Academic and Nonacademic Influences on the College Destinations of 1980 High School Graduates

Academic and Nonacademic Influences on the College Destinations of 1980 High SchoolGraduatesAuthor(s): James C. HearnSource: Sociology of Education, Vol. 64, No. 3 (Jul., 1991), pp. 158-171Published by: American Sociological AssociationStable URL: http://www.jstor.org/stable/2112849 .

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ACADEMIC AND NONACADEMIC INFLUENCES ON THE COLLEGE DESTINATIONS OF 1980 HIGH SCHOOL GRADUATES

James C. Hearn University of Georgia

Social scientists and policymakers have long been interested in equality of opportunity to pursue postsecondary education. This research focused on one aspect of that issue, the relationships between high school graduates' personal characteristics (ability, achievements, expectations, socioeconomic status, race- ethnicity, and gender) and the nature of the postsecondary institutions they attend. Based on national data for college attenders from the high school class of 1980, the findings suggest that nonacademic factors, particularly socioeconomic background, affected graduates' postsecondary destinations. For example, students from lower-income families were particularly likely to attend lower- selectivity institutions, regardless of their levels of academic ability, achievement, and expectations. The possible reasons for the persistence of such inequalities, despite policy efforts to limit or remove them, are discussed.

The pursuit of equal opportunity to attend postsecondary educational institutions has long been a focus of national attention (Aaron 1978; Gladieux and Wolanin 1976; Leslie 1977). One aspect of this issue, the college destinations of recent high school graduates, has become an increasingly significant research topic in recent years. Demographic, socioeconomic, and legislative trends have lowered the barriers to access to college to such an extent that virtually any high school graduate can now obtain entry into some part of the postsecondary system (Carnegie Coun- cil 1980). That system is extremely differentiated, however: While entry into some sectors (such as the community colleges) is granted easily under a relatively egalitarian, "open admissions" ethic, entry into other, more prestigious and better-funded sectors (the elite liberal arts colleges, for example), is highly restricted and granted ostensibly only on the basis of tight meritocratic standards (Clark 1983; Trow 1984). Thus, today,

barriers to attendance appear to be greater in regard to where the high school graduate can attend than in regard to whether the graduate can enter the system.

INSTITUTIONAL STRATIFICATION

Trow (1984) pointed out that these barriers reflect a definite stratification system in U.S. higher education: Institutions are clearly ordered by prestige and levels of resources, and an institution's place in this order tends to be inversely related to its level of openness to the masses. What is more, the stratification system is remarkably durable over time:

The advantages of elite institutions are so overwhelming that they create what is for them (but perhaps not for the rest of higher education or the larger society) a kind of "virtuous circle" in which advantage begets advantage. . . . [T]he resources and activities that mark high-status institutions gravitate toward those same institutions, which already have the most of them. [T]he tendency of like to beget like seems to be strong enough, with a few exceptions, to sustain elite higher education against the strains of rapid growth, democratization, bureaucratization, and governmental regulation. (Trow 1984, p. 149)

Thus, as Trow noted, Merton's (1968) concept of the "Matthew effect" may apply to higher education.' That is, institutional ad-

This research was supported by a research grant from the Spencer Foundation and by computing and faculty research grants from the University of Minnesota. The author would like to thank K. C. Green of the Higher Education Research Institute at UCLA for his help with selectivity data and Susan Urahn and Mary Peterson for their help in the data analysis. The author also appreciates the helpful comments of Elaine El-Khawas, Richard Richardson, and William H. Sewell. Address all correspondence to Professor James C. Hearn, 300 Candler Hall, Institute of Higher Education, University of Georgia, Athens, GA 30602.

' Merton's concept (1968) is drawn from the statement of Jesus in the Gospel of Matthew: "For unto every one that hath shall be given, and he shall have in abundance: but from him that hath not

158 Sociology of Education 1991, Vol. 64 (July): 158-171



INFLUENCES ON COLLEGE DESTINATIONS 159

vantages and disadvantages may tend to cumulate over time, with only rare shifts in institutional fortunes (either from advantaged to disadvantaged status, or vice versa). In an ongoing and largely irreversible process, existing status hierarchies among institutions are reproduced and elaborated.

From the perspective of the opportunity for attainment, this deeply embedded institutional stratification is important only if status, income, power, and other rewards in the society are distributed on the basis of the college one attends. That is, the institutional stratification system's significance depends upon the institutional Matthew effect being paralleled by an individual Matthew effect, through which those who are fortunate enough to attend the most advantaged institutions receive, in turn, further good fortune as a result of their attendance. Such a pattern indeed appears to hold, and in at least three ways.

First, the nature of the college a student attends significantly influences the amount of education he or she is likely to obtain (Wegner and Sewell 1970). The amount of education obtained, in turn, affects eventual socioeconomic attainments (Sewell 1971).

