Despite the expansion of higher education in Russia, significant inequality persists. In 2017, only 5-8% of students from the lowest income quintile attended universities, compared to 44-61% of those from the highest income quintile (Malinovskiy, Shibanova, 2022). Affirmative action programs, which consider applicants' characteristics that are traditionally not advantageous due to corresponding social and economic barriers (e.g., gender, ethnicity, income level, etc.) (Arcidiacono et al., 2012), can serve as a tool to expand access to higher education for those unable to gain admission through highly competitive processes (Malinovskiy, Shibanova, 2022).

This work investigates the academic performance of students enrolled in the "Social Elevator" program at one of TOP-5 Russian universities – HSE University. The program operates under the principle of affirmative action and aims to assist those students who have lower chances of admission due to various social reasons in a highly competitive environment by providing access to tuition-free learning, scholarships and accomodation. 

This study employs the theory of primary and secondary effects of inequality (Boudon, 1974). Primary effects refer to how social background influences students' academic performance—families with higher socio-economic status (SES) can afford additional classes, tutoring services, and other educational resources. Secondary effects reflect how social background shapes students' educational choices toward specific trajectories. These choices are influenced not only by financial resources but also by family values, expectations about education, and its perceived returns (Ibid.). As a result, families with higher SES are more likely to choose prestigious educational paths, even when students perform poorly, whereas families with lower SES often avoid academic tracks, even when students achieve high performance (Khavenson, Chirkina, 2019; Jerrim, et al., 2015).

Currently, there is a lack of empirical evidence on the effectiveness of affirmative action programs in Russia, unlike international studies showing their positive impact on enrollment and completion rates among low-SES students (Herbaut, Geven, 2020). However, Russia’s unique context, including stricter admission criteria, may limit the direct applicability of such findings (Boatman, Long, 2016). Furthermore, student retention rates are not a reliable measure in Russia due to normative per-capita funding, which incentivizes universities to retain students regardless of their behaviour. While some studies suggest positive impacts of such programs on GPA and academic engagement (Ibid.), further research is needed to understand how these measures influence academic success—a critical factor for retention and integration (Pascarella, Terenzini, 2005; Tinto, 2012). High academic performance, in turn, can reflect enhanced human capital investment and greater competitiveness in the labor market (Becker, 2009).

In this study, academic performance is understood as the quantitative outcomes of a student's interaction with the university's educational environment, measured through: 1) GPA (Grade Point Average): A weighted score ranging from 0 to 10. Higher GPA values indicate better academic performance. 2) Performance Percentile: A score ranging from 100 to 0, showing a student's rank in the top N percent of the performance distribution. Lower percentile values indicate better performance. This metric reflects relative performance compared to peers. The study relies on administrative data (student’s socio-demographic characteristics and academic performance) and survey data from university applicants (students' SES). Survey data was used to track SES for students not supported by the "Social Elevator" program (as program participants are known to have low SES due to program requirements). The analysis includes one survey question: "How would you assess your family’s financial situation?" The sample combines three cohorts of first-year students (2020/21, 2021/22, and 2022/23 academic years) who completed their first year of study, after which the GPA and Percentile were calculated. The cohorts were combined to ensure that there would be enough data for analysis – this concern is based on the fact that there’s only 100-150 “Social Elevator” students coming each year, and for some students the data is not sufficient. During data analysis compared two groups of tuition-free students. The first group consists of students who study on a budgetary basis due to their high scores on the Unified State Exam (USE) (N=1575). The second group includes participants in the "Social Elevator" program (N=280) – students whose USE scores were insufficient for state funding but who qualified for program support due to their low SES. To assess differences in the values of dependent variables under otherwise equal conditions, the study employs a linear regression with dummy variables, controlling for year of admission, campus, age, gender, SES, major & department, average score on Unified State Exam.

It was hypothesized that program participants will demonstrate higher academic performance due to their inner drive for upward social mobility, as documented in prior qualitative research (Kurakin, Kusimova, 2024). Resulting models described 28% of variance in GPA and 27% of variance in Percentile. Regression analysis revealed that, all else being equal, students admitted through the "Social Elevator" program exhibit lower academic performance (in terms of GPA and Percentile) compared to students admitted to state-funded places based on their Unified State Exam (USE) results. However, the difference in GPA is only 0.7 points (when controlled for other variables), both groups demonstrate grades at a “good” level with “Social Elevator” having 6.95 GPA and budgetary funded students having a 7.79 GPA. The reason behind this gap can be that these students differ in habitus and program participants can have difficulties with adaptation among people with a different habitus (Bourdieu, Passron, 2007). Therefore, program participants may demonstrate successful academic integration (relatively high USE scores), but unsuccessful social integration (differences in SES) can lead to reduced academic performance and dropout (Tinto, 2012). This highlights the importance of separating secondary effects of inequality and exploring how they can manifest themselves.

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