Abstract The Law School Context Factors That Shape Disparities Within Law School Theoretical Framework Present Study Method Results Discussion Conclusion and Implications Author Note References

Promoting Graduation Outcomes for Racially Minoritized Law School Students: Examining the Role of Finances, Racial Representation, and Prestige

Nicholas A. Bowman*, Nicholas R. Stroup, & Solomon Fenton-Miller

University of Iowa

Abstract

Despite decades of efforts to diversify the legal profession, White lawyers in the U.S. remain substantially overrepresented. As a necessary step for fostering equity in the workplace, law schools must work to reduce or eliminate the current racial disparities in their persistence and graduation rates. Therefore, this study explored the link between various institutional factors and graduation outcomes among students from several racially minoritized identities using school-level data from 2011 to 2019. The results indicate that the ingroup racial representation within the state (in which the law school is primarily housed) was positively related to graduation outcomes among Asian, Black, Latinx, underrepresented racial minority, and all law Students of Color; the percentage of Faculty of Color was also significantly related to graduation when examining most of these racial identities. Within subgroup analyses among lower- versus higher-ranking law schools, finances (e.g., financial aid provided, total tuition and fees, and estimated cost of living) were more consistently associated with graduation outcomes among Students of Color at law schools outside of the top 100, whereas racial representation (among faculty, other students, and within the state) and rankings were more often related to graduation among Students of Color within the top 100 law schools.

* Contact: nick-bowman@uiowa.edu

© 2022 Bowman, et al. This open access article is distributed under a Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)

Keywords: law school, graduation, race, finances, rankings


Promoting Graduation Outcomes for Racially Minoritized Law School Students: Examining the Role of Finances, Racial Representation, and Prestige

In 1983, the Law School Admissions Council resolved to prioritize the recruitment, enrollment, and retention of law Students of Color as part of a push to select “lawyers for the twenty-first century” (Raushenbush, 1986, p. 2). Not long after, the American Bar Association (ABA) formed its first commission to promote racial and ethnic diversity within the legal profession (ABA, 2021c). Despite these and additional efforts, currently 85% of working lawyers in the U.S. are White non-Hispanic (ABA, 2021a), whereas just 60% of U.S. residents are White non-Hispanic (U.S. Census Bureau, n.d.). Increasing the representation of People of Color in the legal profession will help create a legal workforce that resembles the U.S. residents it serves and simultaneously provide access to some of the highest-paying careers in the nation. Indeed, racial disparities in criminal sentencing tend to be smaller in counties with greater representation of People of Color in the legal profession (King et al., 2010), so bolstering equity may lead to creating a more equitable society despite the presence of long-standing systemic racism. Law schools clearly play a critical role in the process of selecting and training future lawyers in the U.S. However, the enrollment of racially minoritized students has only improved very slowly in recent years: Students of Color comprised 28% of incoming law students in 2011 (ABA, 2013) and 31% in 2019 (ABA, 2020). These figures lag far behind the 47% of undergraduates who hold one or more racially minoritized identities (U.S. Department of Education, 2021).

Improving diversity within the legal field requires understanding—and ultimately facilitating—factors that bolster the success of racially minoritized law students, as law school attrition rates also exhibit substantial racial disparities (Thomas & Cochran, 2018). White students are the least likely to leave law school; Hispanic students have non-transfer attrition rates that are more than 50% higher than White students; and Black, Native Hawaiian, and American Indian students have non-transfer attrition rates that are more than twice as high as that of White students. There is limited research, particularly using a quantitative approach, that explores the factors that lead to law school student success generally and racial disparities specifically.

In this study, we examined the extent to which various law school attributes and contexts predict the graduation outcomes of law Students of Color. We focused largely on financial and demographic characteristics over which law schools have some control, which provides actionable implications for practice and policy. We investigated these dynamics among all accredited U.S. law schools and separately for law schools ranked within and outside of the top 100. Higher- and lower-ranked law schools differ in various ways that may lead to divergent factors shaping graduation, such as students’ undergraduate GPAs and LSAT scores (Brunet Marks & Moss, 2016), the financial support that students need and ultimately receive (Taylor, 2018), and the ways in which rankings inform these schools’ decision making (Espeland & Sauder, 2016).

The Law School Context

The number of entry-level law jobs declined precipitously after the Great Recession, ending a pattern of steady growth that began in the 1970s. Burk (2019) documented how some law job sectors were hit harder than others: Very large firms (500+ employees) now hire a greater proportion of law graduates than in 2008, even as overall job numbers remain below 2008 levels. These same “biglaw” firms generally seek out students attending the higher-rank, higher-prestige, and higher-price schools as new hires (Dinovitzer & Garth, 2020), leading to stratification in the profession. At the same time, law students are burdened by an enormous amount of school debt. Law students are more likely than other graduate students to use loans to pay for school (Pyne & Grodsky, 2020), and law students typically borrow larger amounts than their peers when they receive loans (Belasco et al., 2014; Pyne & Grodsky, 2020). In 2020, the average amount borrowed for students who took out loans was $133,480 for private school graduates and $93,131 for public school graduates (Law School Transparency, 2021b). Black and Latinx law school graduates have higher loan debt on average than White graduates and are more likely to retain or increase that debt load in subsequent years (Hanson, 2021).

Media attention on the worsening legal job market and the high cost of law school (Auter, 2018; Olson, 2015), along with digital transparency initiatives (e.g., AccessLex Institute, lawschooltransparency.com), may have convinced potential law students to pursue other professions. The total number of U.S. law students dramatically decreased in the decade after the 2008 recession, from a high of 147,525 in 2010 to 112,878 in 2019 (Law School Transparency, 2021a). However, the 2021 law school application cycle has seen more than 10,000 more applicants and 100,000 more applications than 2016, leaving law school administrators with many more choices to make in terms of admissions, financial support, and future teaching loads.

These substantial application and enrollment shifts in recent years affect who law schools are able to recruit, admit, and train, which may have notable implications for the pipeline of potential future lawyers. With greater numbers of applicants, higher-ranked law schools have the ability to be more selective in crafting their incoming cohorts of students; these schools could exercise this discretion in ways that either promote or undermine racial representation and equity. Lower-ranked law schools could be more selective in these circumstances, but they may instead (or also) choose to enroll more students overall (Spivey, 2019).

Factors That Shape Disparities Within Law School

Attrition rates for law Students of Color have always been high, especially during the academically and psychologically challenging first year (Clydesdale, 2004; Hamlar, 1983). First-year grades play a large part in determining future academic and professional opportunities, such as joining the law review or landing a good summer job (Feingold & Souza, 2013). The limited spots for these opportunities and the strict grading curves exacerbate an academic environment that is already highly competitive and stressful. This environment appears to cause isolation, lowered self-esteem, and exhaustion, especially for Students of Color (Hess, 2002). In 2016–17, the first-year non-transfer attrition rate of law Students of Color was almost twice as high as for White students (Thomas & Cochran, 2018). Most non-transfer attrition is academic (i.e., dismissal for low grades), but a substantial number of students also voluntarily leave due to other reasons. With scholars aware of these ongoing issues, law schools have been encouraged to tailor academic support programs to address the success of first-year law students from minoritized racial backgrounds (Bodamer, 2020).

Beyond the first year, law school can continue to be a deeply marginalizing experience for Students of Color, thereby potentially influencing the path to graduation. Overall, 31% of law students identify as People of Color (ABA, 2020); racial representation varies greatly between institutions, so many students find themselves even more isolated. In 2017, 18% of the 200 accredited U.S. law schools enrolled half of all Black law students (Taylor, 2019). Only 17% of faculty and administrators at law schools are People of Color (Association of American Law Schools, 2020), and research has suggested that student exposure to same-race instructors may contribute to increased academic performance (e.g., Fairlie et al., 2014). Lancaster and colleagues (2019) also found that taking classes with Faculty of Color helped Black law students feel more comfortable in the classroom, even without any feeling of a special bond or mentorship relationship. Birdsall et al. (2020) specifically studied this effect in legal education and found a small but significant same-race grade boost, perhaps due to factors such as students having representative role models and the increased cultural competencies of Faculty of Color.

The history of legal education has been one of racial exclusion and the promotion of White cultural and racial norms (Bhabha, 2014). Black students were denied from enrolling at most law schools before the 1950s, and schools often informally excluded other People of Color (Anderson, 2009). The few People of Color who did pursue law school were not welcome in the profession: The ABA’s policy until 1943 was that “the settled practice of the Association has been to elect only white men as members” (ABA, 2021b). Even by 1970, there were only 3,400 practicing Black lawyers in the U.S., most of whom graduated from historically Black schools, such as Howard University (Littlejohn & Rubinowitz, 1987).