Second, a growing number of studies suggests that the nature of the specific college one attends also influences eventual social and economic attainments in ways that are independent of its effects on subsequent levels of education. Employing a multivariate income-attainment model, Solmon (1975) found that an index of institutions' reputations predicted their graduates' lifetime earnings, independent of students' academic and personal characteristics (see also, Trusheim and Crouse 1981; Wise 1975). In causally focused, longitudinal analyses of status attainment among college graduates, Smart and Pascarella (1986) found that the selectivity of colleges positively affected graduates' eventual status attainments, and Pascarella, Smart,

and Stoecker (1989, p. 101) found that "undergraduate college quality (at least as measured by student-body selectivity and educational resources) may be a particularly salient influence on the early educational and occupational attainments of blacks."

Useem and Karabel (1986) pursued a distinctive "top-down" methodological approach, focusing on the educational back- grounds of corporate managers in different ranks, rather than on the attainment outcomes of a wide sample of college graduates, but came to conclusions similar to those of more traditional studies: The rank of their postsecondary institutions affected the rates of ascent in corporations for both undergraduate and professional degree holders. In addition, several studies have found distinctive college effects on socioeconomic attainment for graduates in particular major fields and occupations (see, for example, Smart 1986, 1988; Tinto 1980). Thus, through such mechanisms as screening, credentialing, and network-based allocation, the most selective and prestigious institutions seem to facilitate the life chances of their graduates.

Third, the nature of individuals' experiences while in college may influence important outcomes other than the eventual attainment of status and income, such as religious and racial-ethnic tolerance, general content- edness, and participation in civic activities (Feldman and Newcomb 1969). To the extent that resource-rich institutions are especially able to devote resources to these educational ends, their advantages may multiply.

Therefore, because attending a more selective, resource-rich institution has been associated with measurable positive impacts on educational attainment, income attainment, status attainment, and socially valued aspects of citizenship, the issues of who attends such institutions and how attendance patterns at such institutions change over time are of both policy and theoretical importance. From a policy perspective, if attendance at elite institutions is made especially difficult (finan- cially or otherwise) for disadvantaged popula- tions, the nation may be said to be short- changing its long-standing goal of equal educational opportunity. From a theoretical perspective, the effects of the educational system on both the alleviation and reproduction of social inequalities and the changes in those relative roles over time are subjects of continuing interest and appreciable dispute

shall be taken away even that which he hath." Merton suggested that among scientists, the effect consisted "in the accruing of greater increments of recognition for particular scientific contributions to scientists of considerable repute and the withhold- ing of such recognition from scientists who have not yet made their mark" (1968, p. 59). For an example of the usage of the concept in recent theoretical and empirical work, see Dannefer (1987).



160 HEARN

(see Hum 1978). Accordingly, an ongoing assessment of possible barriers to equality of opportunity in students' choices of colleges seems warranted. The present research ad- dressed that issue by examining the following question: Are minority, female, and socioeconomically disadvantaged college students in the United States disproportionately attending institutions with lower levels of academic resources?

Previous research on the topic (Alexander and Eckland 1977; Karabel and Astin 1975; Sewell 1971; Sewell and Shah 1967) has consistently suggested that the primary direct forces in the matching of colleges and students have been academic ability, academic achievement, and educational aspirations, but that socioeconomic status (SES), race, ethnicity, and gender not only directly influence college destinations in important ways but play a dominant indirect role, through their effects on academic outcomes in high school. Ascriptive factors help channel the development of youths' ability and achievement and are arguably more influential in the formation of educational aspirations than are the ongoing, putatively universalis- tic cues that students receive regarding their academic talents. Thus, contrary to meritocratic norms, entry into the most prestigious and selective colleges has been found to be a function not only of test scores, grades, and the like, but of ascriptive factors. Disadvan- taged, minority, and female college students in the 1950s, 1960s, and 1970s were disproportionately located in less selective and less materially well-off postsecondary institutions, a pattern that held even after statistical controls for students' academic characteristics were applied.2 The root causes of the unequal pattern may lie more in socialization and contextual factors than in outright discrimination or lack of financing (see Jackson 1982; Rosenfeld 1980), but the

conclusion of Karabel and Astin (1975, p. 395) seems an appropriately concise summary of the research thus far: "The most fundamental aspects of tracking-the allocation of students to educational programs which roughly reflect both their social origins and an occupational destination commensurate with those origins, now exist within higher education. "

The context of college attendance has changed somewhat in the years since the earlier studies' data were gathered, however. For example, between 1972 and 1980, the federal government greatly increased its attention to providing equal opportunity in college choices (Gladieux 1980). To what extent are attendance patterns changing in light of those changes in policy? This development, the growing competition among institutions for students (Stadtman 1980), and a host of other factors provide good reason for a new assessment using nationally representa- tive data for the 1980s.

