Presentation Title

Comparative Analysis of Concentrated Neighborhood Disadvantage in Ventura and San Diego County, California

Faculty Mentor

Dr. Luis Sanchez, Associate Professor of Sociology

Start Date

23-11-2019 12:30 PM

End Date

23-11-2019 12:45 PM

Location

Markstein 303

Session

oral 3

Type of Presentation

Oral Talk

Subject Area

behavioral_social_sciences

Abstract

In this comparative analysis we examine the phenomenon of concentrated neighborhood disadvantage across Ventura and San Diego County neighborhoods. Poverty can have negative impacts on economic, educational, and health outcomes. We use “concentrated” as not limited to one neighborhood, but the surrounding clusters of disadvantage. We sought to answer the following three research questions:

1. Has overall clustering of relative neighborhood disadvantage decreased, increased, or remained stable in Ventura and San Diego County?

2. Where are concentrations of neighborhood disadvantage located? Has relative neighborhood disadvantage remained persistent or has it emerged in new locations throughout the two counties?

3. Are there differences in the contextual characteristics between “persistent” and “emerging” disadvantaged neighborhoods?

We hypothesized there would exist more emerging disadvantaged neighborhoods in both Ventura and San Diego Counties. To test this, we used census tract level data from 1990 and 2000 U.S. Censuses (standardized to 2010 boundaries), and 2012-2016 American Community Survey (5-year estimates) to examine concentrated neighborhood disadvantage in Ventura and San Diego County. Furthermore, we used two main spatial measures, the global Moran’s I and Local Indicators of Spatial Autocorrelation (LISA) Clusters. The Global Moran’s I is an overall measure of spatial concentration, while LISA clusters determine concentrated levels of disadvantage at the “local” level.

Preliminary findings indicate that concentration of neighborhood disadvantage neighborhoods in Ventura County has remained persistent between 1990 and 2016. This refutes our hypothesis anticipating more emerging disadvantaged neighborhoods, however Ventura County remained persistently disadvantaged. Likewise, we found San Diego County had more persistent than emerging tracts which was also counter to our original hypothesis. Our findings highlight the need for further research into the mechanisms behind spatial distribution of neighborhood disadvantage, and the patterns that emerge. This is especially important to inform policy makers regarding the appropriate distribution of resources for disadvantaged neighborhoods.

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Nov 23rd, 12:30 PM Nov 23rd, 12:45 PM

Comparative Analysis of Concentrated Neighborhood Disadvantage in Ventura and San Diego County, California

Markstein 303

In this comparative analysis we examine the phenomenon of concentrated neighborhood disadvantage across Ventura and San Diego County neighborhoods. Poverty can have negative impacts on economic, educational, and health outcomes. We use “concentrated” as not limited to one neighborhood, but the surrounding clusters of disadvantage. We sought to answer the following three research questions:

1. Has overall clustering of relative neighborhood disadvantage decreased, increased, or remained stable in Ventura and San Diego County?

2. Where are concentrations of neighborhood disadvantage located? Has relative neighborhood disadvantage remained persistent or has it emerged in new locations throughout the two counties?

3. Are there differences in the contextual characteristics between “persistent” and “emerging” disadvantaged neighborhoods?

We hypothesized there would exist more emerging disadvantaged neighborhoods in both Ventura and San Diego Counties. To test this, we used census tract level data from 1990 and 2000 U.S. Censuses (standardized to 2010 boundaries), and 2012-2016 American Community Survey (5-year estimates) to examine concentrated neighborhood disadvantage in Ventura and San Diego County. Furthermore, we used two main spatial measures, the global Moran’s I and Local Indicators of Spatial Autocorrelation (LISA) Clusters. The Global Moran’s I is an overall measure of spatial concentration, while LISA clusters determine concentrated levels of disadvantage at the “local” level.

Preliminary findings indicate that concentration of neighborhood disadvantage neighborhoods in Ventura County has remained persistent between 1990 and 2016. This refutes our hypothesis anticipating more emerging disadvantaged neighborhoods, however Ventura County remained persistently disadvantaged. Likewise, we found San Diego County had more persistent than emerging tracts which was also counter to our original hypothesis. Our findings highlight the need for further research into the mechanisms behind spatial distribution of neighborhood disadvantage, and the patterns that emerge. This is especially important to inform policy makers regarding the appropriate distribution of resources for disadvantaged neighborhoods.