UCLA Center for Neighborhood Knowledge

This report documents UCLA Center for Neighborhood Knowledge’s development of a statewide database and data/mapping portal that displays census-tract level information related to transportation disparities. The selected indicators are based on the existing literature and previous research on the causes, characteristics, and consequences of transportation inequality. The project covers vehicle ownership, public transit, active transportation, and transportation networks. The information is designed for decision makers, public agencies, and community groups that are working to address systematic disparities in transportation access, including their root causes and outcomes.  

Access the Transportation Disparities data mapping tool here.

With many schools closed and students working remotely amid the COVID-19 pandemic, this report by CNK indicates improved access to computers and the internet during the Fall school term, but confirms a continuing and persistent digital divide, especially for Black, Hispanic and low -income students.

Using data from the U.S. Census Household Pulse Survey, the research shows the rate of limited digital access for households fell from a high of 42 percent amid the panic and chaos of the closure of schools last Spring to about 31 percent this fall.  However, the data also shows that since mid-October the rate of inaccessibility has increased slowly but unmistakably. The researchers are concerned that the divide may worsen amid a surge in COVID-19 infections and resulting restrictions.

This Factsheet summarizes the findings from a comparison of population counts for Los Angeles County from the 2020 data for political redistricting (P.L. 94-171 Redistricting Data or PL94) and the 2015-19 American Community Survey (ACS). The Census Bureau conducts an enumeration of the population every decade and compiles the information to assist local officials to redraw political boundaries in response to population changes to ensure that electoral districts are equal in population size. While the goal for every decennial census is a complete and accurate count, it has never been perfect, both missing some individuals and double counting others.2 One serious problem with miscounting is a differential undercount, where the enumeration systematically undercounts some populations and overcounts other populations. That is, the inaccuracies are not proportionately the same across groups. This problem has profound implications within the redistricting process, essentially disenfranchising those missed by the census and undermining the “one person, one vote” principle. There are also economic consequences because governmental allocation formulas are based on population. Differential undercount is deeply embedded in and shaped by existing structures of inequality. It is, therefore, not surprising that historically low-income persons and people of color are disproportionately missed by the enumeration, thus disproportionately undercounted.