PAPIRO IV. Las palabras en columnas formando varias cruces y rodeando el busto de un hombre 166
2. Tablillas de defixion o execratorias.
Findings suggest that the social gradient in uptake of STEM subjects is stronger for women than men. Currently, the majority of interventions aimed at getting more women into STEM are targeted either at all girls and young women, those who are particularly high achieving (and thus likely from more advantaged backgrounds). Findings from this research suggest that more focus needs to be directed towards interventions targeting less advantaged girls. Students from lower SES
backgrounds are less likely to receive good quality careers advice, but are the ones that need it most (Archer, et al. 2013). A clear way to get more students to study STEM would be to give them knowledge of the wide range of careers available upon graduation after studying STEM, or of the subjects they need to study at GCSE and
167 A-level to study STEM at university. Advantaged students, particularly those whose parents work in STEM spheres, are most likely to already have access to this knowledge.
Overall, all young people could benefit from more information about the returns and career opportunities associated with different subjects. However, these returns differ depending on students’ backgrounds, with more advantaged young people more likely to gain well-paid employment whatever they choose to study. The analysis in this thesis suggests that students are already likely somewhat aware of this, choosing subjects with higher returns, avoiding arts and humanities, and placing less importance on the potential intrinsic returns of study. This inequality will only be resolved by focusing more broadly on inequalities in the labour market. Differences in motivations for study will be unnecessary if young people were afforded similar opportunities regardless of social background, gender, and ethnicity.
168
Bibliography
Ai, C., & Norton, E. C. (2003). Interaction terms in logit and probit models. Economics Letters, 80(1), 123-129.
Akerlof, G. A. (1997). Social distance and social decisions. Econometrica, 65(5), 1005-1027.
Allison, P. D. (2001). Missing data (Quantitative applications in the social sciences). London UK: Sage Publications.
Alon, S. (2007). Overlapping disadvantages and the racial/ethnic graduation gap among students attending selective institutions. Social Science
Research, 36(4), 1475-1499.
Altonji, J. G., Kahn, L. B., & Speer, J. D. (2016). Cashier or consultant? Entry labor market conditions, field of study, and career success. Journal of Labor
Economics, 34(1), 361-401.
Anders, J. (2012). The link between household income, university applications and university attendance. Fiscal Studies, 33(2), 185–210.
Anders, J. (2017). The influence of socioeconomic status on changes in young people’s expectations of applying to university. Oxford Review of Education,
43(4), 381–401.
Anders, J., Henderson, M., Moulton V., & Sullivan, A. (2018). The role of schools in explaining individuals’ subject choices at age 14. Oxford Review of Education,
44(1), 75-93
Andrews, J., Robinson, D., & Hutchinson, J. (2017). Closing the gap? Trends in
educational attainment and disadvantage. London: Education Policy Unit.
Antill, J. K., Cunningham, J. D. & Cotton, S. (2003). Gender-role attitudes in middle childhood: In what ways do parents influence their children? Australian
Journal of Psychology, 55(3), 148–153.
Archer, L., Dawson, E., DeWitt, J., Seakins, A., & Wong, B. (2015). “Science capital”: A conceptual, methodological, and empirical argument for extending
bourdieusian notions of capital beyond the arts. Journal of Research in Science
Teaching, 52(7), 922–948.
Archer, L., DeWitt, J., & Dillon, J. (2014). ‘It didn’t really change my opinion’:
exploring what works, what doesn’t and why in a school science, technology, engineering and mathematics careers intervention. Research in Science &
169 Archer, L., DeWitt, J., Osborne, J., Dillon, J., Willis, B., & Wong, B. (2012). Science
aspirations, capital, and family habitus how families shape children’s engagement and identification with science. American Educational Research
Journal, 49(5), 881-908.
Archer, L., & Francis, B. (2007). Understanding minority ethnic achievement: race,
gender, class and “success.” London: Routledge.
Archer, L., Francis, B., Moote, J., DeWitt, J., & Yeomans, L. (2016). The “exceptional” physics/engineering girl: A sociological analysis of longitudinal data from girls aged 10–16 to explore gendered patterns of post-16
participation. American Educational Research Journal, 54(1), 88 - 126.
Archer, L., & Moote, J. (2016). ASPIRES 2 project spotlight: year 11 students’ views of
careers education and work experience. London: King's College.
Archer, L., Osborne, J., DeWitt, J., Dillon, J., Wong, B., & Willis, B. (2013). ASPIRES.