Feingold and Souza (2013) argue that the burden, or “racial tax,” for law Students of Color is often subtle and difficult to recognize. Besides the numerical lack of representation at law schools, Students of Color are adversely affected by these institutions’ White-dominant culture, which includes pedagogical norms, ways of thinking, and standards for evaluation (Crenshaw, 1988). Traditional legal pedagogy, known as the case method, assumes that “law has evolved, and continues to function, through race-neutral legal principles” (Feingold & Souza, 2013, p. 97). Students of Color, who have a lived understanding of the importance of race, must adapt to “objective” legal argumentation. Furthermore, the competitive, pro-business ethos of law school does not match the culture of many Students of Color, who are more likely than White students to want to pursue a career in the public interest (Clydesdale, 2004).

Recent research has shown that issues of race in law school are often absent from classroom discussions (Deo, 2011, 2019), and law Students of Color report facing higher levels of discrimination and marginalization than their White peers (Feingold & Souza, 2013). Students of Color at UCLA were 3 to 8 times more likely than their White classmates to report experiencing an incident of racially hostile behavior from other students, faculty, or staff (Feingold & Souza, 2013), and Students of Color are less likely to believe their law school is very supportive of racial and ethnic diversity (Law School Survey of Student Engagement, 2020). Jones (2021) points out that Black law students face various cultural, psychological, and social hurdles, but little research has untangled the relative impact of these factors.

While there is limited empirical research on promoting law student success, qualitative research on other graduate and professional disciplines offers additional context related to success for students with marginalized racial backgrounds. Burt et al. (2018) followed the graduate school journeys of 21 Black engineering students at one predominantly White institution. These students felt isolated in their program and experienced difficulty joining study groups and interacting with classmates and faculty advisors. Truong and Museus (2012) identified the various types of racialized experiences and coping mechanisms of doctoral Students of Color in a range of academic programs. Students reported various forms of overt and subtle racism, such as low expectations paired with high standards, isolation, devaluing of research on race, and exploitation. These types of experiences may have negative effects on graduate students’ sense of belonging and their persistence in school (Strayhorn, 2012).

Faculty support can make a difference in student persistence and graduation. Decades of research on Faculty of Color beyond the legal education context point to the importance of diversity in the professoriate to promote postsecondary student success, particularly for Students of Color. Based on a systematic review of studies of faculty across disciplines at both the undergraduate and graduate levels, Turner and colleagues (2008) argue that increases in Students and Faculty of Color on campus can support the recruitment and retention of both groups and reduce feelings of isolation in the campus community. Substantial racial disparities between graduate students are also observed in the quality and quantity of mentoring in ways that disadvantage Students of Color, and the recruitment of faculty who share students’ identities can play a role in remedying this problem (see Brunsma et al., 2017).

Theoretical Framework

The racial diversity of law schools has been an issue of national importance for decades, with high-profile cases before the Supreme Court driving ongoing media attention about law schools’ affirmative action policies and the state legislation banning such practices. Central to many of these affirmative action cases has been the concept of critical mass, which was discussed in both Grutter and Gratz cases before the Supreme Court in 2003, as well as in the Fisher cases in 2013 and 2016. What constitutes a critical mass, particularly of students from minoritized racial groups, is itself an ambiguous and debated construct. Instead of seeking to identify a single proportion of students, Garces and Jayakumar (2014) recommended instead to consider particular educational contexts. Their alternative, dynamic diversity, focuses on context-specific considerations about nurturing a positive campus racial climate, addressing historical legacies of racial exclusion, attending to the impediments for productive learning environments, and fostering cross-racial interactions in learning spaces. These considerations exist atop omnipresent issues of numerical or proportional racial representation among students and faculty.

This study draws from existing literature on racial representation and student success, acknowledging factors that extend beyond notions of attaining critical mass. We use the Multicontextual Model for Diverse Learning Environments (MMDLE; Hurtado et al., 2012) to consider how overlapping contexts within the learning environment interact to promote or hinder degree attainment. Of particular relevance for this study are the model’s three institutional dimensions: compositional, historical, and organizational. The compositional dimension deals directly with the notion of critical mass in terms of numerical or proportional representation, but it cannot be considered a direct proxy for campus climate for diversity. Instead, the compositional dimension must be acknowledged as an element of the environment that influences student satisfaction, prompts perceptions of equity around campus for all people enmeshed in the organizational environment, and can signal the success of initiatives that promote equity. In the law school context, the compositional dimension is reflected in not only the ongoing enrollment, retention, and graduation of students from racially minoritized backgrounds, but also the representation of law school faculty and campus administrators from racially minoritized backgrounds.

The historical dimension of the MMDLE pertains to how legacies of racial exclusion influence students’ experiences (Hurtado et al., 2012). Students, faculty, and administrators within the legal education environment continue to navigate the remnants of a system that included segregated Jim Crow law schools (Longa, 2007), racist gatekeeping practices (Taylor, 2019), and disregard for the unique needs of Students of Color (Robbins, 2020). These histories influence the present law school climate and the broader learning environment, which then affect outcomes for Students of Color.

Finally, the organizational dimension of the MMDLE comprises processes that normalize ongoing inequity, which often manifest in hiring decisions, budget allocations, and day-to-day organizational practices (Hurtado et al., 2012). Law schools operate in an isomorphic organizational field that is highly stratified by rank, where there is significant competition that leads to inequitable distribution of resources within and across schools (Espeland & Sauder, 2016). Analyses of law student success must not overlook the role of finances in this organizational frame, especially as the weight of similar research at the undergraduate level indicates that grants and scholarships promote student retention, persistence, and graduation (Nguyen et al., 2019), and the role of finances tends to be larger for Students of Color (Goldrick-Rab et al., 2009; Mayhew et al., 2016). Ongoing inequitable funding practices can lead to divergent educational outcomes across race, social class, and other student characteristics.

Considering these organizational constructs in tandem with the historical and compositional features is critical for understanding student success in the multidimensional environments of law schools. For example, law school faculty hiring is a thread that cuts across the compositional, historical, and organizational dimensions of the MMDLE. While the data regarding racial representation of a law school’s faculty may appear simply compositional, the longstanding underrepresentation of law school Faculty of Color and the administrative decisions that lead to this long-standing underrepresentation touch upon both the historical and organizational dimensions. As such, the MMDLE provides a lens for understanding the role of faculty representation that considers dynamic diversity (Garces & Jayakumar, 2014) in the faculty-student relationship. In this regard, law students interact with multiple meanings pertaining to faculty racial representation as they navigate the legal education environment; this multimodal understanding informs the design of our analysis.

Present Study

The present study explored the extent to which financial, demographic, and prestige attributes of U.S. law schools predict the number and percentage of law school graduates who hold several racially minoritized identities. This paper expands and improves upon previous research in several ways. First, it directly examined dynamics that may shape law school student success, which have received limited attention in prior work. Second, it included various predictors that are attributes of law schools themselves (rather than pre-enrollment student attributes), thereby leading to concrete implications for improving policy and practice. Third, the analyses were conducted separately for students who hold different racially minoritized identities, which sheds light into the generality of relevant dynamics across several groups that are often lumped together. Finally, some analyses also predicted outcomes for the number of White graduates, which allowed us to discern whether the potential role of certain factors may diverge between students who hold privileged versus minoritized racial identities.

Method

Data Sources and Sample

The sample was comprised of the 189 ABA-accredited U.S. law schools that did not open, close, or merge with another law school during the time period of the study. The analyses examined data released from 2011 to 2019, since ABA-required disclosures were made publicly available during this time. Data were obtained from three different sources. First, ABA Standard 509 Information Reports provided school-level information about graduation, enrollment, financial aid, tuition and fees, estimated living expenses, and student and faculty demographics. Second, law school rankings were obtained from U.S. News & World Report (USNWR). Third, the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates provided demographics for the state in which each law school primarily operates. Given the lag between the predictors and outcome variables, six years of data were available in the analyses, which yielded a final sample of 1,134 school x year observations.

Measures

Two types of dependent variables were used: the number of racially minoritized J.D. graduates and the percentage of graduates who hold racially minoritized identities. Each of these constructs was operationalized in several ways: all Students of Color (SOC; i.e., any student who was not White/Caucasian), underrepresented racial minority students (URM; i.e., American Indian/Alaska Native, Black/African American, Hispanic/Latinx, Native Hawaiian or other Pacific Islander, multiracial), and individual racial groups that had sufficient representation within U.S. law schools (Asian, Black, Latinx). The number of White graduates was also used as an outcome variable, which allowed us to compare results across analyses and distinguish between predictors that were associated with graduates from all racial identities versus only for racially minoritized students.