THEORETICAL PERSPECTIVE

Debates and studies on the nature of equality of opportunity at precollege levels of education (such as the well-known "Coleman Report," see Coleman et al. 1966) have concentrated on the notion of "equity of condition": Are students receiving a similar quality of schooling, regardless of their background? A parallel definition of the "success" of this policy at the college level would therefore be "equity of condition." Since meritocracy is a legitimated value in the college-selection process in this country, however, a second definition of the success of this policy might be explored: equity of condition among students of equal academic ability, achievement, and aspirations. Such a definition of success would not exclude a pattern of the "best students" attending the "best schools." A third, more radical, definition might be called "redemptive equity": Success lies in providing the "best education" to the least prepared or most disadvantaged students, to narrow the preex- isting differences among college students before they enter the world of work.

Alternative Hypotheses

Each definition of equity has been consid- ered by other analysts as a possible standard

2 The pattern of gender differences in college destinations has paralleled those in other areas of attainment. For example, Sandell (1977) found that ability plays a larger role in men's destinations than in women's, and Alexander and Eckland (1977) found that socioeconomic status plays a somewhat larger role for women than for men. Both findings echo those of studies of attainment in secondary schools, studies of college access, and studies of college graduation (see Rosenfeld 1980; Sewell 1971; Sewell and Shah 1967).




by which to categorize or judge educational systems (see Astin 1971; Bowman 1970; Miller 1977; Trow 1984). The research described here allows an assessment of the extent to which recent national postsecondary data fit each of the three distinct standards. The standards can be stated as alternative hypotheses regarding the current workings of the system that matches postsecondary institutions and their prospective students:

HYPOTHESIS 1. Strict equity of condition: Individual characteristics of prospective college students bear no significant relationship to the level of resources of the institution attended.

HYPOTHESIS 2. Meritocratic equity of condition: The racial, ethnic, gender, and socioeconomic characteristics of prospective college students bear no significant relationship to the level of resources of the institution attended, once the confounding influences of students' academic characteristics are controlled.

HYPOTHESIS 3. Redemptive equity: Minority race or ethnicity, female gender, a lower socioeconomic background, and lower academic ability and achievement each have a positive relationship to the level of resources of the institution attended.

Three criticisms may be raised regarding this approach. First, the three alternative hypotheses carry with them a critical and debatable assumption: that the "quality of education" at postsecondary institutions may be assessed, at least indirectly, by way of the levels of human and material resources at those institutions. Assessments of equity in choices of attendance in postsecondary education are dependent on defensible indicators of institutional quality, but the available indicators are rarely ideal. Selectivity in undergraduate admissions may be viewed as one kind of human resource held by an institution. Selective admissions may suggest a high intellectual quality in campus life, and indicators of selectivity are correlated closely with levels of faculty training (Astin 1982); institutional prestige (see Clark 1983); and, as noted earlier, graduates' attainments. Indica- tors of selectivity, at best, provide only an indirect measure of academic quality, however. Similar criticism may be applied to institutions' per-student spending on educational programs, a second indicator linked to the quality of human and material resources

on campuses. All else being equal, an institution with above-average faculty training, a well-stocked library, extensive com- puter facilities for students, and other evidence of the extraordinary devotion of resources to students' needs would seem superior to one without such characteristics. Yet, like selectivity, spending for education is only an imperfect index of educational quality (Bowen 1981). Both the selectivity and spending approaches to the assessment of quality suffer especially from their aggrega- tion at the institutional level, since in reality each student on a campus experiences a different kind of education, depending on the specifics of his or her major, contacts with faculty members, living situation, and so forth. Unfortunately, these undeniable limita- tions are largely unavoidable in the available national data. At least for the foreseeable future, it appears that national assessments of barriers to equality in college destinations must rely on admittedly inadequate indicators.

Second, as a vision of the college-choice process of individual students, the present model is underspecified. The factors behind the process are numerous, and many are not included here. A comprehensive model may incorporate a more detailed variety of economic variables, as well as a wider-ranging set of personality and contextual variables. It is clear, for example, that the details of financial-aid awards to students, levels of college tuition, and parental income can play a significant role in the specific college one attends (Jackson 1982; Leslie and Brinkman 1988; Manski and Wise 1983). Similarly, personal qualities not included here, such as maturity, poise, and clarity of goals, as determined by admissions officers from autobiographical essays, interviews, and let- ters of recommendation, are associated with applications to, acceptance by, and attendance patterns in colleges (see American Associa- tion of Collegiate Registrars 1980; Klitgaard 1985; Whitla 1984; Willingham and Breland 1982). In addition, the nature of secondary school contexts can play a role in college- attendance behaviors (see Falsey and Heyns 1984).

