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Research in Social Stratification and Mobility 30 (2012) 143–158

Available online at www.sciencedirect.com

The stratification of universities: Structural inequality inCanada and the United States

Scott Davies a,∗, David Zarifa b

a McMaster University, Hamilton, Ontario, Canadab Nipissing University, North Bay, Ontario, Canada

Received 8 March 2011; received in revised form 17 May 2011; accepted 21 May 2011

bstract

This paper conceives national systems of higher education as stratified populations of organizations. This stratification is atructural component of ‘horizontal inequality’ in higher education, and may be exacerbated by current pressures for colleges andniversities to compete for resources and status. To explore this structural inequality, we compare the level of stratification in financialesources across four-year institutions in Canada and the United States over a 35-year period (1971–2006). Our analyses provide

first-look at this form of stratification, employing Gini coefficients, Lorenz curves, and boxplots. Our results provide new andompelling evidence of increasing structural stratification, even in Canada’s predominantly publicly funded postsecondary system.

indings indicate that the distribution of resources is far more stratified in the American system, and that both systems have becomeore stratified over time. We conclude by situating structural inequality within more general processes of stratification in education.

2011 International Sociological Association Research Committee 28 on Social Stratification and Mobility. Published by Elseviertd. All rights reserved.

eywords: Stratification; Universities; Higher education; Inequality

. Introduction: analyzing stratification inigher education

The worldwide expansion of higher education overhe past half century has created an unprecedentedolume of opportunities for an unprecedented numberf students (Schofer & Meyer, 2005). Disadvantagedroups are entering colleges and universities in greaterumbers than ever before. Yet, several decades ofociological research suggests this expansion has not

eaningfully reduced relative inequalities in attainment

Goldthorpe & Jackson, 2008; Lucas, 2001; Walters,000). In most nations, links between social origins and

∗ Corresponding author.E-mail address: daviesrs@mcmaster.ca (S. Davies).

276-5624/$ – see front matter © 2011 International Sociological Association Research Committee

doi:10.1016/j.rssm.2011.05.003

access to higher education have remained largely con-stant (Shavit, Arum, & Gamoran, 2007). Research onattainment processes within higher education is reachingsimilar conclusions (Gerber & Cheung, 2008).

This dual process of expansion and inequality occursboth at individual and structural levels. At the indi-vidual level, sociologists have described “maximallymaintained inequality” as the upward movement ofadvantaged groups to advanced levels of education thatoccurs once a lower credential tier has been accessedby many members of less advantaged groups (Raftery& Hout, 1993). Some further contend that enhancedaccess to any level of education also triggers “effectively

maintained” inequality, in which expansion intensifiesprocesses of sorting and selecting within any creden-tial tier. Lucas (2001) describes how widened accessto higher education has encouraged relatively privileged

28 on Social Stratification and Mobility. Published by Elsevier Ltd. All rights reserved.

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144 S. Davies, D. Zarifa / Research in Socia

groups to migrate towards its more advantageous, selec-tive, or prestigious segments. Numerous studies haveexamined race, class and gender influences on access todifferent kinds of institutions, fields of study and degrees,and their varying payoffs (Ayalon & Yogev, 2005; Davies& Guppy, 1997; Espenshade & Radford, 2009; Gerber &Cheung, 2008; Goyette & Mullen, 2006; Grodsky, 2007;Hearn, 1991; Karen, 2002; Mullen & Goyette, 2010;Mullen, Goyette, & Soares, 2003; van de Werfhorst,de Graaf, & Kraaykamp, 2001; Walters, 2004; Zarifa& Walters, 2008).

At a structural level, a parallel hypothesis is thatexpansion also promotes greater stratification amonghigher education organizations (Davies & Guppy,2010).1 Fields and institutions form hierarchies based ontheir power to confer prestige and advantage to studentsand to gain resources. Expansion can fuel structural strat-ification by creating incentives for institutional differen-tiation and by intensifying competition among similaruniversities and colleges. The former is evidenced espe-cially by the creation of new lower-tiered institutions,such as community colleges (Brint & Karabel, 1989;Dougherty, 1994) and for-profit colleges (Ruch, 2001).The latter is evidenced by the evolution of competitivestrategies for status and resources, as described fur-ther below (for more general commentary, see Gumport,2007; Stevens, Armstrong, & Arum, 2008).

Structural stratification and ‘horizontal’ inequal-ity connect when top-ranked students self-select intoresource-rich schools. At the structural level, sizeabletuition fees and selective admissions provide institu-tions with revenue and academic repute, which serveto stratify institutions. At the individual level, thesefees and admissions become mechanisms of horizon-tal inequality by excluding most students from topschools. The key issue for temporal and internationalcomparison is whether or not more stratified systemsconcentrate their elite students (by SES origin and/oracademics) in better resourced universities. In the UnitedStates, Ivy League universities have long attracted stu-dents from elite origins (Karabel, 2005; Soares, 2007),and appear to be increasingly attracting students whoare highly ranked academically and socioeconomically(e.g., Bowen, Chingos, & McPherson, 2009; Espenshade

& Radford, 2009; Geiger, 2004). In contrast, more egal-itarian systems may disperse top students more evenlyamong institutions.

1 At k-12 levels an emerging international literature is comparingnational structures of achievement inequality. See Montt (2011), Vande Werfhorst and Mijs (2010).

cation and Mobility 30 (2012) 143–158

This paper measures structural inequality in twosystems of higher education. We compare degrees ofstratification among populations of Canadian and Amer-ican universities, and examine changes over time. By“stratification” we refer to meaningful inequalities inthe resources used by universities. Change in stratifi-cation may be triggered by policy environments thatare subjecting universities to greater competition forrevenue, whether in the form of tuition-paying clients,fund-raising, or research grants, and that are offering lessbountiful and reliable government support. It is strategicto compare system-level reactions to this new climate.American universities are incredibly diverse, rangingfrom the world-renowned Ivy League schools, liberalarts colleges to mass state institutions, and organizedinto private and public sectors. Canadian universities,in contrast, are almost entirely publicly governed, areless diversified, and have been long governed by normsof institutional parity. Yet, policy-makers in these andmany other nations have been similarly urging their uni-versities to compete for new sources of revenue and relyless on government support.

Drawing on a wealth of data assembled over a lengthytime frame, this paper extends a new line of structurallevel inquiry by establishing what is happening amongpostsecondary institutions. Our goal is to accuratelydescribe the core facts of structural inequality in orderto set the stage for future explanatory research on whythey are happening (Firebaugh, 2008, p. 4). This taskis a structural complement to individual-level studies ofinequality that have dominated the literature. Our chart-ing of trends over several decades also complementsstudies of higher education change, such as Brint, Riddle,and Hanneman’s (2006) analysis of evolving competi-tive strategies among American college segments. In asense, our data measure some field-level outcomes ofthose dynamics.

We begin by describing the changing context fac-ing universities around the globe and consider how itmay affect structural stratification. Then, after describ-ing key differences between Canadian and Americanhigher education, we examine trends in the distributionsof financial resources across each system’s universitiesbetween 1971 and 2006. We conclude by elaborating theimportance of our findings for more general processes ofstratification in education.