Young people’s science and career aspirations, age 10 – 14. Retrieved from: https://www.kcl.ac.uk/sspp/departments/education/research/aspires/ASPIRE S-final-report-December-2013.pdf
Barone, C., & van de Werfhorst, H. G. (2011). Education, cognitive skills and
earnings in comparative perspective. International Sociology, 26(4), 483–502. Beasley, M. A., & Fischer, M. J. (2012). Why they leave: The impact of stereotype
threat on the attrition of women and minorities from science, math and engineering majors. Social Psychology of Education, 15(4), 427–448. Bécares, L., & Priest, N. (2015). Understanding the influence of race/ethnicity,
gender, and class on inequalities in academic and non-academic outcomes among eighth-grade students: findings from an intersectionality
approach. PloS one, 10(10), e0141363.
Belfield, C., Britton, J., Buscha, F., Dearden, L., Dickson, M., van der Erve, L., Sibieta, L., Vignoles, A., Walker, I., & Zhu, Y. (2018). The relative labour market returns
to different degrees. London: Institute for Fiscal Studies (IFS).
Bernardi, F., & Ballarino, G. (2016). Education, occupation and social origin: a
comparative analysis of the transmission of socio-economic inequalities.
Cheltenham: Edward Elgar Publishing.
Berrington, A., Roberts, S., & Tammes, P. (2016). Educational aspirations among UK young teenagers: Exploring the role of gender, class and ethnicity. British
Educational Research Journal, 42(5), 729-755.
Bhattacharyya, G., Ison, L. & Blair, M. (2003). Minority ethnic attainment and
170 Department for Education and Skills.
Blanden, J., & Gregg, P. (2004). Family income and educational attainment: a review of approaches and evidence for Britain. Oxford Review of Economic Policy,
20(2), 245-263.
Blanden, J., Gregg, P., & Machin, S. (2005). Intergenerational mobility in europe and
north america. London: London School of Economics, Centre for Economic
Performance.
Blanden, J., & Macmillan, L. (2016). Educational inequality, educational expansion and intergenerational mobility. Journal of Social Policy, 45(4), 589–614. Blundell, R., Dearden, L., Goodman, A., & Reed, H. (2000). The returns to higher
education in britain: evidence from a british cohort. The Economic Journal,
110(461), 82–99.
Boaler, J., Altendorff, L. & Kent, G. (2011). Mathematics and science inequalities in the United Kingdom: When elitism, sexism and culture collide. Oxford Review
of Education, 37(4), 457–484.
Boalt, G., & Janson, C. G. (1953). A selected bibliography of the literature on social stratification and social mobility in sweden. Current Sociology, 2, 306–327. Bøe M.V., Henriksen E.K. (2015). Expectancy-value perspectives on choice of
science and technology education in late-modern societies. In: Henriksen E., Dillon J., Ryder J. (Ed.) Understanding student participation and choice in
science and technology education (pp 17-29). Dordrecht: Springer.
Boliver, V. (2013). How fair is access to more prestigious UK universities? British
Journal of Sociology, 64(2), 344–364.
Boliver, V. (2015). Are there distinctive clusters of higher and lower status universities in the UK? Oxford Review of Education, 41(5), 608–627.
Bollen, K. A. (2002). Latent variables in psychology and the social sciences. Annual
Review of Psychology, 53(1), 605–634.
Bostwick, V. (2016). Signaling in higher education: The effect of access to elite colleges on choice of major. Economic Inquiry, 54(3), 1383–1401.
Botcherby, S., & Buckner, L. (2012). Women in Science, Technology, Engineering and
Mathematics: from Classroom to Boardroom. Bradford: WISE Campaign.
Botelho, A., & Pinto, L. C. (2004). Students’ expectations of the economic returns to college education: results of a controlled experiment. Economics of Education
Review, 23(6), 645-653.
Boudon, R. (1974). Education, opportunity, and social inequality: Changing prospects
171 Bourdieu, P. (1984). Distinction: A social critique of the judgement of taste.
Cambridge, Massachusetts: Harvard University Press.
Bradley, K., & Charles, M. (2003). Uneven inroads: understanding women’s status in higher education. Research in the Sociology of Education, 247-274.
Bratti, M., Naylor, R., & Smith, J. (2008). Heterogeneities in the returns to degrees: evidence from the british cohort study 1970. DEAS, University of Milan,
Departmental Working Paper No. 2008-40.
Breen, R. (2010). Educational expansion and social mobility in the 20th century. Social Forces, 89(2), 365-388.
Breen, R., & Goldthorpe, J. H. (1997). Explaining educational differentials: towards a formal rational action theory. Rationality and Society, 9(3), 275–305.
