  ColloquiumMAPSS is proud to announce the inauguration of a new colloquium series in 2005. The series has at least four purposes:
Speaker Bios / Talk Abstracts (as available)
Steve BarleyBio: Dr. Stephen R. Barley is the Charles M. Pigott Professor of Management Science and Engineering and the Co- Director of the Center for Work, Technology and Organization at Stanford's School of Engineering. He holds a Ph.D. in Organization Studies from the Massachusetts Institute of Technology. Barley was a member of the Board of Senior Scholars of the National Center for the Educational Quality of the Workforce and co-chaired National Research Council and the National Academy of Science's committee on the changing occupational structure in the United States. He has written extensively on the impact of new technologies on work, the organization of technical work and organizational culture. Tony BrykBio: Dr. Anthony Bryk is Stanfords Spencer Professor of Education, School of Education, and of Organizational Behavior, Graduate School of Business, and Professor of Sociology (by courtesy). His long-standing interests are in school education, educational reform, and educational statistics. He is known for his work on the Chicago public school system, and particularly for his development, along with Steve Raudenbush, of methods of and software for Hierarchical Linear Modeling (HLM) and generalizations thereof. Erik De CorteBio: Erik De Corte is Professor of Educational Psychology at K.U. Leuven in Belgium and currently a fellow at the Center for Advance Study in Behavioral Science. He is President of the International Academy of Education and a founder of the European Association for Research on Learning and Instruction (EARLI). His research interests include: the learning and teaching of problem solving skills; metacognition and the affective aspects of learning; design and evaluation of learning environments; and the teaching and learning of mathematics. Bradley EfronBio: Prof. Bradley Efron is the Max H. Stein Professor of Humanities and Sciences Professor of Statistics. A member of the National Academy of Sciences, Prof. Efrons research has focused on the intersection of theoretical and applied work in statistics, exploring, for example, the underlying statistical parallels between biostatistics and astrophysics. Creator of the bootstrap, he has been awarded the Ford Prize, MacArthur Prize, and the Wilks Medal for his research work in computer applications in statistics, particularly with techniques known as the bootstrap and the jackknife. He is largely credited with bringing the power of modern computers into statistics. David FreedmanAbstract: I will suggest that experiments-- when feasible-- offer more reliable evidence on causation than observational studies; this is not to gainsay the contribution to knowledge from observation. I will also suggest that experiments should be analyzed as experiments not observational studies. For instance, a simple comparison of rates might be just the right tool. So far as time permits, I will discuss models for experimental data, the intention-to-treat principle, and the effect of treatment on the treated. I have two related papers on the web, plus a handout: http://www.stat.berkeley.edu/~census/oxcause.pdf Bio: David A. Freedman received his B.Sc. degree from McGill and his Ph.D. from Princeton. He is professor of statistics at U.C. Berkeley, and a former chairman of the department. He has been Sloan Professor and Miller Professor, and is now a member of the American Academy of Arts and Sciences. He has written several books, including two widely-used elementary texts, Statistics (with Pisani and Purves, 3rd edition 1997) and Statistical Models (2005), as well as many papers in probability and statistics. He has worked on martingale inequalities, Markov processes, de Finettis theorem, consistency of Bayes estimates, sampling, the bootstrap, procedures for testing and evaluating models, census adjustment, epidemiology, cross-level or "ecological" inference, statistics and the law. In 2003, he received the John J. Carty Award for the Advancement of Science from the National Academy of Sciences. Simon JackmanAbstract: Bayesian Analysis in Social Science Settings What is Bayesian statistical analysis? How does Bayesian
analysis differ from other forms of statistical analysis? Why is the
distinction between Bayesian and non-Bayesian analysis relevant to
statistical work in the social sciences? In this relatively informal
talk, I provide answers to these questions. Via a series of examples
drawn from across the social sciences, I show that a Bayesian approach
offers sensible answers to inferential questions when other approaches
do not or can not. I emphasize the role of advances in computing power,
which has Bio: Prof. Simon Jackman is Associate Professor, Department of Political Science, and, by courtesy, Statistics; Director of Graduate Studies in Political Science; and Director of the Political Science Computational Laboratory. His principal research and teaching interests are Political Methodology and American Politics. He has published important articles and lectured widely on advanced Bayesian methods in econometrics and statistics. A brilliant communicator of technical and theoretical ideas, he was awarded the Deans Award for Distinguished Teaching. J. Scott LongAbstract: Social scientists are often interested in assessing whether the effect of one variable on another is different in different groups of people. Gender, race, political party, country, economic region, experimental/control, and class are but a few examples where group comparisons of the effects of variables on some outcome are of fundamental importance. Extensions of the Chow (1960) test are often computed to compare groups, but this approach confounds the magnitude of the regression coefficients and the error variances in probit and logit models that assume an underlying latent variable, often yielding invalid conclusions. Indeed, Allison (1999) shows that these standard tests confound the magnitude of the regression coefficients and the variance of the error. Allison proposes a test that removes the effect of residual variation, but this