The choice of independent variables was based on theory and prior research. Given the importance of finances for students in law school and beyond (e.g., Nguyen et al., 2019; Pyne & Grodsky, 2020), several financial indicators were used: the percentage of students receiving grants or scholarships for less than half of tuition, percentage of students receiving grants/scholarships for at least half of tuition, combined total of full-time tuition and fees (using in-state tuition at public schools), average cost of off-campus living expenses (as reported by the law school), and whether some scholarships in the law school were conditional in nature (i.e., contingent on students’ academic performance; 0 = no, 1 = yes). Additional ABA variables indicated the average size of a first-year course; the total number of students enrolled at the law school; the percentage of law school instructors who were racially minoritized; and the percentages of first-year law school students who were Asian, Black, Latinx, or identified with another racially minoritized identity. Total student enrollment and student racial representation were important for the analyses, since these lagged variables reflected the entering students at each school who constituted a pool of potential graduates. Moreover, some research on undergraduates suggests that smaller class sizes lead to greater student success and equity in success outcomes (e.g., Bettinger & Long, 2018; Diette & Raghav, 2015).

USNWR law school rankings were also included as a predictor; these were reverse-coded so that higher values represent better rankings. One-year ACS data indicated the percentage of Asian, Black, Latinx, URM, People of Color, and White residents within the state in which the law school was primarily housed. The percentages of Faculty of Color and in-state residents were included, since these forms of representation may shape success outcomes for Students of Color (e.g., Bowman & Denson, 2022; Llamas et al., 2021). Some continuous variables were natural log transformed to reduce skew: percentages of racially minoritized graduates (all groups), percentages of racially minoritized students (all groups), percentages of racially minoritized residents within the state (all groups), percentage of Faculty of Color, and total law school enrollment. Because some law schools had 0% representation of some racial identities and the natural log of zero is undefined, 1.0 was added to each percentage of law school graduates, students, and Faculty of Color before computing the natural log.

Analyses

Random effects analyses were conducted to account for the multilevel structure of the data. These models simultaneously examine between- and within-group variance; this approach is very similar to hierarchical linear modeling with grand-mean centered predictors (see Cheslock & Rios-Aguilar, 2011). Subgroup analyses were conducted to explore potential differences in these relationships as a function of schools’ U.S. News ranking. Many lower-status law schools seek to increase the size of their incoming cohorts of students, whereas higher-status schools generally seek to enroll a fixed number of students (Spivey, 2019), which may be especially relevant to analyses that predict the number of graduates (rather than the percentage). Therefore, separate analyses were conducted for the entire sample, for law schools ranked in the top 100 (within that particular year), and for law schools ranked outside of the top 100. This cutoff at the top 100 created two subsamples that were roughly equivalent in size, so that any differences in results across these groups would not be driven by disparities in statistical power for detecting significant relationships. Preliminary analyses showed that the same general pattern of results was observed when conducting subgroup analyses comparing the top 50 law schools with those outside of the top 50. Additional preliminary analyses showed that the pattern of findings did not differ systematically when conducting subgroup analyses by public versus private institutional control.

The count outcomes for the number of graduates who hold a particular racial identity were modeled using negative binomial regression. This analytic approach accounts for the fact that these count outcome variables were over-dispersed, such that the variance was greater than the mean (see Hilbe, 2011). Likelihood ratio tests showed that negative binomial regression analyses consistently provided a better fit than did Poisson regression analyses (which instead assume that the mean and variance of the outcome variable are identical).

The predictors were lagged so that the law school characteristics and state-level demographics were generally observed during students’ first year of law school. Supplemental analyses of ABA data showed that more than three-quarters of attrition from law schools occurred between fall of the first year and fall of the second year, which highlights the critical importance of first-year experiences for shaping graduation outcomes. This lagging process was complicated by the lack of student-level data, since the ABA graduation statistics include students who were enrolled full-time in law school (who are expected to graduate within three years) and those who were enrolled part-time (who are generally expected to graduate in four years). According to 2020 ABA data, the overwhelming majority of law school students enroll full-time (91.6%), so this issue only introduces a modest amount of error into the analyses. Virtually all predictors discussed above were included in all models; the lone exception was that the only census variable in each model indicated the racial ingroup representation within the state in which the law school was primary housed. Dummy variables for year were also entered.

We considered conducting analyses that employed school-level fixed effects, but the within-school share of the total variance was quite small for outcomes indicating the number of racially minoritized graduates (~5–10%), so fixed effects analyses would have very little variance to explain. Moreover, several independent variables had even lower percentages of within-school variation, including U.S. News rankings (4%), combined tuition/fees (3%), and ingroup racial representation within the state (< 1%). Moreover, the use of a nonlinear transformation for the outcome variable with a small number of observations per group can lead to substantially biased estimates (Austin, 2010; Moineddin et al., 2007), and the presence of only six observations per law school may not be sufficient for conducting fixed effects analyses even for normally distributed continuous outcomes (Kreft, 1996).

Limitations

Some limitations should be noted. First, the ABA does not provide graduation rates for each law school by race. The present analyses accounted for the number and representation of incoming students through several predictors (including lagged variables that sought to account for the number of incoming students for each racial group), but we avoid using the language of “graduation rates” to describe our results for this reason. Second, similar to the Integrated Postsecondary Education Data System (IPEDS), the ABA 509 Disclosures provided codes for nonresident alien and multiracial students as two mutually exclusive options within their “racial” categories, so we were not able to determine the actual racial group(s) with which these students identify. In an attempt to classify students as accurately as possible, we chose to code nonresident alien students as Students of Color but not URM, because approximately 75% of graduate international students in the U.S. are from Asia (Institute of International Education, 2020); we also chose to classify multiracial students as both SOC and URM, as the large majority of multiracial students will hold at least one URM identity. This approach certainly misclassified some students within each of these groups (e.g., White and Asian biracial students), but it seemed superior to other alternative approaches (e.g., ignoring these two groups of students entirely in the calculations). The low prevalence of multiracial and international students (less than 3% each of all graduates in the sample) and the direct examination of Asian, Black, and Latinx students means that these decisions likely had little or no impact on the substantive findings.

Third, although we were able to conduct meaningful analyses separately for Asian, Black, and Latinx students, the modest representation of American Indian/Alaska Native students and Native Hawaiian or other Pacific Islander students in U.S. law schools prevented us from doing so for these groups. Finally, as with all studies that employ secondary data, the analyses were limited to the information that we were able to obtain from relevant sources. These constraints led us, for example, to create a variable for the percentage of all Faculty of Color, since the ABA data in most years only reported the number of faculty who were racially minoritized (rather than the specific racial identities of those faculty).

Results

Full Sample Analyses

Table 1 contains the results of analyses predicting the number of law school graduates by racial identity. As expected, the lagged percentage of first-year students from a particular racial group (i.e., Asian, Black, and Latinx) was very strongly associated with a greater number of graduates from that same group. This pattern also applies to the aggregated racial categories: The presence of first-year students from all three URM identities strongly predicted a higher percentage of URM graduates, and the presence of students from all four racially minoritized identities predicted more Graduates of Color. In addition, the percentage of first-year Black students was positively related to the number of Asian graduates, the percentage of first-year Asian students predicted a greater number of Black graduates but fewer Latinx graduates, the percentage of first-year students from other races was positively related to the number of Latinx and Asian graduates, and the representation of first-year Black and Latinx students was also associated with fewer White graduates. Ingroup racial representation within the state was associated with more graduates for all racial groups, and the percentage of Faculty of Color predicted more Latinx, URM, and Graduates of Color (but fewer White graduates). U.S. News ranking was also associated with greater numbers of graduates for all racial groups. Some scattered significant results were observed for the financial predictors: The presence of conditional scholarships was positively related to the numbers of Black and URM graduates, and the percentage of students who received grants or scholarships for less than half of tuition and for at least half of tuition were both positively related to the number of White graduates. The full cost of tuition and fees was inversely related to the number of URM graduates, and the cost of living was positively associated with the number of Asian graduates. Finally, total student enrollment and the average size of first-year classes were extremely strong, positive predictors of all numerical outcomes, since these essentially served to indicate the lagged number of incoming students who had the potential to graduate.

