Mapping Inequality: Redlining in New Deal America is a project that aims both to make information about the work of the HOLC more accessible and to keep an active discourse and awareness of the ways in which it was problematic and has historically been a source of both prosperity and pain. The Home Owners’ Loan Corporation was a corporation sponsored by the American government in 1933 that is credited with both helping to save the housing sector and simultaneously with strengthening the foundations by which racial segregation occurs. Specifically, it analyzed residential neighborhoods’ “mortgage security”, grading their quality as loan recipients and thereby encouraging responsible mortgage lenders to choose qualified clients carefully. Grades were based on “quality of housing, the recent history of sale and rent values, and, crucially, the racial and ethnic identity and class of residents” (quote from the project introduction page; see more information about the program on the page for Mapping Inequality). Because the grading system discouraged the provision of loans to certain racial and class groups, it contributed to and led to the coining of the term “redlining”: the restriction of mortgage options for certain demographics and areas that leads to an inability for some populations to be homeowners.
If you would like to see information regarding project purpose or its sources (also detailed below), you can find that on their Introduction page. Information about the project creators and methods is available on their About page. If you are looking for the data and visuals, Downloads & Data alphabetically provides all available data by city, using JPEGs, JSONs, and other file types that are manually downloadable for convenience. GitHub links provide further content for an interested user, making the project itself very accessible. You can even search for a specific city — the content presentation is quite straightforward and user friendly.
The project’s sources are separated into several categories: information about housing and appraisal; modern and historical studies of HOLC, segregation, and home finance; historical community studies featuring analysis of HOLC; and sociological racial discrimination and segregation studies. It allows access to maps and scans of the cities the HOLC graded, plus descriptions of each community. This information was compiled by teams working from multiple universities, who collected HOLC information, mapped it, and transcribed it for use on the site. Based on the site’s information and provided content, it seems that Mapping Inequality hopes to make HOLC’s work and information about the HOLC more widely available and accessible; at the same time, the context it provides offers a two-sided description of the HOLC as both an important part of housing in the United States and also in part racially driven and racially limiting. Please reference their About page for information about methods, which they state include the following: “identification and digitization of historical maps and Area Descriptions from the National Archives, crowdsourcing and transcribing of the Area Descriptions, development of a NYPL Scribe-enhanced crowdsourcing platform, georeferencing of historical maps, design and testing of database models, sand developing of a Jupyter Notebook for data cleaning of transcribed Area Descriptions.”
Given its goal of increasing the accessibility of HOLC content, I would argue that this project has a wide intended demographic. That includes you! If you are interested in the hard work of the Mapping Inequality project, please visit their website, linked twice in this blog post and via the image of Decatur above.
Further questions: What other ways might data be constructed and presented for HOLC? What new data might be valuable to add and implement? Personally, I think that it would be interesting to see a comparison of historical data with modern neighborhoods in terms of percent of community members who are now homeowners or something. The effects of redlining could then be further demonstrated quantitatively.
Please note: All quotes have been linked to pages from which the quotes are taken and are not the original work of the blog post writer.