29 November 2006
One of my current research interests is the application of a potential outcomes framework of causation to perceptions of what lawyers call “immutable characteristics" like race, gender, or national origin. In that vein, I’d like to pay tribute to one of the early greats in the area of quantitative analysis of race in the legal setting: the so-called “Baldus Study” of the role of race in imposition of the death penalty in Georgia. The Study authors, David Baldus, George C. Woodworth, and Charles A. Pulaski, Jr,, gathered data on over 1000 Georgia homicides from 1973-1979. Although the Study attempted to tackle a variety of questions, the most publicized was whether recent reforms to Georgia’s sentencing process (enacted in response to the Supreme Court’s decision in Furman v. Georgia) had succeeded in removing the relevance of race in the state’s capital sentencing system. The Study’s primary conclusion on this point was that the race of the victim, but not the race of the defendant, played a significant role in deciding whether death was imposed.
The Study was highly publicized, and it led to its own Supreme Court case. In McCleskey v. Kemp, four justices thought that the conclusions of the Baldus Study were sufficient to render Georgia’s capital sentencing system unconstitutional. Five justices disagreed; they thought that the capital defendant in the case had to show that race had played a role in HIS trial, not that race generally played a role in the set capital trials.
More on the Baldus Study in my next post.
This week the Applied Statistics Workshop will present a talk by Alan Zaslavsky, Professor of Health Care Policy (Statistics) in the Department of Health Care Policy at Harvard Medical School. Dr. Zaslavsky's statistical research interests include surveys, census methodology, small area estimation, official statistics, missing data, hierarchical modeling, and Bayesian methodology. His research topics in health care policy center on measurement of the quality of care provided by health plans through consumer assessments and clinical and administrative data. Among his current major projects are (1) the Consumer Assessments of Healthcare Providers and Systems (CAHPS) survey implementation for the Medicare system, (2) methodology for surveys in psychiatric epidemiology, centered on validation of the CIDI-A (adolescent) survey in the National Comorbidity Study-Adolescent, and (3) studies on determinants of quality of care for cancer, including both the Statistical Coordinating Center and a research site for the NCI-funded CanCORS (Cancer Consortium for Outcomes Research and Surveillance) study. Other research interests include measurement of disparities in health care, and privacy and confidentiality for health care data.
He is a member of the Committee on National Statistics (CNSTAT) of the National Academy of Sciences and has served on CNSTAT panels on census methodology, small area estimation and race/ethnicity measurement, as well as the Committee on the National Quality Report on Health Care Delivery of the Institute of Medicine.
Dr. Zaslavsky received his A.B. degree at Harvard College, his M.S. at Northeastern University, and his Ph.D. at the Massachusetts Institute of Technology. He is a Fellow of the American Statistical Association.
Professor Zaslavsky will present a talk entitled "Modeling the covariance structure of random coefficients to characterize the quality variation in health plans." The presentation will be at noon on Wednesday, November 29th, in Room N354, CGIS North, 1737 Cambridge St. Lunch will be provided.