Social Stratification in Higher Education
by Eric Grodsky & Erika Jackson - 2009
Background/Context: Over the past half century, scholars in a variety of fields have contributed to our understanding of the relationship between higher education and social stratification. We review this literature, highlighting complementarities and inconsistencies.
Purpose/Objective/Research Question/Focus of Study: We situate our review of the literature on inequality and higher education in the context of a behavioral model of postsecondary participation that takes into account the actions of both students and institutions.
Conclusions/Recommendations: We recommend that researchers continue to engage in cross-disciplinary dialogues around challenges in postsecondary research and policy, advocate for an increase in the use of experimental designs, and encourage the development of linkages across administrative data sets. We also recommend that future research improve the alignment among behavioral theories, proposed interventions, study design, and analytic techniques.
Many dimensions of both inequality and stratification impact the process of college matriculation, persistence, and degree attainment. In this review, we focus explicitly on social stratification by race/ethnicity and socioeconomic origins.1 We follow O. D. Duncan (1968) in conceiving of stratification as the persistence of positions in a hierarchy of inequality, either over the life time of a birth cohort of individuals or, more particularly, between generations (p. 681). Although inequality describes a system of differential rewards, stratification is the link between differential rewards and accidents of birth; stratification refers to the pattern of intergenerational (im)mobility experienced by a population or subpopulation.
Under this definition, stratification and meritocracy are not mutually exclusive. Even if all students enjoyed equal access to educational and economic resources, the relationship between parent and child socioeconomic outcomes would persist as a result of parental transmission of genetic endowments (Bowles, Gintis, & Groves, 2005), personality (Farkas, 2003; Heckman & Rubinstein, 2001), values and preferences (Bourdieu, 1973; G. Duncan, Kalil, Mayer, Tepper, & Payne, 2005; Halaby, 2003; Jencks & Tach, 2006; Kohn, 1977), noncognitive skills (Bowles & Gintis, 2002; Heckman & Rubinstein), and other factors that are generally considered beyond the scope of policy intervention.
Nonetheless, we start from the premise that our society can and must do more to reduce the relationship between race/ethnicity, socioeconomic origins, and college destinations and degree attainment. We are far from achieving the level of equality of outcomes we would expect were stratification based exclusively or even largely on factors beyond the control of policy makers. In the following section, we review the pecuniary and nonpecuniary returns to a college education, variation in those returns, and trends in postsecondary participation and completion. Next we describe three theories that have dominated scholarship in the social stratification of higher education as well as their areas of overlap. We close with a discussion of three important areas for future theoretical and empirical work.
RETURNS TO EDUCATION
The economic returns to education in general, and to postsecondary education in particular, increased substantially over the last quarter of the 20th century (Goldin & Katz, 2008; Katz & Autor, 1999; Mishel, Bernstein, & Allegretto, 2005), although much of the relative gain enjoyed by college graduates was due to the decline in the real earnings of high school graduates and dropouts (Morris & Western, 1999). By 1999, the lifetime earnings of college-educated workers were 1.8 times those of high school graduates (Day & Newburger, 2002). Individuals who complete a degree enjoy the greatest returns to their education. At least among community college students, however, credit accumulation beyond the first year leads to increases in earnings even for those who do not complete a degree (Grubb, 2002; Marcotte, Bailey, Borkoski, & Kienzl, 2005). In addition to greater remuneration, education leads to a range of other outcomes connected with occupational attainment. Individuals with more education tend to hold jobs with higher levels of discretion, esteem (Halaby, 2003), and social status (Hout, 1984). In fact, based on their Index of Job Desirability, Jencks, Perman, and Rainwater (1988) found that only a quarter of the job-related benefits of schooling take monetary form (p. 1352). In addition to labor market outcomes, education contributes to psychological well-being, physical health (Cutler & Lleras-Muney, 2006; Ross & Mirowsky, 1999) and longevity (Lauderdale, 2001), and a host of social outcomes (Pallas, 2000).
Although there is broad agreement that the returns to a baccalaureate degree are greater than the returns to an associates degree, scholars disagree about the extent to which returns to baccalaureate degrees vary across institutions. Some researchers report that students who attend an elite college are more likely to complete a baccalaureate degree (Long, 2008; Small & Winship, 2007) and subsequently enjoy higher levels of occupational prestige (Brand & Halaby, 2006), earnings (D. Black & Smith, 2006; Eide, Brewer, & Ehrenberg, 1998; Thomas & Zhang, 2005), and greater chances of gaining entry into the elite or ruling class (Karabel, 2005; Persell & Cookson, 1990) than students who complete their baccalaureates at less competitive institutions. Others studies have found that, at least in the case of earnings, the purported effect of elite colleges simply proxies characteristics of the students who attend such institutions (Brand & Halaby, 2006; Dale & Krueger, 2002). The effects of college quality and student academic aptitude may be difficult to disentangle, given the strong correlation between the two (Heckman & Vytlacil, 2001).
Several scholars have looked at how returns to the baccalaureate degree vary across college majors. In general, expected earnings for baccalaureate recipients seem to vary widely by major (Rumberger & Thomas, 1993; Thomas & Zhang, 2005; Wolniak, Seifert, Reed, & Pascarella, 2008); students majoring in engineering, the physical sciences, and, more recently, health tend to earn the most in their early postcollege years, whereas education and liberal arts majors tend to earn a bit less. However, Hamermesh and Donald (2008) demonstrated that up to half of the wage premium for the most highly compensated majors can be accounted for by differences in precollege academic performance and postcollege activities, especially hours worked. Majors also vary in their association with the likelihood of attending graduate school, an important option value that tilts toward liberal arts majors (Goyette & Mullen, 2006; Zhang, 2005).
STRATIFICATION IN COLLEGE ATTENDANCE AND COMPLETION
In this review, we focus on high school graduates and GED recipients, the individuals most likely to pursue higher education. However, it is important to understand that this is already a relatively selected group; about 70% of the students expected to complete high school in 2001 actually earned a diploma (Swanson, 2004; Warren, 2004). Differences across racial and ethnic groups and by socioeconomic origins are appalling. Swanson has estimated that 74.9% of White students who started high school in 1997 completed in 2001, compared with 50.2% of African American students and 53.2% of Hispanic students. Completion rates are much higher in districts where fewer than 38% of students are eligible for free/reduced lunch (76%) than in districts where more than 38% are eligible for free/reduced lunch (57.6% ).
We find that college attendance has become the rule rather than the exception for individuals who earn a diploma or GED. Fifty-eight percent of high school completers in 1972 attended college, compared with 77% of 1992 completers (Adelman, 2004). Among sophomores in 2002 who had completed a high school diploma or certificate of attendance by 2006, almost 80% had attained some college education by 2006.2 Although going to some sort of college is normative for students completing high school today, postsecondary experiences remain stratified by race/ethnicity, nativity, and socioeconomic origins. Stratification by origin characteristics is mediated in part by academic achievement and the characteristics of the primary and secondary schools that students attend, however. We discuss each of these determinants of postsecondary participation next.
Historically, secondary school academic achievement and track placement have been among the most robust predictors of whether students attend college at all, the type of college (2-year or 4-year) students attend, and, for those pursuing a baccalaureate degree, the prestige of their initial 4-year college (Ellwood & Kane, 2000; Hearn, 1991; Karen, 2002). Some evidence suggests that the importance of academic achievement for postsecondary destinations has actually increased over time, leading to greater segregation across postsecondary institutions in student quality. For example, the proportion of variance in student SAT scores found between institutions increased from 40% among college matriculants who completed high school in 1972 to 55% among those who completed high school in 1992. Similarly, the between-institution portion of variance in years of parental education increased from 27% to 38% (Grodsky, 2002), whereas the within-institution variance at both public and private colleges has declined (Hoxby, 1997).These changes have been driven at least in part by an increase in the concentration of the most academically accomplished students in a handful of elite colleges and universities (Cook & Frank, 1993).
The organizational features of high schools may also contribute to inequality in the likelihood of attending college. It appears that even net of observable differences among their students, Catholic schools increase the likelihood of attending college in general (Evans & Schwab, 1995; Figlio & Stone, 1999), and more elite colleges in particular, as well as the likelihood of completing a college degree, relative to public schools (Eide, Goldhaber, & Showalter, 2004). Likewise, private schools (Falsey & Heyns, 1984) increase the likelihood that students will attend college, and elite private schools ease the way to elite colleges for their alumni (Cookson & Persell, 1985), although the power of these schools to do so may have declined somewhat over time (Karabel, 2005). Among the organizational features that account for the Catholic/private school advantage are school academic press, as evidenced by more demanding curricula and a narrower range of nonacademic classes (Bryk, Lee, & Holland, 1993), and what some have called a college-going culture that ingrains in students an expectation of postsecondary participation (Roderick, Nagaoka, Coca, & Moeller, 2008).
Rates of college attendance for African American high school graduates peaked in the late 1970s, when they exceeded those of Whites, but declined thereafter (S. E. Black & Sufi, 2002; Hauser, 1993). Among recent White high school completers, 66% enrolled in some sort of postsecondary institution, compared with 58% of African American and Hispanic students (Snyder, Tan, & Hoffman, 2006).3 Groups also differ in the types of postsecondary institutions they initially attend, with Black and (especially) Latino students more likely than Whites to begin their postsecondary careers at a community college. Although some research shows that starting at a community college may be beneficial to Hispanic students (Gonzalez & Hilmer, 2006), other research demonstrates the pitfalls of attending a community college with the objective of completing a baccalaureate degree. For example, among students in the class of 1992 who initially attended a community college, 63% expected to earn a baccalaureate degree, but only 27% of them had done so by 2000 (Hoachlander, Sikora, & Horn, 2003).
Many of the marginal differences in attendance across racial/ethnic groups are accounted for by differences in secondary school achievement and socioeconomic background. Academic achievement continues to be seriously stratified by social background (Perie, Moran, & Lutkus, 2005). Among seniors in high school in 2004, 72% of White students exhibited mastery of simple problem solving in mathematics, compared with 43% of Hispanic students and 36% of African American students (Ingels, Planty, & Bozick, 2005). Net of secondary school academic achievement, Blacks are actually more likely than Whites to attend a 4-year college than a community college (Roksa, Grodsky, Arum, & Gamoran, 2007); Hispanics remain less likely to do so, perhaps in part because of their relatively strong preferences for living at home while in college compared with other groups (Turley, 2006).
