The map below shows majority race by area in Spaulding, 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 Spaulding racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Spaulding overall is white, making up 62.1% of residents. The next most-common racial group is native american at 20.3%. There are more white people in the southeast areas of the city. People who identify as native american are most likely to be living in the central 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 Spaulding
Self-Identified Race |
Spaulding, OK Population |
|---|---|
White |
62.1% |
Hispanic |
8.2% |
Black |
0.9% |
Asian |
2.4% |
Native American |
20.3% |
Other |
6.1% |
Diversity and Diversity Scores for Spaulding, OK
The map below shows diversity in Spaulding. 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.
Spaulding Diversity Score
56.2
More diverse than 91% of US cities
Spaulding has a diversity score of 56.2: 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. Spaulding is much more diverse than other US cities, more diverse than 91% of them. Within Spaulding's proper boundaries, the most diverse area is northwest Spaulding, and the least diverse areas are in southeast Spaulding.
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.