Following the long overdue cancellation of the Library of Congress Subject Heading "Illegal alien" many libraries are assessing options for remediating problematic descriptive language in their catalogs. This paper presents a method of evaluating LCSH corresponding to historically marginalized populations—women, African Americans, Indigenous peoples, and LGBTQIA + people—by measuring cooccurrences of LCSH and Library of Congress Classifications (LCC) across a library's collection. Starting with a sample of 468,100 MARC records, data was extracted with Python then organized and graphed with R. The results offer a holistic perspective of descriptive language assigned to these populations and produced data that can help guide collection development and local subject description policies.