African American and White students are not uniformly distributed across types of 4-year institutions. Historically Black colleges and universities (HBCUs), where, on average, over 80% of students are African American, continue to produce almost a quarter of the baccalaureates earned by African American students (Provasnik & Shafer, 2004). Some researchers contend that racial and ethnic minorities attend institutions of lower average prestige (Hearn, 1991; Karen, 2002), whereas others have found that historically underrepresented minority youth are more likely to attend prestigious institutions than White youth, all else equal (Bowen & Bok, 1998; Grodsky, 2007). Within institutions, Adelman (2004) has found only modest differences in the racial/ethnic composition of majors for the high school class of 1992.
Racial/ethnic disparities persist through degree attainment, although they have declined modestly over time. Among students in the high school class of 1972 who achieved at least 10 credits of postsecondary education, about 73% of Whites earned some sort of degree, compared with 46% of African American matriculants and 40% of Hispanics. By the high school class of 1992, all groups had made gains, but they were greater for African American and Hispanic students. Nonetheless, substantial differences in degree attainment remain. Whereas 52% of African American students and 45% of Hispanic students left college with some sort of degree, 68% of White students did so (Adelman, 2004).
Social origins of students, including parental education, occupation, and family income, exert powerful effects on the educational attainment patterns of American youth. These forces operate through multiple pathways, including early socialization (Connell, Ashenden, Kessler, & Dowsett, 1982; Lareau, 2000), community of residence (Domina, 2005), school readiness (Downey, von Hippel, & Broh, 2004; Lee & Burkam, 2002), track/ability group placement (Lucas, 1999; Oakes, Gamoran, & Page, 1992), educational and occupational aspirations (Teachman & Paasch, 1998), and secondary school achievement (Camara & Schmidt, 1999; Perie et al., 2005). In addition to these pathways, social class is correlated with cognitive ability (Hauser, 2002). Whether due to differences in educational opportunity, genetic endowments (Bjorklund, Jantti, & Solon, 2006; Jensen, 1968), environment (Jencks, 1980; Jencks et al., 1979), or some combination of these factors, cognitive ability remains an important component of the social origins-educational attainment relationship.
Parental education and income play a substantial role in college attendance, even net of students academic achievement through secondary school (Ellwood & Kane, 2000; Kane, 2001). The effects of parental education and income appear to have increased over time (Kane, 2001), although in absolute and relative terms, students at the bottom of the distribution of socioeconomic status (SES) appear to have experienced the greatest increase in their probability of attending some sort of college between 1972 and 2000 (Adelman, 2004).4 Among 1992 high school completers, 94% of students in the top quintile of SES went on to attend college within 8 years, compared with 77% of students in the third quintile and 54% in the bottom quintile. Parental education is especially important because it tends to form a floor under which student educational attainment seldom falls (Mare, 1995; Mare & Chang, 2006). Parents who attended college contribute to their childrens likelihood of college attendance not only through their general knowledge and cultural capital but also by passing along information relevant for making that particular transition. Such instrumental information might include what courses a student needs to complete in high school, how to register and study for a college entrance exam, and even how to request secondary school transcripts. Among the highest achieving students who completed high school in 1992, about 25% of children whose parents did not attend college failed to enroll in any postsecondary education by 1994, compared with only 1% of those who had at least one parent with a bachelors degree (Horn & Bobbitt, 2000).
Family income and parental education are both inversely related to the likelihood of attending a community college as opposed to a 4-year college. Almost half of the students who began their postsecondary careers at a community college in 1995 were first-generation college students, compared with roughly a third of students attending a 4-year college (Coley, 2000). Among students who attend 4-year colleges, less advantaged students are more likely to attend a public institution or a less competitive institution. Astin and Oseguera (2004) found that the socioeconomic composition of colleges in the top 10% of average SAT scores became more homogenous between the 1970s and 2000. At competitive colleges and universities, some evidence suggests that the effects of social origins are entirely accounted for by prior academic achievement (Bowen, Kurzweil, & Tobin, 2005), whereas other research demonstrates that children of the most advantaged parents are more likely to attend competitive colleges even net of secondary school achievement (Grodsky, 2007).
There is remarkably little empirical work on the relationship between social origins and choice of college major. Students from disadvantaged backgrounds may prefer majors leading to more lucrative careers (Davies & Guppy, 1997), whereas the most advantaged students appear more likely than the less advantaged to enter both the humanities and majors leading to highly compensated occupations (Davis, 1965). Similarly, parental education is positively associated with choosing a major in the arts and sciences, even more so net of controls for college characteristics and student occupational aspirations and expectations (Goyette & Mullen, 2006).
Finally, first-generation college students are at greater risk of leaving a 4-year college in their first year of enrollment than are other students. This difference persists even after adjusting for the weaker average academic preparation and limited finances of first-generation students. Those students who do persist after their first year of enrollment are less likely to have completed a baccalaureate degree 5 years after matriculating than are second-generation or higher college students (Choy, 2001). Examination of the relationship between family income and degree attainment conditional on college entry produces the same results. Whether measured in terms of real family income (Carnevale & Rose, 2003; Ellwood & Kane, 2000) or permanent income standardized on need5 (Haveman & Wilson, in press), family income continues to shape educational outcomes through baccalaureate completion. Though some argue that the relationship between family income and persistence reflects economic resource constraints that students face during their postsecondary careers (Card, 2001), others have found that much of the association can be accounted for by the contribution of permanent family income to adolescent academic achievement (Carneiro & Heckman, 2002) or to the likelihood that students enjoy school (Stinebrickner & Stinebrickner, 2003).
THE PATHWAY TO A BACCALAUREATE DEGREE
The group differences that we outlined are shaped by a complicated series of decisions made by individual students and their families, colleges and universities, and policy makers at the state and federal levels. Individuals make decisions that are structured by the groups with which they identify (middle class, African American, Latino, and so on), their understandings of the barriers that members of those groups face in (higher) education, and the likelihood and utility of overcoming those barriers. Individual outcomes are also conditioned by how significant others and gatekeepers respond to students based on the groups to which they believe a student belongs. That said, group membership is far from deterministic with respect to educational outcomes. If we are to craft policies that reduce the relationship between ascribed attributes and postsecondary educational attainment, we must understand the micro-level individual and institutional processes that produce the social inequalities that we continue to confront in higher education.
Degree attainment is the culmination of a lengthy choice process involving preferences and decisions of individual students and postsecondary institutions. Colleges and students pursue different objectives in this process and are influenced in their behavior by different sets of actors and different constraints. To make matters more complicated, choices students make at time t can constrain the options available to colleges at time t + 1 and, reciprocally, choices made by a college at time t + 1 can constrain options available to students at time t + 2. For expository purposes, we divide the degree attainment process into five temporally ordered, discrete phases: predisposition, search, choice set formation, matriculation, and persistence. The first four phases evolve over the middle and secondary school years and have fairly clear endpoints, whereas the final phase is less well bounded (Goldrick-Rab, 2006). The behavioral model presented here, through matriculation, is based on the model proposed by Hossler and Gallagher (1987), but with some slight modifications. Our proposed model is illustrated in Figure 1.
Figure 1. Behavioral model of degree attainment process
STUDENTS CHOOSING SCHOOLS
From the students perspective, the college choice process begins with predisposition, a phase of the college choice process that has no clear beginning point, but ends with the decision to continue ones schooling at the postsecondary level. In the predisposition phase, students expectations and aspirations may be shaped by a variety of forces, including the tastes, preferences, and expectations of their parents, peers, and teachers; the successes and failures that they experience in school; and the information that they receive regarding the benefits and costs of continuing their education past the secondary level. Data suggest that students postsecondary educational expectations have increased substantially over time (Morgan, 1998; Schneider & Stevenson, 1999), to the point where they are only weakly associated with their educational and occupational outcomes (Goyette, 2008; Reynolds, Stewart, MacDonald, & Sischo, 2006).
For students who decide to continue their education past secondary school, the next step in the degree attainment process is the search phase, when they must learn about the postsecondary options available to them and then narrow those options to a manageable set of schools to which they will apply. Students interested in attending a 4-year institution rather than a 2-year institution must choose among the more than 2,000 colleges and universities in the United States. Search strategies vary widely, from haphazard strategies whereby students apply only to a local college with which they are familiar or a school attended by a friend or relative, to national searches whereby students engage written and online sources of information, teachers, guidance counselors, and, increasingly, private college counselors (McDonough, 1997; McDonough, Korn, & Yamasaki, 1997). Search strategies vary by social origins, race/ethnicity, and academic achievement.
The outcome of the search process is what we will call, following Roberts and Lattin (1997), the consideration set. This is a subset of the universe of colleges and universities to which students actively consider applying. From this consideration set, students will choose a subset of schools to which they will apply for admission (the student choice set). The choice set may consist of a single institution, or 12 or more colleges and universities. Between 1980 and 2004, the percentage of students who applied to a single college declined from 46% to 28%; by 2004, 21% of students who applied to college applied to five or more schools.6 Although there has been relatively little research on student choice sets, it appears that the composition of student choice sets varies in part as a function of high school characteristics (Niu & Tienda, 2008).
In the final phase of the matriculation process, students choose from among the colleges that admitted them. Students may still opt not to attend any college at all, or they may opt to attend a community college because it generally admits all comers and offers a later deadline for registration. Their choice of college, however, has been reduced from the student choice set (schools to which they apply) to the final choice set (schools to which they have been offered admission). Institutions have, through their admissions decisions, constrained the set of alternatives available to would-be college matriculants.
SCHOOLS CHOOSING STUDENTS
Just as students make choices about which college to attend, if any, secondary schools and colleges make choices about which students to encourage or, in the cases of colleges and universities, recruit. In the student predisposition phase, secondary schools, the federal government, and, increasingly, individual colleges and universities intervene to persuade all students to embrace the goal of attaining a baccalaureate degree. Secondary schools, according to Rosenbaum (2001), encourage the college-for-all norm, which states that all students can and should attend college but fails to tell students what they must do to attain a college degree (p. 56). Under the mantle of the TRIO programs, the federal government has, since 1964, sought to encourage disadvantaged youth to attend college and has provided grants to organizations that engage in outreach and academic tutoring efforts to make it possible for those students to succeed in higher education.7 Finally, there are a number of independent, nonprofit university- and state-based programs designed to encourage students to aspire to college and to support students efforts to achieve their educational goals (U.S. Department of Education, 2001).
