Project Team Members
Project leader: Dr. James Beebe
Dr. Beebe is Professor of Philosophy, Director of the Experimental Epistemology Research Group, and Member of the Center for Cognitive Science at the University at Buffalo (SUNY). His primary research interests are in epistemology and experimental philosophy. Within epistemology Dr. Beebe has written about skeptical challenges to our pretensions to know a good deal about the world and how best to respond to those challenges. Within experimental philosophy, Dr. Beebe has investigated how moral judgments about people’s actions affect judgments about how much knowledge those people have and whether people think that moral judgments are objectively true and universal or more subjective and culturally variable.
Project co-leader: Dr. Jonathan Matheson
Dr. Matheson is Professor of Philosophy at the University of North Florida. He is a leading expert on the epistemology of disagreement—i.e., on questions that concern the extent to which discovering that another person disagrees with you affects the rationality of your beliefs. He has published a book, The Epistemic Significance of Disagreement (Palgrave), and a number of articles on this topic. He has published articles in Philosophical Studies, Erkenntnis, Episteme, Social Epistemology, TOPOI, and Faith & Philosophy, among others. Dr. Matheson is currently editing a collection of 18 original essays on epistemic autonomy that will be published by Routledge.
Project psychometrician: Dr. Joshua Wilt
Dr. Wilt is Senior Research Associate in the Department of Psychological Sciences at Case Western Reserve University. He is a psychometrician with expertise in scale development and data analysis. Dr. Wilt received his Ph.D. in personality psychology from the Northwestern University, where he studied with William Revelle, one of the leaders in psychometric methods. He has considerable training in and experience with a wide range of psychometric techniques relevant to scale development, including exploratory and confirmatory factor analysis, structural equation modeling, and item response theory. Much of his published empirical work has relied on one or more of these techniques. For example, he has applied these techniques to refine measures of authenticity and meaning, delineating higher-order factors from more narrow facets. He created a novel and highly cited hierarchical measure of Big Five traits that makes nuanced distinctions between psychological (i.e., affective, behavioral, cognitive) components of traits. He is especially interested in using sophisticated statistical analyses in combination with sound conceptual reasoning to increase the likelihood that the resultant measures meet the highest standards of reliability, validity, and generalizability.