectives on quantity and location. Quantification is harder with data falsification, because the original data are often not available, and because experimental replication remains surprisingly difficult. The same is true with image manipulation, where tools exist for detecting certain kinds of manipulations, but where the tools are also easily defeated. This lecture looks at how to prevent violations of research integrity from a pragmatic viewpoint, and at what steps can institutions and publishers take to discourage problems beyond the usual ethical admonitions. There are no simple answers, but two measures can help: the systematic use of detection tools and requiring original data and images. These alone do not suffice, but they represent a start. The scholarly community needs a better awareness of the complexity of research integrity decisions. Only an open and wide-spread international discussion can bring about a consensus on where the boundary lines are and when grayscale problems shade into black. One goal of this work is to move that discussion forward.