Just as students search for colleges that possess attributes that they value, colleges and universities search for students with the characteristics that they would like to see (better) represented among their incoming classes. Colleges and universities seek to maximize the quality and size of their applicant pool; some colleges also try to maximize diversity on various dimensions (place, race, socioeconomic origins) or income (students who pay the tuition sticker price). Institutions begin their direct mail campaigns in the students junior year of high school, purchasing the names and addresses of targeted students from the Student Search Service offered by the College Board. In 2003, this search service, which allows colleges to purchase student contact information based on students scores on the SAT or PSAT and their demographic characteristics, included records for about 4.6 million students and was used by 1,600 colleges and universities (The College Board, 2006). Approximately 75% of 4-year public institutions and 85% of 4-year private institutions reported using direct mail to recruit students in 1985 and in 1992. About 60% of public and 70% of private community and junior colleges also appealed to students by mail during this period. In addition to direct mail, colleges seek to convince students to apply by visiting their high schools and advertising in the popular press (Breland, Maxey, Gernand, Cumming, & Trapani, 2002).
The institutional consideration set, or set of students who apply, is constrained by the decisions that students and their parents make: Institutions can only enroll students who make themselves available. This aspect of constraint is seldom considered by researchers studying higher education but is of great concern to many postsecondary institutions. It is also critical for understanding the efficacy of various policy interventions intended to increase equality of college access, as we will discuss. For example, no matter how generous the financial aid packages that colleges intend to offer, if potential applicants are unaware of a schools generosity, they may fail to apply and thus hamper the schools ability to attract the kinds of students it most desires.
From the institutional consideration set, institutions choose the students they wish to enroll, and from those, which students to offer financial assistance. Institutions choose students based on observed characteristics, including academic performance in secondary school, admission test scores (the SAT and/or ACT), participation in extracurricular activities, artistic ability, athletic ability, and a host of other achievements. Institutions also may choose students based on their religious affiliation, racial or ethnic origins, region of residence, and family economic resources. Different institutions have different objectives, seek to serve different populations of students, and have varying degrees of capacity to realize their preferences.
CHOICES MADE AT COLLEGE
Once students begin their postsecondary careers, they are faced with the additional choices of college major and whether to persist to degree, which affect their college experiences and occupational opportunities. Although college major is consequential for postbaccalaureate earnings and graduate education, we know very little about how students choose their major. Work on this topic is methodologically sophisticated but theoretically weak. For example, economists have found that students gravitate toward a major with greater lifetime earnings potential, all else equal (Berger, 1988; Eide & Waehrer, 1998), and that students are more likely to major in subjects in which they are more likely to be successful (Montmarquette, Cannings, & Mahseredijian, 2002). However, we know little about how or why student choices of college major vary across racial/ethnic groups or social class origins, or what, in addition to these admittedly important factors, governs the choice of major.
Overall, only about half of those who graduated from high school in 1972, 1982, or 1992 and went on to earn at least 10 credits in any postsecondary institution actually earned a baccalaureate degree. If we confine our attention to those with at least 10 credits in a baccalaureate-granting college, about two thirds went on to earn a baccalaureate degree (Adelman, 2004). Students fail to complete college for all sorts of reasons, including poor secondary school academic preparation, lack of interest, resource constraints, changes in their personal lives, and a variety of factors related to the college or university they attend. Although we know that completion rates vary substantially across colleges (Carey, 2004; Small & Winship, 2007), we know much less about what factors cause this variation (Kurlaender et al., 2006).
Many students who attend college begin in one institution and later migrate to another or to a series of institutions. The number of college entrants transferring during their postsecondary careers has increased over time, from about 48% for the high school class of 1972 to almost 57% for the high school class of 1992 (Adelman, 2004). The enrollment histories of college students have also become considerably more varied across time as large numbers of students experience multiple discontinuous spells of enrollment. These discontinuities can adversely impact their likelihood of completing a degree (DesJardins, Ahlburg, & McCall, 2006; Goldrick-Rab, 2006; Goldrick-Rab & Pferffer, 2009).
THEORIES OF POSTSECONDARY STRATIFICATION
With an explicit behavioral model as our framework (see Figure 1), we can now situate both theoretical and policy work in the stream of student and institutional actions that lead to baccalaureate attainment. We discuss three general bodies of theory that have dominated research on postsecondary stratification: status attainment, rational choice theory, and reproduction theory. Sociologists have produced most of the status attainment literature, and scholars in both education and sociology have contributed to the literature on reproduction. Economists have generally held sway in rational action models, but more recently, both economists and sociologists have contributed to this literature.
STATUS ATTAINMENT THEORY
Status attainment research relies on the temporal ordering of events within and across generations to account for population variation in educational and occupational attainment. Blau and Duncans (1967) model of the intergenerational attainment process empirically derived the direct and indirect effects of fathers education and occupation on sons education, initial occupation, and occupation at the time of survey. Sewell and his colleagues added measures of educational and occupational aspirations, significant others influence, and mental ability to Blau and Duncans original model, creating what is now known as the Wisconsin model of status attainment (Sewell, Haller, & Ohlendorf, 1970; Sewell, Haller, & Portes, 1969). The Wisconsin model
assumes that predetermined social structural and psychological factors, i.e., socioeconomic status and mental ability, affect the youths academic performance and the influence significant others have on him; that the influence of significant others and possibly his own ability affect his level of educational and occupational aspiration; and that levels of aspiration affect educational and occupational status attainment. (Sewell et al., 1970, p. 1015)
It proposes a clear set of pathways by which social origins, most often represented by parental education and occupation, contribute to stratification in the distribution of educational and occupational attainment. In addition, researchers in this tradition have demonstrated the degree to which unobserved components of family background contribute to educational and occupational attainment substantially above what is contributed by observed parent attributes (Hauser & Featherman, 1976; Jencks et al., 1979). At the same time, the model explicitly acknowledges the sizeable contributions to the attainment process of factors unrelated to social origins. Among the many factors considered by Sewell and colleagues, the social psychological attributes and the processes of planning and of expectation and aspiration formation have been of central importance in the sociological study of postsecondary attendance patterns. Such factors have been invoked in efforts to explain achievement trajectories of individual students and differences in achievement trajectories across demographic groups.
In our view, both the strengths and the weaknesses of the status attainment tradition derive from the relative simplicity of the Wisconsin model. It does not purport to explain why things are as they are, but only how some individuals end up with so many years of education and others end up with relatively few. Empirical results of the Wisconsin model include something for everybody. Those who believe that education is an effective avenue to intergenerational mobility point to the negligible relationship between social origins and occupational attainment net of education. For example, Hauser, Warren, Huang, and Carter (2000) wrote that whatever the explanatory power of school [for occupational attainment], social background adds little to it (p. 194). Conversely, those who maintain that education reinforces social stratification highlight the substantial relationship between social origins and educational attainment. In their review of the literature, Hauser et al. estimated that between 62% and 70% of the variance in educational attainment can be accounted for by observed and unobserved components of family background.
The absence of a more explicit underlying theoretical model has left the Wisconsin model open to a range of theoretical interpretations. As Bielby (1981) noted, some accuse the model of being an inherently functionalist account of the stratification process, whereas others maintain that the model is most consistent with a Marxian perspective on social stratification. Also absent from the Wisconsin model is an explicit consideration of social structure, or the degree to which individuals arrive at their positions in the educational and occupational attainment structure because of allocation rather than socialization (Kerckhoff, 1976). In Kerckhoff s view, structural forces temper the relationships explicated by the model in ways that status attainment researchers sometimes fail to recognize. For example, the models reliance on temporal ordering to establish causality does not mean that earlier dispositions are immune from the effects of later potential outcomes. Actors form their expectations and aspirations in part based on their potentially accurate notions of what is possible, so that aspirations reflect not only background characteristics and academic ability but also stratified opportunity structures.
The Wisconsin model offers a detailed framework for understanding predisposition and attendance components of our behavioral model. It does not, however, provide any obvious insights into student search, choice set formation, or matriculation decisions in terms of the specific institution a student might attend. Furthermore, consistent with Kerckhoffs (1976) insight about the absence of allocation structures from the model, the status attainment model has nothing to say about the institutional side of Figure 1. The supply of education is taken as unproblematic by status attainment researchers, a position readily justified for the K12 years but more difficult to sustain at the postsecondary level, where admission to most colleges is not guaranteed and attendance is rarely free.
RATIONAL ACTION MODELS
Rational action models subsume an array of theoretical approaches to the understanding of social behavior. Contrary to Hechter and Kanazawa (1997), we do not distinguish between decision theory and rational action models in our review, nor do we discuss linkages to the macro level that several theorists assert is critical to rational choice models (Coleman, 1990; Goldthorpe, 2006; Hechter & Kanazawa). For more nuanced discussions of these and other issues, see also Boudon (2003) and McCarthy (2002).
At its simplest, rational action theory assumes that individuals act in ways that maximize the likelihood that their preferences will be satisfied, given the constraints they face. It assumes that (1) individuals have preferences of which they are aware, (2) preferences for the attributes of choice objects combine to form utilities by which individuals can order the desirability of various alternatives, and (3) individuals act instrumentally to achieve the alternative that they find more desirable than any other alternative available to them. In theory, utilities comprise more than the qualities that individuals desire in an object and the relative magnitude of their desire for each quality; they also include the degree to which individuals are averse to risk and an assessment of the risk involved in each choice, as well as the extent to which they are willing to delay the time until they expect to enjoy the returns to each choice. Finally, utilities are inherently subjective; they are muddied by the adequacy of the information that people have regarding the attributes of the alternatives, such that in the absence of perfect information, individuals make mistakes and choose alternatives that they would not have chosen with perfect information.
To the question Who goes to college? rational action research in economics generally replies, Those who would most benefit from doing so. Building on Beckers (1962, 1993) insights into the generation of human capital and especially the idea of comparative advantage, researchers have found that individuals who go to college earn more with their degree than they otherwise would, whereas those who fail to go to college might enjoy lower returns to a college education than those who do attend (Taber, 2001; Willis & Rosen, 1979); that those who fail to go to college would be unlikely to complete a degree had they chosen to attend (Light & Strayer, 2000; Manski & Wise, 1983); and that some who do go to college limit their losses by discovering early on their error in doing so and leaving college (Manski, 1989; Montmarquette, Mahseredjiana, & Houleb, 2001). The same logic applies to the type of college that students attend; many researchers have reported that the advantage of attending a more prestigious school largely reflects the nature of the students who attend such institutions and would be unlikely to accrue to those who do not attend them, were they to attend (Dale & Krueger, 2002; Light & Strayer, 2000). Empirical results are not entirely consistent in this literature, as suggested by evidence for the returns to college quality reviewed earlier in this article.