The emphasis in the present research, however, is more on the structure of outcomes of college choices than on the particulars of the processes of influence. In that sense, the approach is more akin to that



162 HEARN

of a social-structural analysis than to that of a traditional "school and policy effects" model. As Hope (1987, p. 132) noted in his discussion of Blau and Duncan's The Ameri- can Occupational Structure (1967), such causally directed regressions of attainment processes do not purport to "plot the behavior of atomized individuals in a market that is entirely external to them," but rather to characterize "the structure that results from a manifold of decisions: personal, institutional, and political."

Third, one could argue that the present approach may be flawed because of its high level of dependence upon there being ade- quate variation among the sample in scores on the indicators of the independent and outcome variables. Studying the effects of SES or any other characteristic on college destinations is dependent on there being sufficient variation among the indicators to allow meaningful effects to emerge. For example, if college were so expensive that only the rich could attend, then the effects of being from a higher SES background would be negligible in a model of the kind proposed here. What would seem on the surface to be a pristine example of "meritocratic equity of condition" would, in fact, be precisely the opposite. Although this argument is sound, the point may be moot for this analysis. There is, indeed, a high level of variation on the independent and dependent indicators of variables in the national sample used here, as will be noted in later sections of this article. In particular, the income and educational levels of attenders' parents range from quite low to quite high.

RESEARCH DESIGN

Methods. The research presented here employed multiple regression techniques with listwise deletion and weighting of the sample.3 The analysis focused on indicators for two kinds of characteristics of students as explanatory factors: background socioeconomic-ascriptive characteristics (parental income, parents' educational attainments, family size, race, ethnicity, and gender) and academic characteristics (tested ability, high school grades, high school track, high school activities, and educational expectations). As

indicators of dependent variables, the analysis employed indicators of the institution's selectivity and educational and general expenditures per student.

Data. Data on students were drawn from the 1980 and 1982 waves of the High School and Beyond (HS&B) survey of 30,000 American high school seniors (class of 1980). These data were collected for the National Center for Education Statistics (NCES) (see National Opinion Research Center 1983). Data on postsecondary institutions were acquired from NCES and from the Higher Education Research Institute (HERI).4 The sample for the study consisted of the 3,396 high school graduates from the 1980 senior class who responded fully to the relevant HS&B items for this study and attended a recognized postsecondary institution within one year of graduation.5 Senior-year data for these students were matched with follow-up data on the students and with institutional data to construct files with all necessary information for the present study.

Variables and their indicators. Three variables relate to ascribed gender and racial-ethnic characteristics: the indicators for female, Black, and Hispanic students, each of which is in dummy form (1 = yes, 0 = no). Four variables relate to SES characteristics. The first two variables are assessed by indicators of father's education and mother's education, respectively. The code for each indicator is ordinal: 2 = less than high-school graduation; 3 = high-school graduation only;

3Weights used are those suggested by the National Center for Education Statistics.

4 Specifically, data on selectivity were drawn from the HERI SAT File with Additional Institu- tional Data (see HERI 1984). Data on expenditures were drawn from data in the Higher Education General Information Survey for 1980-81 (see NCES 1983). For more details, see the Variables section of this article.

5 The data match was made using the federal government's FICE code. This code is used by the government in its Higher Education General Information Survey (see NCES 1983). Generally, postsecondary institutions having only specialized programs (such as beauticians' schools and bar- bers' colleges) and do not have regular FICE codes, but most other postsecondary institutions do. The number of institutions with FICE codes roughly approximates the 3,000-plus figure often used in studies of the "higher education system," as opposed to the broader notion of the "postsecondary system" (see, for example, Carnegie Council 1980).




4 = fewer than two years of vocational, trade, or business school after high school; 5 = two years or more of vocational, trade, or business school after high school; 6 = fewer than two years of college; 7 = two or more years of college (including a two-year degree); 8 = finished college (a four- or five-year degree); 9 = a master's degree or equivalent; and 10 = a Ph.D., MD, or other advanced professional degree. The second two SES indicators are for family income (coded as follows: 1 = under $7,000, 2 = $7,000 to $11,999, 3 = $12,000 to $15,999, 4 = $16,000 to $19,999, 5 = $20,000 to $24,999, 6 = $25,000 to $37,999, and 7 = $38,000 or more) and family size, as indexed by the number of siblings (coded as follows: 0 = 0 siblings, 1 = 1 sibling, 2 = 2 siblings, 3 = 3 siblings, 4 = 4 siblings, and 5 = 5 or more siblings). This indicator of family size is a composite of several HS&B items. It is used as an SES-related indicator because each sibling represents a potential drain on family income and thus a qualifica- tion on the uncorrected income figure.

