Ethnicity, gender, social class and achievement gaps at age 16: intersectionality and ‘getting it’ for the white working class

Abstract

Perhaps the most prevailing inequalities in educational achievement in England are those associated with socio-economic status (SES), ethnicity and gender. However, little research has sought to compare the relative size of these gaps or to explore interactions between these factors. This paper analyses the educational achievement at age 11, 14 and 16 of over 15,000 students from the nationally representative longitudinal study of young people in England. At age 16, the achievement gap associated with social class was twice as large as the biggest ethnic gap and six times as large as the gender gap. However, the results indicate that ethnicity, gender and SES do not combine in a simple additive fashion; rather, there are substantial interactions particularly between ethnicity and SES and between ethnicity and gender. At age 16 among low SES students, all ethnic minority groups achieve significantly better than White British students (except Black Caribbean boys who do not differ from White British boys), but at high SES only Indian students outperform White British students. A similar pattern of results was apparent in terms of progress age 11–16, with White British low SES students and Black Caribbean boys (particularly the more able) making the least progress. Parents’ educational aspirations for their child and students’ own educational aspirations, academic self-concept, frequency of completing homework, truancy and exclusion could account for the minority ethnic advantage at low SES, but conditioning on such factors simultaneously indicates substantial ethnic underachievement at average and high SES. Accounts of educational achievement framed exclusively in terms of social class, ethnicity or gender are insufficient, and the results challenge educational researchers to develop more nuanced accounts of educational success or failure.

Keywords:

• ethnicity
• gender
• social class
• equity
• achievement
• intersectionality

Acknowledgement

This research was funded by the Government Department for Education (Project Reference EOR/SBU/2006/031).

Notes

1. Prior to 2003 a different ethnic coding system was used in the school census with no direct mapping between to the new codes, thus data prior to 2003 is not directly comparable with current figures.

2. Non-linear or categorical PCA was warranted for two reasons. First, it does not require the assumption that all variables are continuous scales and that the relationship between all variables are linear. Second, the optimal scaling approach offers a sophisticated option for handling missing data which does not use assumptions such as missing at random or missing completely at random. This treatment is possible in nonlinear PCA because its solution is not derived from the correlation matrix (which cannot be computed with missing values) but from the data themselves (see Meulman, Van der Koou, and Heiser 2004; Linting et al. 2007 for further details).

3. This is indicated by the fact that from 2006 onwards the key benchmark at age 16 is achieving five or more GCSE A^∗–C grades or equivalent including English and mathematics. Previously there was no specification of individual subjects within the five passes, which could be in any subject.

4. Of course this does depend on how we express the ethnic gap. If we took this as the largest gap between an ethnic minority and the majority (White British) group, this would be 0.34 SD, so the SES gap would four times larger than the ethnic gap. However here we have chosen the broader measure of the gap between the highest and lowest achieving ethnic groups (0.63 SD).

5. The SES gap among girls reduces by a slightly smaller amount, from 0.99 SD to 0.49 SD (see Tables 4 and 5) or a 50% reduction. This reflects a significant gender by SES interaction in model 5 (see Table 3), so that for White British students, after controlling for all the contextual variables, the gender gap is small and non significant at low SES (0.02 SD) compared to 0.09 SD at the mean SES and 0.15 SD at high SES.

6. Full cross tabulations of ethnic group by each of the contextual variables are given as Appendix 2 in Strand (2011) and so are not repeated here.

7. This is not just because these two authors used a simple binary measure (whether a student gained 5 or more GCSEs at A^∗–C grades or not) rather than a continuous outcome, since a logistic regression on the 5 + A^∗–C including English and mathematics threshold measure with the LSYPE data also revealed significant ethnic by SES interactions. It is more likely to reflect better estimates of SES (direct measures across a range of SES variables rather than student report of parental occupation) and better sampling because of the LSYPE boost for minority ethnic groups.

8. This phenomena is observed across a range of SES variables not just parental SEC, but because the same patterns are seen when using just the SEC of the home, the term ‘working class’ is an appropriate to unite these findings.

9. LSYPE was able to distinguish between students who spoke English only, had English as their first/main language although they spoke other languages as well, or were bilingual, in contrast to those whose first/main language was other than English. The latter group accounted for 42% of Bangladeshi, 26% of Pakistani, 25% of Black African and 17% of Indian students.

10. EAL has not been included in the models reported here because of this non-significant effect. Kingdon and Cassen (2010) note the same finding.

11. Despite this, we should be wary of an uncritical interpretation of educational aspirations as evidence of psychological dispositions to achieve, or of a simple causal relationship between aspirations and subsequent attainment (Strand and Winston 2008). High levels of intending to continue in FTE among minority groups may actually reflect students’ knowledge of the greater risk of unemployment for young members of minority ethnic groups relative to Whites if they enter the labour market at 16, together with the fear of racial discrimination in the workplace (Payne 2003). White British students may have lower ‘educational aspirations’ because they do not face these barriers.

12. General national vocational qualifications are alternatives to GCSE examinations that emphasise vocational aspects of the curriculum, although both GNVQ and GCSE are awarded points values of the same unified scale.