Race and the Reproduction of Educational Inequality

The Advanced Placement Arms Race and the Reproduction of Educational Inequality
Forthcoming in Teachers College Record
Joshua Klugman
E-mail: [email protected]
Phone (cell): 215-219-9107
Phone (office): 215-204-1452
Phone (home): 215-981-0330
Gladfelter Hall 713
1115 West Polett Walk.
Philadelphia, PA 19103
[email protected]
About the Author:
JOSHUA KLUGMAN is an assistant professor in the Department of Sociology and Department
of Psychology at Temple University. His research interests include the college
choice/admissions process, the role of selective colleges in status attainment, and the reception
immigrant children receive in U.S. elementary schools. His recent work includes “The Politics
of Equality: American Support for Redistribution in Education” in Social Science Journal.
Brief Summary of Article:
From 2000-2002, the state of California attempted to expand access to Advanced Placement
subjects for students attending public schools. This study shows this intervention succeeded in
expanding the AP curricula and enrollments at disadvantaged schools; however, schools serving
affluent communities broadened their AP offerings at the same (if not faster) rate, resulting in
effectively maintained inequalities in AP access.
Background: Access to Advanced Placement (AP) courses is stratified by class and race.
Researchers have identified how schools serving disadvantaged students suffer from various
kinds of resource deprivations, concluding that interventions are needed to equalize access to AP
courses. On the other hand, the theory of Effectively Maintained Inequality (EMI) argues that
schools serving advantaged students may perpetuate inequalities by expanding their AP
curriculum so their graduates can be competitive in the college admissions process.
Research Questions: Between 2000 and 2002, California attempted to expand AP offerings and
enrollments. This study answers whether or not this intervention narrowed inequalities in AP
along class and racial lines. It also examines if community affluence affects district officials’
views of pressures to offer AP courses, which could explain any effectively maintained
inequalities in AP access.
Research Design: This study uses a panel dataset of all California public high schools from
1997-2006. It examines the changing effects of school poverty, upper-middle-class presence,
and school racial composition on offerings of and enrollments in AP subjects. It supplements the
quantitative analysis with interviews from 11 school district officials in California conducted in
Results: Hierarchical generalized linear models show that upper-middle-class presence structures
California high schools’ AP subject offerings and enrollments, much more than school poverty.
California’s intervention resulted in increased AP subject offerings and enrollments in high
schools serving disadvantaged and less-advantaged students, but these reductions in deprivation
had trivial effects on inequalities, since schools serving advantaged students increased their own
AP offerings and enrollments. In addition, high schools serving white and Asian students had
larger increases in AP offerings and enrollments than high schools serving black and Hispanic
students. Interview data indicate that officials in affluent districts perceived a greater demand for
AP subjects, and were more likely to report their school staff were proactive to initiate new AP
courses, than officials in districts serving working-class communities.
Conclusions: The findings document that while policies can increase AP access at schools
serving low-income students, the actions of affluent schools and families will pose substantial
barriers to achieving parity in AP offerings and enrollments. Moreover, studies gauging resource
inequalities among schools may underestimate these inequalities if they use school poverty to
measure schools’ socioeconomic composition.
Executive Summary:
In 1999, a group of students and their parents in the nearly all-minority district of
Inglewood sued the state of California. Their lawsuit charged that the distribution of Advanced
Placement (AP) courses was inequitable, and pointed out that while their local high schools
offered only two or three AP courses, nearby high schools serving affluent families offered 14 to
18 courses.
In response, California undertook an intervention to expand access to AP courses in its
public high schools, particularly those with low-income students and those that had low offerings
of AP subjects. The state legislature and governor allocated money for ostensibly four-year long
“AP Challenge Grants” that would be used for teacher training, instructional materials, and
tutoring. The state allocated additional money to the Advancement Via Individual
Determination (AVID) program for supporting the AP curriculum through teacher training and
tutoring, as well to the University of California College Preparatory Initiative (UCCP) to
implement online AP courses for schools where small sizes and low demand made it impractical
to offer AP classes. Due to budget constraints, these interventions were short lived—the AP
Challenge Grants were ended after only three years, and the funds for AVID and UCCP eroded
after two and three years, respectively.
Regardless, there was a short period of time when California high schools were receiving
substantial resources to expand their AP curricula. This study examines how California’s
intervention affected inequalities in AP course offerings and enrollments between high schools
based on the presence of upper-middle-class individuals, poor students, black students, and
Hispanic students.
There are two different ways to think about resource inequalities in education. The
mainstream view—which I call the “resource deprivation” perspective—holds that schools
serving disadvantaged students (students from low-income families and students who are African
American or Hispanic) suffer from resource constraints and other deprivations that prevent them
from offering high levels of advanced courses, and also prevent disadvantaged students from
enrolling in them. Remedying the resource constraints would allow for greater advanced course
offerings and enrollments, and go some way to remedying inequalities in access to those courses.
An alternative perspective, the “Effectively Maintained Inequality” (EMI) perspective,
suggests that scholars need to focus on the actions of advantaged families and their children.
The EMI framework, formulated by University of California-Berkeley educational sociologist
Samuel Lucas, holds that “socioeconomically advantaged actors secure for themselves and their
children some degree of advantage wherever advantages are commonly possible.” Because
affluent families are confronting the challenges of greater competition for admission to selective
colleges, EMI theory predicts they will pressure their schools to offer a broader menu of AP
subjects. Additionally, their children will enroll in these courses at increasing rates. This
dynamic means that adding resources to distressed schools will not ensure greater equality in
access to advanced courses, because advantaged schools will see growth in their AP subjects and
My paper uses annual data from California’s Department of Education on public high
schools. The data covers the years 1997-2006. Using multilevel count models, I analyze
inequalities in offerings of and enrollments in old AP subjects (AP subjects that were established
before 1997) and new AP subjects (AP subjects that were established in 1997 or afterwards).
Data on course offerings was supplemented by data from the UCCP on which high schools had
students taking online AP courses.
In addition to my statistical analysis, I also conducted interviews with 11 school district
officials in California in 2006. This interview data allows me to shed light on whether or not
student and parental pressures compelling schools to offer AP subjects vary by district
demographics. EMI theory identifies these pressures as a key mechanism for the persistence of
inequalities in educational opportunities. In addition, the data from the in-depth interviews will
be used to explain unexpected findings in the statistical analysis.
My main findings are:
(1) The resource deprivation perspective accurately predicts that that California’s
intervention succeeded in increasing AP subject offerings and enrollments in districts
serving less advantaged families. By 2006, less advantaged districts tended to have
the same levels of AP subject offerings and enrollments that more advantaged
districts had in 1997.
(2) However, advantaged districts tended to increase their AP subject offerings and
enrollments at the same pace (if not a faster one) as less advantaged districts. Thus,
inequalities in AP subject offerings and enrollments were maintained over time, in
line with EMI theory.
(3) Also consistent with EMI theory is that inequalities in AP access and enrollments are
based more on the presence of upper-middle-class individuals, rather than the
presence of impoverished students. AP courses depend more on the presence of
advantaged populations, rather than the absence of disadvantaged groups.
Researchers seeking to understand inequalities in educational resources need to focus
on, and problematize, the behaviors of advantaged families and their schools.
(4) While schools serving African American and Hispanic students increased their AP
offerings and enrollments over the 1997-2006 time period, racial inequalities actually
started to grow during the intervention period (particularly for offerings of old AP
subjects). It appears that schools serving fewer minority students were better able to
take advantage of California’s interventions.
(5) In my interviews with school district officials, it was common for those in uppermiddle-class districts to volunteer that their AP curricula was driven by the pressures
students face in the college admissions process. This was case even for
superintendents who reported that they or their teaching staff had objections to the AP
program. In contrast, officials at districts serving largely working-class communities
reported little to no pressure to expand the AP program. This is consistent with EMI
theory. The status anxieties of upper-middle-class families, provoked by the college
admissions process, are driving AP expansion in affluent schools.
(6) Respondents from upper-middle-class districts also reported that their teaching staff
was proactive in anticipating demand for additional AP subjects and introducing
those courses. In contrast, officials at less affluent districts argued that their teaching
staff was overwhelmed by other problems, preventing them from initiating expansion
of their school’s AP curricula. This is a possible explanation for why schools serving
racial minorities tended to fall behind in AP access, despite California’s efforts to
make it easier for high schools to increase their AP curricula.
Overall, my analysis of AP offerings and enrollments suggests California’s intervention
succeeded in alleviating disadvantaged schools’ deprivation in their AP curricula. However, the
intervention failed to remedy inequalities based on class and race (and in fact, the intervention
appears to have exacerbated racial inequalities in AP access). This is consistent with EMI
theory. The paper concludes that inequalities in educational opportunities are symptoms of
deeper structural inequalities between families and communities, and thus are difficult to directly
target using educational interventions.
In the United States, inequalities in opportunities to learn high-level curricular content are
stark reminders that equality of educational opportunity has yet to be achieved. Schools serving
students from low-income families have fewer opportunities to learn advanced content
(Mickelson 1980; Mickelson and Everett 2008; Schmidt, Cogan, Houang, and McKnight 2011).
This study focuses on one type of high-level curricular content, the Advanced Placement (AP)
program, which ostensibly offers standardized, college-level material. Understanding why some
schools offer more of these advanced courses, and have higher enrollments in them, is important
because these courses influence future educational achievements and attainments (Engberg and
Wolniak 2010).
Much research on educational inequalities rests on what I refer to as a resource
deprivation framework, which argues that constraints on disadvantaged families and their
schools pose barriers to low-SES students, black students, and Latino students from accessing
educational opportunities. Increasing advanced courses at their schools should narrow
inequalities in opportunities to learn.
On the other hand, there is reason to believe that inequalities are “effectively maintained”
(Lucas 2001) and are resistant to interventions targeting resources at disadvantaged schools.
This is because enrolling in high-level curriculum is not just an “opportunity to learn” but also an
opportunity to earn marks of distinction—achievements (academic or otherwise) valued by
prestigious gatekeepers such as college admissions officers. To maintain their competitive edge,
students from advantaged groups, such as high-SES families will pursue an increasing number of
distinctions, a dynamic that their schools facilitate. While opportunities to learn may increase
among schools serving disadvantaged populations, they will increase at the same rate—or at a
higher rate—at schools serving advantaged students.
This study examines the generation and maintenance of inequalities in schools’ AP
subject offerings and enrollments in the state of California. It uses quantitative data covering the
years 1997-2006 to trace inequalities in AP subjects, and qualitative interview data with district
officials to gauge their perceptions of the push to offer more AP subjects. Ultimately, it shows
that the state’s attempt to promote access to AP subjects conflicted with dynamics that
preserved—and in some cases, generated—class and racial inequalities in schools’ AP offerings
and enrollments.
Some argue that focusing on inequalities in AP access is counter-productive, since
students who have less access to AP courses are also those who are less likely to succeed in those
courses. According to this argument, the heart of the problem is inequality in the availability of
rigorous curricula at earlier stages in educational careers (Dougherty and Mellor 2010;
Klopfenstein and Thomas 2010; although see Iatarola, Conger, and Long 2011, p. 17, for a
counter-argument). While there may be truth to this argument, inequalities in AP access are
worthy of study because they reveal a dynamic process of advantaged families and their schools
acquiring more opportunities for marks of distinction. This process leads to redefining upwards
the standards of merit used to evaluate students and schools. At one point in time, taking a single
AP subject was considered a mark of distinction that entitled one to enroll in a selective college.
Evidence indicates this is not the case anymore—enrolling in multiple AP courses, and excelling
on their associated exams is now distinctive (Schneider 2009). This makes it harder for students
from disadvantaged backgrounds to achieve a level of distinction comparable to those from
upper-middle-class families (Alon 2009; Bastedo and Jaquette 2011).
Policymakers, educational researchers, and opinion leaders commonly agree that
achieving parity in access to high-level content is desirable. Researchers have argued for
universal offerings of algebra in middle schools (Gamoran and Hannigan 2000; Raudenbush,
Fotiu, and Cheong 1998), and some even go beyond advocating universal access to college-level
curriculum in high schools (i.e., Advanced Placement courses). The Washington Post runs
annual rankings of all local high schools based solely on the ratio of Advanced Placement and
International Baccalaureate tests taken to the number of graduating seniors. In 2009, the U.S.
Department of Education exhorted public schools to use stimulus funds to expand their AP
programs, as well as to help prepare struggling students for the rigor of these classes (U.S.
Department of Education 2009). Disadvantaged groups have pushed for these courses as well.
In 1999, a group of parents of high school students in the nearly all-minority school district of
Inglewood sued the state of California (Daniel v. State of California); their complaint rested on
the fact that while their local high schools offered only 2 to 3 AP courses, nearby high schools
serving affluent families offered 14 to 18.
The lawsuit spurred the state to increase the AP offerings of high schools, particularly
those schools that offered a limited number of AP subjects. The state legislature and governor
allocated money for ostensibly four-year long “AP Challenge Grants” that were awarded to 61
percent of all high schools, to be used for teacher training, instructional materials, and tutoring.1

