The map below shows majority race by area in Whitehorse, 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 Whitehorse racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Whitehorse overall is native american, making up 95.0% of residents. The next most-common racial group is other at 1.9%. There are more native american people in the southwest areas of the city. People who identify as other are most likely to be living in the east 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 Whitehorse
Self-Identified Race |
Whitehorse, NM Population |
|---|---|
White |
1.9% |
Hispanic |
1.2% |
Black |
0.0% |
Asian |
0.0% |
Native American |
95.0% |
Other |
1.9% |
Diversity and Diversity Scores for Whitehorse, NM
The map below shows diversity in Whitehorse. 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.
Whitehorse Diversity Score
9.7
More diverse than 18% of US cities
Whitehorse has a diversity score of 9.7: 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. Whitehorse is much less diverse than other US cities, more diverse than 18% of them. Within Whitehorse's proper boundaries, the most diverse area is east Whitehorse, and the least diverse areas are in southwest Whitehorse.
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.