Table 1. Unstandardized Coefficients for Random Effects Analyses Predicting Student Graduation Counts for All Law Schools

Dependent variable

Independent variable

#

Black

Graduates

#

Latinx

Graduates

#

Asian

Graduates

#

URM

Graduates

#

SOC

Graduates

#

White

Graduates

% students w/ grants < 50% tuition

.000

(.001)

-.001

(.001)

.001

(.001)

-.001

(.001)

.000

(.001)

.001*

(.001)

% students w/ grants ≥ 50% tuition

.000

(.001)

.000

(.001)

.001

(.001)

-.001

(.001)

-.002

(.001)

.003***

(.001)

Offer conditional scholarships

.065**

(.022)

.002

(.019)

-.015

(.028)

.050*

(.025)

.023

(.024)

.023

(.020)

Tuition and fees for full-time students

-.002

(.001)

.000

(.001)

.001

(.001)

-.006**

(.002)

-.003

(.002)

-.003

(.002)

Cost of living

-.005

(.003)

-.001

(.002)

.009**

(.003)

.005

(.003)

.006

(.003)

.001

(.003)

Total student enrollment

.811***

(.026)

.858***

(.024)

.845***

(.034)

.706***

(.045)

.747***

(.045)

.608***

(.048)

Average first-year class size

.004***

(.001)

.004***

(.001)

.005***

(.001)

.005***

(.001)

.005***

(.001)

.005***

(.000)

% of first-year Black students

1.092***

(.021)

.008

(.012)

.042*

(.020)

.271***

(.019)

.204***

(.018)

-.069***

(.014)

% of first-year Latinx students

.022

(.016)

.975***

(.019)

.007

(.020)

.391***

(.020)

.266***

(.018)

-.058***

(.012)

% of first-year Asian students

.042*

(.018)

-.058***

(.015)

.840***

(.027)

.009

(.018)

.141***

(.017)

-.010

(.012)

% of first-year SOC from other races

.036

(.021)

.052**

(.016)

.066**

(.023)

.111***

(.019)

.142***

(.019)

-.006

(.016)

% of Faculty of Color

.011

(.022)

.052**

(.016)

.007

(.028)

.047*

(.023)

.061*

(.024)

-.041*

(.018)

Ingroup state racial representation

.053**

(.018)

.136***

(.017)

.194***

(.026)

.216***

(.050)

.215***

(.054)

.200*

(.077)

U.S. News ranking

.002***

(.000)

.002***

(.000)

.003***

(.000)

.001*

(.000)

.002***

(.000)

.002***

(.000)

Note. Standard errors are in parentheses. URM = underrepresented racial minority. SOC = Students of Color. Negative binomial regression analyses were used to model the count outcomes. Year fixed effects were entered in all models.

*p < .05 **p < .01 ***p < .001

The results of analyses predicting the percentage of graduates who hold racially minoritized identities (among all graduates) are presented in Table 2. The same consistently positive and significant findings for first-year ingroup representation were also observed for the percentage of graduates. In addition, the percentage of first-year Students of Color from other races was positively related to the percentage of Asian graduates, whereas the percentage of first-year Asian students was inversely related to the percentage of Latinx graduates. Also consistent with the findings for the number of graduates, ingroup racial representation within the state was positively related to all outcomes, and the percentage of Faculty of Color predicted higher percentages of Latinx graduates, URM graduates, and Graduates of Color. U.S. News rankings were positively related to the percentage of Asian graduates, but they were negatively associated with the percentage of URM graduates. A handful of additional scattered significant results were also observed, including the same results as the count outcomes for cost of living and for tuition and fees. Moreover, the percentage of students receiving grants and scholarships for at least half of tuition was negatively related to the percentages of URM graduates and Graduates of Color, while total student enrollment was positively related to the percentages of Latinx and Asian graduates.

Subgroup Analyses by Law School Ranking

The results of subgroup analyses predicting the number of graduates appear in Table 3 (for schools ranked in the top 100) and Table 4 (for schools ranked outside the top 100). Although the subsample analyses are separate, we present results for the number of graduates together in order to uplift findings about independent variables of interest and to avoid placing greater emphasis on the stratified ranking system. We then repeat this presentation for the rank group subsamples examining the percentage of graduating students (Tables 5 and 6). While characteristics of institutions at different ranks may vary (such as overall graduation rate or incoming/outgoing transfers), our time-lagged analytical strategy that focuses on disaggregating by racial group accounts for these characteristics and focuses instead on attributes that predict differences within each group of law schools.

Table 2. Unstandardized Coefficients for Random Effects Analyses Predicting Student Graduation Percentages for All Law Schools

Dependent variable

Independent variable

%

Black

Graduates

%

Latinx

Graduates

%

Asian

Graduates

%

URM

Graduates

%

SOC

Graduates

% students w/ grants < 50% tuition

.000

(.001)

.000

(.001)

.001

(.001)

-.001

(.001)

-.001

(.001)

% students w/ grants ≥ 50% tuition

.000

(.001)

.000

(.001)

-.001

(.001)

-.002*

(.001)

-.002**

(.001)

Offer conditional scholarships

.027

(.020)

.003

(.022)

-.010

(.023)

.005

(.022)

-.013

(.021)

Tuition and fees for full-time students

-.002

(.001)

.001

(.001)

.000

(.001)

-.004**

(.001)

-.001

(.001)

Cost of living

.003

(.003)

.002

(.003)

.010**

(.003)

.002

(.003)

.004

(.003)

Total student enrollment

.027

(.028)

.063*

(.030)

.069*

(.032)

.016

(.034)

.054

(.034)

Average first-year class size

.000

(.001)

.001

(.001)

.001*

(.001)

-.001

(.001)

-.001

(.001)

% of first-year Black students

.894***

(.015)

-.016

(.015)

-.012

(.015)

.264***

(.015)

.204***

(.014)

% of first-year Latinx students

-.009

(.014)

.785***

(.018)

.012

(.016)

.361***

(.014)

.268***

(.013)

% of first-year Asian students

.015

(.015)

-.047**

(.017)

.726***

(.021)

-.011

(.015)

.116***

(.014)

% of first-year SOC from other races

.009

(.017)

.015

(.018)

.039*

(.020)

.100***

(.018)

.147***

(.017)

% of Faculty of Color

-.006

(.017)

.053**

(.020)

.016

(.020)

.107***

(.018)

.085***

(.017)

Ingroup state racial representation

.057***

(.015)

.145***

(.018)

.153***

(.019)

.183***

(.033)

.205***

(.036)

U.S. News ranking

-.000

(.000)

-.000

(.000)

.001***

(.000)

-.001**

(.000)

-.000

(.000)

Note. Standard errors are in parentheses. URM = underrepresented racial minority. SOC = Students of Color. Year fixed effects were entered in all models.

*p < .05 **p < .01 ***p < .001

Table 3. Unstandardized Coefficients for Random Effects Analyses Predicting Student Graduation Counts for Law Schools Ranked 1–100

Dependent variable

Independent variable

#

Black

Graduates

#

Latinx

Graduates

#

Asian

Graduates

#

URM

Graduates

#

SOC

Graduates

#

White

Graduates

% students w/ grants < 50% tuition

.000

(.001)

-.001

(.001)

.001

(.001)

-.001

(.001)

-.001

(.001)

.001

(.001)

% students w/ grants ≥ 50% tuition

.001

(.001)

.000

(.001)

.001

(.001)

.000

(.001)

.000

(.001)

.002

(.001)

Offer conditional scholarships

.020

(.031)

.021

(.031)

.004

(.031)

.044

(.029)

.023

(.026)

.014

(.020)

Tuition and fees for full-time students

-.003

(.001)

.001

(.002)

.001

(.001)

-.003*

(.002)

.001

(.001)

-.001

(.001)

Cost of living

-.007

(.004)

.000

(.004)

.005

(.004)

.000

(.004)

.000

(.004)

-.001

(.003)

Total student enrollment

.823***

(.048)

.810***

(.049)

.944***

(.044)

.677***

(.053)

.795***

(.047)

.852***

(.038)

Average first-year class size

.003***

(.001)

.004***

(.001)

.004***

(.001)

.005***

(.001)

.004***

(.001)

.003***

(.001)

% of first-year Black students

1.023***

(.035)

.048

(.027)

.042

(.027)

.246***

(.024)

.179***

(.021)

-.055**

(.016)

% of first-year Latinx students

.022

(.025)

.930***

(.031)

-.027

(.025)

.403***

(.023)

.243***

(.020)

-.062***

(.015)

% of first-year Asian students

.076**

(.025)

-.057*

(.023)

.772***

(.033)

.036

(.020)

.186***

(.018)

-.059***

(.015)

% of first-year SOC from other races

.025

(.030)

.043

(.028)

.058*

(.027)

.162***

(.026)

.199***

(.024)

-.081***

(.018)

% of Faculty of Color

-.049

(.043)

.032

(.040)

.055

(.040)

.078*

(.038)

.117***

(.033)

-.110***

(.026)

Ingroup state racial representation

.050*

(.024)

.158***

(.026)

.185***

(.028)

.116*

(.045)

.103*

(.042)

.083**

(.030)

U.S. News ranking

.002**

(.001)

.002**

(.001)

.004***

(.001)

.001*

(.001)

.003***

(.001)

.002***

(.000)

Note. Standard errors are in parentheses. URM = underrepresented racial minority. SOC = Students of Color. Negative binomial regression analyses were used to model the count outcomes. Year fixed effects were entered in all models.