2. Trends over time: growing stratification?

As higher education expands around the world, manysystems are also undergoing another kind of transi-tion. Under the banner of human capital development

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S. Davies, D. Zarifa / Research in Social

nd wealth creation, states are also attempting to lever-ge a sea-change in higher education norms. No longerdealized as reclusive, disinterested, and aloof ‘ivoryowers’, policy-makers are urging universities to re-

ake themselves into highly differentiated, competitive,esponsive, and entrepreneurial hubs of activity. Uni-ersities are increasingly encouraged to seek corporateartnerships, bid for government research contracts,ngage in massive donation ventures, and forge new aca-emic programs in the pursuit of tuition revenues. Theseressures are particularly acute for public universities,or whom the “golden years” of large and untargetedovernment subsidies are receding into the past (Stevenst al., 2008).

Importantly, this shifting environment is triggeringore competition among universities. Status competi-

ion is not new in higher education – rivalries have longxisted among colleges and universities, particularly inhe United States, home to the world’s largest system.ut considerable evidence suggests American academe

s becoming increasingly competitive, and is spawn-ng a host of new survival strategies (e.g., Brint et al.,006; Espeland & Sauder, 2007; Kirp, 2004; Tuchman,009). Established universities are competing ever-moreenaciously for ‘star’ researchers and are mounting ambi-ious fund-raising campaigns in an effort to improver cement their high ranks (e.g., Geiger, 2004; Kirp,004). Relative newcomers are devising strategies toove up the ranks (e.g., Brint et al., 2006; Gumport,

007; Kirp, 2004; Stevens et al., 2008; Tuchman, 2009).t lower levels in the hierarchy, institutions are seekingiches in vocational programming in order to survive, arocess resembling the ‘anticipatory subordination’ pur-ued earlier by community colleges (Brint & Karabel,989; Dougherty, 1994). And, near the bottom reaches,or-profit and online colleges have emerged as majorompetitors for non-traditional students (Ruch, 2001).

This competitiveness is hardly limited to the U.S.ations around the world are being extolled to make theirniversities more entrepreneurial and attuned to com-etition (e.g., Clark, 2000). One indicator is the spreadf the “ranking mania” in higher education, which haspread from the United States to international promi-ence, and is commanding great international attention,f not admiration (see Dill & Soo, 2005).

Is this new climate triggering greater structuraltratification? Notions of “Matthew effects” in higherducation (Trow, 1984) suggest that stiffer competi-

ion will bolster disparities. The Matthew effect occurshrough a process of cumulative advantage in which aavourable position becomes a resource that producesomentum for further gains. For instance, top insti-

cation and Mobility 30 (2012) 143–158 145

tutions, which already boast expenditures on par withmany entire countries, can leverage their name-brandsfor further advantages. Universities that are alreadyolder, established and wealthy enter new competitionsfor resources with prominent alumni networks, sizeableendowments, favourable locations, and strategic cor-porate ties. These near-exclusive assets each offer anedge for attracting new corporate partnerships, lucra-tive research contracts, and donors with deep pockets. Incontrast, less-established institutions are yet to developreputations, alumni networks, and donor lists, and maybe less able to vie successfully in emerging competi-tions. As a result, they may instead opt to exploit new andemerging revenue streams in lower segments of highereducation. For instance, Brint and Karabel (1989) arguedthat in a previous era, community colleges emerged, sur-vived and grew by avoiding competition with establisheduniversities, and by instead adapting to subordinate posi-tions in specialized niches. Today, mid-level universitiesand for-profit institutions are similarly avoiding directcompetition with elite universities by using new pro-grams to establish their niche (Brint et al., 2006). For ourpurposes, the issue is whether Mathew effects trigger aseries of varying and simultaneous strategies that serveto increase the aggregate amount of structural inequalityin a national system.

In contrast, notions of “path dependence” suggestthat national systems will respond differently to thesame global pressures (Cummings, 2003). Unique lega-cies of higher education in any country can shapepath-dependent adaptations to external change. Somenations have long funded their universities largelyequally, and have accorded them roughly similar status,rather than having designated elite institutions. In suchcases, today’s emerging climate may intensify pressuresfor institutional conformity rather than differentiation.For instance, states are embracing transnational stan-dards of quality assurance and accountability for publicuniversities. As exemplified in the Bologna Accord,universities are being pressured to conform to standard-ized conventions in exchange for global recognition oftheir credentials. Prestigious forms of higher educationsuch as liberal arts colleges and traditional humani-ties fields are now under pressure to change, as seenin the long-term trend towards vocational and pro-fessional programs (Brint et al., 2006), even amongtraditional liberal arts colleges (Kraatz & Zajac, 1996).These kinds of adaptations to new conditions may

serve to reduce system-wide differentiation within anynation, and perhaps reduce stratification. We developthis argument further when discussing the Canadian casebelow.

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3. Comparative issues: Canada and the UnitedStates as strategic cases

Canada and the United States provide a strategic com-parison of higher education systems. As Lipset (1990)remarked decades ago, they have similar economies, lan-guages, religions, and cultures, yet differ crucially alongsome key variables. One such variable is their configu-ration of higher education.2 American higher educationhas long been marked by its sheer size, diversity, andsteep hierarchy (Trow, 1991). Unlike many national sys-tems, it has little central governance (i.e., no federal bodythat oversees higher education) a large private sector, andan extensive array of differentiated forms, ranging fromresearch-intensive institutions, to religious colleges, toliberal arts colleges, to historically Black colleges, tolarge state colleges. The U.S. public sector has clearlydesignated flagship state universities. This unequal statefunding makes the American public sector more similarto England’s Oxbridge and France’s Grandes Ecoles.

In contrast, the Canadian system is less differenti-ated. Almost all Canadian universities are governed by aprovince and funded largely with public money (Jones,1996). Lacking a noticeable private sector, Canada’ssystem resembles those in Europe that have been gov-erned, until recently, by norms of institutional parityand equal funding. Most Canadian universities assumea comprehensive form, providing a range of programsto general populations, and engaging in broad formsof research. Few specialize only in particular fields –there is no Canadian equivalent to MIT or the CaliforniaInstitute of Technology; very few resemble Americanliberal colleges or have religious or ethnic mandates(there is one Aboriginal university, and no historicallyBlack colleges). Furthermore, Canada lacks a set of inter-nationally renowned elite institutions on par with theIvy League or Oxbridge. As such, its national market forundergraduate credentials is quite small, as relatively fewundergraduates cross provincial borders. With lowered

stakes, university admissions in Canada have not gener-ated comparable controversies over affirmative action,legacies, or athletic scholarships. No Canadian could

2 The USA generally has more economic inequality than doesCanada. Canadian income inequality is relatively high in internationalcomparison, but is lower than that in the United States. Canada also hasmore occupational and income mobility than the USA, though muchof that difference is due to greater concentrations of privilege at thetop of the American hierarchy (Beller & Hout, 2006, p. 30). Access tohigher education also appears to be more unequal in the United States(Belley, Frenette, & Lochner, 2011). For reviews of research in theLipset tradition, see Grabb and Curtis (2005) and Ogmundson (2002).

cation and Mobility 30 (2012) 143–158

write a credible counterpart to The Big Test (Lemann,1999) or The Chosen (Karabel, 2005). The practice ofranking colleges, so established in the U.S., is relativelynew to Canada, with the Maclean’s rankings originatingonly in 1991. The sense of a national-level status com-petition among universities is relatively novel north ofthe border (Davies & Hammack, 2005).