Seven indicators in the model are related to the academic characteristics of the student. The indicator of aptitude is a composite score for a standardized test administered to all HS&B respondents. The score is the average of reading, vocabulary, and mathematics scores. The indicator was normed to a mean of 50 for all American high-school seniors in 1980. The indicator for high-school track is a dummy in which 1 = an academic (college- preparatory) track. The indicator of high- school grades is based on a self-report, where 8 = mostly As (or a numerical average of 90 to 100), 7 = about half As and half Bs (or 85-89), 6 = mostly Bs (or an 80-84 average), 5 = about half Bs and half Cs (or a 75-79 average), 4 = mostly Cs (or a 70-74 average), 3 = about half Cs and half Ds (or a 65-69 average), 2 = mostly Ds (or a 60-64 average), and 1 = mostly below D (or an average of below 60). The indicators of high-school activities are each dummies, representing, respectively, student-government work, journalism activity, participation in preprofessional clubs, and participation in debate or drama clubs.

The final indicator of academic characteristics relates to the students' educational expectations. This indicator is coded on a 9-point scale, where 1 = less than high- school graduation; 2 = high-school gradua-

tion only; 3 = vocational, trade, or business school after high school-fewer than two years; 4 = vocational, trade, or business school after high school-two years or more; 5 = college program-fewer than two years of college; 6 = college program-two or more years of college (including a two-year degree); 7 = college program-finished college (four- or five-year degree); 8 = college program-a master's degree or equivalent; and 9 = college program-a Ph.D., MD, or another advanced professional degree.

The two dependent variables for the study relate to the characteristics of the institutions the students first attended in 1980. The first variable, selectivity, is indicated by one-tenth of the combined average score on the Verbal and Math parts of the Scholastic Aptitude Test (SAT) for all students at the institution attended. When the institution tended to rely more for admissions on scores from the American College Testing Program Assess- ment (ACT), a conversion was made to SAT scaling, using a procedure agreed upon by ACT and the Educational Testing Service, producers of the SAT. The selectivity data used are for 1978, the year closest to 1980 of those years for which national selectivity data are available. (For more information on the selectivity indicator and data, which were provided by the Higher Education Research Institute at UCLA, see HERI 1984.) The second dependent variable, institutional spending per undergraduate student, is indicated by one-tenth of the institution's 1980- 81 educational and general expenditures at the undergraduate level per undergraduate full- time-equivalent student.6 The federal govern-

6 This indicator is an approximation of true spending on educational resources per undergraduate. It was constructed by multiplying the proportion of undergraduates of the full-time equivalent [FTE] enrollment at an institution by the total educational and general expenditures at that institution, then dividing the resulting dollar figure by the total enrollment of FTE undergraduates.

It should be noted that the indicator's utility is undoubtedly compromised by two financial facts: economies of scale and institutional differences in spending on graduate students. Economies of scale imply that larger schools will be able to offer educational services similar to those of smaller schools at lower costs. In the present analysis, this pattern implies that schools offering somewhat unequal services may receive the same score on the



164 HEARN

ment's annual Higher Education General Information Survey (see NCES 1983) provided the data used to construct this indicator. These data were collected from the institutions' reports of their financial and enrollment conditions.

RESULTS

Although support for the "strict"-equity and "redemptive"-equity hypotheses was expected to be less pervasive than for the "meritocratic"-equity hypothesis, the explicit statement of the three competing hypotheses was a useful guiding framework for the analysis. Past research suggested that the meritocratic hypothesis would not be fully or consistently supported and that certain aspects of both of the other hypotheses would, indeed, be supported. As the results presented in this section reveal, evidence for each of the three hypotheses was uncovered.

Table 1 presents the correlations, means, and standard deviations for the sample. The simple correlations reveal few surprises: They are in keeping with past results. Blacks and lower-SES students were particularly likely to attend lower-selectivity institutions, and lower-SES students were particularly likely to attend lower-spending institutions. Of course, academically strong students were particularly likely to attend more selective institutions. To a somewhat lesser extent, they were also particularly likely to attend high- spending institutions. Each of these correlations (all significant at p - .05) denies support to the hypothesis of "strict equity of condition" (Hypothesis 1), but some other correlations do not allow that hypothesis to be rejected. For example, Blacks and Hispanics were not especially likely to attend lower- or higher-spending institutions. Although such data are interesting and are not without

relevance for policy, the heart of the study lies in its consideration of the meritocratic- and redemptive-equity hypotheses. The assessment of those hypotheses requires a multivariate approach that goes beyond the bivariate approach of Table 1.