*p < .05 **p < .01 ***p < .001

Table 4. Unstandardized Coefficients for Random Effects Analyses Predicting Student Graduation Counts for Law Schools Ranked 101–200

Dependent variable

Independent variable

#

Black

Graduates

#

Latinx

Graduates

#

Asian

Graduates

#

URM

Graduates

#

SOC

Graduates

#

White

Graduates

% students w/ grants < 50% tuition

.001

(.001)

.000

(.001)

.001

(.002)

-.001

(.001)

-.001

(.001)

.001

(.001)

% students w/ grants ≥ 50% tuition

-.001

(.002)

.000

(.002)

.002

(.002)

-.001

(.002)

-.001

(.002)

.004**

(.001)

Offer conditional scholarships

.134***

(.037)

.006

(.037)

-.010

(.053)

.094*

(.038)

.090*

(.037)

.019

(.030)

Tuition and fees for full-time students

-.003

(.002)

-.003

(.002)

.003

(.003)

-.012***

(.003)

-.012***

(.003)

-.019***

(.004)

Cost of living

-.001

(.006)

.002

(.004)

.007

(.006)

.009

(.005)

.012*

(.004)

-.002

(.004)

Total student enrollment

.810***

(.046)

.834***

(.049)

.765***

(.057)

.733***

(.064)

.743***

(.064)

.470***

(.066)

Average first-year class size

.005***

(.001)

.005***

(.001)

.006***

(.001)

.005***

(.001)

.005***

(.001)

.007***

(.001)

% of first-year Black students

1.116***

(.033)

.017

(.023)

.063

(.033)

.271***

(.030)

.202***

(.028)

-.019

(.021)

% of first-year Latinx students

.018

(.025)

.918***

(.042)

.040

(.035)

.383***

(.032)

.314***

(.030)

-.038*

(.016)

% of first-year Asian students

.047

(.030)

-.055*

(.028)

.965***

(.050)

-.020

(.029)

.090**

(.028)

-.014

(.019)

% of first-year SOC from other races

.050

(.031)

.091***

(.021)

.072

(.040)

.089**

(.026)

.123***

(.025)

.017

(.022)

% of Faculty of Color

-.024

(.035)

.006

(.018)

-.005

(.044)

.034

(.029)

.032

(.028)

-.010

(.023)

Ingroup state racial representation

.059

(.036)

.199***

(.042)

.171**

(.050)

.250**

(.074)

.267**

(.077)

-.021

(.141)

U.S. News ranking

.003**

(.001)

.001

(.001)

.002

(.001)

-.001

(.001)

-.000

(.001)

.001

(.001)

Note. Standard errors are in parentheses. URM = underrepresented racial minority. SOC = Students of Color. Negative binomial regression analyses were used to model the count outcomes. Year fixed effects were entered in all models.

*p < .05 **p < .01 ***p < .001

Some key findings were consistent across both subsamples, including the total student enrollment and average first-year class size being positively associated with all outcomes as well as ingroup law school representation predicting greater numbers of graduates for all groups of racially minoritized students. However, other significant findings for race-related and rankings predictors were much more frequently observed among higher-ranked law schools. Specifically, the percentages of all groups of racially minoritized students were associated with fewer White graduates among top-100 law schools, whereas this inverse relationship was only significant for the percentage of Latinx students among lower-ranked law schools. The percentage of Faculty of Color predicted a larger number of URM graduates and Graduates of Color, along with fewer White graduates, at higher-ranked law schools; in contrast, these results were not significant at lower-ranked law schools. Ingroup racial representation within the state was significantly and positively related to all outcomes among the top 100, whereas it was nonsignificant for the number of Black and White graduates among law schools ranked #101–200. U.S. News ranking was also positively associated with all outcomes at top-100 institutions, whereas it only predicted more Black graduates in the lower-ranked subsample.

Conversely, finances were far more frequently related to the number of graduates among schools outside of the top 100. The only significant result for the financial variables among top-100 schools was that the total cost of tuition and fees was inversely related to the number of URM graduates. At schools ranked #101–200, tuition and fees predicted smaller numbers of URM, SOC, and White graduates, and the presence of conditional scholarships was positively associated with the number of Black graduates, URM graduates, and Graduates of Color. The percentage of grants/scholarships that provided at least half of tuition predicted a larger number of White graduates, and cost of living predicted more Graduates of Color.

Some scattered findings for racial enrollment predictors also differed across these analyses. In analyses of the number of Latinx graduates at lower-ranked schools, the percentage of first-year Students of Color from other races was positively related, whereas the percentage of first-year Asian students was negatively related. At schools ranked within the top 100, the percentage of first-year Asian students predicted more Black graduates but fewer Latinx graduates, and the percentage of enrolled Students of Color from other races predicted more Asian graduates.

The corresponding subgroup analyses predicting the percentage of law school graduates by race appear in Table 5 (for schools in the top 100) and Table 6 (for schools ranked #101–200). Consistent with the patterns for the number of graduates, the percentage of enrolled ingroup students was consistently and positively related to every percentage graduation outcome, since these lagged predictors essentially served as an indicator of the potential racial representation of future graduates. Other indicators of racial representation were more likely to be significant among law schools ranked in the top 100, but these results were not always in the expected direction. Ingroup racial representation within the state was positively related to nearly all outcomes in both subgroups, except that this relationship was nonsignificant for the percentage of Black graduates among schools outside of the top 100. Within the top 100, the percentage of enrolled Students of Color from other races was positively related to the percentage of Latinx and Asian graduates, whereas the percentage of Latinx students was inversely related to the percentage of Asian graduates, and the percentage of Asian students was also negatively associated with the percentage of Latinx graduates. The percentage of Faculty of Color predicted a higher percentage of Latinx graduates among schools ranked #101–200, whereas it was inversely related to the percentage of Black graduates at top-100 law schools.

Table 5. Unstandardized Coefficients for Random Effects Analyses Predicting Student Graduation Percentages for Law Schools Ranked 1–100

Dependent variable

Independent variable

%

Black

Graduates

%

Latinx

Graduates

%

Asian

Graduates

%

URM

Graduates

%

SOC

Graduates

% students w/ grants < 50% tuition

.000

(.001)

-.001

(.001)

.002*

(.001)

-.001

(.001)

-.001

(.001)

% students w/ grants ≥ 50% tuition

.000

(.001)

.000

(.001)

-.001

(.001)

-.002

(.001)

-.001

(.001)

Offer conditional scholarships

-.014

(.027)

.052*

(.022)

.026

(.027)

.019

(.023)

.003

(.021)

Tuition and fees for full-time students

-.003*

(.001)

.000

(.001)

-.001

(.001)

-.003**

(.001)

.001

(.001)

Cost of living

.000

(.004)

.000

(.003)

.010*

(.004)

.000

(.004)

.001

(.003)

Total student enrollment

.066

(.046)

.020

(.037)

.107*

(.045)

-.100*

(.040)

-.013

(.037)

Average first-year class size

.000

(.001)

.001

(.001)

.002**

(.001)

.001

(.001)

.001

(.001)

% of first-year Black students

.788***

(.026)

.027

(.020)

.021

(.024)

.233***

(.020)

.175***

(.017)

% of first-year Latinx students

.017

(.022)

.823***

(.022)

-.055*

(.023)

.371***

(.018)

.230***

(.016)

% of first-year Asian students

.011

(.021)

-.039*

(.018)

.718***

(.025)

.012

(.018)

.182***

(.016)

% of first-year SOC from other races

-.010

(.024)

.048*

(.020)

.066**

(.025)

.197***

(.021)

.232***

(.019)

% of Faculty of Color

-.079*

(.035)

.029

(.030)

.015

(.037)

.122***

(.030)

.120***

(.027)

Ingroup state racial representation

.089***

(.021)

.115***

(.018)

.156***

(.024)

.132***

(.030)

.113***

(.029)

U.S. News ranking

-.000

(.000)

-.000

(.000)

.002***

(.000)

-.001

(.000)

.001

(.000)

Note. Standard errors are in parentheses. URM = underrepresented racial minority. SOC = Students of Color. Year fixed effects were entered in all models.

