Validated names for experimental studies on race and ethnicity

A large and fast-growing number of studies across the social sciences use experiments to better understand the role of race in human interactions, particularly in the American context. Researchers often use names to signal the race of individuals portrayed in these experiments. However, those names might also signal other attributes, such as socioeconomic status (e.g., education and income) and citizenship. If they do, researchers would benefit greatly from pre-tested names with data on perceptions of these attributes; such data would permit researchers to draw correct inferences about the causal effect of race in their experiments. In this paper, we provide the largest dataset of validated name perceptions to date based on three different surveys conducted in the United States. In total, our data include over 44,170 name evaluations from 4,026 respondents for 600 names. In addition to respondent perceptions of race, income, education, and citizenship from names, our data also include respondent characteristics. Our data will be broadly helpful for researchers conducting experiments on the manifold ways in which race shapes American life.

Changes over Time in COVID-19 Vaccination Inequalities in Eight Large U.S. Cities

The authors estimate the associations between community socioeconomic composition and changes in coronavirus disease 2019 (COVID-19) vaccination levels in eight large cities at three time points. In March, communities with high socioeconomic status (SES) had significantly higher vaccination rates than low-SES communities. Between March and April, low-SES communities had significantly lower changes in percentage vaccinated than high-SES communities. Between April and May, this difference was not significant. Thus, the large vaccination gap between communities during restricted vaccine eligibility did not narrow when eligibility opened up. The link between COVID-19 vaccination and community disadvantage may lead to a bifurcated recovery whereby advantaged communities move on from the pandemic more quickly while disadvantaged communities continue to suffer.

COVID-19 Vaccine Rollouts and the Reproduction of Urban Spatial Inequality: Disparities Within Large US Cities in March and April 2021 by Racial/Ethnic and Socioeconomic Composition

Rollouts of COVID-19 vaccines in the USA were opportunities to redress disparities that surfaced during the pandemic. Initial eligibility criteria, however, neglected geographic, racial/ethnic, and socioeconomic considerations. Marginalized populations may have faced barriers to then-scarce vaccines, reinforcing disparities. Inequalities may have subsided as eligibility expanded. Using spatial modeling, we investigate how strongly local vaccination levels were associated with socioeconomic and racial/ethnic composition as authorities first extended vaccine eligibility to all adults. We harmonize administrative, demographic, and geospatial data across postal codes in eight large US cities over 3 weeks in Spring 2021. We find that, although vaccines were free regardless of health insurance coverage, local vaccination levels in March and April were negatively associated with poverty, enrollment in means-tested public health insurance (e.g., Medicaid), and the uninsured population. By April, vaccination levels in Black and Hispanic communities were only beginning to reach those of Asian and White communities in March. Increases in vaccination were smaller in socioeconomically disadvantaged Black and Hispanic communities than in more affluent, Asian, and White communities. Our findings suggest vaccine rollouts contributed to cumulative disadvantage. Populations that were left most vulnerable to COVID-19 benefited least from early expansions in vaccine availability in large US cities.

Enhancing big data in the social sciences with crowdsourcing: Data augmentation practices, techniques, and opportunities

Proponents of big data claim it will fuel a social research revolution, but skeptics challenge its reliability and decontextualization. The largest subset of big data is not designed for social research. Data augmentation–systematic assessment of measurement against known quantities and expansion of extant data with new information–is an important tool to maximize such data's validity and research value. Using trained research assistants or specialized algorithms are common approaches to augmentation but may not scale to big data or appease skeptics. We consider a third alternative: data augmentation with online crowdsourcing. Three empirical cases illustrate strengths and limitations of crowdsourcing, using Amazon Mechanical Turk to verify automated coding, link online databases, and gather data on online resources. Using these, we develop best practice guidelines and a reporting template to enhance reproducibility. Carefully designed, correctly applied, and rigorously documented crowdsourcing help address concerns about big data's usefulness for social research.

