By Kari Williams
As part of the IPUMS mission to democratize data, our user support team strives to answer your questions about the data. Over time, some questions are repeated. This blog post is an extension of an earlier series addressing frequently asked questions. Maybe you’ll learn something. Perhaps you’ll just find the information interesting. Regardless, we hope you enjoy it!
Here’s one of those questions:
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.
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.
IPUMS is excited to announce the winners of its annual IPUMS Research Awards. These awards honor the best-published research and nominated graduate student papers from 2020 that used IPUMS data to advance or deepen our understanding of social and demographic processes.
IPUMS, developed by and housed at the University of Minnesota, is the world’s largest individual-level population database, providing harmonized data on people in the U.S. and around the world to researchers at no cost.
There are six award categories, and each is tied to the following IPUMS projects:
Over 2,500 publications based on IPUMS data appeared in journals, magazines, and newspapers worldwide last year. From these publications and from nominated graduate student papers, the award committees selected the 2020 honorees.
By Jane Lyon Lee, IPUMS International
Last March, when the IPUMS International research team attended the 51st Meeting of the UN Statistical Commission, we were just beginning to hear about the spread of a novel virus. We soon discovered that the Commission meeting would be our last in-person event of the year. Soon after, a pandemic quickly paralyzed our world, including the ever-important census and survey work. We all were called on to seek out and, in some cases, create new paths via which data collection, protection, analysis, and dissemination could continue.
Research, data preparation, story and graphics by Amalea Jubara and Yaxuan Zhang (Minnesota Population Center, Summer Diversity Fellows), mentored by Jonathan Schroeder (IPUMS Research Scientist) and Ying Song (Assistant Professor, Department of Geography, Environment & Society)
Edited by Jonathan Schroeder (IPUMS Research Scientist)
The most spatially precise U.S. census data are block-level tables, summarizing population and housing characteristics for millions of blocks throughout the country. IPUMS NHGIS provides block-level tables for the 1970 to 2010 decennial censuses as well as block boundary files for 1990, 2000 and 2010. This collection is set to grow substantially in the next few years as NHGIS adds new 2020 census block data and as we continue with a major initiative to construct 1980 and 1970 block boundary files. This expansion will open up new possibilities for high-precision spatial analysis across a longer time span.
To demonstrate some of the potential value of this expanding collection, we use NHGIS block data, including some not-yet-released 1980 block boundaries, to explore the recent history of racial segregation and integration in the Black population of the Twin Cities of Minneapolis and St. Paul, Minnesota, from 1980 to 2010. We present the block data in an interactive map along with data on early-20th-century racial covenants and the “redlining” zones of the Home Owners’ Loan Corporation (HOLC), recently published by the Mapping Prejudice and Mapping Inequality projects.
The block-level changes since 1980 show a striking trend toward greater dispersion and integration of Black residents, but segregation persists; several neighborhoods still have uniformly low or high proportions of Black residents. By overlaying racial covenants and HOLC zones with the block data, we can also find cases where the historical discriminatory practices appear to have left a lasting imprint on the distribution of Black residents.
IPUMS Time Use, in partnership with Dr. Teresa Harms of the Centre for Time Use Research, is proud to announce the public release of the 1930-31 USDA College Women Time Use study. These data provide researchers a unique look into the lives of married, college-educated women at the beginning of the Great Depression. The respondents were asked to complete a detailed record of their time use for seven consecutive 24-hour periods (see a sample daily diary below; borrowed with permission from Teresa Harms, CTUR). The women described activities in their own words, listing them consecutively as they occurred throughout the day, with a minimum interval of five minutes. They also recorded the time devoted to various homemaking tasks by other household members and paid help as well as demographic and work status data and information about the household. The data also include the verbatim activity reports and the occupations the women reported at the time of data collection. All data are available via the IPUMS American Heritage Time Use Study (AHTUS) extract system.