Los Angeles County is the most populous county in the country, home to over 10 million residents. It is a large, sprawling region with 88 cities, many unincorporated communities, and nearly boundless cultural and linguistic diversity. The patchwork of municipalities includes cities large and small, some of which contract with the County or with other cities to provide services to residents. The County is an especially complex region, and it can be difficult for researchers to assess whether vulnerable communities have equitable access to services. There are many different agencies that collect data within Los Angeles, and neighborhood boundaries can vary depending on the source. Compounding this problem, the City of Los Angeles hasn’t ever demarcated official neighborhood boundaries. As a result, researchers have to determine how to find the data they need while also making it conform to their study area.
The Mapping L.A. project of the Los Angeles Times has become a frequently relied-upon resource for data analysis within the county. Mapping L.A. uses neighborhoods as a unit, which makes it more intuitive than federal census subdivisions, which generally have little to no relationship with the city as experienced by residents. The other significant asset that the Los Angeles Times map provides to users is standardization. By standardizing neighborhood boundaries, the Times has the ability to develop a database that can be used to effectively track policy outcomes in various regions of the city and county. That database can then be used by outside researchers to develop a more fully-realized picture of equity in Los Angeles. The project Million Dollar Hoods, for instance, tracks the incarceration costs incurred by the Los Angeles Sheriff’s Department and the Los Angeles Police Department. Using internal detention logs from LASD and LAPD, and the neighborhood designations supported by Mapping L.A., Million Dollar Hoods maps the number of incarcerated individuals from each neighborhood in the county, as well as the cost of keeping them imprisoned.
The most thorough source of population and demographic data in the U.S. is the federal census, which provides information for every region of the country. On its smallest scale of measurement, the census uses units called blocks and tracts to identify location. However, the boundaries of these units shift over time, and are not necessarily related to the physical or political characteristics that define neighborhoods in the eyes of residents. Sometimes it can therefore be useful for researchers to substitute larger units called Public Use Microdata Areas, or PUMAs, in their analysis. PUMAs generally follow the boundaries for cities, census-designated places and counties, and contain at least 100,000 residents. In 2006, the Community Institute for Policy Heuristics published a study that examined the relationship between the racial and socioeconomic characteristics of neighborhoods in Los Angeles and the availability of emergency medical services. The researchers used data from the 2000 U.S. Census and from the California Office of Statewide Health Planning and Development to analyze the number of healthcare employees in a given subregion based on its population characteristics. The results of their analysis did not find a significant relationship between race or income and the number of healthcare employees in a region, despite that there are fewer hospitals located in minority communities in South Los Angeles. The researchers note that the PUMAs, because they are designed artificially, fail to adequately take into account the characteristics of segregated subregions.
To analyze equity metrics like access to a vehicle and the proportion of residents unable to speak English, USC’s Program for Environmental and Regional Equity uses a combination of census data and informal neighborhood boundaries. The researchers found that residents in the communities of Watts and Willowbrook were twice as likely to live below the poverty line than the average county resident, while their households are also disproportionately likely to lack access to a car. Using the common neighborhood designations poses challenges because the boundaries may not align directly with census data, but it also provides a smaller unit of analysis than a PUMA. In assessing equity outcomes for a vast diverse region like Los Angeles, this neighborhood-centered approach can help researchers to paint a coherent picture of what life is like in disadvantaged communities.