Race, Diversity, and Ethnicity in Cox, Oakland, CA

The map below shows majority race by area in Cox, 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 Cox racial diversity and diversity scores. Click here to scroll to diversity data.

Cox, Oakland, CA map of race and ethnicity
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White
Hispanic
Black
Asian
Multiple/Other
WhiteHispanicBlackAsianMultiple/Other
Majority race by area

The majority race in Cox overall is hispanic, making up 71.7% of residents. The next most-common racial group is black at 21.3%. There are more hispanic people in the north areas of the neighborhood. People who identify as black are most likely to be living in the northeast 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 Cox
Race
Cox, Oakland, CA Population
White
2.8%
Hispanic
71.7%
Black
21.3%
Asian
2.3%
Native American
0.1%
Other
1.8%
 

Racial Distribution Key

White
Hispanic
Black
Asian
Native American
Other
 
Self-Identified Race
Cox, Oakland, CA Population
White
2.8%
Hispanic
71.7%
Black
21.3%
Asian
2.3%
Native American
0.1%
Other
1.8%
   

Diversity and Diversity Scores for Cox, Oakland, CA

The map below shows diversity in Cox. 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 neighborhood would both be considered lacking diversity.

Cox, Oakland, CA map of race and ethnicity
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Diversity Score

Diverse
Moderately diverse
No diversity
 

Cox Diversity Score

32

With a diversity score of 32 out of 100, Cox is less diverse than other US neighborhoods. The most diverse area within Cox's proper boundaries is to the northeast of the neighborhood. The least diverse areas are located in the north parts of Cox.

Data Sources: U.S. Census, proprietary data mapping and analysis. Special thanks to the University of Virginia.

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