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Cross-national studies of student achievement provide a strong empirical basis to assess the appropriateness of sex-role theory and the same- sex socialization model to students’ educational performance. In the studies reviewed above, education is measured by years of education, which has different meanings between countries. Furthermore in countries with highly tracked systems, it obscures the great variation in student performance between students in different tracks with the same number of years of education. In contrast, in cross-national studies of student achievement educational performance is based on students’ scores in standardized tests. Test score is a much finer measure of educational performance than years of education. Furthermore, the measures of socio- economic background, father ’s and mother ’s occupation and education, are measured in the same way across countries whereas single-country studies often have quite different measures.

Therefore, the purpose of this article is to address two specific research questions: (1) Are there gender differences in the influence of socioeconomic background on students’ educational performance? and (2) Is student performance influenced more by the socioeconomic characteristics of the same-sex parent? These research questions are addressed using student achievement data from a large number of countries that include detailed measures of fathers’ and mothers’ occupation and education. It may be the case that the same-sex socialization role is more applicable for parental education than parental occupation or vice versa. Two internationally comparable measures of educational performance are analysed: reading and mathematics. The same-sex socialization model may be more apparent for mathematics than for reading. For example, men may attach more importance to their sons’ performance in mathematics than their daughters’, so their socioeconomic characteristics have a larger impact among boys for mathematics.

The two general research questions are disaggregated into seven testable hypotheses. They form a hierarchy from the most aggregated measure of socioeconomic background down to hypotheses about its four components, father ’s and mother ’s occupation and education.

 According to sex-role theory:

1. The effect of the family’s socioeconomic level on student performance is stronger among boys.

 According to the same-sex socialization model:

2.1 The effect of father ’s socioeconomic characteristics on student performance is stronger among boys.

2.2 The effect of mother ’s socioeconomic characteristics on student performance is stronger among girls.

3.1 The effect of father ’s occupational status on student performance is stronger among boys.

3.2 The effect of mother ’s occupational status on student performance is stronger among girls.

3.3 The effect of father ’s educational attainment on student performance is stronger among boys.

3.4 The effect of mother ’s educational attainment on student performance is stronger among girls.

Data and Measures

The data analysed are from the OECD’s 2000 Programme for International Student Assessment (PISA) study that examined student achievement in reading, mathematics and science among over 172,000 15-year-old students in 6000 schools in 32 countries. Participating countries include the OECD countries (except Turkey), and several non-OECD countries: Brazil, Latvia and Russia. Within each country, a two-stage sampling procedure was employed: first randomly selecting schools with probabilities proportional to size, and second, randomly selecting 15-year-old students within selected schools. In some countries, schools were stratified by type or location. Details on the sampling and response rates for both schools and students can be found in the initial and technical reports (OECD, 2001, 2002). Japan was excluded from these analyses because there were too much missing data on parental occupation and education. Liechtenstein was also excluded because of the small sample size.

Measures

The outcome measures investigated are reading and mathematics achievement scores. Item response theory (IRT) modelling was used to create scores standardized to an international (OECD) mean of 500 and a standard deviation of 100. Students’ scores are in the form of five plausible values rather than a single score. Details on the plausible values are available from the PISA technical report (OECD, 2002).

Students’ gender was elicited by a simple question asking if the student was a boy or a girl. If missing, the gender of the student was usually ascertained by the sampling frame. In the constructed measure of gender, girls were assigned a score of 1 and boys 0.

Information on parents’ occupation was obtained by two questions, asking students their mother ’s and father ’s main job and what they did in their main job. The information on parental occupation was coded according to the International Standard Classification of Occupation 1988 (ISCO-88), as provided by the International Labour Office. ISCO-88 is a four-digit hierarchical coding schema comprising 390 different occupational categories. Each ISCO-88 occupational category is assigned an occupational status score from the International Socioeconomic Index (ISEI). Ganzeboom and Treiman (1996) provide details on its construction and list ISCO-88 occupational titles with their respective ISEI scores. Information on the educational attainment of each parent was elicited by two questions. The first asked for the level of school education completed. A follow-up question was then asked about whether the parent had obtained any post-secondary qualifications. The responses to these questions were classified according to the International Standard Classification of Education (ISCED) schema (OECD, 1999).