*p < .05 **p < .01 ***p < .001

Other disparate findings across subsamples were identified. Cost of living, total student enrollment, average first-year class size, and U.S. News ranking were all significantly and positively related to the percentage of Asian graduates only among law schools ranked in the top 100. Conversely, several results for the percentage of Graduates of Color were only significant among schools ranked outside of the top 100: Cost of living and total student enrollment were positively related, whereas tuition and fees, average first-year class size, and U.S. News ranking were negatively related. The average first-year class size and U.S. News ranking were also significantly and inversely associated with the percentage of URM graduates only among lower-ranked schools. In scattered findings, offering conditional scholars predicted a higher percentage of Latinx graduates at top-100 schools, whereas the cost of tuition and fees predicted a lower percentage of Black graduates at these institutions. Tuition and fees predicted fewer URM graduates in both subsamples, while U.S. News ranking was associated with a greater percentage of Black graduates at schools ranked #101–200.

Discussion

The present study explored how organizational factors predict law school graduation outcomes among students who hold several racial identities. These dynamics were further investigated through separate analyses of graduation outcomes among higher-ranked and lower-ranked law schools. Given the large number of results across the various predictors, outcomes, and subgroup analyses, the discussion below focuses on four key findings and patterns that were observed consistently across analyses.

First, the representation of Faculty of Color was frequently associated with a greater number and percentage of racially minoritized graduates, whereas this representation was often inversely associated with the number of White graduates, which suggests the potentially important role of Faculty of Color for fostering law school success specifically among racially minoritized students. Faculty of Color may contribute to these graduation outcomes in multiple ways. The presence of Faculty of Color itself could serve as a signal of embracing diversity as a value at that law school. The recruitment of Faculty of Color may run counter to historical exclusionary practices and demonstrate future commitments, which are both emblematic of efforts to advance dynamic diversity rather than simply to meet a numeric or percentage hiring target. Perhaps more importantly, Faculty of Color may engage with students individually or collectively in a manner that facilitates racial equity, whether through the development of formal or informal mentoring relationships, selection of curriculum and course content, use of specific pedagogical practices, creation of an overall positive (or less negative) psychological racial climate, or other mechanisms.

Table 6. Unstandardized Coefficients for Random Effects Analyses Predicting Student Graduation Percentages for Law Schools Ranked 101–200

Dependent variable

Independent variable

%

Black

Graduates

%

Latinx

Graduates

%

Asian

Graduates

%

URM

Graduates

%

SOC

Graduates

% students w/ grants < 50% tuition

-.001

(.001)

.000

(.001)

.000

(.001)

-.001

(.001)

-.001

(.001)

% students w/ grants ≥ 50% tuition

.000

(.001)

-.001

(.002)

.000

(.002)

-.001

(.001)

-.001

(.001)

Offer conditional scholarships

.033

(.029)

-.041

(.040)

-.025

(.039)

.026

(.036)

.030

(.033)

Tuition and fees for full-time students

-.001

(.002)

.002

(.002)

.000

(.002)

-.008**

(.002)

-.007**

(.002)

Cost of living

.006

(.004)

.004

(.005)

.008

(.005)

.006

(.005)

.009*

(.004)

Total student enrollment

.018

(.035)

.073

(.047)

.034

(.046)

.098

(.050)

.109*

(.048)

Average first-year class size

-.001

(.001)

.001

(.001)

.000

(.001)

-.002*

(.001)

-.002**

(.001)

% of first-year Black students

.943***

(.018)

-.035

(.022)

-.025

(.021)

.268***

(.022)

.201***

(.021)

% of first-year Latinx students

-.011

(.018)

.763***

(.028)

.042

(.024)

.347***

(.021)

.294***

(.019)

% of first-year Asian students

.010

(.021)

-.037

(.028)

.750***

(.032)

-.017

(.024)

.080***

(.021)

% of first-year SOC from other races

.016

(.022)

-.004

(.029)

.030

(.029)

.066*

(.026)

.142***

(.024)

% of Faculty of Color

.017

(.021)

.068*

(.029)

.011

(.028)

.089***

(.024)

.065**

(.022)

Ingroup state racial representation

.025

(.020)

.162***

(.032)

.166***

(.031)

.200***

(.052)

.225***

(.052)

U.S. News ranking

.001*

(.001)

-.000

(.001)

.001

(.001)

-.003**

(.001)

-.002**

(.001)

Note. Standard errors are in parentheses. URM = underrepresented racial minority. SOC = Students of Color. Year fixed effects were entered in all models.

*p < .05 **p < .01 ***p < .001

Second, ingroup racial representation within the state was also frequently and positively related to graduation outcomes for all groups of students. This finding is especially impressive given that state-level demographics provide a very rough proxy for the local communities with which students will engage during their time in law school. Of course, this dynamic is outside of the control of law schools, but it provides further evidence of how racial representation—and the climate and culture that is often associated with it—may lead to improved outcomes for students whose identities are often marginalized in their graduate programs and beyond. These findings lend evidence to the broader notion that human geography well outside of the institution affects the academic success of law students. U.S. society is becoming more racially diverse (U.S. Census Bureau, 2021), and this population increase is more rapid than that of the representation of Students of Color enrolled at law schools. Thus, we do not consider the positive significant relationship a success for racial equity in itself, but it may serve as a call to consider how law schools in the U.S. might continue to keep pace with the contemporary demographic landscape of America. Beyond the immediate educational community, many law students have internships or become summer associates in the communities near their law school, thereby providing additional means through which this proximal racial representation may become even more salient and potentially influential.

Third, in the subgroup analyses by law school ranking, financial indicators were much more often related to graduation outcomes at schools outside of the top 100. This greater association at lower-ranked schools may be driven by a combination of compositional student factors and organizational factors. Specifically, students at lower-ranked schools tend to have greater financial need, and these same institutions are also less able to provide the type of financial aid that higher-ranked schools can frequently offer (Taylor, 2018). This combination of factors means that allocating resources toward student financial support may be an especially effective strategy for promoting graduation, whereas charging higher amounts for tuition and fees will be especially likely to hinder graduation. As an additional and perhaps surprising finding, cost of living sometimes had positive associations with graduation outcomes for Students of Color. This cost is partially shaped by whether the school is located within a metropolitan area, which may have a greater representation of People of Color; thus, the positive results may be driven by similar dynamics as those for the association between in-state racial representation and graduation outcomes.

Fourth, the contextual factors of racial representation and law school ranking were more often associated with graduation outcomes at schools ranked within the top 100. Recalling the historical and structural/organizational dimensions of the MMDLE (Hurtado et al., 2012), this finding points to overlapping components of organizational life in an educational environment. The results for U.S. News rankings may be a proxy for the capacity that top-ranked law schools have to mobilize support and resources on behalf of their students, especially since these schools often hold affiliations with the richest, oldest, and/or most heavily supported universities. As the top-ranked law schools are also those that are most rank-aware, they may divert resources away from student support in years following a U.S. News ranking slide, thereby affecting student persistence to graduation. Moreover, the representation of Faculty of Color may be especially important for facilitating the success of Students of Color in higher-ranked law schools, given the weight of historical and ongoing legacies of racial exclusion at these oldest and most prestigious institutions. The presence of Faculty of Color at these law schools demonstrates that students attending the most respected legal institutions can ultimately persist and succeed against the substantial obstacles that they face.

Conclusion and Implications

This study provides important insights into the dynamics that shape law school graduation outcomes among students from various racial identities, which is especially crucial when preparing students for well-paying jobs in an influential profession that is overwhelmingly White (ABA, 2021a). Student success dynamics are understudied in non-STEM graduate and professional school contexts, so these findings highlight various factors related to racial representation, finances, and prestige. Many of the constructs that significantly predicted graduation outcomes are well within the control of law schools, suggesting actionable directions for bolstering the success of racially minoritized students and ultimately of future professionals. Relevant implications include hiring more Faculty of Color, increasing transparency about metrics of student success, and auditing the distribution of financial resources directed to supporting students’ law school attendance and persistence.