The state also allocated additional money to the Advancement via Individual Determination
(AVID) program for supporting the AP curriculum through teacher training and tutoring.
Finally, California spent money on the University of California College Preparatory Initiative
(UCCP) to implement online AP courses for schools where small sizes and low demand made it

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1 Schools serving poor students are slightly overrepresented among grant recipients; among all California high
schools, 22 percent are majority-poor; among the AP Challenge Grant high schools, a third were majority-poor
(California Department of Education 2002).
impractical to offer AP classes.2
Due to budget constraints, these interventions were short
lived—the AP Challenge Grants were ended after only three years, and the funds for AVID and
UCCP also eroded after two and three years, respectively.
Many researchers examining curricular inequalities—including inequalities in the
Advanced Placement curriculum–share a resource deprivation perspective (Conger, Long, and
Iatarola 2009; Corcoran, Evans, Godwin, Murray, and Schwab 2004; Iatarola et al. 2011;
Klopfenstein 2004; Raudenbush et al. 1998; Roscigno, Tomaskovic-Devey, and Crowley 2006).
They view high-level curricula as opportunities to learn and argue that inequalities in access to
high-level curricula result from disadvantaged families’ and schools’ limited resources, be they
material resources (e.g. schools’ funding) or immaterial resources (e.g. student’s academic
preparation, cultural capital, or social capital). These resource constraints affect offerings
through school-level processes, such as school officials’ perceptions of demand for these courses
and their students’ ability to succeed in them (Iatarola et al. 2011; Spade, Columba, and
Vanfossen 1997). These constraints affect enrollments both through school-level processes and
individual-level processes. School-level processes are involved since enrolling in AP courses in
a high school is contingent on the school offering those courses. However, even in schools that
have a broad AP program, individual-level influences still matter for course-taking patterns.
Students from low-SES families are less likely to enroll in these courses (Conger et al. 2009;
Crosnoe and Schneider 2010), owing to disadvantages in academic preparation, fewer perceived
opportunities for upward mobility, or less confidence to assert their rights to advanced
coursework (Conger et al. 2009; Demareth 2009; Roscigno et al. 2006; Useem 1992).

According to data provided by the UCCP, about 20 percent of California high schools used at least one UCCP
online AP course for at least one year during the period being examined here (the average number of years for those
schools using UCCP was 2.2).
Researchers in the resource deprivation framework acknowledge that eliminating educational
inequalities is not just a matter of targeting material and curricular resources as schools and
individuals (e.g. Allensworth, Nomi, Montgomery, and Lee 2009; Crosnoe and Schneider 2010).
However, their framework implies that making it easier for schools to offer AP courses will
result in at least some narrowing of inequalities in subject offerings and enrollments.
Studies in the resource deprivation perspective are invaluable in helping policymakers
and scholars realize the barriers to equalizing access to high-level curricular content. However,
starting in the 1990s researchers began to study the resiliency of educational inequalities in the
face of egalitarian reforms (e.g. Shavit and Blossfeld 1993). This culminated in Lucas’s (2001:
p. 1652) theory of “Effectively Maintained Inequalities” (EMI) which argued that
“socioeconomically advantaged actors secure for themselves and their children some degree of
advantage wherever advantages are commonly possible”. This theory allows for advantaged
actors securing quantitative educational advantages (such as years of schooling) or qualitative
advantages (namely, type of schooling). Lucas applied his EMI thesis to tracking in U.S. high
schools and argued that a crucial mechanism underlying EMI dynamics are parental pressures on
school officials to provide educational opportunities for their children. Since parents’ ability to
influence school officials varies by class, large socioeconomic differentials in track location are
produced. Subsequent studies documented how inequalities in qualitative distinctions among
students can persist (and sometimes even grow) despite the equalization of quantitative
distinctions among students (Alon 2009; Ayalon and Shavit 2004; Bolivar 2011). In the context
of the AP program, enrollment in AP courses and scoring well on AP exams are not just
opportunities to learn (as the resource deprivation perspective views them), but are also marks of
distinction signifying qualitative differences among students who have achieved the same
quantitative level of education (a high school diploma).
The fact that AP courses are marks of distinction valued by selective colleges (Geiser and
Santelices 2006; National Research Council 2002) is an outcome of two processes. First,
selective colleges, acting on their own institutional interests, define the basic contours of what is
considered meritorious achievement. In order to retain their prestige and legitimacy, selective
colleges will emphasize academic achievement in their admissions decisions (Kilgore 2009).
Second, prospective students, particularly those from affluent families, will adapt their behaviors
to fulfill the criteria of selective colleges (Alon 2009). Researchers argue that as selective
colleges face an increasing number of qualified applicants, they naturally respond by selecting
those students who are superior in academic performance (Alon 2009; Hoxby 2009) as well as
those students who can present a coherent and unique narrative about themselves and their
abilities (Stevens 2007).3
As I will discuss later, AP courses, particularly the newer ones, may
help students formulate such unique narratives that help them stand out.
In reaction to changes in selective colleges’ criteria, students aspiring to attend such
colleges will adapt (Alon 2009) and increase their own marks of distinction, including enrolling
in a higher number of AP courses (Schneider 2009), resulting in an “Advanced Placement arms
race” (Davenport 2006). In short: the marks of distinction required to be certified as an
academically successful student deserving admission to a selective college is continually
upgraded. This effectively maintains inequality, as the upgrading makes it more difficult for
students of disadvantaged origins to reach parity in marks of distinction.

3 Because this study is about the AP program, I focus on academic marks of distinction.Others (Espenshade,
Chung, and Walling 2004; Golden 2006; Kilgore 2009; Stevens 2007) have studied the considerable role of nonͲ
academic marks of distinction in the college admissions process.
Prior research has documented EMI processes in individual educational attainments
(Alon 2009; Ayalon and Shavit 2004; Bolivar 2011; Lucas 2001), and this study tests whether or
not they occur for curricular differences between high schools. Schools serving affluent
communities have an interest in keeping their schools attractive to middle- and upper-class
families, maintaining the prestige and status of their communities (Logan and Schneider 1981;
Mintrom 1993; Peterson 1981). Because of the perpetual upgrading of academic standards for
students aspiring to selective colleges, it is expected that affluent families will come to demand
more and more AP offerings from their schools, and children in those families will enroll in
more of these courses. California’s intervention to equalize AP access should barely affect (if at
all) the socioeconomic gradients in schools’ AP offerings and enrollments.
It is even possible that AP inequalities will grow, particularly in newer AP subject
offerings and enrollments (e.g. Human Geography and Statistics). These are not necessarily
more rigorous or prestigious than more traditional AP subjects (e.g. English Literature and
Physics), but adding them to the curriculum expands the menu of choices that give students more
flexibility to package their marks of distinction to colleges. Students seeking to pursue relatively
novel courses of study (facilitating perceptions of them as unique) would benefit from this
flexibility. Another group of students who would benefit are academically weaker students who
cannot excel in the traditional AP subjects. Ayalon and Yogev (2005), for example, found that
EMI processes can thwart expansions to educational opportunities when socioeconomically
advantaged but academically less successful students are quick to take advantage of them. In
short, advantaged students and their parents will pressure their schools to offer the newest and
latest advanced coursework in legitimate subjects for the sake of a broader menu of educational
distinctions. For this study’s purposes, these are AP subjects recently rolled out by the College
Board, the organization overseeing the AP curriculum. Hence, class and racial inequalities in
these latest subjects are expected to grow faster than inequalities in older, established subjects.
Many studies on inequalities in Advanced Placement rely on cross-sectional data, and
document that schools serving poor students and minority students tend to offer fewer AP
subjects (Corcoran et al. 2004; Darity, Castellino, Tyson, Cobb, and McMillen 2001; Iatarola et
al. 2011; Roscigno et al. 2006). Only a few studies used longitudinal data to examine effects of
state interventions to expand access to AP courses. Klopfenstein (2004) analyzed inequalities in
AP course offerings in high schools in 1994 and 2000 in Texas, as did Zarate and Pachon (2006)
for California high schools in 1997 and 2003.4
Klopfenstein’s results showed that while schools
with a high presence of low-income students dramatically increased their AP offerings,
inequalities by school socioeconomic composition grew from 1994 to 2000—schools with a
small low-income presence managed to increase their AP offerings even more over the time
period. Zarate and Pachon (2006) have similar findings. Conger et al. (2009) examined student
enrollments in AP courses in Florida from 2002 to 2005, and found that disparities by student
race and poverty status worsened over time, with advantaged students’ likelihood of enrollment
increasing at a faster rate than disadvantaged students. This was the case even though Florida
was partnering with the College Board to increase AP access though teacher training and
incentives for teachers to take on AP assignments.
These studies improve our understanding of the dynamics of AP inequalities, and show
that EMI is applicable to them. However, their resource deprivation perspective leaves
important issues unaddressed. First, all of these studies use student poverty (or eligibility for

