Posts Filed "Data"

Political Ideology Scores: Comparing Models

Last summer, I wrote a piece on political ideology in the Washington State Senate, and another on my methodology for computing those ideology scores. In the year since, I’ve sunk deeper into political science twitter. A few days ago, I came across a tweet that said “New update to our state legislative ideology data,” and this piqued my interest. In my initial searches last year, I had trouble finding individual-level ideology data for the Washington State Legislature, but sure enough, Boris Shor and Nolan McCarty have taken on the huge task of pulling together an up-to-date data set of state legislators and ideology scores based on Vote Smart’s Political Courage Test.

I was really thrilled to find this data set, and I wondered: how well do the ideology scores in this data set support/refute my conclusions from analyzing roll call votes? I downloaded their data for Washington State Senators and did some analysis to compare the results to mine.
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Mathing My Way Through Football Season

I don’t know much about sports. I played tennis growing up, I used to “watch” football games in college, and I know that Ty Cobb has the highest career batting average in Major League Baseball (I read it somewhere), but that’s about where my knowledge of sports breaks down. I try not to have a snide attitude about it, I just didn’t really find it very accessible – it was hard for me to make it feel relevant to me.

A couple of years ago, my coworkers started a March Madness pool at the office and I was feeling a little left out. I realized after hearing people going on about free throw percentages and win/loss ratios that there is a lot of data out there about sports, and figured that might be my in – could I use data to win the office March Madness bracket contest? Could I put all those sports fanatics to shame using the powers of computer science and mathematics?!

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Partisanship in Pizzaville: Modeling Legislative Positions

After my last blog post, a few of my friends were curious about how I reduced all those votes down to two dimensions. I did kind of gloss over the details last time, so I figured I’d take a stab at explaining my methodology.

Last time around, I pulled all the roll call votes for the Washington State Senate in 2016, and I made a big matrix of senators and their votes. A matrix with over 25,000 cells is not exactly easy to process, so I reduced the dimensions to two, resulting in this scatterplot showing the partisan divide:

How can you take votes on 402 bills and turn it into a two-dimensional graph? Essentially, we’re converting each senator’s list of 402 votes into two new “features.” Those features are all their votes smushed together to give us new points that fall into a lower dimensional space.

How do we reduce dimensions and figure out which votes to use in our new features? Well the key thing to consider is this: all bills are not created equal.  Some bills (and the votes on those bills) tell us more about a person’s politics than others. Before you read on, consider this: if the senate votes unanimously for (or against) a bill, does that tell us much about the differences between the senators that voted on it?

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Political Birds of a Feather

I’ve been thinking a lot about political divisiveness lately. I suspect I’m not alone in this. Who can say why I might be feeling this way? On top of general brooding, I recently finished David Daley’s book on redistricting and gerrymandering, so I have congressional districts on the brain. I started wondering a bit about our state legislature here in Washington. I know a little about state politics – I like to think I’m a relatively informed voter –  but as I started doing some reading, I realized I didn’t know much about the people in our state legislature. I started to wonder, how different are they on the issues?

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