Cultural capital is influential in determining who continues on to and succeeds in higher education. However, scholars debate whether cultural capital serves to reproduce existing inequalities or provide a path to upward mobility. Most quantitative studies focus on point-in-time correlations between cultural capital measures and educational achievement or attainment. Thus, this work is unclear on how or even if disadvantaged adolescents can significantly increase their stores of cultural capital. One potential way of providing adolescents with an opportunity to gain cultural capital is through ties to adults with high educational attainment. We investigate this topic using unique quasi-experimental longitudinal data on mentoring relationships between adolescents and adults in the Big Brothers/Big Sisters of America program. We find that only mentors with a college degree or greater have positive effects on cultural capital for adolescents. Furthermore, most of the effects of social capital on cultural capital hold only for adolescents with a parent with some college or greater. We question whether cultural capital can truly be an engine of social mobility if adolescents from low-SES households cannot obtain or increase their cultural capital.
Since the 1960s, social scientists, fair housing agencies, and the federal government have conducted hundreds of in-person and correspondence housing audits. Researchers use these covert experiments to make strong causal claims about difficult-to-detect behavior, such as racial, gender, and other types of discrimination. These studies have consistently uncovered discrimination in multiple stages and contexts of the housing exchange process. The housing audit literature is broad and robust, and a number of in-depth reviews already exist. In this chapter, we build on those reviews by focusing attention on emerging areas of inquiry and suggest new avenues of research pursuits. We begin by briefly reviewing the long history of housing audits including in-person HUD audits and correspondence audits of home sales and housing rentals. Next, we discuss three emerging areas of housing audit research – housing choice vouchers, short-term rentals, and roommate searches – and highlight important findings, new innovations, and areas of weakness. Finally, we conclude with a discussion about future directions of housing audits including using experiments to test for ways to reduce discrimination, using additional data to examine the mechanisms of housing discrimination, and designing modified audits to explore discrimination in other stages of housing exchange.
Across how many generations do elders’ educational advantages directly benefit their descendants? For most of the modern history of stratification research, scholars believed it might only be one. Research suggested that any associations between grandparents and earlier generations’ educational attainment and descendants’ educational attainment were entirely mediated through intervening generations. The last decade of stratification research has upended this Markovian assumption. Still, it remains unclear how far back direct intergenerational education effects operate because most inquiries are limited to two or three generations. In this paper, we employ four generations of family data from the Panel Study of Income Dynamics to examine the association of great-grandparents’ educational attainment with their great-grandchildren’s early academic achievement, net of intervening generations’ educational attainments. We find that great-grandparent effects on great-grandchild early academic achievement are non-linear, modest, and entirely accounted for by the educational attainment of intervening generations and great-grandchild demographic characteristics. Thus, for early academic achievement, direct intergenerational advantage transmission is limited to three generations in these data. Examining three potential mechanisms of four-generational models of educational advantage — lifespan overlap, resource dilution, and genetic linkage — finds limited support for lifespan overlap, no support for resource dilution, and limited evidence on the genetic linkage mechanism does not support this hypothesis
Mounting reports in the media suggest that the COVID-19 pandemic has intensified prejudice and discrimination against racial/ethnic minorities, especially Asians. Existing research has focused on discrimination against Asians and is primarily based on self-reported incidents or non-representative samples. We investigate the extent to which COVID-19 has fueled prejudice and discrimination against multiple racial/ethnic minority groups in the United States by examining nationally-representative survey data with an embedded vignette experiment about roommate selection (collected in August 2020; n = 5,000). We find that priming COVID-19 salience has an immediate, statistically significant impact: compared to the control group, respondents in the treatment group exhibited increased prejudice and discriminatory intent against East Asian, South Asian, and Hispanic hypothetical room-seekers. The treatment effect is more pronounced in increasing extreme negative attitudes toward the three minority groups than decreasing extreme positive attitudes toward them. This is partly due to the treatment increasing the proportion of respondents who perceive these minority groups as extremely culturally incompatible (Asians and Hispanics) and extremely irresponsible (Asians). Sociopolitical factors did not moderate the treatment effects on attitudes toward Asians, but prior social contact with Hispanics mitigated prejudices against them. These findings suggest that COVID-19 fueled prejudice and discrimination have not been limited to East Asians but are part of a broader phenomenon that has affected Asians generally and Hispanics as well.