As a result of limits on the data and computational resources available to them, researchers working in this area have generally employed simplifying assumptions in their work that deviate substantially from the more flexible theoretical model outlined earlier in the article. For example, although the concept of utility is not reducible to income or wealth, in practice, economists have often conceived of utility as such. Kenny, Lee, Maddala, and Trost (1979) assumed that the decision of whether or not to go to college should depend on the present discounted value of lifetime after tax earnings less costs of college (p. 778), whereas Avery and Hoxby (2004) offered a more detailed equilibrium model that takes into account the fees, living expenses, and various forms of aid on the one hand, and consumption and the present discounted value of various returns on the other. Some recent work in economics, however, takes a broader view of the utility function itself, considering contextual factorslike a sense of group belonging or social distance (Akerlof, 1997), and psychic costs (Cunha, Heckman, & Navarro, 2005)as part of the utility that choosers seek to maximize.
The assumption that students forecast the present discounted value of their lifetime earnings is difficult to take seriously. Manski (1993) wrote, Having witnessed the struggles of econometricians to learn the returns to schooling, I find it difficult to accept the proposition that adolescents are endowed with this knowledge (p. 49). Although research on small and nonrepresentative samples has shown that the average earnings expectations of adolescents are fairly accurate, the expectations also vary substantially across respondents (Dominitz & Manski, 1996; Rouse, 2004). We are not aware of any empirical work that has linked these expectations to postsecondary matriculation decisions. Another assumption often imposed in the economic literature is that students have perfect information with respect to the costs of attendance and the availability of financial aid, an assumption that empirical research resoundingly rejects (American Council on Education, 2006; Grodsky & Jones, 2007; Mundel & Coles, 2004).
Although many sociologists eschew rational choice models in favor of more descriptive or critical perspectives, sociological rational choice theories of educational persistence have been invigorated by the recent work in the field. Sociological rational choice theories generally apply to the predisposition and matriculation phases of student choice and are largely exclusive of the action of postsecondary institutions. For example, Breen and Goldthorpe (1997) conceived of the utility of students and their parents as dominated by fears of downward social mobility. They have asserted that students and their parents make educational continuation decisions based on the perceived costs and benefits of school continuation and their subjective assessments of the probability of success should they continue on to the next grade level. Further, they have demonstrated that their model can account for the stability of social class differences in education in most countries, despite substantial reductions in the barriers that disadvantaged students confront in persisting to the postsecondary level (Arum, Gamoran, & Shavit, 2007; Blossfeld & Shavit, 1993). Although empirical applications of the Breen and Goldthorpe model have been limited, results have been generally favorable to the model (Breen & Yaish, 2006; Stocké, 2007).
Fusing the outlined status attainment tradition with the rational choice framework articulated by Goldthorpe (2006), Morgan (2005) has proposed a theory of belief formation and postsecondary participation, positing that beliefs about the likelihood of successfully attaining ones objectives (prefigurative commitment) contributes directly to the behavior that leads to realizing those objectives (preparatory commitment). Those with less information exhibit less effort in the short term and are less likely to succeed in the long term. People learn, however; Morgan invoked a Bayesian model of learning in which prior beliefs are continually updated based on new information. By incorporating the effects of prior beliefs on future behavior, explicitly allowing for both subjectivity and the influence of information quantity and quality and proposing a simple yet plausible model of student action, Morgan draws on many of the strengths of both economic and sociological rational actor models of educational attainment.
Critical theories on the role of schooling (and, by extension, higher education) in the stratification process implicate schools as a key cog in the social machinery of legitimation, domination, and social reproduction. Critical theorists are diverse in their views on education, however. In this section, we focus exclusively on work of Pierre Bourdieu and related research. Bourdieu developed several concepts that on the surface appear especially well suited to the study of postsecondary stratification. Although his ideas are provocative, empirical applications of his work in higher education must overcome several challenges, which we detail next.
Bourdieu rejects the structure/agency duality implicit in the status attainment and rational actor approaches discussed earlier in the article, arguing instead that each act executed by an individual helps recreate the social structure that enables and constrains individual action (Bourdieu, 1996). His approach to the study of stratification is readily compatible with the two-sided process of degree attainment represented in Figure 1. A Bourdieuian analysis might anticipate that the actions of structure (represented by postsecondary institutions) both shape and are shaped by the actions of individual students and their families. In our brief review of Bourdieu, we highlight two concepts that have been employed in the limited Bourdieu-inspired empirical work in higher education: field and habitus. 8
For Bourdieu, the field is a social space where agents compete with one another for control over various forms of capital. It is the totality of actors and organizations involved in an arena of social or cultural production and the dynamic relationships among them (DiMaggio & Powell, 1983, p. 1463). The social world can thus be divided into overlapping fields in which actors engage in strategic behavior, although not always consciously doing so (as we will discuss).
An understanding of social action requires an understanding of the field in its entirety. In the case of baccalaureate attainment, this means taking account of the behaviors and motivations of all the varied actors involved in the degree production process. In their synthesis of Bourdieuian and organizational field perspectives, McDonough, Ventresca, and Outcalt (2000) wrote that a field approach provides increased analytic insight by integrating individual and institutional levels of analysis, by accounting for the reciprocal influence of students and institutions on each other, and by illuminating the dynamic interactions of student behavior with professionals and policymakers practices (p. 383). Although we confine our attention to postsecondary institutions and students (and, by extension, their parents) in Figure 1, this interplay of mutual constraints is precisely what we mean.
In the field of higher education, Bourdieu (1973) suggested that colleges and universities will exclude the disadvantaged and legitimate the achievements of the children of the ruling class by granting them credentials, a key form of cultural capital. Upward mobility within this stratified system is strictly rationed. Controlled mobility of a limited category of individuals, carefully selected and modified by and for individual ascent, promotes social stability by maintaining institutional legitimacy (Bourdieu, 1973, p. 71). Given the importance of higher education for economic success and Americas ideology of equal opportunity, failure to enroll student bodies that are at least modestly diverse may undermine the legitimacy of these institutions in the eyes of the public.
To understand how individuals act within a field requires understanding their goals and objectives, their perceptions of opportunities and constraints, and their world view more generally. Bourdieu suggested that the key to understanding a persons actions lies in understanding his or her habitus, a constellation of preferences, behaviors, and styles of self-presentation largely shaped during childhood. Although enduring, habitus is also malleable, shaped by the cumulation of an individuals experiences (Reay, 2004). It is at once a primary pathway by which social standing is passed on from parent to child, and a key determinant of individual choice.
Part of the habitus is an assessment of what is possible and what is not in terms of occupational and educational attainment.
We know that to different objective probabilities [of going to university] correspond different sets of attitudes towards school and school-assisted social mobility. Even when they are not the objects of conscious estimation, educational chances . . . help to fix the social image of university education which is in a sense objectively inscribed in a determinate type of social condition. Depending on whether access to higher education is collectively felt, even in a diffuse way, as an impossible, possible, probable, normal or banal future, everything in the conduct of the families and the children (particularly their conduct and performance at school) will vary, because behaviour tends to be governed by what it is reasonable to expect. (Bourdieu & Passeron, 1990, p. 226)
Through patterns of behavior, communication, tastes, and dispositions, habitus plays a critical role in shaping the possibilities that students see and, thus, those they realize. Habitus resolves an important piece of the agency/structure puzzle in Bourdieus work because it enables the claim that students and their parents exhibit agency but in a way that relegates children to the structural positions occupied by their parents.
Researchers have invoked habitus to account for the educational expectations and aspirations of secondary school students and their choices of which college, if any, to attend (Horvat, 2001; McDonough, 1997; Reay, 1998). McDonough took the concept a step further, arguing that, like individuals, secondary schools have their own habitus reflective of the habitus of the students they serve. Affluent schools take for granted that all their students will attend college and therefore provide them with an array of information to help them choose the institution that is right for them, whereas working-class schools do little, if anything, to facilitate the secondary schoolcollege transition.
Despite the appeal of Bourdieus ideas, analysts hoping to apply his theoretical work in an empirical setting must overcome several substantial limitations. His theory of reproduction strikes us as overly deterministic. Although the theory allows for agency, it relies on actors to engage in agency in strictly patterned ways to reproduce the social hierarchy. We do not mean to imply that agency is a fiction in Bourdieus work, but were agents to vary widely in their decisions conditional on social origins, the theory could quickly morph into one of social mobility rather than social reproduction.
Second, several of the generative mechanisms in Bourdieus theory are specified at the subconscious level. Although many of the decisions that people make may in fact be structured by a matrix of perceptions, tastes, and beliefs of which they are not aware, testing such a proposition seems prohibitively difficult to us. Furthermore, from a practical standpoint, it is unclear how much social policy can do to change habitus. In the absence of a strong empirical test, the mechanism of subconscious determinism acts as a deus ex machina to account for anything and everything related to the options of which students are aware and the choices that they make. Furthermore, habitus is at once enduring and malleable, formed in early childhood and subject to revision over the life course. Although both descriptions can be true, Bourdieu leaves one wondering about the extent to which habitus is subject to modification or manipulation, a key point in designing programs to reduce postsecondary stratification.
COMMONALITIES AND CONTRADICTIONS ACROSS THEORETICAL TRADITIONS
Although the theories reviewed in this article differ in the fundamental assumptions that they make about how the world operates, at the behavioral level, we see more common than contested ground. These observations may reflect recent trends in the reduction of disciplinary boundaries in economics and sociology and the willingness of researchers in education to take advantage of the methodological advances in these disciplines. The commonalities form the foundation for substantial advances in our understanding of student and institutional behavior and our capacity to reduce social stratification at the postsecondary level.
Situating the subject
Scholars working across these three theoretical traditions are starting to converge in their recognition of the importance of the subjective assessments of students and their parents in the process of postsecondary stratification. Reproduction theorists, for example, highlight the importance of students subjective probabilities of success in their educational and occupational decisions. Among those working in the rational action tradition, Breen, Goldthorpe, and Morgan acknowledge the behavioral importance of subjective probability assessments and urge future scholars to take the relationship between the objective and subjective probabilities as problematic. Although not directly addressed in status attainment research, subjective probabilities may be the mechanism by which significant others influence educational expectations independent of student cognitive skills and academic success. Students may use information from significant others (including their aspirations and expectations for a students occupational and educational attainment) to update their subjective probabilities of gaining admission to a (competitive) baccalaureate institution, completing a demanding major, and attaining a baccalaureate or graduate degree. The information that students gain from significant others need not conform to reality. In fact, Rosenbaum (2001) and his collaborators have argued that student expectations regarding the likelihood that they will succeed in obtaining a baccalaureate are substantially upwardly biased, in part because of the limited or poor information they receive in various forms from the secondary schools they attend.