Iatarola et al (2011) also examined inequalities in AP subjects in Florida high schools from 2001 to 2005, but they
only presented the changing effects of students’ aggregated test scores on their high schools’ AP offerings.
free/reduced price lunches) to measure student socioeconomic status or school socioeconomic
composition, even though the presence of disadvantage is not the same thing as the absence of
advantage (Brooks-Gunn, Duncan, Klebanov, and Sealand 1993). Effectively Maintained
Inequality directs researchers to examine the actions and behaviors of advantaged actors, and
prior studies focusing on student or school poverty are potentially neglecting important
dimensions of inequality. A second issue that has yet to be addressed is the extent to which
inequalities in older and newer AP subjects differ. As outlined above, it is very plausible the
novelty of the newer subjects means that advantaged families and their schools are more likely to
exploit them once they become available.
Zarate and Pachon (2006) analyzed the effects of the intervention in California. In
addition to relying on measures of school poverty and not distinguishing between older and
newer AP subjects, other aspects of their analysis prevent it from answering questions this study
focuses on. Their analysis potentially underestimates the effectiveness of California’s
intervention because their data excluded online AP courses that were supported by California’s
efforts, a problem this study remedies. Second, Zarate and Pachon (2006) analyzed inequalities
in the 1997-1998 and 2003-2004 school years, and thus they cannot address what happened to
inequalities when the intervention was in full swing (from the 2000-2001 through the 2002-2003
school years), nor in an extended period of time after California retrenched its AP expansion
This study uses a mixed-methods approach. I test hypotheses about inequalities in old
and new AP subject offerings and enrollments with quantitative analyses. I also use data from
in-depth interviews with a handful of school officials in California to determine whether or not
the pressures propelling schools to offer AP subjects (namely parental and student demand) vary
by district socioeconomic composition. EMI theory identifies these pressures as a key
mechanism for the persistence of inequalities in educational opportunities. In addition, the data
from the in-depth interviews will be used to explain unexpected findings in the statistical
This study uses a panel dataset of California high schools, with annual observations of
schools from 1997-2006. The dataset was constructed using information on schools that (a)
report having non-zero enrollment in grades 11 and 12, and (b) that are not classified as special
schools, such as alternative, continuation, special education, or county-run schools. After the
dataset was constructed, there were 10,196 school-observations nested in 1,302 schools which
were nested in 461 districts; after dropping observations with missing values, there are 10,135
school-observations nested in 1,290 schools which were nested in 456 districts. Of all schools,
65 percent had data for all 10 years. For the schools with less than 10 years of data, 86 percent
were established after 1997 and 3 percent were closed down before 2006. Table 1 presents
summary statistics of all variables used in the analyses.
The analysis ends at the 2006-2007 school year for practical reasons. Starting in the
2007-2008 school year, UCCP went “open-access” and made their course materials available to
school districts. The decentralization of online courses makes it difficult to obtain a full
accounting of what AP subjects are offered in schools.
The outcomes analyzed are the number of unique AP subjects offered (offerings), and the
number of enrollments in AP courses, in each high school.5
This study distinguishes between
“old” AP subjects (27 subjects that were introduced by the College Board before the study
period; the most recent of these is AP Psychology, introduced in 1992) and “new” AP subjects
(subjects introduced during the study period, in 1997 or later; this consists of Statistics,
Environmental Science, Human Geography, World History, Chinese, Italian, and Japanese).
The bulk of the data for this variable came from the California Basic Educational Data
System (CBEDS) maintained by the California Department of Education. This database contains
the teaching assignments for every teacher in California’s public schools, as well as the
enrollments in these classes. This database poorly covers AP subjects that were offered through
the UCCP program (of the 1,941 AP courses taught through the UCCP from 1999 to 2006, only
527 were recorded in the CBEDS data). This is remedied by supplementing the CBEDS data
with information on the AP subjects UCCP covered in each school each year from 1999 (when
the UCCP started online AP courses) to 2006. 6
To measure the upper-middle-class presence in a district, data from the 2000 Census School
District Tabulation are used. The percent of employed civilians who work in professional or
managerial occupations, and the percent of adults who have a baccalaureate or higher degree are
scaled (alpha = .95). Because this variable is only available from the 2000 Census, it is static
and does not vary over time. The presence of black, Hispanic, and impoverished students is

5 “Enrollments” refers to the number of enrolled seats in AP courses; a student who enrolled in two separate AP
courses in a single year would contribute two enrollments to the school’s total for that year. 6
Unfortunately, the UCCP did not make available enrollments in their courses. Enrollment in UCCP courses were
imputed by using the median level of enrollment in those UCCP courses that were recorded by CBEDS. For
example, the median enrollment in AP Biology courses offered through UCCP and recorded by CBEDS was .9
percent of a school’s student body. This percentage was used to impute enrollments in UCCP AP Biology courses
not recorded in CBEDS. These imputations were done for only 1,414 AP courses, out of 64,362 AP courses.
measured using the Common Core of Data (CCD), which contains annual information on the
racial composition of schools as well as the proportion of students who eligible for free or
reduced price lunches. Since these variables are measured annually, they are time-varying.
Since this study uses four related measures of the presence of advantaged and
disadvantaged populations in a school or district, multicollinearity is a potential concern. The
strongest correlation among these four variables is .63 (between school poverty and school
proportion Hispanic), followed by -.45 (between school poverty and district upper-middle-class
presence, and between school proportion Hispanic and district upper-middle-class presence). It
is noteworthy that the correlation between poverty and upper-middle-class presence is strong, but
not so strong as to indicate that these variables are part of the same construct. Appendix A
presents the results for modeling separately the effects of upper-middle-class presence, school
poverty, and school racial composition (proportion black and proportion Hispanic). The results
are substantially similar to those presented in the main tables, when all of these variables are
simultaneously controlled for, indicating that multicollinearity is not an issue. The major
differences are that the negative effects of the presence of black and Hispanic students in schools
are substantially attenuated after controlling for school poverty and upper-middle-class presence,
indicating that some, but not all, of the disadvantages accruing to minority schools are reducible
to socioeconomic disadvantage.
Time is measured with dummy indicator variables for each year.7
When time is
interacted with sociodemographic variables, it is categorized into five periods: two preintervention periods (1997-1998 and 1999); the period where California implemented its

The year in which the fall semester occurred represents an entire school year; e.g. 1997 refers to the 1997-1998
school year.
interventions to expand schools’ AP curricula (2000-2002); and two post-intervention periods
(2003-2005 and 2006). There are two pre-intervention periods because 1999 was the first full
year where California had a reimbursement program for AP exam fees, even though AP exam
reimbursement programs are unlikely to have much of an effect on schools’ AP subject offerings
or enrollments (Klopfenstein 2004). There are two post-intervention periods because exploratory
analyses indicated that inequalities in access and enrollments increased from 2005 to 2006.
This study controls for the school’s charter status and metropolitan status (neither of
which vary over time), with dummy indicators for charter school (with traditional public high
schools as the reference) and city and rural location (with suburb as the reference category). The
time-varying log school size is controlled for, since schools with more students can take
advantage of the economies of scale to offer more unique AP subjects.
Both outcomes—AP subject offerings and enrollments–are count outcomes and modeled
using the multilevel analogue of negative binomial regression. When AP subject offerings are
the outcome, all time-varying predictors (racial and poverty compositions and enrollment size)
are lagged one year, since school administrators schedule courses in the prior school year. When
AP enrollments are an outcome, contemporaneous measures of the time-varying predictors are
used, and the number of students in grades 9-12 serves as an exposure variable, making the
outcome a rate. For the enrollment outcomes, this study compares the effects of
sociodemographic predictors with and without controlling for AP subject offerings. This allows
for examining the role of AP course offerings in the maintenance of inequalities in enrollments.
Since this study uses longitudinal data on schools which are nested in districts, to avoid
problems with statistical inference that accompany clustered data, three-level hierarchical
generalized linear models (HGLM) are used, with school-observations at level 1 (encompassing
all variables that vary over time), schools at level 2 (encompassing all static school
characteristics), and districts at level 3 (encompassing all static district characteristics). I present
the population-averaged results with robust standard errors.
To clearly present the changing effects of socioeconomic and racial composition, the
tables show only the main effects of these variables for the different time periods. The
significance of changes in these effects (in other words, the significance of the time period
interactions) is indicated with superscripts. The superscripts indicate if an effect significantly
changed from the prior time period, and if an effect in 2006 (the second post-intervention period)
is significantly different from the effect in the 2000-2002 intervention period.
Coefficients from count models refer to relative, not absolute differences. For example, a
coefficient of 0.50 means that a unit increase in the predictor increases the count (or rate, in the
case of enrollments) by 65 percent [exp(.5)-1 = 0.65]. The expansion of the AP curriculum from
1997 to 2006 will produce situations where relative differences between schools will decrease,
but the absolute differences between schools will grow.8
When examining changes in AP
inequalities over time, the discussion will place more weight on absolute differences between
predicted counts, which is in line with prior research which assumes that the benefits of the
number of AP courses or exams on student outcomes take on a linear form (Engberg and
Wolniak 2010; Geiser and Santelices 2006; Roscigno et al. 2006). On the other hand, since there