Table 2 presents the results of the multiple regression for institutional selectivity. These results provide strong evidence that the system of matching students and institutions is largely meritocratic in its outwardly most visible aspects. In the full model, which contains both academic and nonacademic characteristics of students, the most powerful effects on entry into a selective institution were, as one would expect, academically based. Test scores dominated all other academic indicators in effects, but students' educational expectations, high-school curricu- lar track, and high-school grades, as well as experiences in the student government, were also significant. Such a pattern would be, in large part, the profile that admissions officers and higher-education leaders would consider expected and desirable. Nevertheless, even in the context of a model containing these and several other academic characteristics, there were still traces of direct nonmeritocratic influences on college destinations in the early 1980s. Father's education, mother's education, and parental income showed significant positive effects on the selectivity of the institution attended. In other words, students with less educated or lower-income parents, as well as Blacks and women, were especially likely to attend lower-selectivity institutions, even if their academic ability and achievements were high. Hispanics showed no such tendency, however, and family size was also unrelated to the selectivity of the institution attended. Overall, the full model explained 27 percent of the variance in institutional selectivity.

Results for levels of per-student expenditures are presented in Table 3. As with selectivity, students' socioeconomic profiles were associated with their outcomes in the full model: Father's education showed a significant positive effect. In addition, in the context of controls for associated SES and academic characteristics, Blacks were particularly likely to attend higher-spending institutions. Females, though, were less likely than were males to attend such institutions, all else being equal. As expected, several academic factors were important in the results. Test

spending indicator. Unequal levels of institutional spending on graduate students would lead to overestimates of spending on undergraduates at institutions with higher levels of spending on graduate students. Nevertheless, in the U.S. higher education system as a whole and in this sample, neither the extent of economies of scale nor the proportion of institutions with substantial levels of spending on graduate education is large (Bowen 1981), so the two undeniable biases in the spending indicator do not seem to pose a fatal problem here.




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166 HEARN

Table 2. Regressions for Institutional Selectivitya

Background Factors Only Full Model

Metric Standardized Metric Standardized Coefficient Coefficient Coefficient Coefficient

Black - 5.85 - .12*** - 3.19 -.06*** Hispanic - 3.29 - .07*** - .20 - .00 Female - 1.52 -.06*** -.92 -.04* Father's education .59 .13*** .23 .05** Mother's education .47 .09*** .30 .06*** Parental income .80 .11*** .51 .07*** Number of siblings - .25 -.03 .03 .00 Tested ability .39 .25*** High-school grades .73 .08*** High-school track 2.63 .11*** High-school student government 1.57 .06*** High-school departmental or

preprofessional club -.45 -.02 High-school journalism .53 .02 High-school drama or debate -.17 -.00 Educational expectations 1.06 .14*** Constant 83.51 51.05

R2 .10*** .27*** *p : .05.

** p C .01. *** p ' .001. a Data are weighted. See the text for definitions of indicators.

scores, grades, and expectations were positive influences on attendance at higher-spending institutions, as were participation in the high-school student government and in an

academic club. All told, the regression model explained 13 percent of the variance in the outcome.

The full-model regression results of Tables

Table 3. Regressions for Institutional Educational and General Expenditures Per Studenta

Background Factors Only Full Model

Metric Standardized Metric Standardized Coefficient Coefficient Coefficient Coefficient

Black 43.00 .03 104.38 .06*** Hispanic - 21.42 - .01 49.25 .03 Female - 56.57 - .07*** - 57.39 -.07*** Father's education 17.95 .12*** 9.80 .07*** Mother's education 8.44 .05** 3.61 .02 Parental income 15.97 .06*** 9.68 .04* Number of siblings - 3.48 - .01 3.49 .01 Tested ability 9.50 .18*** High-school grades 25.06 .08*** High-school track 21.87 .03 High-school student government 44.92 .05** High-school departmental or

preprofessional club 30.59 .03* High-school journalism 3.66 .00 High-school drama or debate 26.09 .03 Educational expectations 22.23 .09*** Constant 326.62 -464.98

.04*** .13*** *p < .05.

**p .01. *** p ' .001. a Data are weighted. See the text for definitions of indicators.




2 and 3 were supplemented by results for regressions containing only background nonacademic factors, also presented in Tables 2 and 3. Such an approach allows more detailed investigation of the effects of the nonacademic independent variables in the model.7 Table 2 reveals that student background characteristics (race/ethnicity, gender, and the SES-based characteristics), by themselves, explain 10 percent of the variance in the selectivity of the institution attended. Table 3 reveals that those factors alone explain 4 percent of the variance in the expenditure level of the institution attended. Thus, in both cases, between one-quarter and one-half the explanatory power of the model derives from nonacademic factors. As expected, much of this total influence was apparently mediated through the influences of nonacademic factors on academic factors; comparing the significant direct (full-model) influences of background factors to their respective total influences in the background-only model generally shows smaller direct influences than total influences.8 Two exceptions for the expenditures outcome are worth noting, however. For females, direct and total influences were equivalent (belying any mediating effects) and for Blacks, the significant positive direct effect was larger than was the insignificant positive total effect, which suggests an exogenous advantage that increases through the processes of acquiring academic credentials.

