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Open Access Publications from the University of California

UCLA Center for Neighborhood Knowledge

There are 41 publications in this collection, published between 2020 and 2021.
Recent Work (41)

Economic Impact of the COVID-19, Pandemic in Riverside County, Unemployment Insurance Coverage and Regional Inequality

This brief examines the level of unemployment insurance (UI) coverage at the neighborhood (census-tract) level.The analysis looks at the various Riverside County neighborhoods at risk of not receiving UI benefits as well as somedemographics of those neighborhoods. Current policy efforts such as the CARES Act don’t include provisions forall members of society, and as a result, some groups remain ineligible for UI benefits. This is despite the PandemicUnemployment Assistance (PUA) fund, which aimed to cover workers not typically eligible for UI and those who don’tqualify for CARES Act benefits. An even further extension of UI-related benefits, the Heroes Act, has been proposedto extend benefits to workers ineligible for both the CARES Act and PUA fund. Given that certain members of societymay not qualify for government aid programs, it is important to understand both the geographies and demographicsof at-risk groups. Doing so enables policymakers to ensure that vulnerable neighborhoods and communities do notfall outside the boundaries of economic assistance from pandemic-related disruption.

COVID-19 and the Digital Divide in Virtual Learning

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.

Potential Differential Undercount in 2020 Census Redistricting Data: Los Angeles County, California

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.

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