To illustrate this, say in one year an impoverished school offers 2 AP subjects and a rich school offers 4 AP
subjects; there is an absolute difference of 2 AP subjects; the rich school offers 100 percent more AP subjects than
the impoverished school. In the next year, the impoverished school offers 4 AP subjects and the rich school offers 7
AP subjects; the absolute difference grew to 3 AP subjects but the relative difference shrank; the rich schools offers
only 75 percent more AP subjects than the impoverished school.
are so few new AP subjects compared to old AP subjects (6 versus 27), it will not be surprising
that absolute gaps in old subjects are much larger than gaps in new subjects; consequently, when
comparing inequalities between old and new subjects, I will give more weight to the HGLM
In the spring of 2006 I conducted semi-structured interviews with 11 officials from a
variety of school districts in California. Nine were conducted in person (and transcribed); two
were conducted over the phone (notes were taken immediately after the interview). The districts
were selected from a single metropolitan area, and I sought to have a variety of districts in terms
of class composition and AP offerings. These 11 officials represent eight different school
districts: five districts serving predominantly upper-middle-class families (five superintendents
and one school board member); two districts serving communities with a relatively small uppermiddle-class presence (two superintendents and one school board member); and one large
central-city district (two school board members). Most of the interviews ran 30-45 minutes each.
When I approached prospective informants, I told them I wanted to interview them about the
difficulties they had in obtaining resources they needed, such as AP subjects. Information about
each district is presented in Table 2. To protect the confidentiality of my informants, districts are
identified with pseudonyms.
Table 3 shows the regression results for all four outcomes, and Figures 1-4 graph
socioeconomic and racial inequalities for the entire 1997-2006 period. The figures show the
predicted number of AP subject offerings (per school) and enrollments (per 100 students) for
schools that are one standard deviation above and below the mean in the presence of the upper-
middle class, impoverished students, black students, and Hispanic students, but are average on
all other predictors in the model.
For both old and new subjects, the presence of the upper-middle-class, and not the
presence of poor students, best explains variation in subject offerings. For most time periods, a
large upper-middle-class presence results in more subject offerings (although the effect is only
marginally significant from 1997 to 1998 and 2000 to 2005 for new AP subject offerings). This
indicates that using poverty to measure schools’ socioeconomic composition misses the main
source of inequalities in AP subjects.9

Figure 1 reveals two notable findings. First, for old AP subject offerings, inequalities
based on upper-middle-class presence stays roughly the same (about 1.1 subjects) throughout the
whole time period. The regression coefficients show the effect decreased substantially after
2000, but the absolute gap decreases by only a trivial amount. Inequalities in old AP subject
offerings are lowest in the 2003-2005 period (about 1 subject), after the intervention. Figure 1
shows this decreased inequality was an outcome of a contraction that was more severe for uppermiddle-class schools than for schools serving students of less advantaged origins. In other
words, schools serving upper-middle-class communities benefitted from California’s
interventions, allowing them to expand their old AP offerings, but when California ended their
intervention the upper-middle-class schools had problems maintaining their high levels of AP
offerings, leading to a slight reduction in inequalities in old AP subject offerings.
The second notable finding is that by 2006, schools with a small upper-middle-class
presence were offering about the same number of old AP subject offerings as were schools with

9 The relatively large effects of upper-middle-class presence and the relatively low effects of school poverty are not
artifacts of multicollinearity; Appendix A shows similar findings when these variables are entered in separate
a large upper-middle-class presence in 1997 (around 3.5). In other words, the school with a
small upper-middle-class presence would have “caught up” with the school with a large uppermiddle-class presence if the latter had not increased its own AP offerings. For new AP subjects,
Figure 2 shows the upper-middle-class advantage remains very small up until 2006, when it
jumps from an absolute gap of .07 subjects in 2005 to .23 subjects in 2006, a significant increase
according to the regression results.
For race, these results offer some surprises. Racial inequalities in old AP subject
offerings actually grow starting in 2000 (once California began its efforts to increase high
schools’ AP offerings) and remain stable up through 2006. In fact, the black and Hispanic
disadvantages in old AP subject offerings are not significant in the pre-intervention period, but
become significant afterwards (although the effect of proportion black only became significant at
the .10 level in the 2003-2005 period).
For new AP subjects, there are significant black and Hispanic disadvantages before 2000,
although these are very small inequalities as they appear in Figure 2. The black disadvantage
remains small and becomes insignificant after 2000; the Hispanic disadvantage remains
significant and the absolute gap between Hispanic schools and non-Hispanic schools grow over
time (although there is some closing of the gap in 2006). In short, while minority schools’
access to old and new AP subjects grew over time, overall the results show that access grew even
larger in schools serving whites and Asians. This is as EMI theory (and not the resource
deprivation perspective) expects.
Turning to enrollments, the results are especially consistent with EMI. The regressions
again show that the presence of the upper-middle-class drove inequalities in old AP subjects,
with little effect of poverty.10 Moreover, these effects grew over time, as illustrated by Figure 3.
A school with a small upper-middle-class presence had its enrollments grow from 9 to 13 per
100 students from 1997 to 2006; a school with a large upper-middle-class presence had its
enrollments increase from 13 to 22. As was the case for old AP subject offerings, the school
serving the less advantaged students would have reached parity with the school serving
advantaged parents by 2006 if enrollments in the latter school maintained at their original levels.
In Model 4, old AP subject offerings are controlled for, and while the effect of uppermiddle-class presence is smaller than it is in Model 3, it is still strong and grows over time. The
dashed lines in Figure 3 represent predictions from Model 5; the gap between them represents
inequalities for schools with the same number of AP subject offerings. The fact that the dashed
lines increase over time, and that the gap between them also increases, indicates that even if
schools did not grow their AP curriculum, enrollments in the AP courses would still grow, in
particular in upper-middle-class communities, effectively maintaining inequalities.
Schools with a large Hispanic presence were disadvantaged in their enrollments in old
AP subjects. California’s attempts to expand high schools’ AP offerings made no noticeable
impact on this disadvantage, as shown by Figure 3 (on average, a two-standard deviation
difference in proportion Hispanic corresponds to a difference of about 3.4 enrollments per 100
students in old AP courses). The results show similar inequalities based on the presence of
black students, but these are not statistically significant.
Turning to enrollments in new AP subjects, Figure 4 shows inequalities based on uppermiddle-class presence starting out very small but gradually growing over time; in 2006,
inequalities significantly, and sharply, grow. The effects of poverty and race on enrollments in