Summary. The analyses suggest that the primary direct influences on college destinations are academically based: test scores, high-school grades, academic track, extracur- ricular involvements, and educational expectations. In that sense, the findings resemble those expected under Hypothesis 2, that of

"meritocratic equity of condition." The findings suggest several notable exceptions to the meritocratic hypothesis, however, so the role of nonacademic factors in college destinations should not be understated. What is important is that several findings for nonacademic factors deny basic tenets not only of the meritocratic hypothesis, but of the other two equity hypotheses: There were positive direct SES-based effects on expenditures and selectivity and negative direct effects of female gender on those outcomes. The background-only regressions supplement these results by suggesting that ascriptive factors also have important indirect effects on college destinations, by helping to shape students' academic credentials and expectations.

There was variation among the other exceptions to the meritocratic hypothesis. One exception supports the "redemptive- equity" hypothesis (Hypothesis 3): Blacks had a direct and indirect advantage in entry into higher-cost institutions. A second exception tends to support the "strict-equity- of-condition" hypothesis (Hypothesis 1): The explanatory power of the model was modest, especially for the institutional expenditures outcome. Some academic variables that were expected to have consistent, strong, positive effects (such as high-school track) did not. One way to view this pattern is to infer that the differences among students attending different colleges are more modest than was supposed and are not easily explainable by means of the standard array of major academic and nonacademic factors.

IMPLICATIONS

The results of this study can inform analysis at both the theoretical and policy levels. At the theoretical level, the study addresses some of the concerns about com- prehensiveness, representativeness, and indicators that troubled some earlier studies and thereby allows improved inferences about the structures underlying the matching of colleges and students. At the policy level, the relative timeliness of the data and the data's compara- bility to similar data for 1972 (from Alex- ander and Eckland 1977; Peng, Bailey, and Eckland 1977) and for 1975 (Astin 1978; Hearn 1984) are major assets.

The primary message these results bring to theoretical and policy deliberations is that

7 Path analyses were conducted for the entire model for both outcomes and are available from the author on request.

8 One way to view the extent of mediation, in light of these results, is to compare the results for a model containing only academic characteristics to the results for the full model presented in Tables 2 and 3. Separate regressions (not presented in those tables) revealed that academic characteristics alone accounted for approximately 90 percent of the total variance explained by the full model for both outcomes. Thus, in a path-analytic sense, the direct (unique) effects of background factors account for only about one-tenth of the total variance explained for the two dependent variables.



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patterns in college destinations, like patterns in rates of participation, did not change appreciably in the 1970s and early 1980s. Long-standing SES-linked inequalities per- sisted for at least a decade after serious federal attention to the college-choice issue began with the passage in the early 1970s of choice-oriented amendments to the Higher Education Act of 1965. There remained in the early 1980s a tendency for higher and lower-SES students of equal ability, achievements, and motivation to enroll in somewhat different kinds of schools. For example, all else being equal, offspring of higher-income parents tended in 1980-81 to enroll in more selective institutions, compared to other students. Therefore, earlier findings (see Alexander and Eckland 1977; Heam 1984; Karabel and Astin 1975) of nonmeritocratic tendencies did not disappear when the newer data of the present study were employed. That the U.S. postsecondary system in the early 1980s had expanded to the point of excess capacity (Stadtman 1980) and had been flooded with vastly increased sums of financial aid for students (Gladieux 1980) apparently did not abrogate its tendency to allocate its prime spots to those who were both socioeconomically and academically favored.

To the extent that one can assume that certain kinds of institutions can have uniquely favorable impacts on eventual educational and occupational careers (as suggested by numerous analyses9), the findings here suggest that access to those benefits is not always as equitable as meritocratic norms would suggest. The matching of colleges and students remains in many ways a little understood black box (see Jackson 1982), and the present study focuses mainly on behavioral outcomes (not the evolution of the matching process in individuals). Yet the evidence suggests that within the matching process lies a sorting mechanism that subtly reinforces nonmeritocratic tendencies in U.S. society.

That reinforcement mechanism may be characterized as subtle because nonacademic characteristics played only a limited direct role in explaining the selectivity and expenditures of the institutions attended. Neverthe- less, when one considers the evidence (from

this study and elsewhere) that influential academic characteristics, such as educational expectations, seem to be shaped in significant ways by social origins by way of socialization, tracking, teachers' attitudes, unequal schools, and so forth (see the review by Hum 1978), any purely meritocratic interpretation of the dominant direct effects of academic characteristics in the present analysis is called into question. The most stubborn barriers to meritocracy seem to be those that are directly and indirectly based in SES, rather than those that are based in race, ethnicity, or gender. With regard to the latter factors, as was noted earlier, there were lesser but measurable inequities for Blacks and women, but also some hints of "redemptive equity. ' ' Com- pared to the effects of race, ethnicity, and gender, the effects of social class stand out as both stronger and more consistent. It is hard to dismiss arguments (see Bourdieu 1977; Bowles and Gintis 1976; Karabel 1972; Pincus 1980) that the expansion of status- differentiated postsecondary educational systems, however effective from the standpoint of broadening postsecondary educational opportunity, is not, by itself, a sufficient antidote to enduring social-class differences in educational attainments.