test requires auxiliary information that is often unavailable. This lecture will describe a more feasible approach to comparing group differences in logit, probit and other types of regression models. We illustrate how this new method can be used and will describe software that we have developed to implement the approach. Bio: Dr. J. Scott Long is Chancellors Professor, Department of Sociology, Indiana University. He is on the editorial board of Sociological Methodology, and was awarded the 2002 Paul F. Lazarsfeld Memorial Award for Distinguished Contributions to Sociological Methodology. He is well-known for the important advances he has made in regression models for limited and categorical dependent variables. Currently, his research examines the interplay between womens work and family roles and its implications for physical health; human sexuality and sexual risk-taking, in conjunction with the Kinsey Institute; and the small sample behavior of robust (HCCM) standard errors. Helen LonginoBio: Helen Longino, professor of philosophy, previously was a professor of philosophy and of women's studies at the University of Minnesota. Her research interests include philosophy of science, social epistemology, feminist philosophy and the development of a social approach to scientific knowledge. Her books include Science as Social Knowledge (1990) and The Fate of Knowledge (2002). Eric SheppardAbstract: A methodology for evaluating complex
spatial dynamics Over the last three decades, considerable effort has been put into developing methods of analysis for maps: i.e., for spatially distributed data. These include methods for the identification of spatial autocorrelation, and spatial econometrics—methods for rigorous statistical inference in the presence of spatially correlated data and residuals. Methods also exist for extending time series analysis to include spatial lags. Yet these methods are of limited utility for the analysis of the kind of out-of-equilibrium evolutionary theoretical models that are consistent with complexity theory. Such models generally are capable of generating a wide range of possible space-time trajectories, which need to be evaluated in light of a single observed empirical trajectory. In this talk, we will review complexity theory and its applicability in economic geography, summarize the challenges it poses for spatial analysis, and discuss one proposed methodology for addressing these challenges, based in the mathematics of coded dynamics. Bio: Dr. Eric Sheppard is Professor of Geography at the University of Minnesota, currently a Fellow at the Center for Advanced Study in the Behavioral Sciences. Prof. Sheppard is coauthor of The Capitalist Space Economy, a monograph applying radical political economy as an approach to economic geography. His current research interests include: How the geographic nature of society both affects economic change and also requires us to reconsider the theories we use to understand economic systems; contested urban futures in North America and Europe; the impact of information technologies on the geography of globalization; the utility of GIS for assessing environmental (in)justice. Katherine StovelAbstract: We present a framework for simulating labor market matching processes in order to study mechanisms that generate segregation. Empirical evidence reveals that labor markets are often highly segregated with respect to the ascribed attributes of workers. Many occupations are sex-typed, while in heterogeneous societies certain fields are often dominated by specific ethnic groups. Various explanations have been proposed to account for segregation in labor markets. On balance, most of these explanations can be classified as essentially 'supply-side' arguments, emphasizing differences in human capital distributions between groups, or 'demand-side' accounts, based on employer preferences (either in-group or out-group biases). Yet the process of labor market stratification is not merely a matter of the human capital characteristics of workers or the preferences of employers; it also a function of the complex process by which persons are matched with one another, including the way that agents in the market find and evaluate information. In our research we address these oft-overlooked issues by considering two network-related aspects of the matching process explicitly: who knows about jobs, and how employers evaluate referrals. Using an agent-based simulation model, we show how referral hiring combined with network homophily results in acute segregation by ascribed attribute, even in the absence of discriminatory preferences on the part of employers or supply-side human capital differences. Further, we consider how variation in network structure and network dynamics can amplify or mitigate these effects. Bio: Katherine Stovel (A.B Stanford, Political Science; PhD. UNC-Chapel Hill, Sociology) is Associate Professor of Sociology at the University of Washington. While her research spans number of substantive areas--including economic sociology, adolescent health, and quantitative methods--her work is motivated by a general concern with how basic principles of social interaction are expressed in specific historical or cultural contexts, and why these expressions may result in new institutional arrangements or new identities for individuals. Leonard WantchekonAbstract: This paper provides
experimental estimates of the effect of ethnic ties between voters and
candidates on electoral support for nation-building policies. The
estimates are based on voting outcomes in selected non-competitive
districts that were randomly assigned to
"purified" national public goods and redistributive platforms by Bio: Dr. Leonard Wantchekon is Associate Professor of the Wilf Family Department of Politics at New York University. He is founder and director of the Institute for Empirical Research in Political Economy. His research interests include Political Economy, Development, Applied Game Theory and Comparative Politics. He has published in the American Political Science Review, Comparative Political Studies, and the Quarterly Journal of Economics, among others.
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