The potential role of information
On a related note, researchers are beginning to take more seriously the relationship between social stratification and the quantity and quality of the postsecondary information available to students and their parents (Mundel & Coles, 2004; Person, Rosenbaum, & Deil-Amen, 2006; Vargas, 2004). The relationship between information and postsecondary outcomes is complex; it varies across students and over stages of the behavioral process outlined in Figure 1. For example, although the degree of upward bias in estimates of tuition provided by students and their parents seems uniform across social origins (Avery & Kane, 2004; Grodsky & Jones, 2007), the effect of this bias may vary by SES. Price sensitivity is inversely related to economic resources, so the effect of a dollar increase in (perceived) costs will be greater on disadvantaged than advantaged families. Likewise, information about the availability of financial aid may have a greater impact on college attendance if it is known early in the choice process, at the predisposition phase, rather than later, when decisions consequential to college opportunity have already been made (or not made; Blanco, 2005).
Understanding reciprocal constraints
The behavioral model we propose emphasizes the importance of reciprocity in the postsecondary attainment process; students constrain colleges in the decisions they make, and colleges constrain students in the decisions they make. Status attainment theory has little, if anything, to say about the institutional side of this process. Reproduction theory and rational choice, however, can easily accommodate the two-sided nature of this process, although in practice, this is seldom done.
Through the concept of field, reproduction theory is especially well suited to this task. It not only anticipates the interplay between institutional and individual agency but also considers that interplay to be fundamental to the evolution of actions of all players (colleges, students, parents, and so on) involved in higher education. Rational choice theories can also incorporate ideas of mutual constraint that characterize the process outlined in Figure 1. Postsecondary institutions and the students they serve have different utility functions, and the objectives of institutions shape how they interact with students and the kinds of students with whom they choose to interact; the same is true for students.
Decisions not made
Rational choice models assume that social action arises from the choices that individuals make subject to constraints. Those models are not equipped to understand the absence of choice. Yet, empirical work on college choice has documented that for many students, the decision about whether to attend college is hardly a decision at all; they know from an early age that they are going to college and do not seriously entertain the possibility of doing otherwise (Horvat, 2001; McDonough, 1997; Reay, David, & Ball, 2005). It may be that the decision of whether to attend is one made largely by less advantaged or less academically prepared students, whereas more advantaged students are predisposed to attend without ever reaching a conscious decision point.
Scholars whose work is motivated by Bourdieus theories of social reproduction are in a much better position to shed light on nondecisions than those working with the other theories we have reviewed. Understanding who does and does not make a conscious, calculated decision about college attendance would be a substantial advance for both behavioral and policy reasons. At the same time, adjudicating between those who do and do not believe that college is in their future is increasingly difficult given the unrealistically high proportion of adolescents who believe that they are bound for college.
DIRECTIONS FOR FUTURE RESEARCH
The time is right for advances in understanding and remedying postsecondary stratification. Leaders in higher education are beginning to take socioeconomic inequalities in access to higher education more seriously, as evidenced by Bowen et al.s recent work (2005); Harvards decision to substantially expand its support of students from families earning less than $40,000 per year (Basinger & Smallwood, 2004) and Yales decision to follow suit (Pacia & Sadeghi, 2005); and, most recently, the decision of several competitive colleges, including Harvard, Princeton, and the University of Virginia, to abandon early decision programs.9 At the federal level, former Secretary of Education Margaret Spellings recently promised to substantially increase financial aid to economically disadvantaged students and dramatically simplify the federal financial aid application process, acknowledging that information barriers contributed substantially to the inability of such students to plan for college.
Research in the social sciences is also evolving rapidly. We believe that the necessary conditions are in place to advance the knowledge base that policy makers need to guide them, as a result of increasingly permeable disciplinary boundaries, advances in theoretical and statistical models, promising work in survey measurement, and a push toward experimental research design. In the closing pages of this review, we highlight two timely and important substantive areas of research that we hope researchers and funders will explore in the near future.
ANALYSIS OF THE INFORMATION AVAILABLE TO COLLEGE ASPIRANTS
Information as a potential mediating factor in postsecondary stratification comes up repeatedly in rational choice workwork building on Bourdieus theory of reproduction, and the empirical literature in both fields. Information also holds clear appeal in the arena of social policy. Providing people with better information is relatively inexpensive and certainly uncontroversial. If information proves to be a useful tool in reducing postsecondary stratification, we would have a knowledge base on social marketing from which to develop information campaigns targeted explicitly toward those for whom information would be most useful.
Unfortunately, data on what parents and students know about higher education are mostly cross-sectional, whereas data that allow us to understand pathways to degree attainment are necessarily longitudinal. If we are to learn how information can be used to reduce stratification in higher education, we need to begin with a theoretically informed analysis of how information varies by social origins and what impact this variation has on college attendance and completion.
The four most critical domains of college knowledge are the following: (1) the costs of attendance (mandatory tuition and fees, room and board, books, and supplies), (2) the availability of financial aid (grants and loans from institutions and the state), (3) the likelihood of admission, conditional on application, and (4) the academic and personal resources necessary to complete a degree. Beyond learning students and parents point estimates for these resources, we also need to know something about their uncertainty. The less certain that individuals are about the quality of their information, the less likely they are to act in ways that help them achieve their goals.
Survey measures of probabilities and uncertainty can be meaningfully collected from adults (Bassett & Lumsdaine, 2001) and adolescents (Fischhoff et al., 2000). Furthermore, we know from other work that students are capable of providing both point estimates and confidence bounds for quantities like the returns to a college education (Dominitz & Manski, 1996; Rouse, 2004). The survey methods exist to support an analysis of the kind we propose.
Cataloguing the quantity and quality of information held by students and their parents is a good start, but it is not enough. The estimates of respondents may be incorrect or subject to substantial uncertainty because they have limited access to good information, because they are not inclined to acquire good information, or because, despite being exposed to good information, they are not in a position to process or absorb it. Although we can and should collect data on the sources of information on which individuals estimates are based, we believe that experimental designs will be much more effective than observational designs in disentangling the exogenous effect of information on postsecondary outcomes. We will discuss this point in more detail.
ASSESSMENT OF COLLEGE SUPPORT FOR STUDENT COMPLETION
Researchers and policy makers have made a concerted effort to expand postsecondary participation through financial aid, affirmative action, college outreach, and other programs. As a result, we have increased the flow of historically underrepresented groups into higher education. But how well have we served these students?
Based on limited but high-quality research on elite colleges and universities, we are confident that African American students who attend these institutions are more likely to complete their degree than they would have been had they attended a less prestigious school (Bowen & Bok, 1998; Long, 2008; Small & Winship, 2007). However, beyond the observation that completion rates vary widely across colleges and universities that appear to serve similar populations of students, we do not know what leads some students to complete their degree and others to fail to do so. More to the point, we do not know whether the costs of attendance borne by marginal students who are the intended beneficiaries of programs that expand postsecondary participation outweigh the benefits they receive from attendance.
Let us be clear here: We believe that expanding postsecondary access is a moral imperative. Expanding access is not enough, however. In an oft-quoted speech that anticipated federal affirmative action programs, President Lyndon B. Johnson said, You do not take a person who, for years, has been hobbled by chains and liberate him, bring him up to the starting line in a race and then say, you are free to compete with all the others, and still justly believe that you have been completely fair (Bowen & Bok 1998, p. 6). In the absence of adequate programs of social and academic support, we fear that this is exactly what we have said to disadvantaged students whom we have induced to attend (competitive) colleges and universities. We have been satisfied with expanding access to college, assuming that the rest would take care of itself.
Of course, institutions vary in the degree to which they provide the sort of support services that might help students persist in college. We know little about the services that institutions provide or the degree to which their programs are effective in helping students attain a degree. This strikes us as a critically important area for future research.
DATA SHARING AND THE USE OF EXPERIMENTAL STUDY DESIGN
Much of what we are calling for requires new data collection efforts, and data collection is very costly. However, we believe that researchers and funders can minimize costs by coordinating their efforts with state education agencies and taking advantage of the data collected by other organizations, such as the College Board, ACT, and the National Student Clearinghouse. If students are willing to allow their records to be linked to these sources and if these organizations agree to provide those data, we can drastically reduce the burden placed on student and parent respondents and thus reduce the cost of data collection. Through grants from the U.S. Department of Education and private foundations like the Bill and Melinda Gates Foundation (Lederman, 2009), a number of states and organizations (most notably the National Student Clearinghouse) are making progress in this area.
This approach has another potential benefit as well. If we can rely on other organizations to collect essential outcome data, like transfer and persistence to degree, and inputs like test scores, parental education, and family income, we can concentrate more of our research resources on designing and implementing interventions through field experiments. Experimental design has long been considered the gold standard for causal inference, but for a variety of reasons, field experiments in education in general, and higher education in particular, are rare (Kurlaender et al., 2006). Yet some of the questions we believe are most important could be answered most effectively, at least in part, through carefully designed field experiments.
Although experiments are more effective than other designs in establishing the mean effect of an intervention on an outcome, they are limited in their capacity to illuminate how and why effects occur. Furthermore, the power to measure differences in the treatment effect across subpopulations is limited by sample stratification decisions made at the beginning of the study and population distributions. To overcome these important limitations, we urge researchers to continue collecting carefully designed survey data and to involve small groups of test subjects in qualitative studies. Qualitative studies can be especially informative because they help researchers generate new ideas and provide insights into the thought processes and subjective experiences of students and parents.
Finally, we urge researchers and funders alike to demand better alignment among behavioral theories, proposed interventions, study design, and analytic techniques. We should be explicit in our studies on all these points and should not limit ourselves to what has been done in the past. For example, studies that aim to understand how information affects postsecondary success should be explicit about how information matters in theoretical and behavioral terms, when it matters (predisposition, search, and so on), and how the studys design will increase our understanding of this process. Statistical models must match behavioral models. If uncertainty is an important theoretical component of a model, uncertainty should be properly operationalized formally rather than plugged into a standard linear probability or discrete choice model. If learning is theorized to occur over some period of time, statistical models that allow for updating and correlated errors in subjective assessments should be estimated, rather than estimating a series of hierarchical linear models and hoping for the best.
