Cultural capital and academic achievement in post-socialist Eastern Europe

Abstract

Using the 2000 and 2009 waves of Program for International Student Assessment (PISA) data, we examined the relationships between family socio-economic status (SES), cultural capital, and reading achievement among students in five post-socialist Eastern European countries while comparing the findings with three Western bench-marking countries. Findings: In all studied countries, higher-SES students possessed higher levels of cultural capital and exhibited higher reading achievement. Cultural capital was uniformly positively associated with reading achievement. We found the least stratification by SES in Russia both in the distribution of cultural capital and reading achievement. The findings provide no evidence of the overall decline of the importance of cultural capital over time; most of the associations between cultural capital measures and reading achievement remained stable across the waves. Between-country variation in the findings does not indicate East–West divide (with the exception of Russia).

Keywords:

• Cultural capital
• Eastern Europe
• reading achievement

Acknowledgement

The authors would like to thank Volha Chykina for her help with the manuscript preparation.

Notes

1.  Studies have shown that the ‘classless’ structure was essentially a myth and inequality existed throughout socialist history. Unequal educational outcomes have been documented by parental education, gender, region and rural vs. urban areas (Gerber 2000; Gerber and Hout 1995; Titma, Tuma, and Roosma 2003).

2.  The original responses were slightly different between the 2000 and 2009 PISA surveys. In PISA 2000, the responses were categories are (1) none; (2) 1–10; (3) 11–50; (4) 51–100; (5) 101–250; (6) 251–500; and (7) more than 500. In PISA 2009, the response categories were (1) 0–10; (2) 11–25; (3) 26–100; (4) 101–200; (5) 201–500; and (6) more than 500. We chose the median of each category (e.g., 1–10 = 5, 11–50 = 30) and transformed the value into natural log.

3.  We used the ‘pisareg’ module in STATA that is designed to be used with the PISA data by allowing analysis with plausible values calculating standard errors with the BRR method implemented in PISAFor more information about this module, see https://ideas.repec.org/c/boc/bocode/s457754.html.

4.  In calculations not shown but available upon request, we also tested a potentially gendered nature of the cultural capital effects by examining whether the effect of embodied cultural capital on educational outcomes differed by gender. Results indicated that the effect of embodied cultural capital on reading achievement was greater for girls than for boys in Hungary and Macedonia. No interaction effects were found in the rest of the countries. In terms of academic track enrollment, none of the countries showed a significant interaction effect.

5.  Assuming that missingness is missing at random (MAR), we employed Stata’s ice command (Royston 2005), which uses the multiple imputation by chained equations (MICE) approach to imputing missing values.

6.  It should be noted that literature does not have a consensus about the best way to combine fit statistics, such as r-squared, with multiple imputation.

7.  Because the data are cross-sectional, the reverse relationship is possible; children with higher reading literacy may exhibit more positive reading habits.