The present findings were pursued not only to improve models of college choice, but to update and replicate earlier published research." Thus, certain potentially productive paths to better understanding were not initially pursued. Among those paths are the

9 Some authors (see, for example, Alwin 1974) have questioned whether institutional characteristics indeed have uniquely important effects, however.

1o Similar evidence was found for Asian Amer- icans. An indicator for Asian status was included in regressions not presented here, and this indicator had significant positive effects on both selectivity and expenditures. These findings fit into a category that Meyer (1986) termed "reversals," that is, findings that are not in keeping with the dominant styles of explanation in the sociology of education.

l The model employed in the present analysis is similar to that employed in an earlier national study of the topic using 1975 high-school graduates (see Hearn 1984). The one difference is the addition here of an indicator of high-school track. Research by Alexander and Eckland (1977) suggested the significance of tracking in college attainments. For comparison, the earlier Hearn model was fitted to the present data. The results of that analysis suggest that the addition of the track indicator adds slightly to the explained variance for both selectivity and expenditures, but does not otherwise alter the pattern of results.




following: assessing interactions among students' characteristics (such as race and ability) in affecting destinations, delving more fully into the ambiguities of "college quality" (see Astin 1982), evaluating the influence of parents' occupational status on the process of college choice, and investigating the importance of students' financial knowledgeability (see El-Khawas 1977; Ol- son and Rosenfeld 1984). The data currently exist for addressing these additional topics in college destinations, and there is good reason for initiating such analyses.

The most pressing impetus for conducting replications and designing new research models is policy related. In the past decade, student- aid policies have been subjected to intense scru- tiny and reconsideration by Congress, the federal executive branch, state governments, and institutional leaders. Whether the multi- billion-dollar federal programs that were de- signed to guarantee equal access and choice have succeeded continues to be a major consideration, and a number of well-known analysts have weighed in on the pro and con sides of the issue (see Breneman 1982; Hansen 1982; Heyns and O'Meara 1982; Jackson 1988; Leslie and Brinkman 1988; McPherson 1988). Rob- ert Zemsky, director of the Institute for Re- search on Higher Education at the University of Pennsylvania (cited in Evangelauf 1988, p. A37), recently argued for major cuts and re- visions in the programs, concluding that "despite nearly two decades of massive invest- ment in student-aid programs by both state and federal agencies, and the adoption by most institutions of largely open-admission policies, college participation rates have not sub- stantially changed."

Zemsky's argument, like most regarding federal aid policies, focuses on barriers to access to postsecondary education (the issue of participation rates), rather than barriers to college choice. Opportunity for both access and choice has been pursued through the federal policies, however, and choice remains an underresearched topic. Indeed, for reasons discussed earlier, the most fundamental threats to equality of opportunity may lie in the realm of choice. The research presented here may add to ongoing debates on this issue.

The 1980s saw a retreat in federal attention to barriers to student choice, and federal funding for financial aid to students declined in inflation-adjusted terms (College Entrance

Examination Board 1983, 1990). Between 1985 and 1988, the U.S. secretary of education repeatedly told the public, the press, and legislators that he was not upset by the prospect that cuts in financial aid under the Reagan administration would restrict lower- and middle-income students' college choices (see, for example, "Is College Worth It?" 1985). Stressing that the federal government's rapid expansion of student aid in the 1970s for guaranteeing "free choice" was ill advised, the secretary contended that the government should be involved in helping ensure that needy students can go to college someplace, but not anyplace. The federal government's retreat from concerns about choice may be creating a major exogenous influence on the processes of matching students and colleges in the United States and may have national implications for equity and the development of talent. It seems appropri- ate to ask, therefore, whether the present analysis's finding of limited, albeit significant, direct relationships in 1980-81 between parental income and college destinations, net of other factors, will be repeated in data for 1990-91. The rapidly increasing costs of college attendance, coupled with a federal retreat from the agenda of choice at the national level, may well lead to a tightening of the relationships between college destinations and parental income.

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James C. Hearn, Ph.D., is Professor, Institute of Higher Education, University of Georgia, Athens. His main fields of interest are educational attainment, higher-education policy, and higher-education organizaticn. He is currently completing a project, funded by the Spencer Foundation, investigating the effects of the changing demography offaculty on the functioning of academic departments.



Documents

Academic and Nonacademic Influences on the College Destinations of 1980 High School Graduates