Conceptualizing Structural Racism with IPUMS Data

By Solvejg Wastvedt and Yash Singh

A major challenge for researchers studying racism is measuring the consequences of this macro-level phenomenon in people’s everyday lives. For the purposes of this post we define structural racism as a system of racialized advantage and disadvantage underlying and structuring multiple domains of life, including housing, interactions with government, education, the criminal legal system, and more. 1 2 3 4 5 Structural racism does not refer to individual prejudices or discriminatory beliefs. Rather, it is a macro-level phenomenon: a principle upon which structures in our society are built. When researchers study racism as a structural force, its impacts in any one area affect and reinforce impacts in every other area.

The consequences of structural racism for individuals are well-documented; for example, research shows structural racism produces poorer health outcomes for racialized groups. 6 However, research often focuses on a single aspect of structural racism, such as police brutality, and struggles to capture the full impact of this multidimensional phenomenon. Measures used to assess impacts of structural racism typically differ by domain, and while robust research documents these impacts, it can also be difficult to capture the mechanisms through which they occur.

Time — specifically time use — is a type of data that can unite studies of structural racism across domains and offer a glimpse into how this macro-level force acts on individuals.

Time is a form of capital: we only have so much of it, and time spent in one place is not spent elsewhere. For example, an individual living in a segregated neighborhood because of residential discrimination may be required to drive long distances for work or health care. This reduces time available for all other activities, including exercise. The resulting lack of time may lead, in turn, to negative health outcomes. While simply an illustration of one possible pathway linking the macro and micro levels, this example shows how time use data can capture impacts across multiple domains and, ultimately, on daily life.

IPUMS Time Use provides data from the American Time Use Survey (ATUS), a nationally representative U.S. time diary survey. In this post, we highlight measures from the ATUS corresponding to two aspects of structural racism: residential segregation and discrimination in government services. Researchers interested in other aspects can create and select variables from IPUMS ATUS data to match their areas of interest.

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An Age-Based Approach to Disability

By Solvejg Wastvedt and Yash Singh

Disability is dynamic: it evolves over time and interacts with environmental and societal factors. Due to the complex nature of disability, researchers conceptualize and measure disability differently depending on their research question and available data. For instance, an identical condition might evolve differently for a child facing food insecurity compared to one that has stable access to food. Similarly, a physical limitation for a worker in New York City may have a vastly different impact compared to a similar worker in rural Iowa. Disability can be viewed as the relational concept between individuals with physical or mental impairment and the environment.1 2 This complexity makes measuring disability a challenging task. The following post aims to help researchers understand and use disability measurements available in IPUMS data collections.

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Things to Consider when Using the 2020 American Time Use Survey

By Kelsey J. Drotning

Curious about how COVID-19 has affected time in leisure, sleep, work, and family activities in the United States? The 2020 ATUS will provide some clues. Data from the 2020 American Time Use Survey (ATUS) were released by the Bureau of Labor Statistics on July 22, 2021. The data have been harmonized with previous ATUS surveys by the IPUMS team, released on July 30, 2021. The 2020 ATUS provides a window into how daily lives shifted in response to COVID-19 pandemic conditions and the corresponding economic recession via 24-hour time diaries. Potential research topics include, but are not limited to:

• What, where, and with whom people spent their time post-onset compared to pre-onset of the pandemic
• Differences in daily activities by gender, race, ethnicity, nativity, age, parental and marital status, household composition, employment status, education.
• How daily activities, such as work, time with children, school, commuting, socializing and sleep changed as social distancing restrictions were enacted, lifted or maintained across U.S. states

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