Reflective blog post, Week 2: Mapping Inequality

Mapping Inequality

Mapping Inequality is the third version of a Digital Humanities project. This project examines data collected from 1935 to 1945 that graded the United States based on what is deemed a hazardous or non-hazardous location for banks and other lenders to invest in. From this, I became interested in Mapping Inequality‘s portrayal of the United States and what, in particular, made a location diminish in value.

Sources

While collecting the data, the maps and area descriptions are from the City Survey Files at the National Archives. However, while the project doesn’t explain why, there were three areas where Mapping Inequality took outside sources: San Antonio, Portland, and Maine. As I was exploring the project, I found it really engaging as this website enabled the public to download the data they collected.

Processes

The services for this project began with the data. The data collected were first organized into race, class, or environmental burden. Then, mapping tools were used to connect the data with different locations. Bar charts were also used to give another visual aid for the grades of the locations. There were also web design aspects in this project, like links to get to other websites.

Presentation

The project is presented in three ways. The first portion is essays with scholarly sources. This section is familiar to traditional humanities, where someone’s work is written. The next portion is filled with only links about redlining and different societal issues. Lastly, the website includes a portion with the United States map that is color-coded based on the grade an area received and organized into race, class, or environmental burden.

Project Goal, Academic Fields That Can Align With This Project, and New Question

I believe the project goal is to educate users about redlining while creating an engaging platform that is easy to explore. Academic fields this project will align with could be Political Science and History. Political Science, due to the redlining aspect and how that has impacted the United States. Additionally, with History, the project goes into the history of race, redlining, and real estate. A question I had while I was exploring this project was whether or not the creators of this project wanted to update the dataset with a newer dataset. This is because I wanted to see whether or not a more current dataset would alter the map and its other works.