The present results indicate that larger tuition grants predicted lower percentages of racially minoritized graduates, while the percentage of Faculty of Color led to both greater numbers and percentages of racially minoritized graduates. The choices around the number and size of tuition grants, or how legal scholars are incented to join a law school faculty, are unquestionably discretionary budget decisions. Aligning with the MMDLE’s perspective on interlocking organizational, historical, and compositional dimensions (Hurtado et al., 2012), it is important for administrators to recognize that the avenue for promoting graduation among law Students of Color should involve understanding their annual budgets as organizational routines that have become historicized and normalized, resulting in graduating classes who are often demographically dissimilar to their geographic communities. In viewing choices around hiring and student support through this lens, and with the data to understand their role in the shaping of law school graduating classes, administrators can adjust their policies and practices to move toward more racially equitable outcomes.

Further research should directly examine the organizational dynamics that lead to racialized experiences and outcomes in legal education. Providing a potential lens for doing so, Ray (2019) describes racialized organizations as “social structures that limit the personal agency and collective efficacy of subordinate racial groups while magnifying the agency of the dominant racial group” (p. 36). Research on other professional education systems has adopted this approach in understanding the role of different racial groups’ agency in reported systemic outcomes. For example, studies of medical education have noted ways that student success metrics and leadership decisions offer evidence for ongoing racialized dynamics within medical education (e.g., Nguemeni Tiako et al., 2021). The extension of these understandings to legal education, bolstered by the quantitative findings of this study about campus organizational features, could aid in shifting the practices of the legal education system toward racial equity.

Moving forward, the legal field would have greater understanding about the mechanisms behind these racialized findings in this study if there were greater transparency around how funding was distributed to Students and Faculty of Color. While the current ABA disclosure requirement mandates that law schools report the size and proportion of scholarships, this study’s unexpected finding about large scholarships leading to a decrease in the number of graduating Students of Color suggests that the mobilization of these scholarships and who receives them may be inequitable. The ABA recently decided that it would require law schools to report financial aid information by students’ racial identity (ABA, 2021d), which will shed light on how law schools are targeting certain students in their recruitment and retention strategies (at least in future years). This change represents a positive step toward transparency so that law schools may be held accountable for their role in perpetuating (or ideally alleviating) racial inequities; additional movement toward disaggregating racial data for students and faculty would provide further insights.

Organizational changes for equity would shift not only the legal education system itself in terms of student success outcomes, but also the legal profession and communities served by newly minted J.D.s. Graduating more People of Color from U.S. law schools would likely contribute to more racial diversity among prosecutors and judges, which Ward and colleagues (2009) found had the potential to advance racial justice in American courtrooms. As law school administrators faced a boom in the number of law school applicants and students in 2021, leaders of educational institutions seeking to advance racial justice must consider orienting their ongoing immediate faculty hiring and student financial aid practices toward achieving long-term aims to graduate more Students of Color.

Author Note

This material is based upon work supported by AccessLex Institute and the Association for Institutional Research.

References

American Bar Association. (2013). ABA approved 1st year JD and minority enrollment: Fall 2013. https://www.americanbar.org/groups/legal_education/resources/statistics/

American Bar Association. (2020). 2020 JD enrollment and ethnicity. [Data set]. http://abarequireddisclosures.org/Disclosure509.aspx

American Bar Association. (2021a). ABA national lawyer population survey: 10-year trend in lawyer demographics. https://www.americanbar.org/content/dam/aba/administrative/market_research/2021-national-lawyer-population-survey.pdf

American Bar Association. (2021b). ABA timeline. https://www.americanbar.org/about_the_aba/timeline/

American Bar Association. (2021c). Commission on racial and ethnic diversity in the profession. https://www.americanbar.org/groups/diversity/DiversityCommission/

American Bar Association. (2021d). Memorandum re: 509 report, auditing, financial data, and agenda for 2021–22. https://qa.americanbar.org/content/dam/aba/administrative/legal_education_and_admissions_to_the_bar/council_reports_and_resolutions/aug21/21-aug-aq-memo-to-council.pdf

Anderson, M. J. (2009). Legal education reform, diversity, and access to justice. Rutgers Law Review, 61(4), 1011–1036.

Association of American Law Schools. (2020, January 25). Legal education at a glance: 2020. https://www.aals.org/wp-content/uploads/2021/01/2020-Legal-Ed-at-a-Glance.pdf

Austin, P. C. (2010). Estimating multilevel logistic regression models when the number of clusters is low: A comparison of different statistical software procedures. The International Journal of Biostatistics, 6(1), Article 16. https://doi.org/10.2202/1557-4679.1195

Auter, Z. (2018, February 16). Few MBA, law grads say their degree prepared them well. Gallup. https://news.gallup.com/poll/227039/few-mba-law-grads-say-degree-prepared.aspx

Belasco, A. S., Trivette, M. J., & Webber, K. L. (2014). Advanced degrees of debt: Analyzing the patterns and determinants of graduate student borrowing. Review of Higher Education, 37(4), 469–497. https://doi.org/10.1353/rhe.2014.0030

Bettinger, E. P., & Long, B. T. (2018). Mass instruction or higher learning? The impact of college class size on student retention and graduation. Education Finance and Policy, 13(1), 97–118. https://doi.org/10.1162/edfp_a_00221

Bhabha, F. (2014). Towards a pedagogy of diversity in legal education. Osgoode Hall Law Journal, 52(1), 59–108.

Birdsall, C., Gershenson, S., & Zuniga, R. (2020). The effects of demographic mismatch in an elite professional school setting. Education Finance and Policy, 15(3), 457–486. https://doi.org/10.1162/edfp_a_00280

Bodamer, J. D. (2020). Do I belong here? Examining perceived experiences of bias, stereotype concerns, and sense of belonging in US law schools. Journal of Legal Education, 69(2), 455–490.

Bowman, N. A., & Denson, N. (2022). Institutional racial representation and equity gaps in college graduation. Journal of Higher Education, 93(3), 399–423. https://doi.org/10.1080/00221546.2021.1971487

Brunet Marks, A., & Moss, S. A. (2016). What predicts law student success? A longitudinal study correlating law student applicant data and law school outcomes. Journal of Empirical Legal Studies, 13(2), 205–265. https://doi.org/10.1111/jels.12114

Brunsma, D. L., Embrick, D. G., & Shin, J. H. (2017). Graduate students of color: Race, racism, and mentoring in the white waters of academia. Sociology of Race and Ethnicity, 3(1), 1–13. https://doi.org/10.1177/2332649216681565

Burk, B. A. (2019). The new normal ten years in: The job market for new lawyers today and what it means for the legal academy tomorrow. FIU Law Review, 13(3), 341–382. https://doi.org/10.25148/lawrev.13.3.5

Burt, B. A., Williams, K. L., & Smith, W. A. (2018). Into the storm: Ecological and sociological impediments to Black males’ persistence in engineering graduate programs. American Educational Research Journal, 55(5), 965–1006. https://doi.org/10.3102/0002831218763587

Cheslock, J. J., & Rios-Aguilar, C. (2011). Multilevel analysis in higher education: A multidisciplinary approach. In J. C. Smart & M. B. Paulsen (Eds.), Higher education: Handbook of theory and research (Vol. 26, pp. 85–123). Springer.

Clydesdale, T. T. (2004). A forked river runs through law school: Toward understanding race, gender, age, and related gaps in law school performance and bar passage. Law & Social Inquiry, 29(4), 711–769. https://doi.org/10.1111/j.1747-4469.2004.tb01075.x

Crenshaw, K. W. (1988). Toward a race-conscious pedagogy in legal education. National Black Law Journal, 11(1), 1–14.

Deo, M. E. (2011). The promise of Grutter: Diverse interactions at the University of Michigan Law School. Michigan Journal of Race & Law, 17(1), 63–118. https://repository.law.umich.edu/mjrl/vol17/iss1/2/

Deo, M. E. (2019). Unequal profession: Race and gender in legal academia. Stanford University Press.

Diette, T. M., & Raghav, M. (2015). Class size matters: Heterogeneous effects of larger classes on college student learning. Eastern Economic Journal, 41(2), 273–283. https://doi.org/10.1057/eej.2014.31

Dinovitzer, R., & Garth, B. (2020). The new place of corporate law firms in the structuring of elite legal careers. Law & Social Inquiry, 45(2), 339–371. https://doi.org/10.1017/lsi.2019.62

Espeland, W. N., & Sauder, M. (2016). Engines of anxiety: Academic rankings, reputation, and accountability. Russell Sage Foundation.

Fairlie, R. W., Hoffmann, F., & Oreopoulos, P. (2014). A community college instructor like me: Race and ethnicity interactions in the classroom. The American Economic Review, 104(8), 2567–2591. https://doi.org/10.1257/aer.104.8.2567

Feingold, J. P., & Souza, D. (2013). Measuring the racial unevenness of law school. Berkeley Journal of African-American Law & Policy, 15(1), 71–116.

