Working with Georgia Watch was one of the highlights of my year.  The team included Brennan and I, as well as Trey Cason and Beth Stephens from Georgia Watch. Georgia Watch, a consumer protection group, wanted to show how title lenders in Georgia were using predatory methods to target the state’s “more vulnerable” population. Trey and Beth wanted to focus on poor areas and military bases and their surrounding areas. The Georgia Watch collaboration with ATLmaps was originally meant to focus on insurance rates, but we switched to title lenders because we felt the data was more readily available. And boy, was there a lot of data! I don’t think anyone on the team was prepared for the amount of title lending locations: over 300.

After compiling a list of all the title lenders, Brennan and I met with Georgia Watch to figure out how to visualize the data in a way that was supportive to their cause. For the purpose and goal of their legislative push, Georgia Watch wanted us to focus on showing how title lenders were populated in areas of high poverty and around military bases. The poverty data was pulled from the national census and we had the information organized by census tract. I never realized how numerous census tracts were; I always thought they were just zip codes. Contrary to my beliefs, census tracts don’t follow city lines. Census tracts are “neighborhood zones” created by the Bureau of Census that contain roughly 2,500 to 8,000 people.   The next task was to map out all of Georgia’s active military bases which shouldn’t have been difficult. However, when it was time to put the bases on the map, we ran into an issue. Military bases can cover large swaths of land, so it doesn’t make sense to map them with just a single pinpoint. This gave our developers the chance to figure out how to create polygons to better represent an area rather than an exact location. Our developing team figured out an effective process and are currently updating the military bases on the map with polygons.

The project took the entirety of the semester, but when all of the data came together it painted a pretty damning picture. Georgia Watch used our findings at a statewide conference in the spring, and later in a published policy paper. Some of my biggest takeaways from this experience include learning how to share workload and responsibilities. I would try and take on all the data scrubbing myself only to realize that I had overwhelmed myself with work or that I didn’t have the skills to finish tasks efficiently. This is when I leaned on Brennan for help. I also learned the great skill of communicating complex data in comprehensive ways. From my initial introduction of ATLmaps and its capabilities to the Georgia Watch team to explaining the census data collection process, I learned how to put something so abstract into words that made sense. This collaboration was a great opportunity to showcase the power of ATLmaps for policy-making and it was a chance for me to develop both technical as well as communication skills.