Nonetheless, the political climate surrounding Cana-dian higher education is changing. As elsewhere aroundthe globe, Canadian policy-makers are using marketlanguage to urge universities to expand, differenti-ate, compete and innovate. Provinces are de-regulatingtuition in ways that allow universities to raise feesfor professional schools like law, medicine, dentistry,and business. Politicians are encouraging institutions tomake closer ties with industry. Most provinces now per-mit private universities and colleges to operate, and somemay push for a more explicitly tiered system. The leadersof top research universities have openly expressed theirwishes to emulate elite U.S. schools.

How might the new environment affect Canadianuniversities? On the one hand, it could generate morestratification through the Matthew effect, as more estab-lished and wealthy institutions use their superior positionto seize emerging opportunities. On the other hand,Canada’s adaptation may be path dependent. Legaciesof pubic governance may channel new pressures inways that homogenize rather than stratify the system.Provinces may pressure universities to each adapt bysimilarly re-deploying their resources for research andteaching.

With comparative and temporal issues in mind, thispaper pursues two groups of research questions. First, areAmerican universities more stratified in their financialresources than Canadian universities? Is the Americansystem, which is larger, more differentiated, and moredecentralized, also more unequal? Does Canada’s tighterstate regulation minimize inequality? Second, is there atrend towards greater stratification among universities?Are current global pressures triggering similar trendsin both national systems, or are they responding differ-ently?

4. Data and methods

4.1. Measuring structural stratification in highereducation

Characterizations of structural stratification in Amer-ican higher education often use broad impressions,qualitative, case study or narrative data (e.g., Davies &Hammack, 2005; Geiger, 2004; Stevens et al., 2008).

Stratification and Mobility 30 (2012) 143–158 147

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Table 1List of U.S. data sources.

HEGIS IPEDS

1971 1986• Fall enrollment • Enrollments• Finance • Finance• Degrees earned • Institutional characteristics• Faculty salaries

19911976 • Enrollments• College and university libraries • Finance• Finance • Institutional characteristics• Fall enrollment• Earned degrees 1996

• Enrollments1981 • Finance• Fall enrollment • Institutional characteristics• Finance• Faculty salaries 2001• Earned degrees • Enrollments

• Finance• Institutional characteristics

2006• Enrollments

S. Davies, D. Zarifa / Research in Social

o previous studies to our knowledge have attempted touantitatively measure its system-wide degree of strat-fication. Some images of system-wide hierarchy comerom the mass media in the form of rankings. The U.Sews & World Report and Canada’s Maclean’s, for

nstance, provide marketable snap-shots of universities.ut rankings have several methodological and concep-

ual shortcomings. Their ordinal level of measurementepicts places on a vertical ladder, not distances betweenanks, and thereby conceals which institutions clusternd score closely on measures, and which are greatlyispersed. They cannot summarize the shape and rangef whole systems, and make analyses of changing institu-ional positions difficult, since many have significantlyltered their methodology over time. Further, popularankings have been criticized for using weak and invalidndicators, questionable weighting methods, and debat-ble categories (see Kong & Veall, 2005; McGuire, 1995;onks & Ehrenberg, 1999; Page, 1995; Shale & Liu,

002; Stuart, 1995).We depict stratification using measures that allow for

tatistical and visual comparisons over time. We examinewo metrics of financial resources: income and expen-itures. Resources are good measures because they areritical for research, teaching and operations. Financesan directly and indirectly shape quality of education byffecting student–teacher ratios, physical plants, rangesf courses and programs, faculty salaries (which is cor-elated with productivity), and capacity to recruit toptudents (Astin & Henson, 1977; Geiger, 2004; Kraatz &ajac, 2001; Ross, 1976). Resources are also correlatedith other dimensions of stratification.3

.2. Data

American Data on institutions’ incomes and expendi-ures come from the Integrated Postsecondary Education

ystem (IPEDS) and the Higher Education Generalnformation System (HEGIS). The IPEDS data replacedhe HEGIS in the mid-1980s. We combined HEGIS data

3 In tables not shown, we also examined relationships betweenesources and selectivity. For the U.S. in 1970’s and 1980’s, corre-ations ranged from .23 to .45; during the 2000’s, they ranged frompproximately .48 to .59. For Canada in the 1990’s and 2000’s, corre-ations ranged from .47 to .70. These moderate to strong associationsuggest resource-rich institutions are also relatively selective, andikely use their resources to attract higher-ranked students throughcholarships, financial aid, teaching quality, and general reputation.

hile these data cannot determine causal direction, they suggest thatnancial and cognitive resources co-vary across institutions in bothountries. For reasons of space, we do not develop these analyses here,ut will do so in future papers.

• Finance• Institutional characteristics

for 1971, 1976 and 1981 and IPEDS data for 1986, 1991,1996, 2001, and 2006. In 2001, the IPEDS was com-pletely redesigned, as data collection was converted frompaper-based surveys to a fully web-based system. Theuniverse of postsecondary schools was divided into two:institutions with Postsecondary Participation Agreement(PPA) with the Department of Education’s Office of Post-secondary Education (OPE) and all other schools. Thosewith PPA’s were required to complete the IPEDS surveyand subsequent follow-ups, while those without werenot bound to participate. Significant efforts were madeto ensure comparability over time. These cross-sectionaldata were merged into a longitudinal data set in twostages. First, for each of the IPEDS and HEGIS surveys,a number of component surveys were merged to formone data set for each observation year. Second, institu-tional identifiers (e.g., FICE codes and INSTID codes)were used to combine yearly data sets into a longitudinaldata set from 1971 to 2006 (see Table 1 for a detailed listof component surveys). However, the new system pre-sented some minor inconsistencies with previous years,as some data items were tailored for and/or excludedcertain types of institutions. For example, private-for-

profit institutions were given a different finance formthan private not-for-profit institutions or public insti-tutions. Nonetheless, the IPEDS provides data on allprimary providers of postsecondary education, and is

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148 S. Davies, D. Zarifa / Research in Socia

regarded as the most comprehensive institutional infor-mation currently available in the United States (Brint,2002).

Canadian data come from annual Statistics Canadasurveys: the Financial Information of Universities andColleges (FIUC), Tuition and Living AccommodationCosts Survey (TLAC) and the University Student Infor-mation System (USIS). The FIUC provides annualinformation on income and expenditures for all universi-ties and degree-granting colleges. Data are collected ona voluntary basis via questionnaires and administrativefiles. Each institution’s responses are compared to theprevious year to detect possible errors. Missing, incon-sistent, or invalid responses were imputed by StatisticsCanada using historical information, and adjusted forinflation based on enrolment and Consumer Price Index(CPI) fluctuations. The TLAC surveys provide annualfinancial information (e.g., tuition fees, living accom-modation costs) on all degree-granting universities andcolleges. As in the FIUC surveys, these data are col-lected on a voluntary basis via questionnaires as well astelephone follow-up surveys to minimize non-response.Significant efforts are also taken to detect errors andensure data comparability from year to year. The USISprovides annual information on student background(e.g., gender, citizenship, age) and level and type ofeducation. These data are collected from all institutionsthrough questionnaires and administrative files. Similarefforts are also taken to ensure 100% completion ratesand data accuracy.