Breen, R., & Jonsson, J. O. (2005). Inequality of opportunity in comparative
perspective: recent research on educational attainment and social mobility.
Annual Review of Sociology, 31, 223–243.
Breen, R., Luijkx, R., Müller, W., & Pollak, R. (2009). Nonpersistent inequality in educational attainment: evidence from eight european countries. American
Journal of Sociology, 114(5), 1475–1521.
Breen, R., Luijkx, R., Müller, W., & Pollak, R. (2010). Long-term trends in educational inequality in europe: Class inequalities and gender differences. European
Sociological Review, 26(1), 31–48.
Breen, R., & Yaish, M. (2006). Testing the Breen-Goldthorpe model of educational decision making. In: Morgan SL, Grusky D. B. and Fields G. S. (Ed.) Mobility
and inequality: frontiers of research from sociology and economics (pp 232-
58). Stanford, CA: Stanford University Press.
Britton, J., Dearden, L., Shephard, N., & Vignoles, A. (2016). How english domiciled graduate earnings vary with gender , institution attended , subject and socio- economic background. IFS Working Paper W16/06
Broughton, N. (2013). In the balance: The STEM human capital crunch. Retrieved from: http://www.smf.co.uk/wp-content/uploads/2013/03/Publication-In- The-Balance-The-STEM-human-capital-crunch.pdf
Browne, I., & Misra, J. (2003). The intersection of gender and race in the labor market. Annual Review of Sociology, 29, 487–513.
Buchmann, C., DiPrete, T., & McDaniel, A. (2008). Gender inequalities in education.
Annual Review of Sociology, 34, 319-337.
Bukodi, E., Erikson, R., & Goldthorpe, J. H. (2014). The effects of social origins and cognitive ability in educational attainment: evidence from britain and
172 sweden. Acta Sociologica, 57(4), 293–310.
Bukodi, E & Goldthorpe, J. H. (2013). Decomposing social origins: the effects of parents class, status, and education on the educational attainment of their children. European Sociological Review 29(5): 1024–1039.
Bukodi, E., Goldthorpe, J. H., Waller, L., & Kuha, J. (2015). The mobility problem in Britain: new findings from the analysis of birth cohort data. The British
journal of sociology, 66(1), 93-117.
Burgess, S., Wilson, D., & Worth, J. (2009). Passing through school: the evolution of
attainment of England’s ethnic minorities. Bristol: CMPO.
Campbell, T. (2015). Stereotyped at seven? Biases in teacher judgement of pupils’ ability and attainment. Journal of Social Policy, 44(3), 517–547.
Card, D. (1999). The causal effect of education on earnings. Handbook of Labor
Economics, 3, 1801–1863.
CaSE (2014). Improving diversity in STEM. Retrieved from:
http://www.sciencecampaign.org.uk/resource/ImprovingDiversityinSTEM2 014.html
Catsambis, S. (1994). The path to math: Gender and racial-ethnic differences in mathematics participation from middle school to high school. Sociology of
Education, 67(3), 199-215.
CBI. (2014). Engineering our future: stepping up the urgency on stem. London: Confederation for British Industry.
Cech, E., Rubineau, B., Silbey, S., & Seron, C. (2011). Professional role confidence and gendered persistence in engineering. American Sociological Review,
76(5), 641–666.
Charles, M. (2017). Venus, Mars, and math: Gender, societal affluence, and eighth graders’ aspirations for STEM. Socius, 3, 1-16.
Charles, M., & Bradley, K. (2002). Equal but separate? A cross-national study of sex segregation in higher education. American Sociological Review, 67(4), 573– 599.
Charles, M., and Bradley, K. (2004). Uneven inroads: Understanding women's status in higher education. Research in Sociology of Education, 14, 247-274.
Charles, M., & Bradley, K. (2009). Indulging our gendered selves? Sex segregation by field of study in 44 countries. American Journal of Sociology, 114(4), 924– 976.
173 Checchi, D., & van de Werfhorst, H. G. (2017). Policies, skills and earnings: how
educational inequality affects earnings inequality. Socio-Economic Review, 16 (1), 137-160.
Chetty, R., Hendren, N., Jones, M. R., & Porter, S. R. (2018). Race and economic
opportunity in the united states: an intergenerational perspective (Working
paper no. 24441). Cambridge, MA: National Bureau of Economic Research. Chevalier, A. (2011). Subject choice and earnings of UK graduates. Economics of
Education Review, 30(6), 1187–1201.
