Changing The Conversation Together

Posted by Jarrod Valentine on January 18, 2018

I've been looking at voter registration and history information from New York, focusing primarily on Staten Island and a bit of South Brooklyn. The 11th Congressional District is a bit of an outlier in New York politics. It's the only Congressional District to have consistently elected a republican to congress, and as a district it tends to lean republican. It's also been a swing district in many elections, voting for the democratic presidentail candidate in each race since 1992 except in 2016 when they elected Trump by 56 - 44%. This is our target demographic for deep canvassing! And this and this and this is what we're investigating.

The data I've been working with is the publicly available New York State Board of Elections voter file, giving the voter registrationand history for the voters of New York. It is very messy data. I've had to do a lot of cleaning and digging online and asking other people what they think some of the abbreviations and election districts mean. As a Californian, I know virtually nothing about New York politics, so I am definitely learning a lot.

I've been working on segmenting voters by party to find individual swing voters, but this proved to be fruitless because we don't have a record of how people voted, just to which party they are registered and when they voted. My strategy to find these swing voters was to flag each voter as D or R (mostly ignoring other part affiliations) at each election, aggregate, and see if any voters changed party registrations between elections. To my surprise, not a single voter switched from either R to D or vice versa, so it looks like we'll instead be identifying swing voters in aggregate.

Next, I looked at voter turnout according to election district (ED) for each of the 2016, 2012, and 2008 presidential elections, as well as the 2010, 2012, and 2014 midterm congressional elections. The strategy here is to look at the changes in voter turnout between elections by ED to identify which districts' voter turnout varied and, with the aid of some helpful ED maps created by a co-volunteer, to identify which districts had the lowest swing margins to begin focusing canvassing efforts there.