These American and Canada data are very compa-rable. Both report full populations of universities ratherthan samples. Each excludes educational sites that areclosed to the public, such as military bases, prisons,corporate education facilities, and test-prep companies.Both are in five-year intervals from 1971 to 2006. Bothcontain a wide range of indicators of resources. Nineindicators were selected as the most comparable acrossnations and over time (for a complete list, see Table 2).To allow comparisons over time, all measures were con-verted to 2006 constant dollars using the CPI in Canadaand United States, and both are reported in per Full-TimeEquivalent (FTE) enrolments.

To make the populations comparable, we exam-ine only degree-granting institutions that award abaccalaureate or higher degree, and omit two-yearand less-than-two-year institutions (as defined by theNational Center for Education Statistics). American

four-year universities and colleges are comparable toCanadian universities, which are also four-year institu-tions. However, American two-year institutions are notreadily comparable to any Canadian institution. Cana-

cation and Mobility 30 (2012) 143–158

dian community colleges have one, two, and three-yearprograms, and depending on the province, do not allowfor transfer to universities. Given this lack of compara-bility, we exclude American two-year institutions andcommunity colleges along with Canadian communitycolleges. In the U.S., 1500–2000 units met those criteriain any given year; in Canada, the comparable popu-lation ranges from 50 to just over 70. This exclusionlikely reduces much variability in resources. To furtherenhance comparability, in 2001 and 2006, we separateU.S. private and public universities.

5. Analysis

For each measure, we calculate Gini coefficients andgraph Lorenz curves and boxplots. Gini coefficients area standardized measure of inequality. They represent thecumulative difference in proportions of all adjacent pairsof measures in a population. Formally, the Gini coeffi-cient is defined using the following formula (Cowell,2009, 2008):

1

2n2x̄

n∑

i=1

n∑

j=1

|xi − xj|,

where n is the population size, and xi is the income ofinstitution i, i = 1, 2, . . ., n. The Gini takes all possiblepairs of institutions in our populations (i, j), calculatesthe absolute differences between them, and normalisesthe average of those differences (Cowell, 2008, p. 10).Gini coefficients range on a scale from zero to one,where zero represents perfect equality and one representstotal inequality, and where larger coefficients indicate ahigher degree of inequality, and lower scores indicatemore parity. Gini coefficients are widely used to com-pare income inequality across countries or over time,where scores typically range from .2 to .5 (e.g., Förster& Mira d’Ercole, 2005).

We also plot Lorenz curves to graph Gini coefficients.These curves plot the cumulative proportion of a variableagainst the cumulative proportion of institutions. When avariable is evenly distributed across all units, with everyunit having the same amount, and the Gini coefficientequalling zero, these graphs have a 45◦ line that connectsthe lowest x and y proportions at the origin (0,0) to thehighest possible proportions on the x and y axes (1.0,1.0).

Conversely, a line of perfect inequality, where Gini = 1.0,traces the x axis at y = 0 until x = 1.0, where it then tracesthe y axis. The Gini coefficient represents twice the areabetween the line of perfect equality and the Lorenz curve,

S. Davies, D. Zarifa / Research in Social Stratification and Mobility 30 (2012) 143–158 149

Table 2Variable descriptions.

Canada: TLAC, FIUC and USIS measures United States: IPEDS and HEGIS measures

Total income from federal government grants Total income from federal grants and contractsTotal income from provincial government grants Total income from state and local grants and contractsTotal income from course fees Total income from tuition and feesTotal income from bequests, donations and non-government grants Total income from private gifts, grants, and contractsTotal income from sales of services and products Total income from sales and services of educational activities

Total income from sales and services of auxiliary enterprisesTotal income Total income from revenues and investment returnTotal expenditures on scholarships, bursaries and prizes Total expenditures on net grant aid to studentsTotal expenditures Total expenditures

Table 3Gini coefficients for American public and private degree-granting institutions per FTE, 1971–1996.

Variable 1971 1976 1981 1986 1991 1996 Change 1971–1996

Total income from federal grants and contracts .8584 .7366 .7010 .6358 .6832 .6743 − .1841Total income from state and local grants and contracts .8066 .7817 .7761 .7865 .8033 .7747 − .0319Total income from tuition and fees .3442 .3451 .3624 .3804 .4249 .3804 + .0362Total income from private gifts, grants, and contracts .6414 .6605 .6783 .7010 .7111 .7000 + .0586Total income from sales and services of educational activities .8798 .7811 .7920 .8335 .8605 .8532 − .0266Total income from endowments .7613 .8010 .7685 .7795 .7787 .7689 + .0076Total income from revenues and investment return .4203 .4216 .4284 .4907 .5124 .4684 + .0481T 3 .47T 0 .42

aa

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6

6

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otal expenditures on scholarships and student grants .460otal expenditures .427

nd is the proportion of the area between perfect equalitynd perfect inequality.4

We also use boxplots to graph the distribution ofesources among universities. Boxplots offer visualnformation by depicting distances between institu-ions, ranges between top and bottom, and positions ofutliers.5 Systems with relatively equal distributions willave short ‘whiskers’, small inter-quartile ranges, andew outliers. More stratified systems will have longerwhiskers’, larger inter-quartile ranges, more outliers,nd a substantial amount of skew.

. Results

.1. Canada–U.S. comparisons

Tables 3–5 present Gini coefficients for several mea-ures of income and expenditures per FTE over time.

able 3 contains coefficients for the U.S. between 1976nd 1996. Table 5 contains American coefficients for001 and 2006, distinguishing public and private univer-

4 Gini coefficients and Lorenz curves were calculated using the ineqackage for R Statistical Software (Zeileis, 2006).5 Outliers have values more than 1.5 times the inter-quartile rangeelow and above the quartiles.

28 .4874 .3890 .3946 .3955 − .064843 .4331 .4881 .5121 .4668 + .0398

sities. Table 4 presents comparable Canadian coefficientsbetween 1971 and 2006, and Table 5 reproduces the 2001and 2006 coefficients for comparison with U.S. publicand private sectors.

Overall, the tables show the U.S. system to be moreunequal than the Canadian system on every measure.Along key measures such as total income and totalexpenditures the U.S. system is strikingly more strati-fied. Some American coefficients more than double theirCanadian counterparts. In Table 3, U.S. measures of totalincome from revenues and investment return range from.42 in 1971 to .47 in 1996, while Canada’s coefficientsrange from .16 in 1976 to .21 in 2006. A similar storyis told by expenditures. In Table 5, American figuresrange from .43 to .79 in 2001 and 2006 (dependingon the sector), while Canadian coefficients range from.18 to .21. In Table 5, many U.S. coefficients exceed.70 and few fall below .45 (e.g., income from tuitionand fees, income from course fees and expenditures onscholarships). By contrast, only one Canadian coefficientexceeds .50 (income from bequests, donations, and non-government grants). Overall, these data suggest the U.S.

system is more unequal, while the Canadian system hasa modicum of parity across institutions. An exceptioncan be seen by comparing Canadian institutions withthe U.S. public sector. Table 5 shows that U.S. public

150 S. Davies, D. Zarifa / Research in Social Stratification and Mobility 30 (2012) 143–158

Table 4Gini coefficients per FTE for degree-granting institutions, Canada, 1971–2006.