Survey research finds that millennials have less prejudiced views of racial/ethnic minorities than other generations, leading some to label millennials as post-racial. 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.
This study examines the association between 6 higher education institutional-level characteristics (institutional type, enrollment size, sector, housing, admissions selectivity, and graduation rate) and individual endorsed and perceived mental health treatment stigma scores among college students. We use data from the Healthy Minds Study during 2009–2017. The sample for this analysis includes 89,644 students at 105 unique institutions. We find a negative association between individual-level stigma scores and small enrollment institutions, private institutions, highly residential institutions, and institutions with the highest admissions selectivity and highest graduation rates. Moreover, these findings are generally similar across both individual measures of endorsed stigma and perceived stigma. Overall, our findings suggest that institutional environments where interactions are perhaps more frequent and personal (small enrollment institutions and highly residential institutions) are less likely to be associated with individual-level endorsements and perceptions of mental health treatment stigma.
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.
Following Mare’s (2011) presidential address to the Population Association of America, much research has examined the dynamics of intergenerational mobility and socioeconomic inequality. However, this research is starkly divided on the existence of multigenerational effects and pathways. In this article, we examine educational attainment across three generations using the Panel Study of Income Dynamics. We test three key hypothesized mechanisms of grandparent educational advantage transmission that have been documented in international samples: compensation and augmentation, grandparent lifespan, and genetic transmission. To further interrogate how these mechanisms function across social contexts, we also race-stratify all analyses. As a more stringent test, we also test all hypotheses using cousin fixed effects models. We find no evidence in favor of the compensation hypothesis, but do find descriptive support for the augmentation hypothesis, as well as some limited support among whites for college graduation outcomes in cousin fixed effects models. Findings on the lifespan overlap and genetic transmission hypotheses are highly race-stratified. Overall, our findings support the importance of investigating the mechanisms of three-generation processes of educational attainment across contexts and sub-groups.
Researchers have used audit studies to provide causal evidence of racial discrimination for nearly 60 years. Although audits are an excellent methodological tool to investigate the “what,” “where,” and “when” aspects of racial-ethnic discrimination, audits are less appropriate, by themselves, to investigate the “how” and “why” aspects of racial-ethnic discrimination. In this article, I review why audit studies are necessary to study racial-ethnic discrimination, the evidence from audit studies, and their limitations. I then argue that scholars should adopt a multimethod approach to audit studies to move from documenting the existence of racial-ethnic discrimination to examining how and why racial-ethnic discrimination occurs. Adoption of this multimethod approach will result in a deeper understanding of racial-ethnic discrimination with the potential to shape both opinions and policy surrounding discrimination.
Evidence of racial and ethnic discrimination stems mostly from experiments in the U.S., Europe, and elsewhere that use names to signal race/ethnicity. Although recent work has examined individual racial perceptions of names in the U.S., no research has examined how names might convey immigrant generational status – an important signal for discrimination experiments across the world. I conduct a survey experiment that presents respondents with a series of first and last names to examine perceptions of immigrant generational status in the U.S. In total, 1,659 respondents provide information on 56 different names. I find that when presented with both traditional first and last Hispanic, Indian, or Chinese names, respondents most often believe that person was not born in the U.S. When presented with traditional white or Anglo first names combined with Hispanic or Asian last names, respondents most often believe that person was born in the U.S. but their parents were not. Individual names provide some variation within these results and some groups have stronger results than others. These findings have important implications for discrimination experiments in the U.S. and open the door for future research to distinguish between discrimination based on race/ethnicity and discrimination based on immigration status.
