Politics & Polls #142: Normalizing Chaos Featuring Jennifer Rubin

Jun 06 2019
By Sarah M. Binder
Topics Politics
Source Woodrow Wilson School

Many in the media argue that the Trump administration is challenging democratic norms. Are they right or overstating the case? Washington Post columnist Jennifer Rubin joins Sam Wang to discuss the role of the fourth estate, the danger of “normalizing chaos,” and how Rubin transitioned from a passionate Reagan conservative to a never-Trumper who left the GOP.

Rubin’s column covers politics and policy and provides insight into the conservative movement, the Republican and Democratic parties, and threats to Western democracies. She is also a contributor to MSNBC. Previously, Rubin worked at The Weekly Standard and Commentary magazine, and practiced labor law for two decades before becoming a journalist.

Rubin will be visiting the Woodrow Wilson School as part of its Leadership through Mentorship Program Oct. 16-17, 2019.


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.