Variable 1976 1981 1986 1991 1996 2001 2006 Change1976–2006

Total income from federal grants .4430 .4195 .3927 .4558 .5307 .4777 .4340 − .0090Total income from provincial grants .1969 .2016 .2182 .1615 .2356 .2354 .2843 + .0874Total income from course fees .1150 .1247 .1872 .1427 .1796 .2424 .2535 + .1385Total income from bequests, donations and non-government grants .4577 .4476 .4986 .4751 .4852 .5466 .5578 + .1001Total income from sales of services and products .2944 .2880 .3112 .3128 .3417 .3505 .3623 + .0679Total income .1598 .1672 .1920 .1603 .1684 .1857 .2164 + .0566Total expenditures on scholarships, bursaries, prizes .6016 .3718 .4135 .4008 .4266 .3789 .3749 − .2267Total expenditures .1665 .1701 .1913 .1625 .1723 .1792 .2118 + .0453

.1404

Total general operating expenditures

universities are comparable to Canadian coefficients forincome from tuition fees, and in 2001 are indeed smallerfor expenditures on scholarships, bursaries, prizes, andstudent grants.

To further grasp these differences, we turn to box-plots. Figs. 1.1–1.3 reveal a great range and upward skewof resources in the U.S. The American outliers create avertical scale in which the bottom 75% is flattened anddominated by top institutions that straggle upwards in anelongated skew. The squatness of the mid-box indicatesthat the inter-quartile ranges are small compared to theoverall range. Overall, these plots depict a hierarchicalsystem dominated by a small number of super-resourced,elite institutions that are highly distinct from the masses.They contrast starkly with Figs. 2 and 3, in which theCanadian distributions are clearly stratified, but are farless skewed and more normally distributed.

To what extent is the greater stratification in the U.S.

attributable to its private sector? Boxplots in Figs. 4 and 5reveal that sector matters. The private sector is muchmore skewed and contains a longer trail of upper outliers

Table 5Gini coefficients per FTE for Canadian, U.S. public, and U.S. private instituti

Variable

Total income from federal grants

Total income from provincial/state grants

Total income from course/tuition fees

Total income from bequests, donations and non-government grants; private ggrants, and contracts

Total income from sales of services and products

Total income/total income from revenues and investment return

Total expenditures on scholarships, bursaries, prizes/student grants

Total expendituresTotal general operating expenditures

.1491 .1460 .1227 .1460 .1492 .1819 + .0415

compared to the public sector. Yet, even the U.S. pub-lic sector is more stratified than the Canadian system,indicating that national differences cannot be reduced tothe presence of the U.S. private sector. Indeed, the U.S.distributions have greater ranges, squatter mid-boxesand more outliers, while the Canadian distributions arerelatively symmetric. Similarly, Fig. 5 compares totalexpenditures, and also contrasts Canada’s relatively sym-metric distribution to an American distribution thatclusters most institutions into a flat mid-box, and hasmany outliers straggling upwards, with a vast overallrange. Over time, the U.S. figures show an increasingseparation of upper outliers from the rest of the distri-bution, illustrating that elite institutions have not onlymaintained their advantages, but have pulled away fromthe pack. Overall, these findings reveal a relatively strat-ified American university system, marked by a largecluster of institutions into a relatively narrow range

underneath several upper outliers. In contrast, the distri-bution of resources among Canada’s universities is lessstratified and marked by fewer dominant outliers.

ons, 2001 and 2006.

Canada United States

2001 2006 2001 2006

Public Private Public Private

.4777 .4340 .6177 .8333 .7055 .8628

.2354 .2843 .7108 .7756 .7539 .7803

.2424 .2535 .2426 .3269 .2920 .3029ifts, .5466 .5578 .7846 .6159 .7445 .6565

.3505 .3623 – .8566 – .8158

.1857 .2164 .5360 .4792 .5836 .5045

.3789 .3749 .2572 .5661 .4210 .5984

.1792 .2118 .5406 .4814 .5786 .4591

.1492 .1819 – – – –

S. Davies, D. Zarifa / Research in Social Stratification and Mobility 30 (2012) 143–158 151

F nvestmed 008).

6

tGu

FP

ig. 1.1. U.S. boxplots 1971–1996. Total income from revenues and iollars as per the Consumer Price Index (Bureau of Labor Statistics, 2

.2. Trends over time (1971–2006)

Have university systems become more stratified over

ime in their incomes and expenditures? Table 4 reportsini coefficients for Canada between 1971 and 2006,sing constant 2006 dollars. There are mixed trends.

ig. 1.2. U.S. boxplots 1971–1996. Total expenditures per FTE student. Notrice Index (Bureau of Labor Statistics, 2008).

nt return per FTE student. Note: figures are reported in 2006 constant

Income from federal grants, and expenditures on schol-arships, bursaries and prizes appear to have lessenedstratification over time. Several measures show mild

increases, such as total income from sales of servicesand products. Some show larger increases, such as totalincome from course fees. Importantly, the coefficients

e: figures are reported in 2006 constant dollars as per the Consumer

152 S. Davies, D. Zarifa / Research in Social Stratification and Mobility 30 (2012) 143–158

er FTE

Fig. 1.3. U.S. boxplots 1971–1996. Total income from endowments pConsumer Price Index (Bureau of Labor Statistics, 2008).

for the two key measures – total income and total expen-ditures – show that the Canadian system became morestratified over time, with much of the increase occurring

between 2001 and 2006.

However, for many measures, there are no cleartrends. Coefficients for federal income grow and then

Fig. 2. Canadian degree-granting institutions. Total expenditures(thousands) per FTE. Note: figures are reported in 2006 constant dollarsas per the Consumer Price Index (Statistics Canada, 2008).

student. Note: figures are reported in 2006 constant dollars as per the

shrink somewhat over time, while provincial sourcesbecame more disparate since 1991. Income from pri-vate sources (bequests, donations and non-government

grants) grew over the time period, particularly since1996, as did income from sales and services. Yet, formost Canadian measures, increases over the time period

Fig. 3. Canadian degree-granting institutions. Total income, allsources (thousands) per FTE. Note: figures are reported in 2006 con-stant dollars as per the Consumer Price Index (Statistics Canada, 2008).

S. Davies, D. Zarifa / Research in Social Stratifi

Fig. 4. Total income (thousands), Canadian and American degree-granting institutions, 2001 and 2006. Notes: 1. This figure does notaccount for FTE enrollment differences. 2. The populations reportingpositive, non-zero incomes are as follows: Canada, 2001 (N = 73) and2006 (N = 72); U.S. private, 2001 (N = 1865) and 2006 (N = 1538); andU.S. public, 2001 (N = 622) and 2006 (N = 626). 3. For a list of the topfive institutions by year and institution type see Appendix A.