10 As was the case with AP subject offerings, the importance of upper-middle-class presence is robust even when
this variable is entered in models without controlling for school poverty or racial composition, indicating it is not an
artifact of multicollinearity.
new AP subjects are very similar to their effects on enrollments in old AP subjects. The
exception is that there some evidence that the negative effect of proportion Hispanic weakened
substantially for enrollments in new AP subjects in the 2006 period.
It was argued earlier that advantaged actors are quicker to secure new forms of distinction
for their children in order to increase their menu of options for obtaining distinctiveness. Thus,
inequalities should grow faster for newer AP subjects and enrollments than for older AP subjects
and enrollments. Indeed, inequalities based on upper-middle-class presence follow this pattern.
For old AP subjects, the effect of upper-middle-class presence declines gradually, from a
regression coefficient of 1.41 to .96, but for new AP subjects, the effect starts out at 1.10, shrinks
to around half that in the 1999-2005 period, and then in 2006 sharply increases so it is 1.4 times
the effect it was in the pre-intervention period. Inequalities grew for both old and new AP
enrollments, but the growth was again faster for enrollments in new subjects (from .91 to 1.99)
than for old subjects (from 1.30 to 1.87)
This study faces the problem of ecological inference on two levels. First, in the
examination of AP subject offerings, upper-middle-class presence is measured at the district level,
leading to the inference that upper-middle-class presence in schools leads to more AP subject
offerings. However, another possibility is that within districts, schools serving advantaged
families have fewer AP subject offerings, invalidating my ecological inference. This is rather
unlikely, in light of evidence that intra-district inequalities in school resources favor schools with
a larger advantaged (or smaller disadvantaged) student population (Condron and Roscigno 2003;
Rubenstein, Schwartz, Stiefel, and Amor 2007). If anything, since these results use a districtlevel measure of advantaged populations, the estimated effects are conservative.
The second problem of ecological inference is that of inferring the effects of student
characteristics on AP enrollments, based on district- and school-level predictors. Results from
prior studies again indicate that if anything, the effects of socioeconomic status and race should
be stronger at the student level than at the district or school level. A number of studies document
that high schools serving advantaged populations tend to have more strict and exclusionary
tracking policies (Kelly 2009; Kelly and Price 2011; Kilgore 1991), including exclusionary
practices regarding access to AP courses (Attewell 2001), which likely create SES inequalities
favoring students of upper-middle-class origins. While it is possible that California’s reforms
affected school social organization to such an extent that within schools, disadvantaged students
were more likely to enroll in AP courses than advantaged students, such a scenario is not
plausible, especially considering evidence that upper-middle-class parents will staunchly protect
their children’s educational advantages at the expense of children from less advantaged families
(Cucchiara and Horvat 2009; Demareth 2009; Oakes, Wells, Jones, and Datnow 1997; Wells and
Serna 1996). Moreover, the interview data (presented below) indicates that officials in uppermiddle-class districts are responsive to the prerogatives of upper-middle-class families.
There is an unsettling implication of this. Consider enrollments in old and new AP
courses as shown in Figures 4 and 5. In 2006, an “upper-middle-class school” (a school one
standard deviation above the mean in upper-middle-class composition) would have 25.2 students
per 100 enrolled in old and new AP courses. To put it another way, in 2006 there were 1.2 AP
enrollments for every member of the senior class (on average, 21 percent of the student bodies in
California high schools were seniors). Compare this school to a school that is two standard
deviations lower on upper-middle-class presence. In this school, there were 14.8 students per 100
enrolled in AP courses in 2006, or .7 enrollments for every member of the senior class.
Prior studies document that the distribution of AP enrollments are more unevenly
distributed in the upper-middle-class school, and more evenly distributed in the less affluent
school (Attewell, 2001). In 2006, if one were to compare the AP courseload of an average AP
student in the upper-middle-class school to that of an average AP student in a working-class
school, the difference will probably be much bigger than is suggested by comparing 1.2 to .7
enrollments per member of the senior class.
This study shows persistent gaps in school AP offerings and increasing gaps in AP
enrollments. Schools with a large upper-middle-class presence maintained their positional
advantage. EMI theory infers these persistent gaps occurred because upper-middle-class families
exert pressures on their schools to make available educational opportunities for their children.
While I did not directly ask my respondents if college admissions criteria influenced their
curriculum, of the five upper-middle-class districts, respondents from three volunteered that this
was a factor in response to questions about the future of the AP program in their district or
student/parent demand for AP courses.
Superintendent, La Mar Azul district: There’s a thread among our teaching
staff at the high school that believes that all of our students are high-performing
and so we should not be separating them…where some students take AP classes.
But I think a reality has set in that, yes it’s true to treat every student equally and
not separate them, but our parents demand it, and so we do cater to parent wishes
and we recognize that it’s almost a factor in helping students get into the UCs
[Universities of California].
Superintendent, Bailey district: The main driver or variable on that [the growth
of the AP curriculum in his district] is what’s happening in the college admissions
process. Particularly what’s happening in the admissions process of top
universities. Because even though, you know, [a] relatively small percentage of
students go to top universities, what they’re doing kind of drives sort of the whole
perception of what you need to do…I don’t like it, and hopefully it’s not going to
last forever, but we’re very much in a period in which the number of college-level
classes that high schools students take, whether it’s through the AP program or
whether they’re actually going to community colleges to take classes—is a really
significant factor for a lot of students in terms of whether they get into top
universities or not. And parents know that. Parents in this community are
extremely sophisticated about that. Kids know this stuff. So as long as that’s
there there’s going to continue to be pressure on the schools to increase the
opportunities for kids to take college-level classes.
Superintendent, Sterling district: We believe that we need to provide our
students with every advantage because they’re all going to competitive colleges
and that’s the expectation that we prepare them for that.
These respondents’ answers are in accordance with a survey of AP teachers conducted in
2008 (Farkas and Duffett 2009). Teachers were asked how convincing they found various
explanations for the growth in the AP Program. Of those surveyed, 90 percent indicated they
were convinced by the explanation that “there are more students who want their college
applications to look better” and 76 percent were convinced that “high schools are expanding their
AP Program to improve their school’s ranking and reputation in the community.” Only 32
percent agreed that “there are more students who want to be challenged at a higher academic
level”, an explanation never mentioned by my respondents.
It is clear that many district officials, particularly those serving affluent communities,
perceive that they have to offer opportunities for marks of distinction for the college application
process (even if they personally object to the program), which is consistent with EMI theory.
Two other reasons were offered as well. The superintendent of the affluent Sterling district was
the only person who referred to APs as facilitating occupational success, but only in the context
of explaining why his district was shifting away from advanced courses in European languages
and towards those covering Asian languages. In his view, “if you’re going to be in business you
need an Asian language”. However, this perspective does not explain why advanced, collegelevel courses in Asian languages are needed.
A school board member at the large, central city district of Musuraca offered another
explanation. In addition to the benefits of “pumping up your resume and your transcript”, he
also referred to students enrolling in AP courses to obtain college credit to avoid scheduling
problems endemic at the Universities of California. Earning college credits was in fact the
original rationale for the AP program (Schneider 2009), and this remains a substantial motivation
for AP students (Farkas and Duffett 2009). It is nonetheless striking that the main reason for
broad AP curricula volunteered by the respondents is the college admissions process, not the
needs of employers, nor the requirements of citizenship.
Understanding how schools initiate new AP subjects can shed light on the class and racial
differences in AP subject growth documented in the statistical analysis. If EMI theory is correct,
schools officials in districts serving affluent communities should especially perceive parental
demands for AP courses, while officials in districts serving less advantaged communities should
be less likely to report such perceptions. I asked my respondents for their perceptions of student
and parental demand for AP courses and if it influences the breadth of their AP curriculum.
Respondents from all of the five upper-middle-class districts indicated that their schools were
responsive to student and parental demands for AP courses. A typical response comes from the
superintendent of the Sterling district:
Author: Is the major source of pressure to expand, to add an AP course, does
that come from the district, principals and teachers, or parents? Which do you
think would be the major push?
Superintendent, Sterling district: Parents and students…We have three or four
new ones [AP courses] coming in this year. The teachers have created human
geography…I think teachers know that is what parents and students are looking
for. So if they’re sitting down to write a course, that, I think influences them. So
it’s a mixture of it.
The superintendent from La Mar Azul reported that a similar dynamic compelled his district’s
high school to offer AP Art History.
Author: I don’t remember what the last AP course that was added to the district…
Superintendent, La Mar Azul district: Art History
Author: Was that pushed by parents?
SLMAD: Yeah. And by our principal, too. I think the reason it was added is because
there was a growing desire for additional new elective courses. That was one course that
we could offer.
Other respondents had similar stories of specific courses added due to parent and student
interest, or teachers’ anticipation of it. The superintendent of Tourneur district mentioned that
the conjunction of parental demand, as well as the interest of a Mandarin speaker on his teaching
staff, led one of his high schools to offer AP Chinese. The superintendent of Bailey district
emphasized his staff’s proactiveness in offering unique subject material, such as Japanese (“just
because they wanted to offer something other than French and Spanish”) and robotics.
Comparing the accounts of AP pressures and initiations in upper-middle-class schools to
working-class, racially diverse schools can shed some light on the puzzling finding that racial
inequalities in AP offerings actually grew during the intervention period. Respondents from both
of the two working-class districts told me that parental demand for AP courses was virtually nonexistent. Consider the response of the superintendent of the Greer district, which serves a mostly
working-class community, and at the time of the interview was dealing with a severe budget
crunch, when I asked him if parents complained about the lack of resources:
Author: Have you heard from parents who raise concerns or issues with school
resources at all? Like do they complain about buildings or do they say, you
know, like ‘my kid needs better instructional materials’ or things like that?
Superintendent, Greer district: A lot of apathy [is] in the community. Their
engagement is not where…you would want it. Small urban district, basically.
And the level of parent engagement…is low.…
[Later in the interview I ask him specifically about AP courses]
Author: Have parents, I know you said before there was this apathy, but have
parents come to you asking for more AP courses or anything like that?
SGD: No.
The lack of demand for AP courses, as well as dealing with the problems of a school
population composed disproportionately of poor students, gives little incentive for school
teachers or administrators to initiate new AP subjects. This is also evident in the accounts of two
board members (interviewed separately) from the large urban Musuraca district. Musuraca is
diverse racially and economically; some schools are dominated by children from upper-middleclass families and others draw disproportionately from poor neighborhoods. State- and federallevel accountability measures compelled schools serving impoverished students to focus on
remedial education, at the cost of high-level curricula such as AP, until the district mandated that
all high schools offer AP subjects. One of them described a situation where a combination of a
lack of demand and a focus on dealing with the problems of an at-risk student population force
schools to put as minimal an effort into AP as much as possible.11
Board member, Musuraca district: The push for school improvement is always
from the parents. It’s never from the teachers and principals.
Author: Even for courses like Advanced Placement…?
BMMD: It’s never from the teachers and principals.
Author: So parents have come to the school board: ‘I want’, uh…
BMMD: More AP. Yes.
Author: Really?
BMMD: Yeah. Or they go to their PTA and they go to their principal and the
principal can do it. They don’t have to talk to us. He just has to say ‘I want to put
it in’ and the [district] administration will OK it. The administration will say,
‘…Why don’t you have a gifted and talented program?….So we have pushed
principals to improve, the community has pushed principals to improve. It’s a
rare principal that jumps forward and says: ‘this is what we’re going to do.’

