Politics & Polls #130: 2020 Prospects
The 2020 election is on the horizon. In this episode, Sam Wang and Julian Zelizer discuss prospects for the 2020 election, analyzing data-based and qualitative factors. The pair is particularly interested in the potential for a Joe Biden candidacy and consider the question of whether Biden would be the best candidate for the Democratic Party.
Wang and Zelizer also consider the implications of such a large Democratic field of candidates and the different characteristics required to run in the primary election as compared to the general election against President Donald Trump.
ABOUT THE HOSTS
Zelizer has been among the pioneers in the revival of American political history. He is the Malcolm Stevenson Forbes, Class of 1941 Professor of History and Public Affairs at Princeton University and a CNN political analyst. He has written more than 900 op-eds, including his popular weekly column for CNN.com and The Atlantic. This year, he is the distinguished senior fellow at the New York Historical Society, where he is writing a biography of Rabbi Abraham Joshua Heschel for Yale University's Jewish Lives Series. He is the author and editor of more than 19 books including, “The Fierce Urgency of Now: Lyndon Johnson, Congress, and the Battle for the Great Society,” the winner of the D.B. Hardeman Prize for the Best Book on Congress. In January 2019, Norton will publish his new book, co-authored with Kevin Kruse, “Fault Lines: A History of the United States Since 1974.” In spring 2020, Penguin Press will publish his other book, “Burning Down the House: Newt Gingrich, The Fall of a Speaker, and the Rise of the New Republican Party.” He has received fellowships from the Brookings Institution, the Guggenheim Foundation, the Russell Sage Foundation and New America.
Wang is a professor at Princeton University, appointed in neuroscience with affiliate appointments in the Program in Law and Public Affairs and the Center for Information Technology Policy. An alumnus of Caltech, where he received a B.S. with honors in physics, he went on to earn a Ph.D. in neuroscience from the Stanford University School of Medicine. He conducted postdoctoral research at Duke University Medical Center and at Bell Labs Lucent Technologies. He has also worked on science and education policy for the U.S. Senate Committee on Labor and Human Resources. He is noted for his application of data analytics and poll aggregation to American politics. He is leading an effort at the Princeton Gerrymandering Project to build a 50-state data resource for legislative-quality citizen redistricting. His work to define a state-level legal theory to limit partisan gerrymandering recently won Common Cause’s Gerrymandering Standard Writing Contest. His neuroscience research concerns how the brain learns from sensory experience in early life, adulthood and autism.