The map below shows majority race by area in Girdletree, as self-identified on the US census. Darker shades indicate a larger racial majority in that neighborhood. This page also contains data and maps on Girdletree racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Girdletree overall is white, making up 72.9% of residents. The next most-common racial group is black at 25.8%. There are more white people in the central areas of the city. People who identify as black are most likely to be living in the southwest places. The data below shows how many people identify themselves as each of the following races, which most Americans base on their family's national origin:
Race in Girdletree
Self-Identified Race |
Girdletree, MD Population |
|---|---|
White |
72.9% |
Hispanic |
0.0% |
Black |
25.8% |
Asian |
0.0% |
Native American |
0.0% |
Other |
1.3% |
Diversity and Diversity Scores for Girdletree, MD
The map below shows diversity in Girdletree. Areas in green are more diverse, while areas in red are much less diverse. Diversity, in this case, means a mixture of people with different race and ethnicity living close to one another. For example, all-black and all-white areas in the city would both be considered lacking diversity.
Girdletree Diversity Score
40.2
More diverse than 73% of US cities
Girdletree has a diversity score of 40.2: the chance, in percent, that two residents picked at random belong to different racial or ethnic groups, from ACS race counts. A place where everyone shares one group scores 0, and an even mix of the six groups in the chart above scores the maximum, 83.3. Girdletree is more diverse than other US cities, more diverse than 73% of them. Within Girdletree's proper boundaries, the most diverse area is northwest Girdletree, and the least diverse areas are in central Girdletree.
Source: BestNeighborhood calculations from the U.S. Census Bureau, American Community Survey (ACS) 2020-2024 5-year estimates (race and Hispanic origin); proprietary data mapping and analysis. Special thanks to the University of Virginia.