Below we use Optimal Classification (OC) in R to plot the Senate’s vote to approve the Keystone pipeline (which failed, by a 56-42 margin, to reach the required 3/5 supermajority threshold), and the House’s vote on House Majority Leader Eric Cantor’s (R-VA) JOBS (Jumpstart Our Business Startupts) Act, which passed by a 390-23 margin.
Both votes divide Democratic members: 11 moderate Senate Democrats and 23 liberal House Democrats broke from the majority of the party in these votes. Consequently, these votes are good examples of the utility of the spatial (geometric) model of choice in modeling roll call voting behavior. OC performs well on both votes, drawing a vertical cutting line to divide members of Congress by their first dimension (x-axis) location (which represents the standard liberal-conservative scale). Indeed, this makes sense: both proposals involved questions of the desired extent of government intervention in the economy.
In the Senate’s Keystone vote, the cutting line runs through the moderate wing of the Democratic caucus; while in the House’s JOBS Act vote, the cutting line divides the most liberal bloc of House Democrats from the remainder of the party. The major outlier in the Senate vote was Senator Ben Nelson (D-NE), who voted “Nay” but was classified as a “Yea” vote (though in this case ideological factors were complicated by local concerns about how the routing of the Keystone XL pipeline through Nebraska).