Viz: political polarization visualized -- it's real, and it's the right that's moved

These folks are doing great work, and their simple plots are very powerful. 

Polarization is Real (and Asymmetric)

Revised 16 May 2012

Christopher Hare is a PhD student in Political Science at the University of Georgia.

Nolan McCarty is the Susan Dod Brown Professor of Politics and Public Affairs and Chair of the Department of Politics at Princeton University.

Keith T. Poole is Philip H. Alston Distinguished Chair, Professor of Political Science at the University of Georgia and Professor Emeritus at the University of California, San Diego.

Howard Rosenthal is Professor of Politics at New York University and the Roger Williams Straus Professor of Social Sciences, Emeritus, at Princeton University.

The recent outburst of scholarly and popular interest in political polarization has attracted attention to the methods we use to measure this phenomenon. One frequently voiced concern (see a recent column by Sean Trende) is that Congress may not have polarized as we have claimed in publications and blogs stretching as far back as 1984. The concern is that the meaning of ideological (NOMINATE) scores are tied to the legislative and historical context of the roll call votes that are used to estimate them. For example, the content of roll calls votes cast by members of 90th Senate that dealt with the Vietnam War, civil rights, and funding for LBJ’s “Great Society” programs are quite different than those votes cast in the current Senate. Thus, being the most conservative Senator (with a score of 1.0) in 1968 would mean something different than having an identical 1.0 score in 2012.

#more 

Indeed, temporal comparisons should not be made for ideal points generated from static scaling methods. Static methods (like W-NOMINATE) treat each legislative session separately and there is no valid way to compare the scores of legislators from different years. However, we developed a dynamic methodology, DW-NOMINATE (McCarty, Poole and Rosenthal 1997), to allow for over-time comparisons of legislator ideological positions. The key innovation is the use of “bridge” legislators — members of Congress (MCs) who have served in multiple sessions — to compare the positions of legislators who have never served together.

A sports analogy to the overlapping cohorts method is the “common opponents” statistic. If we want to compare two teams who have not played each other, we compare their performances against a common opponent(s). Likewise, MCs who have not served together can be compared with the use of a “bridge” legislator who has served with both. For example, if we know that Sen. George McGovern (D-SD) is more liberal than Sen. Patrick Leahy (D-VT), and that Sen. Leahy is more liberal than Sen. Max Baucus (D-MT), then we can say that Sen. McGovern is more liberal than Sen. Baucus. Though intransitivities may arise cases involving 3 or more sports teams, Poole shows in his 2007 Pub...