Increasing alignment is not easy; it requires continually learning new methods of data collection and analysis. Fortunately, we have available to us literatures that few higher education researchers have tapped. For example, work in transportation science and marketing has substantially advanced the flexibility of discrete choice models, and marketing research has developed complex and behaviorally realistic ways of measuring and modeling the choice process. Psychologists have made tremendous strides in the area of cognition, information processing, and decision making. We should not limit ourselves to the substantive areas in which we were trained, but should instead take advantage of the tremendous knowledge base that those in other fields have accumulated. Much of what we advocate is readily attainable by engaging more seriously in interdisciplinary dialogue.
This research was supported by funding from Lumina Foundation and the Social Science Research Council. The authors are grateful to Luis Fraga, Jennifer Holdaway, David Mustard, Margaret Terry Orr, Barbara Schneider, Bill Trent, and other participants in the Transition to Higher Education Project for valuable guidance and to Kim Goyette and Ann Mullen for comments on an earlier draft. Any remaining errors are those of the authors.
1. Note, however, that other articles in this volume address stratification by sex (Buchmann, 2009) and by English language ability and citizenship status (Rodriguez & Cruz, 2009).
2. Authors calculations based on Table 6 in Bozick and Lauff (2007)
3. Unfortunately, the authors did not present data by nativity for Hispanics, blurring an important distinction between the educational outcomes of those born in the United States and those who had immigrated.
4. The definition of socioeconomic status changes across data sets used by Adelman. In general, it is an aggregate of parental education; occupation; family income; and home resources like encyclopedias, newspapers, and magazines.
5. Need is defined as the average poverty threshold for a family of a given size, taken over the same period as average family income.
6. Our estimates are based on tabulations of data from High School and Beyond (senior cohort), the National Educational Longitudinal Study (1988), and the Educational Longitudinal Study (2002).
7. The TRIO programs include Talent Search, Upward Bound, and the McNair scholars program.
8. Much of our discussion of these concepts draws from more comprehensive reviews of Bourdieus work produced by Horvat (2001) and DiMaggio (1979). In singling out these concepts, we recognize that some would accuse us of disregarding the project in which Bourdieu is engaged, a complete account of social stratification. Reviewers of Bourdieus work have emphasized the cohesiveness of his approach to understanding social action and the problems inherent in extrapolating from his theoretical framework (Horvat).
9. For an analysis of how early decision benefits advantaged students, see Avery, Fairbanks, and Zeckhouser (2004).
Adelman, C. (2004). Principal indicators of student academic histories in postsecondary education: 19722000. Washington, DC: U.S. Department of Education.
Akerlof, G. A. (1997). Social distance and social decisions. Econometrica, 65, 10051027.
American Council on Education. (2006). Missed opportunities revisited: New information on students who do not apply for financial aid. Washington, DC: Author.
Arum, R., Gamoran, A., & Shavit, Y. (2007). More inclusion than diversion: Expansion, differentiation, and market structure in higher education. In Y. Shavit, R. Arum, & A. Gamoran (Eds.), Stratification in higher education (pp. 138). Palo Alto, CA: Stanford University Press.
Astin, A. W., & Oseguera, L. (2004). The declining equity of American higher education. Review of Higher Education, 27, 321341.
Avery, C., Fairbanks, A., & Zeckhouser, R. (2004). The early admissions game: Joining the elite. Cambridge, MA: Harvard University Press.
Avery, C., & Hoxby, C. (2004). Do and should financial aid packages affect students' college choices? In C. Hoxby (Ed.), College choices: The economics of where to go, when to go, and how to pay for it (pp. 239299). Chicago: University of Chicago Press.
Avery, C., & Kane, T. (2004). Student perceptions of college opportunities: The Boston COACH Program. In C. M. Hoxby (Ed.), College choices: The economics of where to go, when to go, and how to pay for it (pp. 355394). Chicago: University of Chicago Press.
Basinger, J., & Smallwood, S. (2004, March 12). Harvard gives a break to parents who earn less than $40,000 a year. Chronicle of Higher Education, 50, A35.
Bassett, W. F., & Lumsdaine, R. L. (2001). Probability limits: Are subjective assessments adequately accurate? Journal of Human Resources, 36, 327363.
Becker, G. S. (1962). Investment in human capital: A theoretical analysis. Journal of Political Economy, 70(5 Pt. 2), 949.
Becker, G. S. (1993). Human capital : A theoretical and empirical analysis, with special reference to education (3rd ed.). Chicago: University of Chicago Press.
Berger, M. C. (1988). Predicted future earnings and choice of college major. Industrial and Labor Relations Review, 41, 418429.
Bielby, W. T. (1981). Models of status attainment. Research in Social Stratification and Mobility, 1, 326.
Bjorklund, A., Jantti, M., & Solon, G. (2006). Nature and nurture in the intergenerational transmission of socioeconomic status: Evidence from Swedish children and their biological and rearing parents. Unpublished manuscript, National Bureau of Economic Research, Cambridge, MA.
Black, D., & Smith, J. (2006). Estimating the returns to college quality with multiple proxies for quality. Journal of Labor Economics, 24, 701728.
Black, S. E., & Sufi, A. (2002). Who goes to college? Differential enrollment by race and family background. Unpublished manuscript, National Bureau of Economic Research, Cambridge, MA.
Blanco, C. D. (2005). Early commitment financial aid programs: Promises, practices, and policies: Boston: Education Resources Institute, Pathways to College Network.
Blau, P. M., & Duncan, O. D. (1967). The American occupational structure. New York: Free Press.
Blossfeld, H.-P., & Shavit, Y. (1993). Persisting barriers: Changes in educational opportunities in thirteen countries. In Y. Shavit & H.-P. Blossfeld (Eds.), Persistent inequality: Changing educational attainment in thirteen countries (pp. 123). Boulder, CO: Westview Press.
Boudon, R. (2003). Beyond rational choice theory. Annual Review of Sociology, 29, 121.
Bourdieu, P. (1973). Cultural reproduction and social reproduction. In R. Brown (Ed.), Knowledge, education, and cultural change: Papers in the sociology of education (pp. 71112). London: Tavistock.
Bourdieu, P. (1996). The state nobility: Elite schools in the field of power (L. C. Clough, Trans.). Stanford, CA: Stanford University Press.
Bourdieu, P., & Passeron, J.-C. (1990). Reproduction in education, society and culture (R. Nice, Trans.). London: Sage.
Bowen, W. G., & Bok, D. (1998). The shape of the river: Long-term consequences of considering race in college and university admissions. Princeton, NJ: Princeton University Press.
Bowen, W. G., Kurzweil, M. A., & Tobin, E. M. (2005). Equity and excellence in American higher education. Charlottesville: University of Virginia Press.
Bowles, S., & Gintis, H. (2002). Schooling in capitalist America revisited. Sociology of Education, 75, 118.
Bowles, S., Gintis, H., & Groves, M. O. (2005). Introduction. In S. Bowles, H. Gintis, & M. O. Groves (Eds.), Unequal chances: Family background and economic success (pp. 122). Princeton, NJ: Russell Sage Foundation.
Bozick, R., & Lauff, E. (2007). Education longitudinal study of 2002 (ELS:2002): A first look at the initial postsecondary experiences of the high school sophomore class of 2002 (No. NCES 2008-308). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.
Brand, J. E., & Halaby, C. N. (2006). Regression and matching estimates of the effects of elite college attendance on educational and career achievement. Social Science Research, 35, 749770.
Breen, R., & Goldthorpe, J. H. (1997). Explaining educational differentials: Towards a formal rational action theory. Rationality and Society, 9, 275305.
Breen, R., & Yaish, M. (2006). Testing the Breen-Goldthorpe model of educational decision making. In S. L. Morgan, D. B. Grusky, & G. S. Fields (Eds.), Mobility and inequality: Frontiers of research in sociology and economics (pp. 232258). Palo Alto, CA: Stanford University Press.
Breland, H., Maxey, J., Gernand, R., Cumming, T., & Trapani, C. (2002). Trends in college admissions 2000: A report of a survey of undergraduate admissions policies, practices, and procedures. New York: College Board.
Bryk, A. S., Lee, V. E., & Holland, P. B. (1993). Catholic schools and the common good. Cambridge, MA: Harvard University Press.
Buchmann, C. (2009). Gender inequalities in the transition to college. Teachers College Record, 111(10).
Camara, W. J., & Schmidt, A. E. (1999). Group differences in standardized testing and social stratification. New York: College Entrance Examination Board.
Card, D. (2001). Estimating the return to schooling: Progress on some persistent econometric problems. Econometrica, 69, 11271160.
Carey, K. (2004). A matter of degrees: Improving graduation rates in four-year colleges and universities. Washington, DC: Education Trust.
Carneiro, P., & Heckman, J. J. (2002). The evidence on credit constraints in post-secondary schooling. Economic Journal, 112(482), 705734.
Carnevale, A. P., & Rose, S. J. (2003). Socioeconomic status, race/ethnicity and selective college admissions. New York: Century Foundation.
Choy, S. P. (2001). Students whose parents did not go to college: Postsecondary access, persistence, and attainment (No. NCES 2001-072). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Coleman, J. S. (1990). Foundations of social theory. Cambridge, MA: Belknap Press of Harvard University Press.
Coley, R. J. (2000). The American community college turns 100: A look at its students, programs, and prospects. Princeton, NJ: Educational Testing Service.
The College Board. (2006). Student search service. Retrieved September 13, 2006, from http://www.collegeboard.com/prod_downloads/highered/ra/StudentSearch.pdf.
Connell, R. W., Ashenden, D. J., Kessler, S., & Dowsett, G. W. (1982). Making the difference: Schools, families and social division. Sydney, Australia: Allan & Unwin.
Cook, P. J., & Frank, R. H. (1993). The growing concentration of top students at elite schools. In C. Clotfelter & M. Rothschild (Eds.), Studies of supply and demand in higher education (pp. 121144). Chicago: University of Chicago Press.
Cookson, P. W., Jr., & Persell, C. H. (1985). Preparing for power : America's elite boarding schools. New York: Basic Books.
Cunha, F., Heckman, J., & Navarro, S. (2005). Separating uncertainty from heterogeneity in life cycle earnings. Oxford Economic Papers, 57, 191261.
