The map below shows majority race by area in Red Shirt, 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 Red Shirt racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Red Shirt overall is native american, making up 57.6% of residents. The next most-common racial group is white at 39.1%. There are more native american people in the southeast areas of the city. People who identify as white are most likely to be living in the northwest 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 Red Shirt
Self-Identified Race |
Red Shirt, SD Population |
|---|---|
White |
39.1% |
Hispanic |
2.3% |
Black |
0.0% |
Asian |
0.1% |
Native American |
57.6% |
Other |
0.9% |
Diversity and Diversity Scores for Red Shirt, SD
The map below shows diversity in Red Shirt. 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.
Red Shirt Diversity Score
51.5
More diverse than 85% of US cities
Red Shirt has a diversity score of 51.5: 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. Red Shirt is much more diverse than other US cities, more diverse than 85% of them. Within Red Shirt's proper boundaries, the most diverse area is north Red Shirt, and the least diverse areas are in southeast Red Shirt.
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.