Fig. 5. Total expenditures (thousands), Canadian and Americandegree-granting institutions, 2001 and 2006. Notes: 1. This figuredoes not account for FTE enrollment differences. 2. The populationsof institutions reporting positive, non-zero expenditures are as fol-lows: Canada, 2001 (N = 73) and 2006 (N = 72); U.S. private, 2001(N = 1877) and 2006 (N = 1538); and U.S. public, 2001 (N = 622) and2006 (N = 627).

cation and Mobility 30 (2012) 143–158 153

are not dramatic, likely because the bulk of universityincome comes from provincial sources, which gener-ally distribute resources more equally than do othersources. There are unclear trends for expenditures, ascoefficients for total expenditures and general operatingexpenditures rose slightly over time, while disparitiesfor expenditures on scholarships actually fell. Return-ing to boxplots, Figs. 2 and 3 both show slightly risingmedians between 1976 and 2006, an expanding range,yet relatively normal distributions. Nonetheless, the plotsdo reveal a rising amount of stratification, as indicatedby the longer whiskers and mid-boxes in later years.

Tables 3 and 5 present Gini coefficients for the UnitedStates.6 As in the Canadian analyses, nearly all mea-sures increased over the 30-year span, with incomes fromfederal grants and contracts and expenditures on schol-arships and student aid being the exceptions. Althoughthe U.S. coefficients are much larger for all measures, thelevel of structural inequality grew at a similar rate overthe period. Table 3 shows overall rises in the Gini coef-ficients for the two aggregate measures – total incomefrom revenue and investment return, and total expendi-tures. While not linear over time, both increased duringthe 25-year time period overall: total income inequalityincreased by almost .05, while total expenditure inequal-ity increased by almost .04. Moving to Table 5 shows thatGini’s for expenditures and income rose considerablybetween 1996 and 2006 (note that data were disaggre-gated in 2001 and 2006). Income inequality was higher inboth sectors in 2006 than in aggregate in 1996, and publicsector expenditure inequality was also higher. This sug-gests that structural stratification increased in the U.S.system between 1996 and 2006.

Lorenz curves provide some additional insight.Figs. 6 and 7 illustrate greater inequality among U.S. uni-versities, with narrower Canadian curves nested withinlarger and wider U.S. curves. The Canadian curves aresmoother and more constant, as all portions of their dis-tribution contribute fairly equally to the total amountof stratification, reflecting more institutional parity. U.S.curves reveal much greater inequality at the top end of thedistribution, where a few institutions hold a large shareof total resources. Additional analyses (not shown) ofother measures (e.g., income from federal grants, income

from state grants, income from sales and services, totalincome, and total expenditures), reveal that 80–90% ofthese resources were largely concentrated among the

6 Gini coefficients for private for-profit degree-granting institutionswere calculated but are not shown, since the number of institutions wasquite small for many measures, making these coefficients unreliable.

154 S. Davies, D. Zarifa / Research in Social Stratifi

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0Lorenz Curves for Total Income Per FTE Student, 2006

Cumulative Proportion of Institutions

Cum

ulat

ive

Pro

port

ion

of In

com

e

Perfect EqualityUS PrivateCanadaUS Public

Fig. 6. Lorenz curves for total income per FTE student, 2006.

top 10 or 20% of institutions, illustrating the wealth ofwell-established elite institutions at the summit of theU.S. hierarchy. Unlike the Canadian curves, the distancebetween the U.S. curves and the line of perfect equalityis much greater. In Fig. 6, for example, the Lorenz curvesfor total income in 2006 nearly traces the x and y axes,indicating a substantial skew of resources among rela-tively few institutions. These distributions also change

over time. In the seventies and eighties, levels of inequal-ity were quite high yet constant across all segments ofthe population, but in the last 15 years, resources were

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.2

0.4

0.6

0.8

1.0

Lorenz Curves for Total Expenditures Per FTE Student, 2006

Cumulative Proportion of Institutions

Cum

ulat

ive

Pro

port

ion

of In

com

e

Perfect EqualityUS PrivateCanadaUS Public

Fig. 7. Lorenz curves for total expenditures per FTE student, 2006.

cation and Mobility 30 (2012) 143–158

increasingly concentrated among the top 5–10%. Over-all, these data illustrate that both systems have becomemore stratified over time. In Canada, the trend is gradualand less marked by outlying elites, while in the U.S.,stratification is clearer and increasingly driven by dom-inating elite institutions.

7. Discussion

This paper joins several data sources to compareinequality in the distribution of resources among Cana-dian and American universities during a period of highereducation expansion. Results indicate that U.S. systemis much more stratified than Canada’s, and that structuralinequality generally grew in both systems. These find-ings provide new and compelling evidence of increasingstructural stratification in higher education. They area likely outcome of a combination of social forces,including new competitive strategies among universi-ties (Brint et al., 2006; Kirp, 2004), academic capitalism(Slaughter & Leslie, 1997), the spreading influence ofrankings (Espeland & Sauder, 2007), and greater con-centrations of top-ranked students among universities(Geiger, 2004), among others. These findings are alsoconsistent with claims that horizontal inequality is grow-ing (Gerber & Cheung, 2008).

More specifically, our data can be interpreted asproviding support for both of our guiding hypotheses.“Mathew effects” are suggested by the general trendof rising resource stratification in both nations, andparticularly by the increasing advantages of already-wealthy American institutions. These universities wereupper outliers in all decades, and widened the gulfbetween themselves and lesser-ranked institutions overtime. This trend likely reflects the benefits of beingnot only elite on a domestic scale, but also beingtop-ranked globally, a commanding international posi-tion that brings great advantages over their regionalcompetitors. But “path dependency” is also suggestedby persisting Canada–U.S. differences in the shapesof their resource distributions. Canadian distributionshad few extreme outliers, less skew, more symmetry,and rising medians. This pattern indicates that manyCanadian institutions were gaining similar amounts ofresources, not only the top-ranked. Structural inequalitythus appears to be taking a more gradual “creeping” formin Canada. With few world-ranked universities and lessextreme concentration at the tip of its hierarchy, Canada’s

persisting norms of institutional parity – which for nowremain embedded in provincial funding arrangements –have likely muted social forces that would otherwise fuelinequality.

Stratifi

rFhpTpshTl2o

lidiicrbspvsgliIlbstvoSs

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See Table A1.

7 Future research can ald so examine endowment inequality.In graphs not shown, Canadian universities like Toronto, BritishColumbia, and Alberta, along with McGill University, formed upperoutliers in patterns resembling U.S. elites like Princeton, Yale and Har-

S. Davies, D. Zarifa / Research in Social

We conclude by suggesting three areas for futureesearch that are implied by our methods and findings.irst, our methods for measuring structural inequality inigher education could be broadened further to encom-ass many more nations, such as OECD or EU countries.he challenge is to find data with measures that are com-arable across countries. Lessons might be learned fromtudies of international k-12 achievement inequality thatave been enabled by international data sets like PIRLS,IMMS and PISA that offer standardized measures of

earning (e.g., Montt, 2011; Van de Werfhorst & Mijs,010). It is worthwhile to search for parallel measuresf structural inequality.