Cutler, D. M., & Lleras-Muney, A. (2006). Education and health: Evaluating theories and evidence. Unpublished manuscript, National Bureau of Economic Research, Cambridge, MA.
Dale, S. B., & Krueger, A. B. (2002). Estimating the payoff to attending a more selective college: An application of selection on observables and unobservables. Quarterly Journal of Economics, 117, 14911527.
Davies, S., & Guppy, N. (1997). Fields of study, college selectivity, and student inequalities in higher education. Social Forces, 75, 14171438.
Davis, J. (1965). Undergraduate career decisions. Chicago: Aldine.
Day, J. C., & Newburger, E. C. (2002). The big payoff: Educational attainment and synthetic estimates of work-life earnings (No. P23-210). Washington, DC: U. S. Census Bureau.
DesJardins, S. L., Ahlburg, D. A., & McCall, B. P. (2006). The effects of interrupted enrollment on graduation from college: Racial, income, and ability differences. Economics of Education Review, 25, 575590.
DiMaggio, P. J. (1979). Review essay: On Pierre Bourdieu. American Journal of Sociology, 84, 14601474.
DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48, 147160.
Domina, T. (2005). Brain drain and brain gain: Rising educational segregation in the United States, 19402000. City and Community, 5, 387407.
Dominitz, J., & Manski, C. F. (1996). Eliciting student expectations of the returns to schooling. Journal of Human Resources, 31, 126.
Downey, D. B., von Hippel, P. T., & Broh, B. (2004). Are schools the great equalizer? School and non-school sources of inequality in cognitive skills. American Sociological Review, 69, 613635.
Duncan, O. D. (1968). Social stratification and mobility. In E. H. B. Sheldon & W. E. Moore (Eds.), Indicators of social change: Concepts and measurement (pp. 675719). New York: Russell Sage Foundation.
Duncan, G., Kalil, A., Mayer, S. E., Tepper, R., & Payne, M. R. (2005). The apple does not fall far from the tree. In S. Bowles, H. Gintis, & M. O. Groves (Eds.), Unequal chances: Family background and economic success (pp. 2379). New York: Russell Sage Foundation.
Eide, E., Brewer, D. J., & Ehrenberg, R. G. (1998). Does it pay to attend an elite private college? Evidence on the effects of undergraduate college quality on graduate school attendance. Economics of Education Review, 17, 371376.
Eide, E., Goldhaber, D. D., & Showalter, M. H. (2004). Does Catholic high school attendance lead to attendance at a more selective college? Social Science Quarterly, 85, 13351352.
Eide, E., & Waehrer, G. (1998). The role of the option value of college attendance in college major choice. Economics of Education Review, 17, 7382.
Ellwood, D. T., & Kane, T. J. (2000). Who is getting a college education? Family background and growing gaps in enrollment. In S. Danziger & J. Waldfogel (Eds.), Securing the future: Investing in children from birth to college (pp. 283324). New York: Russell Sage Foundation.
Evans, W. N., & Schwab, R. M. (1995). Finishing high school and starting college: Do Catholic schools make a difference? Quarterly Journal of Economics 110, 941974.
Falsey, B., & Heyns, B. (1984). The college channel: Private and public schools reconsidered. Sociology of Education, 75, 111122.
Farkas, G. (2003). Cognitive and noncognitive traits and behaviors in stratification processes. Annual Review of Sociology, 29, 541562.
Figlio, D. N., & Stone, J. A. (1999). Are private schools really better? Research in Labor Economics, 18, 115140.
Fischhoff, B., Parker, A. M., De Bruin, W. B., Downs, J., Palmgren, C., Dawes, R., et al. (2000). Teen expectations for significant life events. Public Opinion Quarterly, 64, 189205.
Goldin, C., & Katz, L. (2008). The race between education and technology. Cambridge, MA: Belknap Press of Harvard University Press.
Goldrick-Rab, S. (2006). Following their every move: An investigation of social-class differences in college pathways. Sociology of Education, 79, 6179.
Goldrick-Rab, S., & Pferffer, F. (2009). Beyond access: Explaining social class differences in college student mobility. Sociology of Education, 82, 101125.
Goldthorpe, J. H. (2006). On sociology: Illustration and retrospect (2nd ed.). Palo Alto, CA: Stanford University Press.
Gonzalez, A., & Hilmer, M. J. (2006). The role of 2-year colleges in the improving situation of Hispanic postsecondary education. Economics of Education Review, 25, 249257.
Goyette, K. A. (2008). College for some to college for all: Social background, occupational expectations, and educational expectations over time. Social Science Research, 37, 461484.
Goyette, K., & Mullen, A. L. (2006). Who studies the arts and sciences? Social background and the choice and consequences of undergraduate field of study. Journal of Higher Education, 77, 497538.
Grodsky, E. (2002). Constrained opportunity and student choice in American higher education. Dissertation Abstracts International, 63 (8), 3008A.
Grodsky, E. (2007). Compensatory sponsorship in higher education. American Journal of Sociology, 112, 16621712.
Grodsky, E., & Jones, M. T. (2007). Real and imagined barriers to college entry: Perceptions of cost. Social Science Research, 36, 745766.
Grubb, W. N. (2002). Learning and earning in the middle, Part I: National studies of pre-baccalaureate education. Economics of Education Review, 21, 299321.
Halaby, C. N. (2003). Where job values come from: family and schooling background, cognitive ability, and gender. American Sociological Review, 68, 251278.
Hamermesh, D. S., & Donald, S. G. (2008). The effect of college curriculum on earnings: An affinity identifier for non-ignorable non-response bias. Journal of Econometrics, 144, 479491.
Hauser, R. M. (1993). The decline in college entry among African Americans: Findings in search of explanations. In P. M. Sniderman, P. E. Tetlock, & E. G. Carmines (Eds.), Prejudice, politics, and the American dilemma (pp. 271306). Stanford, CA: Stanford University Press.
Hauser, R. M. (2002). Meritocracy, cognitive ability, and the sources of occupational success (Working Paper). Center for Demography and Ecology Working Paper Series. Madison: University of Wisconsin, Center for Demography.
Hauser, R. M., & Featherman, D. L. (1976). Equality of schooling: Trends and prospects. Sociology of Education, 49, 99120.
Hauser, R. M., Warren, J. R., Huang, M.-H., & Carter, W. Y. (2000). Occupational status, education, and social mobility in the meritocracy. In K. Arrow, S. Bowles, & S. Durlauf (Eds.), Meritocracy and economic inequality (pp. 179229). Oxford, England: Oxford University Press.
Haveman, R., & Wilson, K. (in press). Economic inequality in college access, matriculation, and graduation. In S. Dickert-Conlin & R. Rubenstein (Eds.), Higher education and inequality. New York: Russell Sage Foundation.
Hearn, J. C. (1991). Academic and nonacademic influences on the college destinations of 1980 high school graduates. Sociology of Education, 64, 158171.
Hechter, M., & Kanazawa, S. (1997). Sociological rational choice theory. Annual Review of Sociology, 23, 191214.
Heckman, J. J., & Rubinstein, Y. (2001). The importance of noncognitive skills: Lessons from the GED testing program. American Economic Review, 91, 145149.
Heckman, J. J., & Vytlacil, E. (2001). Identifying the role of cognitive ability in explaining the level of and change in the return to schooling. Review of Economics and Statistics, 83, 112.
Hoachlander, G., Sikora, A. C., & Horn, L. (2003). Community college students: Goals, academic preparation, and outcomes (NCES 2003164). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Horn, L., & Bobbitt, L. (2000). Mapping the road to college: First-generation students' math track, planning strategies, and context of support (No. NCES 2000-153). Washington, DC: National Center for Education Statistics.
Horvat, E. M. (2001). Understanding equity and access in higher education: The potential contribution of Pierre Bourdieu. Higher Education: Handbook of Theory and Research, 16, 195238.
Hossler, D., & Gallagher, K. S. (1987). Studying student college choice: A three-phase model and the implications for policymakers. College and University, 62, 207221.
Hout, M. (1984). Status, autonomy, and training in occupational mobility. American Journal of Sociology, 89, 13791409.
Hoxby, C. (1997). How the changing market structure of U.S. higher education explains college tuition. Unpublished manuscript, National Bureau of Economic Research, Cambridge, MA.
Ingels, S. J., Planty, M., & Bozick, R. (2005). A profile of the American high school seniors in 2004: A first lookinitial results from the first follow-up of the Education Longitudinal Study of 2002 (ELS:2002) (No. NCES 2006348). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Jencks, C. (1980). Heredity, environment, and public policy reconsidered. American Sociological Review, 45, 723736.
Jencks, C., Bartlett, S., Corcoran, M., Crouse, J., Eaglesfield, D., Jackson, G., et al. (1979). Who gets ahead? The determinants of economic success in America. New York: Basic Books.
Jencks, C., Perman, L., & Rainwater, L. (1988). What is a good job? A new measure of labor-market success. American Journal of Sociology, 93, 13221357.
Jencks, C., & Tach, L. (2006). Would equal opportunity mean more mobility? In S. L. Morgan, D. B. Grusky, & G. S. Fields (Eds.), Mobility and inequality: Frontiers of research in sociology and economics (pp. 2358). Palo Alto, CA: Stanford University Press.
Jensen, A. R. (1968). Social class, race, and genetics: Implications for education. American Educational Research Journal, 5, 142.
Kane, T. (2001). College-going and inequality: A literature review: New York: Russell Sage Foundation.
Karabel, J. (2005). The chosen: The hidden history of admission and exclusion at Harvard, Yale, and Princeton. Boston: Houghton Mifflin.
Karen, D. (2002). Changes in access to higher education in the United States: 19801992. Sociology of Education, 75, 191210.
Katz, L. F., & Autor, D. H. (1999). Changes in the wage structure and earnings inequality. In O. Ashenfelter & D. Card (Eds.), Handbook of labor economics (Vol. 3A, pp. 14631555). New York: Elsevier Science.
Kenny, L. W., Lee, L.-F., Maddala, G. S., & Trost, R. P. (1979). Returns to college education: An investigation of self-selection bias based on the Project TALENT data. International Economic Review, 20, 775789.
Kerckhoff, A. C. (1976). The status attainment process: Socialization or allocation? Social Forces, 55, 368381.
Kohn, M. L. (1977). Class and conformity: A study in values. Chicago: University of Chicago Press.
Kurlaender, M., Scott-Clayton, J., Dynarski, S., Jencks, C., Kane, T., & Mehta, J. (2006). Strategies for increasing college completion: An experimental approach. Cambridge, MA: New Vision.