Searching for a Roommate: A Correspondence Audit Examining Racial/Ethnic and Immigrant Discrimination among Millennials

Survey research finds that millennials have less prejudiced views of racial/ethnic minorities than other generations, leading some to label millennials as postracial. However, attitudinal survey research may be subject to social desirability bias because it documents statements or beliefs instead of actions. Moreover, most audit studies focus on people who make hiring decisions or own rental property and are therefore often older than millennials. This study uses a correspondence audit to investigate discrimination among millennials via "roommate wanted" advertisements. We sent over 4,000 emails and found a tiered pattern of discrimination against Asian (Indian and Chinese), Hispanic, and Black room-seekers. However, whether Asian and Hispanic room-seekers face significant discrimination varies based on whether they use predominantly White first names or traditional first names. Our findings shed light on the future of our racial system, expand our knowledge of discrimination beyond the traditional Black/White binary, and illustrate the persistence of anti-Blackness.

Job Characteristics, Job Preferences, and Physical and Mental Health in Later Life

Existing research linking SES with work primarily focuses on the precursors (educational attainment) and outcomes (income) of work, rather than asking how diverse facets of work influence health. Using four waves of data from the Wisconsin Longitudinal Study, we evaluate whether multiple measures of respondent job characteristics, respondent preferences for those characteristics, and their interaction substantially improve the fit of sociological models of men's and women's physical and mental health at midlife and old age compared to traditional models using educational attainment, parental SES, and income. We find that non-wage job characteristics predict men's and women's physical and mental health over the lifecourse, although we find little evidence that the degree to which one's job accords with one's job preferences matters for health. These findings expand what we know about how work matters for health, demonstrating how the manner and condition under which one works has lasting impacts on wellbeing.

Variations in Student Mental Health and Treatment Utilization Across US Colleges and Universities

OBJECTIVE

On US college campuses, mental health problems are highly prevalent, appear to be increasing, and are often untreated. Concerns about student mental health are well documented, but little is known about potential variations across the diversity of institutions of higher education.

PARTICIPANTS

Participants were 43,210 undergraduates at 72 campuses that participated in the Healthy Minds Study from 2007 to 2013.

METHODS

Multivariable logistic regressions focus on associations between institutional characteristics and student mental health and treatment utilization.

RESULTS

The following institutional characteristics are associated with worse mental health: doctoral-granting, public, large enrollment, nonresidential, less competitive, and lower graduation rates. Among students with apparent mental health problems, treatment utilization is higher at doctorate-granting institutions, baccalaureate colleges, institutions with small enrollments, and schools with strong residential systems.

CONCLUSIONS

Although high rates of mental health problems and low treatment utilization are major concerns at all types of institutions of higher education, substantial variation occurs across campuses.

School accountability and the black-white test score gap

Since at least the 1960s, researchers have closely examined the respective roles of families, neighborhoods, and schools in producing the black-white achievement gap. Although many researchers minimize the ability of schools to eliminate achievement gaps, the No Child Left Behind Act (NCLB) increased pressure on schools to do so by 2014. In this study, we examine the effects of NCLB's subgroup-specific accountability pressure on changes in black-white math and reading test score gaps using a school-level panel dataset on all North Carolina public elementary and middle schools between 2001 and 2009. Using difference-in-difference models with school fixed effects, we find that accountability pressure reduces black-white achievement gaps by raising mean black achievement without harming mean white achievement. We find no differential effects of accountability pressure based on the racial composition of schools, but schools with more affluent populations are the most successful at reducing the black-white math achievement gap. Thus, our findings suggest that school-based interventions have the potential to close test score gaps, but differences in school composition and resources play a significant role in the ability of schools to reduce racial inequality.

The influence of habitus in the relationship between cultural capital and academic achievement

Scholars routinely use cultural capital theory in an effort to explain class differences in academic success but often overlook the key concept of habitus. Rich, longstanding debates within the literature suggest the need for a closer examination of the individual effects of cultural capital and habitus. Drawing upon the writings of Pierre Bourdieu, I use a longitudinal dataset to examine the effects of multiple operationalizations of cultural capital on academic achievement and the mediating effects of habitus. Using first difference models to control for time-invariant unobserved characteristics, I find that typical operationalizations of cultural capital (i.e. high-arts participation and reading habits) have positive effects on GPA that are completely mediated through habitus. These results stress the importance of habitus in the relationship between cultural capital and academic achievement for disadvantaged youth.