11 The other board member of Musuraca, when I asked him to locate the key actor behind the push for AP courses
(parents, the district, or schools), gave a very similar account, emphasizing the role of the district in pushing
schools serving impoverished students to broaden their AP offerings.
There’s some. I don’t mean to tar them with a black brush. But…the push for
school improvement doesn’t come from school faculty. They’re too busy working
trying to keep things together, dealing with today’s crisis, tomorrow’s crisis,
planning to do long-range academic planning. It’s difficult in that level unless it’s
supported and encouraged.
The situation in Musuraca provides an explanation for increasing racial inequality in AP
subjects and enrollments. While the Musuraca district ordered its high schools to offer more AP
subjects, schools in other districts serving disproportionately black and Hispanic students may not
have had this kind of district oversight. Instead, like the Musuraca schools the board member
describes, they are weighed down by a combination of factors—lack of student and parent
demand, accountability measures, and administrative inertia—that precluded them from
exploiting California’s intervention to the same extent as other schools serving white and Asian
This paper examines changes in socioeconomic and racial inequalities in high schools’
Advanced Placement offerings and enrollments in California. It did so during a period when
California attempted—and retrenched–a number of interventions to expand access to Advanced
Placement courses. It adjudicates between two perspectives for understanding inequalities in
educational opportunities. On the one hand, there is the resource deprivation framework, which
focuses on “opportunities to learn” and concludes that California’s interventions would help
schools serving disadvantaged students to increase their AP offerings and enrollments, and thus
reduce inequalities. On the other hand, there is Effectively Maintained Inequality theory, which
views AP courses as not just opportunities to learn but as opportunities to earn marks of
distinction. Making it easier for schools to offer AP courses may alleviate deprivation, but any
attempted reductions in inequalities are offset by the actions of advantaged families and schools,
who are motivated to accumulate more opportunities for distinction, given intensified competition
over admission to selective colleges (as reported by my respondents from affluent districts).
In sum, California’s intervention succeeded in raising AP subject offerings and
enrollments in schools serving disadvantaged populations, but as EMI theory predicts, it did very
little to decrease inequalities on these outcomes. The resource deprivation framework is
supported, in that California’s support for expanding the AP curriculum increased subject
offerings and enrollments in schools serving disadvantaged populations (namely, schools with a
small upper-middle-class presence or a large Hispanic or black population). But EMI theory
correctly points out that advantaged schools will increase their subject offerings and enrollments,
resulting in stable—or sometimes growing—inequalities in AP subject offerings and enrollments.
These inequalities are growing particularly fast for offerings of and enrollments in the newer AP
subjects, reflecting advantaged families’ (and their schools) quickly taking advantage of newer
marks of distinction.
Interviews with school district officials help us understand these results. Officials in
affluent districts candidly volunteered—without me raising the issue beforehand—that they
expanded the breadth of their AP curricula to help their students be competitive in admissions at
selective colleges, in line with the expectations of EMI theory. The interview data also hints at an
explanation for the surprising creation of racial disparities in AP subject offerings that occurred
once California started its intervention. School officials and teachers in schools serving black and
Latino students were unable to take advantage of California’s policies possibly because of lack of
student demand and constraints on school staffers’ own time, since they have to deal with
problems that occur in schools serving disadvantaged students.
This study has broader implications than just the success (or lack thereof) of California’s
interventions. First, studies using school poverty to gauge inequalities in advanced curriculum
(Corcoran et al. 2004; Darity et al. 2001; Iatarola et al. 2011; Klopfenstein 2004; Roscigno et al.
2006; Zarate and Pachon 2006) may underestimate the extent to which socioeconomic status
structures opportunities to obtain educational distinctions. Instead, this study shows that the
presence of low-income students has at best modest associations with AP subject offerings and
enrollments; the presence of advantaged families is a much better predictor. Unfortunately, such
measures are not commonly available at the school level. In fact, this study had to use a measure
of upper-middle-class presence at the district level, and consequently probably also is
underestimating school-level socioeconomic inequalities in AP subjects and enrollments.
The second implication is that the robust disparities in AP offerings and enrollments
indicate that inequalities of educational opportunity are symptoms of deeper structural inequalities
between families. My results indicate that it is difficult (if not impossible) to directly attack these
inequalities using educational interventions. Admittedly, California’s intervention did not
strongly target disadvantaged communities; a more prolonged and aggressive intervention may
have effectively reduced inequalities. However, analyses of AP inequalities in other states, such
as Texas and Florida, have also found the effective maintenance of inequalities (Conger et al.
2009; Klopfenstein 2004). It is worth pondering if EMI not only explains the lack of
consequences of these interventions, but their design as well: it is not in the interest of political
actors to legislate that disadvantaged communities have the same broad array of opportunities for
educational distinctions that affluent communities have (Mintrom 1993).
The third implication is that researchers could apply the tension between attempts to
alleviate resource deprivation in schools and EMI processes to other educational resources. It is
possible that the more removed the resource is from facilitating marks of distinction, the less
relevant EMI theory is for that resource, which would explain the success of state interventions in
reducing school finance inequalities (Evans, Murray, and Schwab 1997; Murray, Evans, and
Schwab 1998). Recently, researchers have been paying more attention to inequalities in observed
measures of teacher quality (e.g. Clotfelter, Ladd, and Vigdor 2011; Lankford, Loeb, and
Wyckoff 2002) and EMI theory may be more applicable to teacher quality than to education
spending. Affluent actors may work harder to procure high-quality teachers for their children
than high-spending schools.
Finally, the durability of inequalities this study uncovered raises important issues about
advanced curricula in general. As AP subjects and enrollments increase in schools serving uppermiddle-class students, it is very likely that at an individual level, inequalities in accumulating AP
courses are growing as well. The rising ceiling on individuals’ participation in AP courses might
influence perceptions about what the standard AP courseload is for students entitled to
scholarships or admission to selective colleges, a dynamic that other studies have observed for
other kinds of marks of distinction, such as grades and SAT scores (Alon 2009; Bastedo and
Jaquette 2011). In other words, EMI processes influence notions of meritorious achievement
(Alon 2009).
Between-school inequalities in AP offerings may not be problematic in the college
admissions process, given that college admissions officers reportedly evaluate applicants relative
to other students from the same school (Attewell 2001; Espenshade, Hale, and Chung 2005;
National Research Council 2002). Still, attending a disadvantaged school with a low level of AP
offerings may negatively affect students’ own self-perceptions about their academic worthiness
and exacerbate inequalities generated by self-selection behaviors.
There are also indications that “AP is no longer the zenith of academic challenge”
(Schneider 2009: p. 826), being surpassed by “homegrown” college-level courses taught in elite
secondary schools. This is an outcome EMI predicts. It remains to be seen if this movement
expands beyond the small fraction of high schools that “already have near perfect reputations
with elite colleges”, as one private school dean quoted by Schneider (2009: p. 827) put it. If it
does, and Advanced Placement becomes the college-level curriculum of last resort in high
schools, states will experience even more difficulty remedying the deprivations high schools
experience, and inequalities in students’ college destinations will probably increase even more
than they have in the past. Less importantly, tracking inequalities in opportunities for
educational distinctions will become even more of a challenge for researchers and educational
advocates, since the standardization of the AP program makes it relatively easy to record in
surveys and databases.
As noted in the introduction, some researchers argue that expanding AP access has little
potential to increase educational opportunities for disadvantaged students simply because they
lack the preparation to succeed in these classes (Dougherty and Mellor 2010; Klopfenstein and
Thomas 2010). Instead, these authors propose increasing academic rigor at earlier stages in
secondary and primary education. This study cannot speak to these claims, but the implication of
this study’s results is that whatever benefits there are for increasing rigor in schools, reducing
inequalities in students’ marks of distinction may not be one of them.
This research was supported by a Spencer dissertation fellowship and a dissertation grant from
the American Educational Research Association, the latter being funded by the National Science
Foundation and the National Center for Education Statistics under NSF grant #REC-0310268. I
thank Andrea Hesse and Lois Locci at UCCP for providing me with their data, and Marjorie
McConnell and Joe Radding at the California Department of Education and Laura Izuel at AVID
for helping me understand the intricacies of California’s interventions. I also thank Roberta
Klugman and Don Link for research assistance. I am grateful for useful feedback from Art
Alderson, Maia Cucchiara, Kim Goyette, Erin McNamara Horvat, David James, Robert
Toutkoushian, Pam Walters, and Elliot Weininger.
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0 1 2
AP Subjects
1998 2000 2002 2004 2006
14% Upper-Middle Class
42% Upper-Middle Class
Presence of Upper-Middle Class in District
0 1 2
AP Subjects
1998 2000 2002 2004 2006
58% Impoverished
8% Impoverished
Presence of Impoverished Students in School
0 1 2
AP Subjects
1998 2000 2002 2004 2006
24% Black 0% Black
Presence of Black Students in School
0 1 2
