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Gender differences in mathematical performance have received considerable scrutiny in the fields of sociology, economics and psychology. We analyse a large data-set of high school graduates who took a standardised mathematical test in Russia in 2011 (n = 738,456) and find no substantial difference in mean test scores across boys and girls. However, boys have a greater variance of scores and are more numerous at the top of the distribution. We apply quantile regression to model the association between school characteristics and gender differences in test scores throughout the distribution of test scores. Male advantage in test scores, particularly at the top of the distribution, is concentrated in cities and in the schools with an advanced curriculum. In other high schools, especially in the countryside, gender differences in all parts of the distribution are small. We suggest several mechanisms based on selection and school effects that account for our findings.

Across most Western societies, trends towards increased ethnic intermarriage have been observed across the second half of the twentieth century. Whether such trends hold across the multi-ethnic society of Russia is not known. We analyze Russian census data and describe levels and trends in ethnic intermarriage in four highly different Russian cities. We find no change in ethnic intermarriage in Moscow, but more intermarriage in younger cohorts in the other three cities where the populations are more ethnically heterogeneous. Levels and trends in ethnic intermarriage vary substantially throughout Russia by locality and ethnic group. Our study highlights how trends in intermarriage can vary within a society, and how the local, historical context may play an important role. [ABSTRACT FROM AUTHOR]

Gender differences in mathematical performance have received considerable scrutiny in the fields of sociology, economics and psychology. We analyse a large data-set of high school graduates who took a standardised mathematical test in Russia in 2011 (n = 738,456) and find no substantial difference in mean test scores across boys and girls. However, boys have a greater variance of scores and are more numerous at the top of the distribution. We apply quantile regression to model the association between school characteristics and gender differences in test scores throughout the distribution of test scores. Male advantage in test scores, particularly at the top of the distribution, is concentrated in cities and in the schools with an advanced curriculum. In other high schools, especially in the countryside, gender differences in all parts of the distribution are small. We suggest several mechanisms based on selection and school effects that account for our findings. [ABSTRACT FROM PUBLISHER]