The resulting measure of parental educational attainment comprised seven categories: no schooling, primary school, middle secondary school, higher secondary school (non-academic), higher secondary school (academic), tertiary education (non-academic) and tertiary education (academic). Scores for each category were constructed through optimal scaling techniques estimating scores that maximize the relationship between parents’ education and student achievement across the three domains within countries. This was done because the ordinal and cardinal relationships between the categorical measure of parental education and student achievement differ between countries.

Family socioeconomic status comprises four variables: father’s and mother’s occupational status and educational attainment. Father’s socioeconomic characteristics comprise two variables, father’s occupational status and father’s education. Similarly, mother’s socioeconomic characteristics comprise mother’s occupational status and education. The composite measures of family’s, father’s and mother’s socioeconomic characteristics were constructed using the sheaf variable technique (see Whitt, 1986), which maximizes the combined relationship of the constituent variables with the dependent variable. The resultant single sheaf variable explains exactly the same amount of variance as do the constituent variables in a parallel OLS regression analysis. The sheaf variables used the ISEI indices for the measures of parental occupation and the optimal scaled measures of parental education. These resultant measures were centred at the country means and standardized with a mean of 0 and a standard deviation of 1. The sheaf variables were constructed within countries, not across the pooled data set.

In the tables of results the regression coefficients for socioeconomic background variables reflect the average change in student achievement score for a one standard deviation change in the corresponding independent variable. The coefficients for gender are estimated on the difference in achievement (in reading or mathematics) of girls compared to boys. The interaction terms between the measures of socioeconomic background and gender are estimates of the difference in the effect of the measure of socioeconomic background on achievement for girls compared to boys. If the coefficient is negative then the effect of the measure of socioeconomic background on student achievement is weaker among girls compared to boys. If it is positive then the effect is stronger among girls than boys.

The standard errors associated with the regression coefficients have been adjusted to take into account the cluster design of the sample and sample stratification (if employed). Each regression coefficient and associated standard error was calculated by averaging the results obtained from separate analyses of the five plausible values. The OECD’s (2002) PISA weights were employed but adjusted to the original sample sizes rather than countries’ populations of 15-year-olds.

The composite variables comprised only variables with non-missing data. For example, mother ’s socioeconomic characteristics comprised only mother ’s education for cases where data on mother ’s occupation was missing. For the analyses that included the four separate measures of father ’s and mother ’s occupation and education, missing cases were deleted list-wise. Other approaches to handling missing cases were experimented with but did not substantially change the results.

Results

Gender Differences in the Effects of Father’s and Mother’s Characteristics

The estimates for father ’s and mother ’s socioeconomic characteristics, gender and the gender interactions are presented in Table 2 for reading and Table 3 for mathematics. These analyses provide support for the same-sex socialization model but only in a limited number of countries.

The effects of father’s socioeconomic characteristics on reading achievement are significantly weaker among girls in five countries: Australia, Belgium, Canada, Denmark and France. For Norway, the interaction term was significant at the .05 < p < .10 level. The effects of mother’s occupational and educational characteristics are significantly stronger (at the conventional level) among girls in only three countries: Australia, Canada and France. In Denmark, the effect is significant at the .05 < p < .10 level.

So only in Australia, Canada, Denmark and France are gender differences in the effects of father’s and mother ’s characteristics on reading achievement consistent with the same-sex socialization model.

For mathematics, the effects of father’s socioeconomic characteristics are significantly weaker among girls in Austria, Belgium, Denmark, Ireland and Latvia (Table 3). At the more generous level of statistical significance, the effect of father’s characteristics was also weaker among girls in the Czech Republic. In Austria, Belgium and Denmark the magnitude of the difference between boys and girls in the effect of father ’s socioeconomic characteristics is relatively large: over 10 score points. Contrary to the same-sex socialization hypothesis, in Poland the effect of father ’s socioeconomic characteristics was substantially stronger among girls, but not at the conventional level of statistical significance. In no country was the effect of mother ’s socioeconomic characteristics on mathematics achievement significantly stronger (at conventional levels of statistical significance) among girls.