This study uses experimental methods to investigate covert racial discrimination in “roommate wanted” ads on Craigslist. Roommate relationships include significant social dimensions, and are an important site through which segregation may be reproduced or broken down, but have received very little attention by researchers. We develop fictitious racially-coded female names and identities for white, black, Hispanic, Chinese, and Indian room-seekers, along with Hispanic, Chinese, and Indian room-seekers with “Americanized” first names. We implement a field experiment and respond to over 1,500 “roommate wanted” advertisements on Craigslist across three metropolitan areas. Our emails express interest in the roommate-wanted ad, and mention that the sender is college-educated and employed full-time. We monitor response rates in the aggregate and within Census tracts of varying racial and economic characteristics. We find severe discrimination against African Americans, Hispanics, and Chinese-origin individuals. Asians with Americanized first names are treated equally to whites, while traditional Indian names and Americanized Latina names face moderate levels of discrimination. Patterns of discrimination by neighborhood race and class characteristics yield better access to upward mobility for Asian Americans than for underrepresented minority group members. Our findings reveal an important social mechanism that constricts integration and opportunity, shed new light on Asians’ and Latinas’ place in the US race system, reveal important interactions of race and presumed nativity, and show the ongoing relevance of race.
Existing research linking socioeconomic status with work focuses primarily 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, the authors 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 with traditional models using educational attainment, parental socioeconomic status, and income. The authors find that nonwage job characteristics predict men’s and women’s physical and mental health over the life course, although there is little evidence that the degree to which one’s job accords with one’s job preferences matters for health. These findings expand what is known about how work matters for health, demonstrating how the manner and condition under which one works has lasting impacts on well-being.
This book offers practical instruction on the use of audit studies in the social sciences. It features essays from sociologists, economists, and other experts who have employed this powerful and flexible tool. Readers will learn how to implement an audit study to examine a variety of questions in their own research. The essays first discuss situations where audit studies are the most effective. These tools allow researchers to make strong causal claims and explore questions that are often difficult to answer with observational data. Audit studies also stand as the single best way to conduct research on discrimination. The authors highlight what these studies have uncovered about labor market processes in the past decade. The next section gives some guidance on how to design an audit study. The essays cover the difficult task of getting a study through an institutional review board, the technical setup of matching procedures, and statistical power and analysis techniques.
The last part focuses on more advanced aspects. Coverage includes understanding context, what variables may signal, and the use of technology. The book concludes with a discussion of challenges and limitations with an eye towards the future of audit studies.
“Field experiments studying and testing for housing and labor market discrimination have, rightly, become the dominant mode of discrimination-related research in economics and sociology. This book brings together a number of interesting and useful perspectives on these field experiments. Many different kinds of readers will find it valuable, ranging from those interested in getting an overview of the evidence, to researchers looking for guidance on the nuts and bolts of conducting these complex experiments.”
David Neumark, Chancellor’s Professor of Economics at the University of California – Irvine
“For decades, researchers have used experimental audit studies to uncover discrimination in a variety of markets. Although this approach has become more popular in recent years, few publications provide detailed information on the design and implementation of the method. This volume provides the first deep examination of the audit method, with details on the practical, political, analytical, and theoretical considerations of this research. Social scientists interested in consuming or contributing to this literature will find this volume immensely useful.”
Devah Pager, Professor of Sociology and Public Policy at Harvard University
An audit study is a specific type of field experiment primarily used to test for discriminatory behavior when survey and interview questions induce social desirability bias. In this chapter, I first review the language and definitions related to audit studies and encourage adoption of a common language. I then discuss why researchers use the audit method as well as when researchers can and should use this method. Next, I give an overview of the history of audit studies, focusing on major developments and changes in the overall body of work. Finally, I discuss the limitations of correspondence audits and provide some thoughts on future directions.