Chipuer, H. M., Rovine, M. J., & Plomin, R. (1990). LISREL modeling: Genetic and environmental influences on IQ revisited. Intelligence, 14(1), 11–29. Choo, H. Y., & Ferree, M. M. (2010). Practicing intersectionality in sociological
research: A critical analysis of inclusions, interactions, and institutions in the study of inequalities. Sociological Theory, 28(2), 129–149.
Chowdry, H., Crawford, C., Dearden, L., Goodman, A., & Vignoles, A. (2013). Widening participation in higher education: Analysis using linked
administrative data. Journal of the Royal Statistical Society. Series A: Statistics
in Society, 176(2), 431–457.
Chowdry, H., Crawford, C. & Goodman, A. (2011). The role of attitudes and
behaviours in explaining socio-economic differences in attainment at age 16.
Longitudinal and Life Course Studies, 2(1), 59–76.
Codiroli, N. (2015). Inequalities in students’ choice of stem subjects. CLS Working Paper 2015/6, Centre for Longitudinal Studies, UCL Institute of Education. Codiroli Mcmaster, N. (2017). Who studies STEM subjects at A level and degree in
England? An investigation into the intersections between students’ family background, gender and ethnicity in determining choice. British Educational
Research Journal, 43(3), 528–553.
Codiroli Mcmaster, N. (2017a, July 10). Women are less likely to study STEM subjects – but disadvantaged women are even less so. [Blog post]. Retrived from: http://blogs.lse.ac.uk/politicsandpolicy/who-studies-stem/
Codiroli Mcmaster, N. (2017b, August 8). Which subjects bring the best career outcomes for UK university students? [Blog post]. Retrived from:
http://blogs.lse.ac.uk/businessreview/2017/08/08/which-subjects-bring- the-best-career-outcomes-for-uk-university-students/
Codiroli Mcmaster, N., & Cook, R. (2018). The contribution of intersectionality to quantitative research into educational inequalities. Review of Education. (Online First). doi: 10.1002/rev3.3116
174 Coe, R., Searle, J., Barmby, P., Jones, K., & Higgins, S. (2008). Relative difficulty of
examinations in different subjects. Durham, UK: Centre for Educational
Management.
Collings, J. & Smithers, A. (1984). Person orientation and science choice. European
Journal for Science Education, 6, 55–65.
Conti, G., Heckman, J., & Urzua, S. (2010). The education-health gradient. American
Economic Review, 100(2), 234–238.
Crawford, C. (2014). Socio-economic differences in university outcomes in the UK: drop-out, degree completion and degree class. Institute for Fiscal Studies, (W14/31).
Crawford, C., & Greaves, E. (2015). Socio-economic, ethnic and gender differences in
HE participation. Retrieved from
https://assets.publishing.service.gov.uk/government/uploads/system/uploa ds/attachment_data/file/474273/BIS-15-85-socio-economic-ethnic-and- gender-differences.pdf
Crenshaw, K. (1989). Demarginalizing the intersection of race and sex: A black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum, 1989(1), 139-167. Crenshaw, K. (1991). Mapping the margins: intersectionality, identity politics, and
violence against women of color. Stanford Law Review, 43(6), 1241-1299. Crompton, R., & Lyonette, C. (2005). The new gender essentialism - Domestic and
family “choices” and their relation to attitudes. British Journal of Sociology,
56(4), 601-620.
Cunha, F., & Heckman, J. J. (2009). The economics and psychology of inequality and human development. Journal of the European Economic Association, 7(2–3), 320–364.
Davies, P., Mangan, J., Hughes, A., & Slack, K. (2013). Labour market motivation and undergraduates' choice of degree subject. British Educational Research
Journal, 39(2), 361-382.
Davies, S., & Guppy, N. (1997). Fields of study, college selectivity, and student inequalities in higher education. Social Forces, 75(4), 1417–1438.
Davis, K. (2008). Intersectionality as buzzword: A sociology of science perspective on what makes a feminist theory successful. Feminist Theory, 9(1), 67–85. Davis, S. N., & Greenstein, T. N. (2004). Cross-national variations in the division of
175 Dekkers, H. P. J. M., Bosker, R. J., & Driessen, G. W. J. M. (2000). Complex inequalities
of educational opportunities: A large-scale longitudinal study on the relation between gender, social class, ethnicity and school success. Educational
Research and Evaluation, 6(1), 69-82.
