Concentrated Disadvantage, the Geography of Power, and the Spatial Distribution of Nonprofit Human Service Organizations
Methodology: The study uses a 2011 census of 501(c) (3) nonprofit human services in Los Angeles County drawn from the National Center for Charitable Statistics Business Master Files. It includes student services, health and rehabilitative programs, mental health, crime control and prevention, abuse prevention, employment, food and nutrition, housing, youth development, human services, and civil rights programs. ArcGIS was used to geocode the organizations to their respective census tracts. The dependent variable is nonprofit density, operationalized as the number of nonprofit human service organizations per 10,000 persons in the census tract. Census data from the American Community Survey 5-year estimates and voting data from the Harvard Election Results Archive Dataverse were used to construct the independent variables. Ordinary least squares (OLS) regression was used to test the hypotheses.
Results: While the analysis provides contingent support that poverty increases the density of nonprofits, results indicate that nonprofit density is negatively related to poor neighborhoods of concentrated disadvantage and positively related to political advantages such as electoral power and collective efficacy. In addition, the analysis suggests that the negative association between concentrated disadvantage and nonprofit density can be attributed, in part, to lack of electoral power.
Conclusions and implications: The findings suggest that the nonprofit sector does not simply respond to neighborhood need by providing more service organizations. Although the sector seems to respond to some poverty neighborhoods with more services, nonprofits are scarce in the most severely disadvantaged and politically marginalized poor neighborhoods. The analysis raises the possibility that extra-local funders contribute to these disparities by channeling funding away from the most disadvantaged neighborhoods.