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Issues in the Conceptualisation and Measurement of Socioeconomic Background: Do Different Measures Generate Different Conclusions?

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Abstract

Parental occupation and education are used extensively in the analysis of socioeconomic inequalities in education and subsequent social and economic outcomes. The purpose of this paper is to examine if different ways of measuring socioeconomic background substantially alter substantive conclusions on cross-national differences in socioeconomic inequalities in student achievement. The effects of father’s occupational group are largely consistent across countries, with students from teaching backgrounds scoring very highly in many countries. Student performance by mother’s educational group is quite similar across countries although the relative performance of students whose mothers completed vocational education differs between countries. Notwithstanding these differences, continuous measures of father’s and mother’s occupation and education, and composite measures comprising combinations of these four indicators and additional indicators produce similar, but not identical, orderings of countries in terms of socioeconomic inequalities in student performance. However common single indicator measures, mother’s education and father’s occupation do not show a particularly high correspondence, cross-nationally. On theoretical and empirical grounds, the preferred measure is a composite of both parents’ occupation and education.

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Notes

  1. For example, the intercorrelations of the indicators used in the this paper among students in OECD countries using the PISA 2000 data are as follows:

      

    1

    2

    3

    4

    5

    6

    7

    8

    1

    Father’s occupation

    1.00

    0.37

    0.46

    0.30

    0.27

    0.16

    0.26

    0.28

    2

    Mother’s occupation

     

    1.00

    0.33

    0.45

    0.23

    0.14

    0.23

    0.27

    3

    Father’s education

      

    1.00

    0.55

    0.23

    0.14

    0.22

    0.28

    4

    Mother’s education

       

    1.00

    0.23

    0.12

    0.21

    0.28

    5

    Wealth (Possessions)

        

    1.00

    0.24

    0.15

    0.18

    6

    Educational resources

         

    1.00

    0.27

    0.21

    7

    Cultural possessions

          

    1.00

    0.40

    8

    Books in the home

           

    1.00

    1. The Cronbach’s alpha statistic is 0.74
  2. The correlations between the measures of socioeconomic used in this paper and student performance in mathematics or science are very close to those presented here for reading (results available on request).

  3. In TIMSS the correlations between a weaker measure of mother’s education than that used here and mathematics achievement were highest in Hungary (0.28), Portugal (0.28), French-speaking Belgium (0.26) and the United States (0.23). The correlations are weakest in Norway (0.10), the Netherlands (0.10), Denmark (0.11), Iceland (0.14), Austria (0.15) and Sweden (0.16). However, there are differences between the TIMSS 1996 and PISA 2000 studies in the relative strength of the association for some countries, notably Denmark, the Netherlands and Germany.

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Appendix

Appendix

See Tables 6 and 7.

Table 6 Mean scores (Standard Error) for reading by father’s occupational group
Table 7 Mean scores (SE) for reading by mother’s educational group

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Marks, G.N. Issues in the Conceptualisation and Measurement of Socioeconomic Background: Do Different Measures Generate Different Conclusions?. Soc Indic Res 104, 225–251 (2011). https://doi.org/10.1007/s11205-010-9741-1

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