Scholars suggest that public mental health stigma operates at a meso-level and is associated with severity of symptoms, disclosure, self-esteem, and treatment-seeking behavior. However, the operationalization of public stigma nearly always comes from an individual-level generalization of what others believe. Using data from over 60,000 students on 75 U.S. college and university campuses between 2009 and 2015, we contextualize public stigma by creating a school-level measure of students’ individual-level endorsed mental health treatment stigma. We present multilevel logistic regression models for 21 different dependent variables. We find that even after controlling for individual-level stigma scores, school-level stigma is negatively associated with self-reports of suicidal ideation and self-injury, although not associated with screens for depression or anxiety. Moreover, school-level stigma is negatively associated with medication use, counseling and therapy visits, and to a lesser degree, informal support. We suggest that future research should continue to examine the contextual environment of public stigma, while policymakers may be able to implement changes to significantly reduce stigma at this level.
Existing research on support for anti‐poverty programs largely focuses on broad categories of welfare. In this article, we examine variations in support across different public assistance programs. We use an experimental survey design to examine whether support for public assistance is dependent on the type of aid offered. We find that programs that offer benefits in‐kind are more popular than cash transfers. Moreover, food stamps and child‐care subsidies enjoy more support than housing assistance. Open‐ended survey responses show that when evaluating anti‐poverty programs, respondents adopt one of two perspectives: (1) cash assistance is problematic but other forms of assistance are acceptable or (2) any assistance is problematic. By too narrowly focusing on welfare, social scientists run the risk of developing theories and explanations that may not apply to the much larger part of the safety net that is delivered in‐kind.
Researchers increasingly use correspondence audit studies to study racial/ethnic discrimination in employment, housing, and other domains. Although this method provides strong causal evidence of racial/ethnic discrimination, these claims depend on the signal being clearly conveyed through names. Few studies have pretested individual racial and ethnic perceptions of the names used to examine discrimination. The author conducts a survey experiment in which respondents are asked to identify the races or ethnicities they associate with a series of names. Respondents are provided with combinations of Hispanic and Anglo first and last names. Hispanic first names paired with Anglo last names are least likely to be recognized as Hispanic, while all versions of Hispanic first and last names are highly recognized (≥90 percent). The results suggest that researchers must use caution when trying to signal Hispanic ethnicity in experiments, and prior findings from correspondence audits may be biased from poor signals.
Online correspondence audit studies have emerged as the primary method to examine racial discrimination. Although audits use distinctive names to signal race, few studies scientifically examine data regarding the perception of race from names. Different names treated as black or white may be perceived in heterogeneous ways. I conduct a survey experiment that asks respondents to identify the race they associate with a series of names. I alter the first names given to each respondent and inclusion of last names. Names more commonly given by highly educated black mothers (e.g., Jalen and Nia) are less likely to be perceived as black than names given by less educated black mothers (e.g., DaShawn and Tanisha). The results suggest that a large body of social science evidence on racial discrimination operates under a misguided assumption that all black names are alike, and the findings from correspondence audits are likely sensitive to name selection.
Despite common conceptions, evidence on whether No Child Left Behind (NCLB) has had adverse effects for low achieving students is mixed. We hypothesize that the incentive to shift attention away from the lowest achieving students increases with the rigor of state standards. Using panel data from students in North Carolina, we exploit two natural experiments: increases in the rigor of standards in math in 2006 and then again in reading in 2008. We report an increase in test score gaps between low and high achievers and students near grade level. Adverse effects on low achievers are largest in the lowest achieving schools. We discuss the policy implications of our findings given the widespread adoption of more rigorous Common Core Standards.
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 were 43,210 undergraduates at 72 campuses that participated in the Healthy Minds Study from 2007 to 2013. Multivariable logistic regressions focus on associations between institutional characteristics and student mental health and treatment utilization. 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. 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.