Fisher v. University of Texas, 770 U.S. 297 (2013). https://www.oyez.org/cases/2012/11-345

Fisher v. University of Texas, 579 U.S. 365 (2016). https://www.oyez.org/cases/2015/14-981

Garces, L. M., & Jayakumar, U. M. (2014). Dynamic diversity: Toward a contextual understanding of critical mass. Educational Researcher, 43(3), 115–124. https://doi.org/10.3102/0013189X14529814

Goldrick-Rab, S., Harris, D. N., & Trostel, P. A. (2009). Why financial aid matters (or does not) for college success: Toward a new interdisciplinary perspective. In J. C. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 24, pp. 1–45). Springer. http://dx.doi.org/10.1007/978-1-4020-9628-0_1

Gratz v. Bollinger, 539 U.S. 244. (2003). https://www.oyez.org/cases/2002/02-516

Grutter v. Bollinger, 539 U.S. 982. (2003). https://www.oyez.org/cases/2002/02-241

Hamlar, P. Y. (1983). Minority tokenism in American law schools. Howard Law Journal, 26(2), 443–599.

Hanson, M. (2021, December 5). Average law school debt. EducationData.org. https://educationdata.org/average-law-school-debt

Hess, G. F. (2002). Heads and hearts: The teaching and learning environment in law school. Journal of Legal Education, 52(1/2), 75–111.

Hilbe, J. M. (2011). Negative binomial regression. Cambridge University Press. https://doi.org/10.1017/CBO9780511973420

Hurtado, S., Alvarez, C. L., Guillermo-Wann, C., Cuellar, M., & Arellano, L. (2012). A model for diverse learning environments. In J. C. Smart & M. B. Paulsen (Eds.), Higher education: Handbook of theory and research (Vol. 27, pp. 41–122). Springer. https://doi.org/10.1007/978-94-007-2950-6_2

Institute of International Education. (2020). International students by academic level and place of origin, 2000/01-2019-20. Open Doors Report on International Exchange. https://opendoorsdata.org/data/international-students/academic-level-and-places-of-origin/

Jones, C. E. (2021). Still strangers in the land: Achievement barriers, burdens, and bridges facing African American students within predominately white law schools. Law & Inequality, 39(1), 13–46. https://doi.org/10.24926/25730037.621

King, R. D., Johnson, K. R., & McGeever, K. (2010). Demography of the legal profession and racial disparities in sentencing. Law & Society Review, 44(1), 1–32. https://doi.org/10.1111/j.1540-5893.2010.00394.x

Kreft, I. G. G. (1996). Are multilevel techniques necessary? An overview, including simulation studies. [Unpublished manuscript]. California State University, Los Angeles.

Lancaster, C., Xu, Y., Ovrebo, E., & Hosman, E. (2019). A critical race inquiry of African American female law students’ educational experiences at a racially diverse law school. Journal of Education & Social Policy, 6(2), 21–31.

Law School Survey of Student Engagement. (2020). Diversity & exclusion 2020 annual survey results. https://lssse.indiana.edu/wp-content/uploads/2020/09/Diversity-and-Exclusion-Final-9.29.20.pdf

Law School Transparency. (2021a, August 10). Law school enrollment. https://data.lawschooltransparency.com/enrollment/all/

Law School Transparency. (2021b, August 12). Law school costs. https://data.lawschooltransparency.com/costs/debt/

Littlejohn, E. J., & Rubinowitz, L. S. (1987). Black enrollment in law schools: Forward to the past? Thurgood Marshall Law Review, 12(2), 415–455.

Llamas, J. D., Nguyen, K., & Tran, A. G. (2021). The case for greater faculty diversity: Examining the educational impacts of student-faculty racial/ethnic match. Race, Ethnicity and Education, 24(3), 375–391. https://doi.org/10.1080/13613324.2019.1679759

Longa, E. (2007). A history of America’s first Jim Crow law school library and staff. Connecticut Public Interest Law Journal, 7(1), 77–104. https://heinonline.org/HOL/Page?handle=hein.journals/cpilj7&div=6

Mayhew, M. J., Rockenbach, A. N., Bowman, N. A., Seifert, T. A., & Wolniak, G. C., with Pascarella, E. T., & Terenzini, P. T. (2016). How college affects students (Vol. 3): 21st century evidence that higher education works. Jossey-Bass.

Moineddin, R., Matheson, F. I., & Glazier, R. H. (2007). A simulation study of sample size for multilevel logistic regression models. BMC Medical Research Methodology, 7(1), 34–34. https://doi.org/10.1186/1471-2288-7-34

Nguemeni Tiako, M. J., South, E. C., & Ray, V. (2021). Medical schools as racialized organizations: A primer. Annals of Internal Medicine, 174(8), 1143–1144. https://doi.org/10.7326/M21-0369

Nguyen, T. D., Kramer, J. W., & Evans, B. J. (2019). The effects of grant aid on student persistence and degree attainment: A systematic review and meta-analysis of the causal evidence. Review of Educational Research, 89(6), 831–874. https://doi.org/10.3102/0034654319877156

Olson, E. (2015, April 26). Burdened with debt, law school graduates struggle in job market. The New York Times. https://www.nytimes.com/2015/04/27/business/dealbook/burdened-with-debt-law-school-graduates-struggle-in-job-market.html

Pyne, J., & Grodsky, E. (2020). Inequality and opportunity in a perfect storm of graduate student debt. Sociology of Education, 93(1), 20–39. https://doi.org/10.1177/0038040719876245

Raushenbush, W. B. (1986). Law school admissions, 1984–2001: Selecting lawyers for the twenty-first century (W. B. Raushenbush, Ed.). Law School Admission Services, Inc.

Ray, V. (2019). A theory of racialized organizations. American Sociological Review, 84(1), 26–53. https://doi.org/10.1177/0003122418822335

Robbins, A. (2020). Preventing attrition: Critical interventions to close the racial gap in non-transfer attrition. Widener Law Review, 26(2), 143–180. https://heinonline.org/HOL/Page?handle=hein.journals/wlsj26&id=163

Spivey, M. (2019, December 15). An in-depth analysis of the 2019 law school admissions & entering class data. Spivey Consulting. https://blog.spiveyconsulting.com/aba-2019-data/

Strayhorn, T. L. (2012). College students’ sense of belonging: A key to educational success for all students. Routledge.

Taylor, A. N. (2018). Robin hood, in reverse: How law school scholarships compound inequality. Journal of Law & Education, 47(1), 41–107. https://heinonline.org/HOL/P?h=hein.journals/jle47&i=43

Taylor, A. N. (2019). The marginalization of Black aspiring lawyers. FIU Law Review, 13(3), 489–512. https://doi.org/10.25148/lawrev.13.3.8

Thomas, K., & Cochran, T. (2018, September 18). ABA data reveals minority students are disproportionately represented in attrition figures. AccessLex Institute. https://www.accesslex.org/xblog/aba-data-reveals-minority-students-are-disproportionately-represented-in-attrition-figures

Truong, K., & Museus, S. (2012). Responding to racism and racial trauma in doctoral study: An inventory for coping and mediating relationships. Harvard Educational Review, 82(2), 226–254. https://doi.org/10.17763/haer.82.2.u54154j787323302

Turner, C. S. V., González, J. C., & Wood, J. L. (2008). Faculty of color in academe: What 20 years of literature tells us. Journal of Diversity in Higher Education, 1(3), 139–168. https://doi.org/10.1037/a0012837

U.S. Census Bureau. (n.d.). QuickFacts: United States. U.S. Department of Commerce. https://www.census.gov/quickfacts/fact/table/US/PST045219

U.S. Census Bureau. (2021). 2020 census statistics highlight local population changes and nation’s racial and ethnic diversity. U.S. Department of Commerce. https://www.census.gov/newsroom/press-releases/2021/population-changes-nations-diversity.html

U.S. Department of Education. (2021, November). Total fall enrollment in degree-granting postsecondary institutions, by level of enrollment, sex, attendance status, and race/ethnicity or nonresident alien status of student: Selected years, 1976 through 2020. https://nces.ed.gov/programs/digest/d21/tables/dt21_306.10.asp

Ward, G., Farrell, A., & Rousseau, D. (2009). Does racial balance in workforce representation yield equal justice? Race relations of sentencing in federal court organizations. Law & Society Review, 43(4), 757–806. https://doi.org/10.1111/j.1540-5893.2009.00388.x