Second, research should attempt to unravel causalinks between structural and individual processes. Fornstance, the trend of increasing concentrations of aca-emically able and affluent students in highly resourcednstitutions can be explained by two different scenar-os. In one, structural inequality can be seen to be aausal force if resource-rich institutions provide a supe-ior education and develop student skills in ways thatoost their life chances. In this scenario, an exclusiveet of universities attract the best teachers and studenteers, create superior learning environments, and pro-ide incentives that lure the best (and often wealthiest)tudents. Here, structural inequality is a prime cause ofrowing concentrations of elite students and individual-evel stratification. But in a second scenario, structuralnequality is merely a channel for student self-selection.n this scenario, highly resourced institutions contributeittle added-value to learning, but their excellent ‘namerands’ attract status-conscious students who seek exclu-ive credentials. Here, individual-level stratification inhe form of concentrations of elite students in top uni-ersities is a product of student self-selection basedn pre-existing ability, drive, and financial capacity.tructural inequality is simply the setting in which thiself-selection plays out.

Our data cannot be used to directly unravel this causaluzzle since individual-level data in Canada do not iden-ify respondents’ university. American evidence on theausal impact of college quality is mixed. Some econo-etric analyses estimate only small impacts of college

uality on graduate outcomes net of individual character-stics; others suggest college quality effects are sizeablesee Gerber & Cheung, 2008). Future research canncover clues about causal links between individual andtructural level processes by testing these two scenarios.

Third, future research can adopt our methods toxamine inequalities within national systems. We foundizeable differences between American public and pri-ate universities; similar differences may exist for

cation and Mobility 30 (2012) 143–158 155

finer-grained sectors, such as the Carnegie classifica-tions. Likewise, our methods could be modified toexamine stratification within universities themselves.Many are searching for new revenue streams not bydevising comprehensive, institution-wide strategies, butby funnelling their investments to a limited number offields, programs or schools, especially those with linksto lucrative markets. This strategy may generate moreresource stratification within rather than between uni-versities. For instance, Canadian provinces continue torestrain fee hikes for undergraduate arts and sciences –where the vast bulk of students are found – by incre-ments of no more than 5–10% per year. Academicadministrators in humanities, social sciences and naturalsciences often decry these policies as starving them ofneeded resources. Simultaneously, provinces are also de-regulating tuition for professional and applied programs,permitting fees for medicine, dentistry, business or lawto double, triple, or more. Whereas regular baccalaureatefees average $5000 per year, professional fees range from$10,000 to $25,000. Further, most of the “action” for cor-porate and alumni funds occurs in these professional andapplied programs. Expensive buildings, typically namedafter corporations or wealthy patrons, are seen mainlyin business, medicine, law and applied sciences, wheremarket forces are far more present. These forces arelikely to bolster resource inequality within universities,even within publicly regulated systems, and our methodscould be adapted to chart these trends.

Overall, expansion has transformed university sys-tems. Compared to just a few decades ago, they offermore aggregate opportunity for an unprecedented num-ber of students. But these systems, even those withrelative institutional parity, are increasingly stratified.7

Can they accommodate new pressures without becom-ing more hierarchical? This paper has established someof the facts of structural inequality; future research canuncover their causal mechanisms.

Appendix A.

vard. However, those American institutions operate on a far granderscale. Canada’s richest institution (the University of Toronto) had anendowment of $1.75 billion CDN in 2006. Harvard’s was nearly $23billion USD.

156 S. Davies, D. Zarifa / Research in Social StratifiTa

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cation and Mobility 30 (2012) 143–158

References

Astin, A. W., & Henson, J. W. (1977). New measures of college selec-tivity. Research in Higher Education, 6, 1–9.

Ayalon, H., & Yogev, A. (2005). Field of study and students’ stratifica-tion in an expanded system of higher education: The case of Israel.European Sociological Review, 21(3), 227–241.

Beller, E., & Hout, M. (2006). Intergenerational social mobility: TheUnited States in comparative perspective. The Future of Children,16(2), 19–36.

Belley, P., Frenette, M., & Lochner, L. (2011). Post secondary atten-dance, parental income, and financial aid: Comparing Canada andthe U.S. University of Western Ontario: Centre for Human Capitaland Productivity Policy Brief.

Bowen, W. G., Chingos, M. M., & McPherson, M. S. (2009). Crossingthe Finish Line: Completing College at America’s Public Univer-sities. Princeton, New Jersey: Princeton University Press.

Brint, S. (2002). Data on higher education in the United States: Arethe existing resources adequate? American Behavioral Scientist,45(10), 1493–1522.

Brint, S., & Karabel, J. (1989). The diverted dream: Community col-leges and the promise of educational opportunity in America,1900–1985. New York: Oxford University Press.

Brint, S., Riddle, M., & Hanneman, R. A. (2006). Reference sets,identities, and aspirations in a complex organizational field: Thecase of American four-year colleges and universities. Sociology ofEducation, 79(3), 229–252.

Bureau of Labor Statistics. (2008). CPI inflation calculator. UnitedStates Department of Labor. http://www.bls.gov/data/inflationcalculator.htm

Clark, B. (2000). The entrepreneurial university: New foundations forcollegiality, autonomy, and achievement. Retrieved July 2010 atwww.oecd.org/dataoecd/1/47/37446098.pdf

Cowell, F. A. (2009). Measuring inequality (3rd edition). HemelHempstead: Oxford University Press.

Cowell, F. A. (2008). Income distribution and inequality. In J. B. Davis,& W. Dolfsma (Eds.), The Elgar companion to social economics.Edward Elgar: Cheltenham [Chapter 13].

Cummings, W. (2003). The institutions of education. A comparativestudy of educational development in the six core nations. In Oxfordstudies in comparative education: Symposium books.

Davies, S., & Guppy, N. (1997). Fields of study, college selectivity,and student inequalities. Social Forces, 73(4), 131–151.

Davies, S., & Guppy, N. (2010). The schooled society (second edition).Toronto: Oxford University Press.

Davies, S., & Hammack, F. (2005). Channelling competition in highereducation: Comparing Canada and the US. Journal of Higher Edu-cation, 76(1), 89–106.

Dill, D. D., & Soo, M. (2005). Academic quality, league tables, andpublic policy: A cross-national analysis of university ranking sys-tems. Higher Education, 49, 495–533.

Dougherty, K. (1994). The contradictory college: The conflicting ori-gins, impacts, and futures of the community college. Albany: StateUniversity of New York Press.

Espeland, W., & Sauder, M. (2007). Rankings and reactivity: How pub-lic measures recreate social worlds. American Journal of Sociology,113(1), 1–40.

Espenshade, T. J., & Radford, A. W. (2009). No longer separate, notyet equal: Race and class in elite college admission and campus

life. Princeton, N.J.: Princeton University Press.

Firebaugh, G. (2008). Seven rules for social research. Princeton, N.J.:Princeton University Press.

