Studying interethnic relations by means of social network analysis (SNA) focuses on behavior (forming friendship ties) rather than on attitudes, and we employ SNA to study the integration of minority students in Russian schools. Most studies, including our research, have found that ethnic homophily is usually asymmetric with ethnic majority students being “ethnically blind” (i.e., not giving a clear preference to friendships with other majority students) and ethnic minority students tending to form ties with peers of similar background (Ivaniushina & Alexandrov, 2012) similar to schools in Europe (for example, Vermeij et al., 2009). At the same time, prior research on interethnic relations indicates that the effects of ethnicity on ethnic homophily might differ in schools with varying ethnic composition.

Several theories were used to discuss the empirical findings (Leszczensky & Kretschmer, 2022). In line with Allport’s contact theory, exposure to peers from different ethnic groups might lead to improved attitudes towards the outgroup and decreased ethnic homophily (Allport, 1954; Pettigrew & Tropp, 2006). Threat theory, on the other hand, assumes that the increase in the number of outgroup members will lead to the feeling of threat of ingroup members, leading to the increase in ethnic homophily (Blalock, 1967). Finally, empirical studies observe a non-linear relationship between two variables with ethnic homophily reaching its peak in an “us vs. them” situation when the number of groups is more or less equal (Moody, 2001; Smith et al., 2016).

In our study, we decided to test these theories in Russian schools. Our previous studies did not provide definite results due to the lack of data on classes with a high share of minority students. To discern the effects of ethnic composition of schools on homophily in adolescent networks we recently sampled schools in Russian cities with varying presence of minorities, including ones with 70-90% of minority students. Following research tradition, we also differentiate between ethnic majority and ethnic minority homophily. The need for differentiation is explained by the differences in experiences ethnic minorities and majorities go through. While ethnic majorities are used to the position of power, ethnic minorities are used to a position in which adjustment is expected and might be more open to interethnic contacts (Vermeij et al., 2009). Thus, our research question: How do interethnic relations differ in classes with different proportions of ethnic minority students? To address this research question, we use social network analysis of friendship ties of adolescent children in Russian schools. 

Our work utilizes two datasets: one collected in St. Petersburg in 2010, and the other in Novosibirsk in 2023-24. While the analysis of the St.Petersburg dataset has led to some previous important findings (Ivaniushina & Alexandrov, 2012), the use of two datasets allows for the comparison of classes with varying ethnic compositions, ranging from 10-40% minority students in St. Petersburg (104 schools, 419 classes, and 7381 students) to 20-90% in Novosibirsk (14 schools, 212 classes, and 3879 students). The surveys in both cases include similar questions on school grades, school attitudes, educational motivation, and family background, along with socio-economic characteristics. Students were also asked to name classmates they communicate with most often and these nominations were used to construct social networks of each class. Only classes with a response rate of 75% and higher were analyzed to get reliable results. We used exponential random graph modeling (ERGM) as a method of statistical assessment of homophily. We build exponential random graph models for each class in our dataset. Each model includes both actor (ethnicity, sex, GPA, SES) and network (transitivity, reciprocity, density) characteristics. It allows us to consider different explanations of ties emergence. In our analysis, we differentiate between ethnic majority and ethnic minority homophily rather than focusing on general homophily. Meta-analysis techniques are applied to summarize the results of ERGMs. Additionally, meta-regression with random effects is used to model the effect of class ethnic composition (measured as the share of minority students in class) on ethnic minority and ethnic majority homophily.

Preliminary results of the analysis show that both ethnic minority and ethnic majority homophily persists in the dataset even after controlling for other possible explanations of tie formation (e.g., gender homophily or transitivity). Minority students tend to choose minority students for communication over ethnic majority students more often. While in St.Petersburg schools with low level presence of minorities ethnic majority students exhibit no ethnic homophily, in Novosibirsk schools ethnic majority students prefer communication with ethnic majority students thus showing increasing ethnic segregation in the schools with higher share of minority students. Moreover, the effect of class ethnic composition on ethnic minority and ethnic majority homophily is not the same. Ethnic minority homophily relates to class ethnic composition in a non-linear way showing the peak in network segregation when the minority / majority ratio is 0.4-0.5 – a situation very similar to the observed in American and European schools (Moody, 2001; Smith et al., 2016). Such results highlight the importance of local school and classroom context in the study of interethnic relations.

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