AP Subjects
1998 2000 2002 2004 2006
61% Hispanic 9% Hispanic
Presence of Hispanic Students in School
NOTE: Predicted old AP subject offerings calculated from coefficients presented in Model 1, Table 3.
Figure 1: Old AP Subjects
0 .25 .5 .75
AP Subjects
1998 2000 2002 2004 2006
14% Upper-Middle Class
42% Upper-Middle Class
Presence of Upper-Middle Class in District
0 .25 .5 .75
AP Subjects
1998 2000 2002 2004 2006
58% Impoverished
8% Impoverished
Presence of Impoverished Students in School
0 .25 .5 .75
AP Subjects
1998 2000 2002 2004 2006
24% Black 0% Black
Presence of Black Students in School
0 .25 .5 .75
AP Subjects
1998 2000 2002 2004 2006
61% Hispanic 9% Hispanic
Presence of Hispanic Students in School
NOTE: Predicted new AP subject offerings calculated from coefficients presented in Model 2, Table 3.
Figure 2: New AP Subjects
10 15 20 25
AP Enrollments
1998 2000 2002 2004 2006
14% Upper-Middle Class
42% Upper-Middle Class
Presence of Upper-Middle Class in District
10 15 20 25
AP Enrollments
1998 2000 2002 2004 2006
58% Impoverished
8% Impoverished
Presence of Impoverished Students in School
10 15 20 25
AP Enrollments
1998 2000 2002 2004 2006
24% Black 0% Black
Presence of Black Students in School
10 15 20 25
AP Enrollments
1998 2000 2002 2004 2006
61% Hispanic 9% Hispanic
Presence of Hispanic Students in School
NOTE: Solid lines are predicted old AP subject enrollments (per 100 students) calculated from
coefficients presented in Model 3, Table 3. Dashed lines, calculated from coefficients presented
in Model 4, Table 3, represent predictions after controlling for old AP subject offerings.
Figure 3: Old AP Enrollments Per 100 Students
0 1 2 3
AP Enrollments
1998 2000 2002 2004 2006
14% Upper-Middle Class
42% Upper-Middle Class
Presence of Upper-Middle Class in District
0 1 2 3
AP Enrollments
1998 2000 2002 2004 2006
58% Impoverished
8% Impoverished
Presence of Impoverished Students in School
0 1 2 3
AP Enrollments
1998 2000 2002 2004 2006
24% Black 0% Black
Presence of Black Students in School
0 1 2 3
AP Enrollments
1998 2000 2002 2004 2006
61% Hispanic 9% Hispanic
Presence of Hispanic Students in School
NOTE: Solid lines are predicted new AP subject enrollments (per 100 students) calculated from
coefficients presented in Model 5, Table 3. Dashed lines, calculated from coefficients presented
in Model 6, Table 3, represent predictions after controlling for old AP subject offerings.
Figure 4: New AP Enrollments Per 100 Students
Table 1 • Summary Statistics
Variable M SD
AP Subjects 6.34 4.64
Old AP Subjects 5.87 4.25
New AP Subjects 0.47 0.7
AP Enrollments 294.86 332.7
Old AP Enrollments 271.82 302.25
New AP Enrollments 23.05 51.53
AP Enrollments Per 100 Students 16.75 49.37
Old AP Enrollments Per 100 Students 15.51 48.97
New AP Enrollments Per 100 Students 1.24 3.06
SchoolͲYear Level (10,135 observations)
Proportion Impoverished 0.33 0.25
Proportion Black 0.08 0.12
Proportion Hispanic 0.35 0.26
Enrollment (1000s) 1.59 1.06
Log enrollment 0.178 1.311
SchoolͲLevel (1,290 schools)
Charter School 0.2 —
DistrictͲLevel (456 districts)
UpperͲMiddleͲClass 0.28 0.14
Suburb 0.64 —
City 0.13 —
Rural 0.18 —
Average AP
Subjects Per
Total High
School Enrollment
Number of
Schools Interviewed
Bailey 15 60 1 1 5 5,001 to 10,000 2 to 5 Board member; superintendent
Greer 5 30 30 35 20 1,001 to 5,000 2 to 5 Board member; superintendent
La Mar Azul 10 70 10 10 10 0 to 1,000 1 Superintendent
Markham 10 60 10 1 10 5,001 to 10,000 2 to 5 Superintendent
Moffat 5 30 15 20 20 0 to 1,000 1 Superintendent
Musuraca 5 50 40 10 20 10,001 + 5 + Two board members
Sterling 10 60 1 1 5 1,001 to 5,000 2 to 5 Superintendent
Tourneur 10 70 5 5 5 1,001 to 5,000 2 to 5 Superintedent
Table 2: Description of School Districts Where Informants Served
NOTE: To preserve informants’ confidentiality, district names are pseudonyms and district statistics are rounded.
1997Ͳ1998 1.405 *** 1.097 * 1.304 *** 0.488 * 0.913 Ͳ0.926
(0.200) (0.634) (0.359) (0.255) (0.822) (0.816)
1999 1.469 *** 0.666 1.546 ***b 0.628 ** 1.005 0.638 a
(0.200) (0.530) (0.297) (0.244) (0.614) (0.626)
2000Ͳ2002 1.034 ***
a 0.565 * 1.717 *** 0.928 ***
a 1.222 *** 0.981 ***
(0.168) (0.332) (0.229) (0.205) (0.401) (0.325)
2003Ͳ2005 0.897 ***
b 0.515 * 1.655 *** 0.957 *** 0.993 *** 0.624 **
(0.176) (0.296) (0.235) (0.188) (0.369) (0.288)
2006 0.955 *** 1.528 ***ac 1.873 *** 1.170 *** 1.994 ***ad 0.406
(0.211) (0.286) (0.275) (0.250) (0.360) (0.353)
1997Ͳ1998 Ͳ0.128 Ͳ0.428 Ͳ0.215 * Ͳ0.278 ** Ͳ1.498 * Ͳ1.469 **
(0.130) (0.656) (0.235) (0.121) (0.909) (0.580)
1999 Ͳ0.107 Ͳ0.354 Ͳ0.147 Ͳ0.123 Ͳ0.789 Ͳ0.808 **
(0.099) (0.458) (0.160) (0.110) (0.539) (0.363)
2000Ͳ2002 0.148 *
a 0.244 0.047 0.036 a Ͳ0.180 Ͳ0.113 b
(0.086) (0.185) (0.103) (0.094) (0.317) (0.244)
2003Ͳ2005 0.051 0.107 Ͳ0.021 0.035 0.002 Ͳ0.075
(0.080) (0.145) (0.109) (0.089) (0.222) (0.201)
2006 0.025 0.122 Ͳ0.018 0.026 Ͳ0.218 Ͳ0.374
(0.134) (0.159) (0.140) (0.026) (0.364) (0.296)
1997Ͳ1998 Ͳ0.175 Ͳ2.330 ** Ͳ0.234 Ͳ0.037 Ͳ0.141 1.969
(0.267) (1.095) (0.581) (0.299) (1.644) (1.217)
1999 Ͳ0.150 Ͳ1.720 ** Ͳ0.296 Ͳ0.077 Ͳ1.154 Ͳ0.491 a
(0.366) (0.793) (0.450) (0.215) (1.291) (0.728)
2000Ͳ2002 Ͳ0.581 a Ͳ0.457 Ͳ0.597 Ͳ0.276 Ͳ0.527 0.287
(0.370) (0.400) (0.448) (0.233) (0.466) (0.416)
2003Ͳ2005 Ͳ0.646 * Ͳ0.248 Ͳ0.660 Ͳ0.336 Ͳ0.708 Ͳ0.059
(0.332) (0.359) (0.476) (0.234) (0.470) (0.365)
2006 Ͳ0.572 Ͳ0.246 Ͳ0.788 Ͳ0.423 Ͳ0.728 Ͳ0.565 d
a. Effectissignificantlydifferentfromeffectinpriortimeperiod, p <.05
b. Effectissignificantlydifferentfromeffectinpriortimeperiod, p <.10
c. 2006Effectissignificantlydifferentfrom2000Ͳ2002effect, p <.05
d. 2006Effectissignificantlydifferentfrom2000Ͳ2002effect, p <.10
NOTE: Standarderrorspresentedinparentheses.ForAPsubjectmodels, poverty,race, andenrollmentvariablesarelaggedbyoneyear.For
APenrollmentmodels, poverty,race, andenrollmentarecontemporaneous.Allmodelsincludecontrolsforyearindicators.
Model 3 Model 5 Model 6
Model 1 Model 2 Model 4
1997Ͳ1998 0.000 Ͳ1.102 ** Ͳ0.616 ** Ͳ0.240 ** Ͳ2.027 *** Ͳ1.058 **
(0.134) (0.551) (0.170) (0.110) (0.716) (0.535)
1999 0.018 Ͳ1.219 ** Ͳ0.500 *** Ͳ0.215 * Ͳ2.492 *** Ͳ0.725
(0.125) (0.441) (0.146) (0.111) (0.574) (0.454)
2000Ͳ2002 Ͳ0.262 **a Ͳ0.869 *** Ͳ0.448 *** Ͳ0.198 * Ͳ1.188 ***
a Ͳ0.535 **
(0.117) (0.205) (0.144) (0.103) (0.318) (0.243)
2003Ͳ2005 Ͳ0.241 ** Ͳ0.839 *** Ͳ0.442 *** Ͳ0.218 ** Ͳ1.188 *** Ͳ0.655 **
(0.119) (0.223) (0.169) (0.105) (0.312) (0.222)
2006 Ͳ0.225 * Ͳ0.484 **
ac Ͳ0.451 *** Ͳ0.159 Ͳ0.475 b Ͳ0.165
(0.118) (0.207) (0.167) (0.103) (0.421) (0.387)
1997Ͳ1998 0.145 *** 2.339 ***
(0.008) (0.121)
1999 0.138 ***
a 1.823 ***a
(0.009) (0.089)
2000Ͳ2002 0.123 ***
a 1.471 ***a
(0.007) (0.053)
2003Ͳ2005 0.118 *** 1.110 ***a
(0.007) (0.050)
2006 0.110 ***
ac 0.946 ***ac
(0.007) (0.048)
Location(ref =Suburb)
City Ͳ0.017 Ͳ0.088 0.029 0.025 Ͳ0.082 Ͳ0.072
(0.050) (0.092) (0.075) (0.053) (0.096) (0.086)
Rural Ͳ0.011 0.105 Ͳ0.150 * Ͳ0.121 Ͳ0.042 Ͳ0.188
(0.071) (0.124) (0.091) (0.075) (0.230) (0.152)
CharterSchool Ͳ0.754 *** Ͳ0.790 *** Ͳ0.363 Ͳ0.388 ** Ͳ0.467 ** Ͳ0.462 *
(0.213) (0.227) (0.264) (0.198) (0.236) (0.245)
LogEnrollment 0.658 *** 0.691 *** 0.097 * Ͳ0.253 *** 0.223 *** Ͳ0.277 ***
(0.026) (0.042) (0.050) (0.039) (0.056) (0.049)
SchoolͲLevel 0.264 *** 0.682 *** 0.279 *** 0.140 *** 0.782 *** 0.381 ***
DistrictͲLevel 0.032 *** 0.334 *** 0.051 *** 0.019 *** 0.376 *** 0.132 ***
a. Effectissignificantlydifferentfromeffectinpriortimeperiod, p <.05
b. Effectissignificantlydifferentfromeffectinpriortimeperiod, p <.10
c. 2006Effectissignificantlydifferentfrom2000Ͳ2002effect, p <.05
d. 2006Effectissignificantlydifferentfrom2000Ͳ2002effect, p <.10
NOTE: Standarderrorspresentedinparentheses.ForAPsubjectmodels, poverty,race, andenrollmentvariablesarelaggedbyoneyear.For
APenrollmentmodels, poverty,race, andenrollmentarecontemporaneous.All modelsincludecontrolsforyearindicators.
1997Ͳ1998 1.489 *** 2.495 *** 2.073 *** 3.590 ***
(0.172) (0.528) (0.223) (0.596)
1999 1.528 *** 2.149 *** 2.186 *** 3.791 ***
(0.166) (0.430) (0.187) (0.470)
2000Ͳ2002 1.180 ***a 1.304 ***a 2.190 *** 2.696 ***a
(0.142) (0.273) (0.156) (0.303)
2003Ͳ2005 1.131 *** 1.385 *** 2.225 *** 2.446 ***
(0.146) (0.237) (0.161) (0.255)
2006 1.199 *** 2.029 ***ac 2.487 ***a 2.933 ***a
(0.164) (0.225) (0.213) (0.299)
1997Ͳ1998 Ͳ0.165 Ͳ1.452 *** Ͳ0.586 *** Ͳ2.682 ***
(0.103) (0.459) (0.143) (0.534)
1999 Ͳ0.144 Ͳ1.242 *** Ͳ0.510 *** Ͳ2.528 ***
(0.090) (0.380) (0.136) (0.394)
2000Ͳ2002 Ͳ0.031 Ͳ0.189 a Ͳ0.362 ***a Ͳ0.999 ***a
(0.062) (0.142) (0.103) (0.195)
2003Ͳ2005 Ͳ0.075 Ͳ0.277 ** Ͳ0.403 *** Ͳ0.747 ***
(0.070) (0.119) (0.085) (0.178)
2006 Ͳ0.084 Ͳ0.287 ** Ͳ0.505 *** Ͳ0.776 ***
(0.110) (0.134) (0.115) (0.195)
*p <.10;**p<.05;***p <.01
a. Effectissignificantlydifferentfromeffectinpriortimeperiod, p <.05
b. Effectissignificantlydifferentfromeffectinpriortimeperiod, p <.10
c. 2006Effectissignificantlydifferentfrom2000Ͳ2002effect, p <.05
d. 2006Effectissignificantlydifferentfrom2000Ͳ2002effect, p <.10
Appendix A • Effects of Upper-Middle-Class Presence, Student Poverty Presence, and Racial Composition Modeled
NOTE: Standarderrorsarepresentedinparentheses.ProportionupperͲmiddleͲclass, proportionimpoverished
students, andracial composition(proportionblackandproportionHispanic) areenteredinseparatemodels.
Proportionimpoverishedstudentsandracial compositionvariablesarelaggedbyoneyearforsubjects;for
enrollmentsthesemeasuresarecontemporaneous.Allmodels control forcity/suburb/rural location, log
enrollment(inthecaseof enrollments), laggedlogenrollment(inthecaseofsubjects), charterschoolstatus, and
1997Ͳ1998 Ͳ0.300 Ͳ2.721 ** Ͳ0.555 Ͳ1.112
(0.260) (1.064) (0.510) (1.554)
1999 Ͳ0.272 Ͳ2.041 ** Ͳ0.611 Ͳ1.710
(0.353) (0.819) (0.456) (1.221)
2000Ͳ2002 Ͳ0.539 a Ͳ0.462 b Ͳ0.837 * Ͳ0.778 *
(0.333) (0.395) (0.484) (0.462)
2003Ͳ2005 Ͳ0.613 ** Ͳ0.275 Ͳ0.896 * Ͳ0.806 *
(0.301) (0.367) (0.534) (0.466)
2006 Ͳ0.550 * Ͳ0.362 Ͳ1.041 * Ͳ1.172 **
(0.309) (0.368) (0.560) (0.547)
1997Ͳ1998 Ͳ0.356 *** Ͳ1.646 *** Ͳ1.107 *** Ͳ3.122 ***
(0.112) (0.442) (0.167) (0.594)
1999 Ͳ0.350 *** Ͳ1.593 *** Ͳ1.023 *** Ͳ3.234 ***
(0.106) (0.395) (0.149) (0.493)
2000Ͳ2002 Ͳ0.326 *** Ͳ0.835 ***a Ͳ0.881 ***a Ͳ1.631 ***a
(0.086) (0.165) (0.123) (0.231)
2003Ͳ2005 Ͳ0.326 *** Ͳ0.873 *** Ͳ0.896 *** Ͳ1.412 ***
(0.090) (0.172) (0.125) (0.247)
2006 Ͳ0.341 *** Ͳ0.827 *** Ͳ0.969 *** Ͳ1.226 ***
(0.104) (0.157) (0.142) (0.269)
*p <.10;**p<.05;***p <.01
a. Effectissignificantlydifferentfromeffectinpriortimeperiod, p <.05
b. Effectissignificantlydifferentfromeffectinpriortimeperiod, p <.10
c. 2006Effectissignificantlydifferentfrom2000Ͳ2002effect, p <.05
d. 2006Effectissignificantlydifferentfrom2000Ͳ2002effect, p <.10
Appendix A • Effects of Upper-Middle-Class Presence, Student Poverty Presence, and Racial Composition Modeled
Separately (continued)
NOTE: Standarderrorsarepresentedinparentheses.ProportionupperͲmiddleͲclass, proportionimpoverished
students, andracial composition(proportionblackandproportionHispanic) areenteredinseparatemodels.
Proportionimpoverishedstudentsandracial compositionvariablesarelaggedbyoneyearforsubjects;for
enrollmentsthesemeasuresarecontemporaneous.All models control forcity/suburb/rural location, log
enrollment(inthecaseof enrollments), laggedlogenrollment(inthecaseofsubjects), charterschoolstatus, and

