An Analysis of San Diego County and San Diego City

I am taking an in-depth look into San Diego County's racial/ethnic demographics and median household income. My goal is to analyze and interpret the relationship between median household income and racial/ethnic demographics within the county to determine if there is any income disparity between races/ethnicities. In addition, I will be taking a closer look at San Diego City and analyze racial/ethnic demographics, segregation, and income differences. I will be using the 5-year American Community Survey data for 2018-2014 to study my research question. As well as utilizing R Studio to conduct quantitative and spatial analysis.

I chose this topic because San Diego City is my hometown, and growing up I saw the drastic differences in quality of life, educational opportunities, and neighborhood upkeep depending on the neighborhood you lived in. My neighborhood, Barrio Logan, has the highest population of Hispanics in San Diego, but also the lowest median household income. I grew up seeing the stark differences between my neighborhood and the wealthier, better quality areas that were just 10 minutes away from my house. I realized as I grew older that with these more prosperous neighborhoods came racial differences in their demographics. I wondered why I never saw any White people or other Asians in my neighborhood, but they were so abundant in the neighborhoods with well-kept parks and big houses. I wondered why the people around me lived hard, poverty-filled lives and why us brown and black people were sequestered away in areas of high poverty.

This research topic is important and worth studying because it peels away San Diego’s beautiful and prosperous mask to reveal the deep racial divides behind it. It calls to attention the need for more resources and help in communities like mine where majority of our residents are immigrants or minorities. Where children can either get an amazing public education or lackluster one based on where they live. Where neighborhoods where people are struggling to make ends meet can be a few miles away from luxurious city condos and beachfront houses. This topic is meant to understand the world that I grew up in in a more spatially analytical and critical view.

• Median household income in San Diego County & City
• Percent and number White in San Diego County & City
• Percent and number Black in San Diego County & City
• Percent and number Asian in San Diego County & City
• Percent and number Hispanic in San Diego County & City
• Percent and number non-White in San Diego City
• Entropy Score for San Diego County & City

To analyze segregation in San Diego City, I will be utilizing three different analysis methods: Dissimilarity Index, Interaction Index, and Multigroup Entropy Index.

A Dissimilarity Index analyzes what percentage a specific race will have to move to a certain neighborhood to reach uniformity of all races.

An Interaction Index analyzes the level interaction (how often an encounter happens) between two races in a neighborhood.

A Multigroup Entropy Index, or an Entropy Score, is a multi group measure of segregation. The Entropy index goes from 0 to 1, with 0 indicating complete integration and 1 indicating complete segregation.

Legend

• BWD = Black/White Dissimilarity
• AWD = Asian/White Dissimilarity
• NWWD = Non-White/White Dissimilarity

According to the Dissimilarity Index analysis, for San Diego City, you would need 57% of Blacks, 47% of Asians, 55% of Hispanics, and 45% of non-Whites to move in to achieve total racial uniformity in the city.

These somewhat high percentages show that there is a proportion of minorities missing in San Diego City to make it more diverse.

Legend

• BWI = Black/White Interaction
• AWI = Asian/White Interaction
• HWI = Hispanic/White Interaction

The Interaction Index analysis for San Diego City shows the chance of a person from X ethnicity to interact with a person who is White in San Diego City.

According to the calculations, the chance of an Asian person interacting with a White person is about 38%, and the chance of a Hispanic person interacting with a White person is about 27%, but a chance of a Black person interacting with a white person in this same tract is 29%.

This means that 38 of every 100 people an Asian person meets in his or her neighborhood will be White, while 27 out of every 100 people a Hispanic person meets will be White. But, this also means that 38 out of every 100 people a Black person meets in this same neighborhood will be White.

These chances indicate major segregation in San Diego. Likewise, this analysis also shows that there is higher segregation between Black and White people and Hispanic and White people than Asian and White people within San Diego City.

I calculated the Multigroup Entropy Index on R Studio and created a variable for it. But to better visualize the data, I created a map to show the different Entropy Scores for San Diego County and San Diego City.

A formula to calculate the maximum entropy score is log(5) because we calculated 5 racial groups (White, Black, Hispanic, Asian, and Other). This score is 1.609438. The higher the Entropy Score the greater the diversity.

This map shows that the areas with the highest levels of diversity are in some areas in the North (Mira Mesa area), central San Diego (mainly in the Clairmont Mesa and Sierra Mesa areas), and in the North East (Skyline-Paradise Hills area, North Park area, and some parts of Otay Mesa).

Areas with the lowest levels of diversity are found mostly along the coast of the City. Areas such as Downtown San Diego, Barrio Logan, La Jolla, and even as far as Fairbanks are included.

Most of the areas with low diversity are neighborhoods with either high percentage of Whites or Hispanics.

This map of San Diego County shows that the areas with the highest diversity is located mainly in Southern San Diego. These areas include San Diego City, El Cajon area, National City area, Torrey Pines area, Poway area, the Vista City Area.

Areas with the lowest levels of diversity can be found in central San Diego and the central coastal areas. These locations include San Diego City (Downtown area), La Jolla, and Carlsbad. As well as the areas near Julian in the center.

Interestingly enough, these areas of low diversity along the coast have high concentrations of White percentages or Hispanic percentages, while the area in the center is a location of many Native American Reservations.

Based on all the data collected and the analysis conducted, it appears that San Diego County has evidence of a racial relationship to median household income in terms of White and Hispanic demographics. There tends to be higher levels of median household income in neighborhoods with higher concentrations of Whites, while there are lower levels of median household income in areas with higher concentrations of Hispanics.

Likewise, analysis done on segregation through dissimilarity and interaction shows that there is high segregation in San Diego City between minorities and White populations. The data shows that minorities and Whites tend to be separated from each other spatially within the city.

Similarly, this lack of diversity can be seen in many parts of San Diego County, most especially in areas with either high percentages of Whites or high percentages of Hispanics. This data also coincides with the spread of median household income, where areas of mostly White populations tend to have higher median household incomes and areas with higher Hispanic populations have lower median household incomes.

However, although much of the data may show low evidence for Black and Asian minorities in terms of median household income and strong evidence of segregation in San Diego City, this data is skewed because in general San Diego has higher proportions of Hispanic and White populations than Asian and Black. This can be seen in the graphs below where number of Whites and Hispanics are much larger and widespread than number of Blacks and Asians which are skewed to the right. This means that there is a lower population count for Blacks and Asians than Hispanics and Whites in San Diego City. The low population count for these minorities must be taken into consideration when analyzing the data.

Overall, this study has further strengthened the reality I saw growing up in San Diego. It has illustrated the injustice and inequality I grew up seeing in my little neighborhood, Barrio Logan. My neighborhood, and many of the areas around it were hotspots for minority and immigrant households, and the location of some of the poorest families within San Diego County. Through this study, I realize that although San Diego's beauty, hot tourist spots and wealth is famous, behind it all is a story of racial divides and need. One I hope to see change for the better in the future.

Below is a link to the RMarkdown sheet I created to conduct this study:

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