Gender Differences in the Effects of Father’s and Mother’s Occupational Status and Education

The effects of father’s and mother ’s occupational status and education, gender and the gender interactions on student achievement are presented in Table 4 for reading and Table 5 for mathematics. There are four interaction terms, one each for father ’s and mother ’s occupational status

and education.

The effects of father’s occupational status on reading (Table 4) were significantly stronger among boys in six countries: Canada, the Czech Republic, Denmark, Finland, Germany and Hungary. (In Switzerland the effect was significant at the .05 < p < .10 level.) In several of these countries, the gender difference was fairly substantial around, or above, 10 score points. The effects of mother’s occupational status were significantly stronger among girls in only four countries: Canada, France, Hungary and Norway. The effect for Denmark was significant at the less demanding .05 > p > .10 level.

In no country was the effect of father’s education on reading significantly stronger among boys compared to girls at conventional levels of statistical significance. In Belgium and France, the effect was consistent with the same-sex socialization model but significant only at the .05 > p > .10 significance level. Contrary to the same-sex socialization model, the effects of father’s education were significantly stronger among girls in Luxembourg and in Germany at the less demanding significance level. Mother’s education had significantly stronger effects among girls only in Iceland.

For performance in mathematics (Table 5), the effect of father ’s socio-economic status was significantly stronger among boys in five countries: Austria, Belgium, Germany, Hungary and the Netherlands. The effect was significant at the .05 > p > .10 level in Finland and Luxembourg. There was no significant difference between boys and girls in the magnitude of the effect of mother’s occupational status on mathematics score in any of the countries examined.

The effects of father’s education on mathematics score were consistent with the same-sex socialization model in only three countries: Belgium, Denmark and Latvia but only at the .05 > p > .10 significance level. Again, only in Iceland was the effect of mother’s education significantly stronger among girls.

Key Words:

gender role – гендерные роли

sex-role theory - традиционные представления о том, что является уделом женщины и мужчины

socialization - социализация

socioeconomically advantaged families - социально и экономически благополучные семьи

occupational mobility – профессиональная мобильность

longitudinal study - лонгитудинальное исследование (длительное и непрерывное)

educational attainment – уровень образования

gender-specific behaviours особенности поведения, обусловленные полом

biological predispositions – биологическая предрасположенность

testable hypotheses - проверяемые гипотезы

hierarchy - иерархия

aggregate measure - комплексный показатель, совокупный показатель

OECD countries – страны организации экономического сотрудничества и развития

randomly selecting - отобранные в произвольном порядке

response theory – теория отклика

standard deviation – допустимое /стандартное/ среднеквадратическое отклонение

plausible values – правдоподобное значение

PISA - Международная программа по оценке образовательных достижений учащихся

follow-up question - уточняющий вопрос

primary school- начальная школа

middle secondary school - младшие классы средней школы

higher secondary school (non-academic) – старшие классы средней школы (нетрадиционной)

higher secondary school (academic),

tertiary education (non-academic) - высшее образование

tertiary education (academic) - высшее образование (классическое)

cluster design – кластерного вида

results obtained – полученные результаты

data on sth. is missing – отсутствуют данные по, отсутствует информация о

gender interactions – взаимодействие между полами

Summary

This article examines two related questions: (1) Are there gender differences in the influence of socioeconomic background on students’ educational performance? and (2) Is student performance influenced more by the socioeconomic characteristics of the same-sex parent? Seven hypotheses are derived and tested using data from 30 countries on student performance in reading and mathematics. There is little or no gender difference in the effects of socioeconomic background on educational performance in almost all countries examined. In no country are all the hypotheses relating to the same-sex socialization model supported, although there is a tendency for father’s socioeconomic characteristics and father’s occupation to have a stronger impact among boys in some countries. There were very few instances where mother’s characteristics were stronger among girls. In sum, there is only limited evidence to support the same-sex socialization model for educational performance.