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Whichever your reason is, it is valid! You can get professional academic help from our service at affordable rates. We have a team of professional academic writers who can handle all your assignments.

Why Choose Our Academic Writing Service?

  • Plagiarism free papers
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  • Any deadline
  • Skilled, Experienced Native English Writers
  • Subject-relevant academic writer
  • Adherence to paper instructions
  • Ability to tackle bulk assignments
  • Reasonable prices
  • 24/7 Customer Support
  • Get superb grades consistently

Online Academic Help With Different Subjects


Students barely have time to read. We got you! Have your literature essay or book review written without having the hassle of reading the book. You can get your literature paper custom-written for you by our literature specialists.


Do you struggle with finance? No need to torture yourself if finance is not your cup of tea. You can order your finance paper from our academic writing service and get 100% original work from competent finance experts.

Computer science

Computer science is a tough subject. Fortunately, our computer science experts are up to the match. No need to stress and have sleepless nights. Our academic writers will tackle all your computer science assignments and deliver them on time. Let us handle all your python, java, ruby, JavaScript, php , C+ assignments!


While psychology may be an interesting subject, you may lack sufficient time to handle your assignments. Don’t despair; by using our academic writing service, you can be assured of perfect grades. Moreover, your grades will be consistent.


Engineering is quite a demanding subject. Students face a lot of pressure and barely have enough time to do what they love to do. Our academic writing service got you covered! Our engineering specialists follow the paper instructions and ensure timely delivery of the paper.


In the nursing course, you may have difficulties with literature reviews, annotated bibliographies, critical essays, and other assignments. Our nursing assignment writers will offer you professional nursing paper help at low prices.


Truth be told, sociology papers can be quite exhausting. Our academic writing service relieves you of fatigue, pressure, and stress. You can relax and have peace of mind as our academic writers handle your sociology assignment.


We take pride in having some of the best business writers in the industry. Our business writers have a lot of experience in the field. They are reliable, and you can be assured of a high-grade paper. They are able to handle business papers of any subject, length, deadline, and difficulty!


We boast of having some of the most experienced statistics experts in the industry. Our statistics experts have diverse skills, expertise, and knowledge to handle any kind of assignment. They have access to all kinds of software to get your assignment done.


Writing a law essay may prove to be an insurmountable obstacle, especially when you need to know the peculiarities of the legislative framework. Take advantage of our top-notch law specialists and get superb grades and 100% satisfaction.

What discipline/subjects do you deal in?

We have highlighted some of the most popular subjects we handle above. Those are just a tip of the iceberg. We deal in all academic disciplines since our writers are as diverse. They have been drawn from across all disciplines, and orders are assigned to those writers believed to be the best in the field. In a nutshell, there is no task we cannot handle; all you need to do is place your order with us. As long as your instructions are clear, just trust we shall deliver irrespective of the discipline.

Are your writers competent enough to handle my paper?

Our essay writers are graduates with bachelor's, masters, Ph.D., and doctorate degrees in various subjects. The minimum requirement to be an essay writer with our essay writing service is to have a college degree. All our academic writers have a minimum of two years of academic writing. We have a stringent recruitment process to ensure that we get only the most competent essay writers in the industry. We also ensure that the writers are handsomely compensated for their value. The majority of our writers are native English speakers. As such, the fluency of language and grammar is impeccable.

What if I don’t like the paper?

There is a very low likelihood that you won’t like the paper.

Reasons being:

  • When assigning your order, we match the paper’s discipline with the writer’s field/specialization. Since all our writers are graduates, we match the paper’s subject with the field the writer studied. For instance, if it’s a nursing paper, only a nursing graduate and writer will handle it. Furthermore, all our writers have academic writing experience and top-notch research skills.
  • We have a quality assurance that reviews the paper before it gets to you. As such, we ensure that you get a paper that meets the required standard and will most definitely make the grade.

In the event that you don’t like your paper:

  • The writer will revise the paper up to your pleasing. You have unlimited revisions. You simply need to highlight what specifically you don’t like about the paper, and the writer will make the amendments. The paper will be revised until you are satisfied. Revisions are free of charge
  • We will have a different writer write the paper from scratch.
  • Last resort, if the above does not work, we will refund your money.

Will the professor find out I didn’t write the paper myself?

Not at all. All papers are written from scratch. There is no way your tutor or instructor will realize that you did not write the paper yourself. In fact, we recommend using our assignment help services for consistent results.

What if the paper is plagiarized?

We check all papers for plagiarism before we submit them. We use powerful plagiarism checking software such as SafeAssign, LopesWrite, and Turnitin. We also upload the plagiarism report so that you can review it. We understand that plagiarism is academic suicide. We would not take the risk of submitting plagiarized work and jeopardize your academic journey. Furthermore, we do not sell or use prewritten papers, and each paper is written from scratch.

When will I get my paper?

You determine when you get the paper by setting the deadline when placing the order. All papers are delivered within the deadline. We are well aware that we operate in a time-sensitive industry. As such, we have laid out strategies to ensure that the client receives the paper on time and they never miss the deadline. We understand that papers that are submitted late have some points deducted. We do not want you to miss any points due to late submission. We work on beating deadlines by huge margins in order to ensure that you have ample time to review the paper before you submit it.

Will anyone find out that I used your services?

We have a privacy and confidentiality policy that guides our work. We NEVER share any customer information with third parties. Noone will ever know that you used our assignment help services. It’s only between you and us. We are bound by our policies to protect the customer’s identity and information. All your information, such as your names, phone number, email, order information, and so on, are protected. We have robust security systems that ensure that your data is protected. Hacking our systems is close to impossible, and it has never happened.

How our Assignment Help Service Works

1. Place an order

You fill all the paper instructions in the order form. Make sure you include all the helpful materials so that our academic writers can deliver the perfect paper. It will also help to eliminate unnecessary revisions.

2. Pay for the order

Proceed to pay for the paper so that it can be assigned to one of our expert academic writers. The paper subject is matched with the writer’s area of specialization.

3. Track the progress

You communicate with the writer and know about the progress of the paper. The client can ask the writer for drafts of the paper. The client can upload extra material and include additional instructions from the lecturer. Receive a paper.

4. Download the paper

The paper is sent to your email and uploaded to your personal account. You also get a plagiarism report attached to your paper.

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550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
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The price is based on these factors:
Academic level
Number of pages
Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

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Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

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Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

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