The map below shows majority race by area in Jobs Corners, 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 Jobs Corners racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Jobs Corners overall is white, making up 95.7% of residents. The next most-common racial group is other at 3.5%. There are more white people in the north areas of the city. People who identify as other are most likely to be living in the south 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 Jobs Corners
Self-Identified Race |
Jobs Corners, PA Population |
|---|---|
White |
95.7% |
Hispanic |
0.3% |
Black |
0.2% |
Asian |
0.2% |
Native American |
0.0% |
Other |
3.5% |
Diversity and Diversity Scores for Jobs Corners, PA
The map below shows diversity in Jobs Corners. 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.
Jobs Corners Diversity Score
8.2
More diverse than 14% of US cities
Jobs Corners has a diversity score of 8.2: 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. Jobs Corners is much less diverse than other US cities, more diverse than 14% of them. Within Jobs Corners's proper boundaries, the most diverse area is south Jobs Corners, and the least diverse areas are in north Jobs Corners.
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.