Stratifi

F

G

G

G

G

G

G

G

H

J

K

K

K

K

K

K

L

L

L

M

S. Davies, D. Zarifa / Research in Social

örster, M., d’Ercole Marco, M. (2005). Income distribution andpoverty in OECD countries in the second half of the 1990s. OECDSocial, Employment and Migration Working Paper No. 22. Paris:OECD.

eiger, R. (2004). Knowledge and money research universities andthe paradox of the marketplace. Stanford, CA: Stanford UniversityPress.

erber, T. P., & Cheung, S. Y. (2008). Horizontal stratification inpostsecondary education: Forms, explanations, and implications.Annual Review of Sociology, 34, 299–318.

oldthorpe, J., & Jackson, M. (2008). Education-based meritocracy:The barriers to its realization. In A. Lareau, & D. Conley (Eds.),Social class: How does it work? New York: Russell Sage [Chapter3].

oyette, K. A., & Mullen, A. L. (2006). Who studies arts and sci-ences? Social background and the choice and consequences ofundergraduate field of study. The Journal of Higher Education,77(3), 497–538.

rabb, E. G., & Curtis, J. E. (2005). Regions apart: The four societiesof Canada and the United States. Toronto: Oxford University Press.

rodsky, Eric. (2007). Compensatory sponsorship in higher education.American Journal of Sociology, 112(6), 1662–1712.

umport, P. (Ed.). (2007). The sociology of higher education: Con-tributions and their contexts. Stanford CA: Stanford UniversityPress.

earn, J. C. (1991). Academic and nonacademic influences on thecollege destinations of 1980 high school graduates. Sociology ofEducation, 64(3), 158–171.

ones, G. A. (1996). Diversity within a decentralized higher educa-tion system: The case of Canada. In V. L. Meek (Ed.), The mockersand the mocked: Comparative perspectives on differentiation, con-vergence, and diversity in higher education (pp. 79–95). Oxford:Pergamon.

arabel, J. (2005). The chosen: The hidden history of admission andexclusion at Harvard, Yale, and Princeton. Houghton Mifflin.

aren, D. (2002). Changes in access to higher education inthe United States: 1980–1992. Sociology of Education, 75(3),191–210.

irp, D. (2004). Shakespeare, Einstein, and the bottom line: Highereducation goes to market. Cambridge, MA: Harvard UniversityPress.

ong, Q., & Veall, M. R. (2005). Does the Maclean’s ranking matter?Canadian Public Policy, 31(3), 231–242.

raatz, M. S., & Zajac, E. J. (1996). Exploring the limits of thenew institutionalism: The causes and consequences of illegiti-mate organizational change. American Sociological Review, 61,812–836.

raatz, M. S., & Zajac, E. J. (2001). How organizational resourcesaffect strategic change and performance in turbulent environments:Theory and evidence. Organization Science, 12(5), 632–657.

emann, N. (1999). The big test: The secret history of the Americanmeritocracy. New York: Farrar, Straus.

ipset, S. M. (1990). Continental divide: The values and institutionsof the United States and Canada. New York: Routledge.

ucas, S. R. (2001). Effectively maintained inequality:Education transitions, track mobility, and social back-ground effects. American Journal of Sociology, 106(6),1642–1690.

cGuire, M. D. (1995). Validity issues for reputational studies. InR. D. Walleri, & M. K. Moss (Eds.), Evaluating and respondingto college guidebooks and rankings. San Francisco: Jossey-BassPublishers.

cation and Mobility 30 (2012) 143–158 157

Monks, J., & Ehrenberg, R. G. (1999). US news and world report’scollege rankings: Why they matter. Change, 31(6), 42–51.

Montt, G. (2011). Cross-national differences in educational achieve-ment inequality. Sociology of Education, 84(1), 49–68.

Mullen, A. L, Goyette, K. A., & Soares, J. A. (2003). Who goes tograduate school? Social and academic correlates of educationalcontinuation after college. Sociology of Education, 76(2), 143–169.

Mullen, A. L., & Goyette, K. A. (2010). The advantage of ambition:How class-based application patterns help explain stratification inhigher education. In Paper presented to international sociologi-cal association research committee 28 on social stratification andmobility.

Ogmundson, R. (2002). The Canadian case: Cornucopia of neglectedresearch opportunities. The American Sociologist, (Spring), 55–78.

Page, S. (1995). Rankings of Canadian universities: Pitfalls in inter-pretation. The Canadian Journal of Higher Education, 25(2),17–28.

Raftery, A. E., & Hout, M. (1993). Maximally maintained inequality:Expansion, reform and opportunity in Irish education, 1921–75.Sociology of Education, 66(1), 41–62.

Ross, R. D. (1976). The institutionalization of academic innovations:Two models. Sociology of Education, 49(2), 146–155.

Ruch, R. S. (2001). Higher Ed. Inc.: The rise of the for-profit university.Baltimore: Johns Hopkins University Press.

Schofer, E., & Meyer, J. W. (2005). The world-wide expansion ofhigher education in the twentieth century. American SociologicalReview, 70(6), 898–920.

Shale, D., & Liu, Y. (2002). Ranking the rankers of universities:Canada’s Maclean’s Magazine vs. US News & World Report. InPaper presented at the forty-second annual forum of the associationfor institutional research Toronto.

Shavit, Y., Arum, R., & Gamoran, A. (2007). Stratification in highereducation: A comparative study. Stanford, CA: Stanford UniversityPress.

Slaughter, S., & Leslie, L. L. (1997). Academic capitalism: Politics,policies, and the entrepreneurial university. Baltimore: Johns Hop-kins Press.

Soares, J. (2007). The power of privilege: Yale and America’s elitecolleges. Stanford: Stanford University Press.

Statistics Canada. (2008). Table 326-0021 – consumer price index(CPI), 2005 basket. CANSIM (database). http://cansim2.statcan.ca/cgi-win/cnsmcgi.exe?Lang=E&CANSIMFile=CII\CII 1 E.htm&RootDir=CII/

Stevens, M. L., Armstrong, E. A., & Arum, R. (2008). Sieve, incubator,temple, hub: Empirical and theoretical advances in the sociologyof higher education. Annual Review of Sociology, 34, 127–151.

Stuart, D. L. (1995). Reputational rankings: Background and devel-opment. In R. D. Walleri, & K. M. Moss (Eds.), Evaluating andresponding to college guidebooks and rankings. San Francisco:Jossey-Bass Publishers.

Trow, M. A. (1984). The analysis of status. In B. R. Clark (Ed.), Per-spectives on higher education: Eight disciplinary and comparativeviews. Berkeley: University of California Press [Chapter 5].

Trow, M. A. (1991). The exceptionalism of American higher education.In M. A. Trow, & T. Nybom (Eds.), University and society: Essayson the social role of research and higher Education (pp. 156–172).London: Kingsley Publications.

Tuchman, G. (2009). Wannabe U.: Inside the corporate university.

Chicago: University of Chicago Press.

van de Werfhorst, H. G., de Graaf, N. D., & Kraaykamp, G. (2001).Intergenerational resemblance in field of study in the Netherlands.European Sociological Review, 17(3), 275–293.

l Stratifi

158 S. Davies, D. Zarifa / Research in Socia

Van de Werfhorst, H. G., & Mijs, J. J. B. (2010). Achievementinequality and the institutional structure of education systems:A comparative perspective. Annual Review of Sociology, 36,407–428.

Walters, D. (2004). A comparison of the labour market outcomesof postsecondary graduates of various levels and fields overa four-cohort period. Canadian Journal of Sociology, 29(1),1–27.

cation and Mobility 30 (2012) 143–158

Walters, P. B. (2000). The limits of growth: School expansion andschool reform in historical perspective. In M. Hallinan (Ed.), Hand-book of sociology of education. Springer [Chapter 10].

Zarifa, D., & Walters, D. (2008). Revisiting Canada’s brain drain:

Evidence from the 2000 cohort of Canadian university graduates.Canadian Public Policy, 34(3), 305–319.

Zeileis, A. (2006). ineq: Measuring inequality, concentration andpoverty. R package version 0.2–7.