Racial inequality in economic outcomes, particularly among the college educated, persists throughout US society. Scholars debate whether this inequality stems from racial differences in human capital (e.g., college selectivity, GPA, college major) or employer discrimination against black job candidates. However, limited measures of human capital and the inherent difficulties in measuring discrimination using observational data make determining the cause of racial differences in labor-market outcomes a difficult endeavor. In this research, I examine employment opportunities for white and black graduates of elite top-ranked universities versus high-ranked but less selective institutions. Using an audit design, I create matched candidate pairs and apply for 1,008 jobs on a national job-search website. I also exploit existing birth-record data in selecting names to control for differences across social class within racialized names. The results show that although a credential from an elite university results in more employer responses for all candidates, black candidates from elite universities only do as well as white candidates from less selective universities. Moreover, race results in a double penalty: When employers respond to black candidates, it is for jobs with lower starting salaries and lower prestige than those of white peers. These racial differences suggest that a bachelor’s degree, even one from an elite institution, cannot fully counteract the importance of race in the labor market. Thus, both discrimination and differences in human capital contribute to racial economic inequality.
This study uses a field experiment to study bias against living with Arab American women, a group whose position in the U.S. race system remains uncertain. We developed fictitious female white and Arab American identities and used the audit method to respond to 560 roommate-wanted advertisements in four metro areas: Los Angeles, New York, Detroit, and Houston. To focus on social—rather than purely economic—biases, all responses identified the sender as college-educated and employed and were written in grammatically correct English. We compare the number of replies received, finding that Arab-origin names receive about 40 percent fewer replies. We then model variation in discrimination rates by proximity to mosques, geographic concentration of mosques, and the percentage of Arabs living in a census tract so as to test ethnic competition theory and the contact hypothesis. In Los Angeles and New York, greater discrimination occurred in neighborhoods with the highest concentration of mosques.
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 introductory chapter to this special issue highlights contemporary scholarship on networks, work, and inequality. We review the last decade of research on this topic, identifying four key areas investigation: (1) networks and hiring, (2) networks and the labor process, (3) networks and outcomes at work, and (4) networks and institutional dynamics. Social networks play an important role in understanding the mechanisms by which and the conditions under which economic inequality is reproduced across gender, race, and social class distinctions. Throughout the review, we point to numerous opportunities for future research to enhance our understanding of these social processes.
The theory of action behind the No Child Left Behind Act of 2001 is that “shining a light” on subgroup performance will increase reading and math test scores for minority and disadvantaged students. Using a panel of all students in Grades 3 through 8 in North Carolina from 2000 to 2008 (N = 1.7 million students in 1,800 schools), the authors estimate double- and triple-differenced models with school fixed effects to examine whether subgroup-specific accountability threats increase high-stakes test scores. These sanctions are found to have positive effects for minority and disadvantaged students. Larger positive effects emerge for the lowest achieving schools rather than schools near the margin of passing. Some evidence of adverse effects is also found for low and high achievers in math, but not in reading, a finding attributed to the combination of increases in the rigor of state standards in math and responses to an accountability metric based on test score status rather than growth. The implications of the findings for the design of educational accountability systems are discussed.
After 25 years of intense scrutiny, social capital remains an important yet highly debated concept in social science research. This research uses data from youth and mentors in several chapters of Big Brothers/Big Sisters to assess the importance of different mentoring relationship characteristics in creating positive outcomes among youths. The literature on social capital suggests that key characteristics are: (1. the amount of time spent between individuals, (2. racial similarity, (3. level of trust, (4. social class difference, and (5. intergenerational closure. I examine the effects of these social capital measures on academic and deviant behavioral outcomes and run models using propensity score weights to address selection bias. The results indicate that both the amount of time spent in a relationship and the level of trust consistently have positive effects for youths. Counter to what some theory suggests, race-matching and closure between parent and mentor have limited effects, and social class difference between individuals has no significant effect on any of the examined outcomes. These findings have important implications for future work on social capital and adolescent relationships in general