Lareau, A. (2000). Home advantage: Social class and parental intervention in elementary education. Lanham, MD: Rowman and Littlefield.
Lauderdale, D. S. (2001). Education and survival: Birth cohort, period, and age effects. Demography, 38, 551561.
Lederman, D. (2009, February 13). A national (but not federal) student database? Inside Higher Education. Retrieved from http://www.insidehighered.com/news/2009/02/13/data.
Lee, V. E., & Burkam, D. T. (2002). Inequality at the starting gate: Social background differences in achievement as children begin school. Washington, DC: Economic Policy Institute.
Light, A., & Strayer, W. (2000). Determinants of college completion: School quality or student ability? Journal of Human Resources, 35, 299332.
Long, M. C. (2008). College quality and early adult outcomes. Economics of Education Review, 27, 588602.
Lucas, S. R. (1999). Tracking inequality: Stratification and mobility in American high schools. New York: Teachers College Press.
Manski, C. F. (1989). Schooling as experimentation: A reappraisal of the postsecondary dropout phenomenon. Economics of Education Review, 8, 305397.
Manski, C. F. (1993). Adolescent econometricians: How do youth infer the returns to schooling? In C. Clotfelter & M. Rothschild (Eds.), Studies of supply and demand in higher education (pp. 4357). Chicago: University of Chicago Press.
Manski, C. F., & Wise, D. A. (1983). College choice in America. Cambridge, MA: Harvard University Press.
Marcotte, D. E., Bailey, T., Borkoski, C., & Kienzl, G. S. (2005). The returns of a community college education: Evidence from the National Education Longitudinal Survey. Educational Evaluation and Policy Analysis, 27, 157175.
Mare, R. D. (1995). Changes in educational attainment and school enrollment. In R. Farley (Ed.), State of the union: America in the 1990s (pp. 155213). New York: Russell Sage Foundation.
Mare, R. D., & Chang, H.-C. (2006). Family attainment norms and educational stratification in the United States and Taiwan: Changing patterns of educational attainment in the United States. In S. L. Morgan, D. B. Grusky, & G. S. Fields (Eds.), Mobility and inequality: Frontiers of research in sociology and economics (pp. 195231). Palo Alto, CA: Stanford University Press.
McCarthy, B. (2002). New economics of sociological criminology. Annual Review of Sociology, 28, 417442.
McDonough, P. M. (1997). Choosing colleges: How social class and schools structure opportunity. Albany: State University of New York Press.
McDonough, P. M., Korn, J., & Yamasaki, E. (1997). Access, equity, and the privatization of college counseling. Review of Higher Education, 20, 297317.
McDonough, P. M., Ventresca, M., & Outcalt, C. (2000). Field of dreams: Organization field approaches to understanding the transformation of college access, 19651995. In J. C. Smart & W. G. Tierney (Eds.), Higher education: Handbook of theory and research (Vol. 15, pp. 371405). New York: Agathon Press.
Mishel, L., Bernstein, J., & Allegretto, S. (2005). The state of working America 2004/2005. Ithaca: ILR Press, an imprint of Cornell University Press.
Montmarquette, C., Cannings, K., & Mahseredijian, S. (2002). How do young people choose college majors? Economics of Education Review, 21, 543556.
Montmarquette, C., Mahseredjiana, S., & Houleb, R. (2001). The determinants of university dropouts: A bivariate probability model with sample selection. Economics of Education Review, 20, 475484.
Morgan, S. L. (1998). Adolescent educational expectations: Rationalized, fantasized, or both? Rationality and Society, 10, 131161.
Morgan, S. L. (2005). On the edge of commitment: Educational attainment and race in the United States. Palo Alto, CA: Stanford University Press.
Morris, M., & Western, B. (1999). Inequality in earnings at the close of the twentieth century. Annual Review of Sociology, 25, 623657.
Mundel, D. S., & Coles, A. S. (2004). Summary project report: An exploration of what we know about the formation and impact of perceptions of college prices, student aid, and the affordability of college-going and a prospectus for future research. Boston: Education Resources Institute.
Niu, S. X., & Tienda, M. (2008). Choosing colleges: Identifying and modeling choice sets. Social Science Research, 37, 416433.
Oakes, J., Gamoran, A., & Page, R. (1992). Curriculum differentiation: Opportunities, outcomes, and meanings. In P. W. Jackson (Ed.), Handbook of research on curriculum: A project of the American Educational Research Association (pp. 570608). New York: Macmillan.
Pacia, R., & Sadeghi, Y. (2005). Yale reforms financial aid policy. Retrieved September 27, 2006, from http://www.yaledailynews.com/articles/findlegacy/28709.
Pallas, A. (2000). The effects of schooling on individual lives. In M. T. Hallinan (Ed.), Handbook of the sociology of education (pp. 499525). New York: Kluwer Academic.
Perie, M., Moran, R., & Lutkus, A. D. (2005). NAEP 2004 trends in academic progress: Three decades of student performance in reading and mathematics (No. NCES 2005-464). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Statistics.
Persell, C. H., & Cookson, P. W., Jr. (1990). Chartering and bartering: Elite education and social reproduction. In P. W. Kingston & L. Lewis (Eds.), The high-status track (pp. 2549). Albany: State University of New York Press.
Person, A. E., Rosenbaum, J. E., & Deil-Amen, R. (2006). Student planning and information problems in different college structures. Teachers College Record, 108, 374396.
Provasnik, S., & Shafer, L. L. (2004). Historically Black colleges and universities, 1976 to 2001 (No. NCES 2004062). Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Reay, D. (1998). Always knowing and never being sure: Familial and institutional habituses and higher education choice. Journal of Education Policy, 13, 519529.
Reay, D. (2004). It's all becoming a habitus: Beyond the habitual use of habitus in educational research. British Journal of Sociology of Education, 25, 421444.
Reay, D., David, M. E., & Ball, S. (2005). Degrees of choice: Social class, race, gender and higher education. Sterling, VA: Trentham Books.
Reynolds, J., Stewart, M., MacDonald, R., & Sischo, L. (2006). Have adolescents become too ambitious? High school seniors' educational and occupational plans, 1976 to 2000. Social Problems, 53, 186206.
Roberts, J. H., & Lattin, J. M. (1997). Consideration: Review of research and prospects for future insights. Journal of Marketing Research, 34, 406410.
Roderick, M., Nagaoka, J., Coca, V., & Moeller, E. (2008). From high school to the future: Potholes on the road to college. Chicago: Consortium on Chicago School Research.
Rodriguez, G. M., & Cruz, L. (2009). The transition to college of English learner and undocumented immigrant students: Resource and policy implications. Teachers College Record, 111(10).
Roksa, J., Grodsky, E., Arum, R., & Gamoran, A. (2007). Changes in higher education and social stratification in the United States. In Y. Shavit, R. Arum, & A. Gamoran (Eds.), Stratification in higher education (pp. 165191). Palo Alto, CA: Stanford University Press.
Rosenbaum, J. E. (2001). Beyond college for all: Career paths for the forgotten half. New York: Russell Sage Foundation.
Ross, C. E., & Mirowsky, J. (1999). Refining the association between education and health: The effects of quantity, credential, and selectivity. Demography, 36, 445460.
Rouse, C. (2004). Low-income students and college attendance: An exploration of income expectations. Social Science Quarterly, 85, 12991317.
Rumberger, R. W., & Thomas, S. L. (1993). The economic returns to college major, quality and performance: A multilevel analysis of recent graduates. Economics of Education Review, 12, 119.
Schneider, B. L., & Stevenson, D. (1999). The ambitious generation: America's teenagers, motivated but directionless. New Haven, CT: Yale University Press.
Sewell, W. H., Haller, A. O., & Ohlendorf, G. W. (1970). The educational and early occupational status attainment process: Replication and revision. American Sociological Review, 35, 10141024.
Sewell, W. H., Haller, A. O., & Portes, A. (1969). The educational and early occupational attainment process. American Sociological Review, 34, 8392.
Small, M. L., & Winship, C. (2007). Black students graduation from elite colleges: Institutional characteristics and between-institution differences. Social Science Research, 36, 12571275.
Snyder, T. D., Tan, A. G., & Hoffman, C. M. (2006). Table 181: College enrollment and enrollment rates of recent high school completers, by race/ethnicity: 1960 through 2004. Digest of Education Statistics 2005. Washington, DC: U.S. Department of Education, National Center for Education Statistics.
Stinebrickner, T. R., & Stinebrickner, R. (2003). Understanding educational outcomes of students from low income families: Evidence from a liberal arts college with a full tuition subsidy program. Journal of Human Resources, 38, 591617.
Stocké, V. (2007). Explaining educational decision and effects of families social class position: An empirical test of the BreenGoldthorpe model of educational attainment. European Sociological Review, 23, 505519.
Swanson, C. B. (2004). Who graduates? Who doesn't? A statistical portrait of public high school graduation, Class of 2001. Washington, DC: Urban Institute.
Taber, C. R. (2001). The rising college premium in the eighties: Return to college or return to unobserved ability? Review of Economic Studies, 68, 665691.
Teachman, J. D., & Paasch, K. (1998). The family and educational aspirations. Journal of Marriage and the Family, 60, 704714.
Thomas, S. L., & Zhang, L. (2005). Post-baccalaureate wage growth within four years of graduation: The effects of college quality and college major. Research in Higher Education, 46, 437459.
Turley, R. N. L. (2006). When parents want children to stay home for college. Research in Higher Education, 47, 823846.
U.S. Department of Education, N. C. f. E. S. (2001). Paving the way to postsecondary education: K-12 intervention programs for underrepresented youth. Report of the National Postsecondary Education Cooperative Working Group on Access to Postsecondary Education (No. NCES-2001-205). Washington, DC: ED Pubs.
Vargas, J. H. (2004). College knowledge: Addressing information barriers to college. Boston: Education Resources Institute.
Warren, J. R. (2004). State-level high school completion rates: Concepts, measures, and trends. Education Policy Analysis Archives, 13(51), 138.
Willis, R. J., & Rosen, S. (1979). Education and self-selection. Journal of Political Economy, 87(5), S7S36.
Wolniak, G. C., Seifert, T. A., Reed, E. J., & Pascarella, E. T. (2008). College majors and social mobility. Research in Social Stratification and Mobility, 26, 123139.
Zhang, L. (2005). Advance to graduate education: The effect of college quality and undergraduate majors. Review of Higher Education, 28, 313338.