Department for Business, Innovation and Skills. (2015). 2010 to 2015 government
policy: public understanidng of science and engineering. London: The
Stationary Office
Department for Education. (2011). LSYPE User Guide to the Datasets: Wave 1 to
Wave 7. London: The Stationary Office
Department for Education (2014). Launch of new high-quality post-16 maths
qualifications. Retrieved from:
https://www.gov.uk/government/news/launch-of-new-high-quality-post- 16-maths-qualifications
Department for Education (2016). The lives of young carers in England. Retrieved from: https://www.gov.uk/government/publications/the-lives-of-young- carers-in-england
Department for Education. (2017). Employment and earnings outcomes of higher
education graduates by subject and institution: experimental statistics using the Longitudinal Education Outcomes (LEO) data. London: The Stationary
Office.
DeWitt, J., Archer, L., & Osborne, J. (2013). Nerdy, brainy and normal: Children’s and parents’ constructions of those who are highly engaged with science.
Research in Science Education, 43(4), 1455-1476.
DeWitt, J., Osborne, J., Archer, L., Dillon, J., Willis, B., & Wong, B. (2013). Young children's aspirations in science: The unequivocal, the uncertain and the unthinkable. International Journal of Science Education, 35(6), 1037-1063. Dickerson, A., & Popli, G. (2016). Persistent poverty and children’s cognitive
development: Evidence from the UK Millennium Cohort Study. Statistics in
Society: Series A, 179(2), 535–558.
Dilnot, C. (2016). How does the choice of A‐level subjects vary with students' socio‐ economic status in English state schools? British Educational Research
Journal, 42(6), 1081-1106.
DiPrete, T. A., Erikson, R., & Goldthorpe, J. H. (1993). The constant flux: a study of class mobility in industrial societies. Contemporary Sociology, 22(4), 536. Dolton, P. J. & Vignoles, A. (2002). The return on post-compulsory school
176 Dynarski, S. M. (2003). Does aid matter? Measuring the effect of student aid on
college attendance and completion. American Economic Review, 93(1), 279- 288.
Eccles, J. (1983). Expectancies, values, and academic behaviors. In J. T. Spence (Ed.), Achievement and achievement motives: Psychological and sociological approaches (pp. 75-146). San Francisco, California: W. H. Freeman.
Eccles, J. (1983). Female achievement patterns: Attributions, expectancies, values, and choice. Journal of Social Issues, 1, 1-22.
Eccles, J. (2011). Gendered educational and occupational choices: Applying the Eccles et al. model of achievement-related choices. International Journal of
Behavioral Development, 35(3), 195-201.
Eccles, J., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual
review of psychology, 53(1), 109-132.
Economic and Social Research Council. (2017). ESRC Longitudinal Studies Review
2017 Specification. Retrieved from: https://esrc.ukri.org/news-events-and-
publications/publications/corporate-publications/longitudinal-studies- review-2017
Else-Quest, N. M., & Hyde, J. S. (2016). Intersectionality in quantitative
psychological research: I. Theoretical and epistemological issues. Psychology
of Women Quarterly, 40(2), 155–170.
England, P., Allison, P., Li, S., Mark, N., Thompson, J., Budig, M. J., & Sun, H. (2007). Why are some academic fields tipping toward female? The sex composition of u.s. Fields of doctoral degree receipt, 1971-2002. Sociology of Education,
80(1), 23–42.
England, P., Farkas, G., Kilbourne, B. S., & Dou, T. (1988). Explaining occupational sex segregation and wages: findings from a model with fixed effects.
American Sociological Review, 53(4), 544.
Entwisle, D. R., Alexander, K. L., & Olson, L. S. (2007). Early schooling: The handicap of being poor and male. Sociology of Education, 80(2), 114-138.
Equality Challenge Unit. (2014). Equality in higher education: Statistical report
2014. London: Equality Challenge Unit.
Equality Challenge Unit. (2016). Equality in higher education: Statistical Report
2016. London: Equality Challenge Unit.
Farré, L., & Vella, F. (2013). The intergenerational transmission of gender role attitudes and its implications for female labour force participation.
177 Feinstein, L. (2003). Inequality in the early cognitive development of British
children in the 1970 cohort. Economica, 70(277), 73–97.
Ferree, M. M., & Hall, E. J. (1996). Rethinking stratification from a feminist perspective: Gender, race, and class in mainstream textbooks. American
Sociological Review, 61(6), 929-950.
Few-Demo, A. L. (2014). Intersectionality as the “new” critical approach in feminist family studies: Evolving racial/ethnic feminisms and critical race theories.
Journal of Family Theory & Review, 6(2), 169–183.
Frenzel, A. C., Goetz, T., Pekrun, R., & Watt, H. M. G. (2010). Development of
mathematics interest in adolescence: Influences of gender, family, and school