My Old Man's a Dustman: Exploring Microsocial Classes and Parental Influence on Educational Attainment

1. ‘My old man’s a refuse and salvage collector’ – Thinking about microsocial classes and the potential relationships between parents and filial educational attainment Professor Vernon Gayle and Dr Paul Lambert , University of Stirling 6th April 2011 AQMeN Stirling Trinity Term Lecture Series

2. Lonnie Donegan MBE (29 April 1931 – 3 November 2002) was a skiffle musician with more than 20 UK Top UK Top 30 hits. He is known as the ‘King of Skiffle’. The Guinness Book of British Hit Singles & Albums states Donegan was ‘Britain’s most successful and influential recording artist before The Beatles. He chalked up 24 successive Top 30 hits, and was the first UK male to score two U.S. Top 10s’. Oh, my old man's a dustman, He wears a dustman's hat, He wears cor-blimey trousers And he lives in a council flat. He looks a proper nana, In his great big hobnail boots, He's got such a job to pull them up, That he calls 'em daisy roots.

3. BEWARE! WORK IN PROGRESS Mainly exploratory analyses

4. The overall motivation… • Undertake a piece of work that locates within a wider sociological perspectives on social stratification • ‘inter’-generational relationships • A long running empirical research theme within the sociology of education and the sociology of youth has been the relationship between parental social background (often measured by parental occupation) and educational attainment • Historically the weight of evidence has indicated that educational attainment is stratified - typically, those from more advantaged social backgrounds generally achieve higher levels of attainment than their counterparts from less advantaged backgrounds • An attempt to use some recently harmonised large-scale survey data • augment analyses with additional measures • Start to think about analyses of microclasses

5. Background • Current obsession • Presently a ‘giant’ sensitivity analysis • Builds on work in the DAMES project • Writing a paper (3/4 finished) for RC28 Conference • Exciting debate emerging between the heavyweights • Goldthorpe &Erikson V Grusky, Weeden and Jonsson

6. General Certificate of Education • General Certificate of Secondary Education (GCSE) introduced in the late 1980s • The standard qualification for pupils in England and Wales in year 11 (aged 15/16) • Usually a mixture of assessed coursework and examinations • Generally each subject is assessed separately and a subject specific GCSE awarded • It is usual for pupils to study for about nine subjects, which will include core subjects (e.g. English, Maths and Science) and non-core subjects • GCSEs are graded in discrete ordered categories • The highest being A*, followed by grades A through to G (A* from 1994) • Arran Fernandez gained A* in Maths at age 8 !

7. General Certificate of Education • The Education Reform Act 1988 led to rapid changes in the secondary school curriculum, and to the organisation, management and financing of schools • A major change for pupils was the introduction of the General Certificate of Secondary Education (GCSE) • GCSEs differed from the qualifications that they replaced • A new grading scheme was established and all pupils were entered for a common set of examinations • There were also changes in the content and format of examinations and assessment by coursework was introduced • School league tables were published • A newsworthy item each summer • Previously only teachers, parents and pupils knew when exam day was

8. Why explore GCSE attainment? • GCSEs are public examinations and mark the first major branching point in a young person’s educational career • Poor GCSE attainment is a considerable obstacle which precludes young people from pursuing more advanced educational courses • Young people with low levels of GCSE attainment are usually more likely to leave education at the minimum school leaving age and their qualification level frequently disadvantages them in the labour market • Low levels of qualifications are also likely to have a longer term impact on experiences in the adult labour market • Therefore, we argue that gaps in GCSE attainment are sociologically important

9. Youth Cohort Study of England & Wales (YCS) • Major Longitudinal Study began Mid-1980s • Designed to monitor behaviour of young people as they reach the minimum school leaving age and either stay on in education of enter the labour market • Experiences of Education (qualifications); Employment; Training; Aspirations; Family; Personal characteristic & circumstances • Nationally representative; Large sample size; Panel data (albeit short); Possible to compare cohorts (trends over time) • Study contacts a sample from an academic year group (cohort) in the spring following completion of compulsory education • The sample is designed to be representative of all Year 11 pupils in England & Wales • Sample are tracked for 3 (sometimes 4) waves (called Sweeps) of data collection • Growing up in the 1990s the GCSE era; Partly fills the gap left by the missing 198(2) birth cohort

10. Working with the YCS • Documentation is very poor especially in the older cohorts – usually handwritten annotation on questionnaires (pdf) (Compare this with the BHPS for example) • Changes in qualifications, educational policy etc adds data complications • Changes is questions, measures, coding, timing etc, all add to the general confusion • Recently available harmonized dataset SN 5765 Title: Youth Cohort Time Series for England, Wales and Scotland, 1984-2002 Depositor(s): Croxford, L., University of Edinburgh. Centre for Educational Sociology Principal Investigator(s): Croxford, L., University of Edinburgh. Centre for Educational SociologyIannelli, C., University of Edinburgh. Centre for Educational SociologyShapira, M., University of Edinburgh. Centre for Educational Sociology Economic and Social Research Council Grant Number: R000239852

11. Why parental occupation • Occupations is a key measure of social stratification • Maps onto wider sociological conception of social class • Why not income or wealth? • 16/17 year olds are being questioned • fluctuation in income and wealth • parents’ location on the age/income distribution • Occupation is a proxy • lifetime income • life chances (and opportunities) • lifestyle & consumption patterns • (even correlates with health)

12. A proxy for income? In this respect, we would argue that the use of socio-economic classifications in research is not simply to act as a proxy for income where income data themselves are unavailable. We use socio-economic classifications because they are measures designed to help us identify key forms of social relations to which income is merely epiphenomenal… It is also the case that socio-economic classifications are relatively more general and stable measures than income. Income is well known to fluctuate over the lifecourse; indeed panel data regularly reveals a high level of ‘income churning’ from year to year (for the UK see Jarvis and Jenkins 1997). What socio-economic classifications might reasonably be expected to proxy is the lifecourse/earnings profile. (Rose and Pevalin 2003) A Researcher’s Guide to the National Statistics Socio-economic Classification

13. Which measure of occupation? Forty years ago, Bechhofer’s review of the use of occupational information in sociology bemoaned the abundance of, and inconsistencies between, occupationally based social classifications, noting that “..researchers are advised not to add to the already existing plethora of classifications without very good reason” (1969 p.118) However since that recommendation, the number of new classifications has increased steadily We argue for the transparent use of classifications that have ‘agreed’ standards of measurement and can therefore be replicated and compared within and across analyses

14. Various (unsystematic) parental occupation measures deposited with individual YCS cohorts • NS-SEC (8 and 3 category) deposited with SN 5765 • We have added a large number of additional measures not in SN 5765 • Derived from data using GEODE Resources • www.geode.stir.ac.uk • www.dames.org.uk/ • Some of the measures are approximations because detailed parental employment status is not available

15. Parental Occupational Measures • We have derived measures for mother’s and fathers • In the following analyses we present ‘parental’ measures • Dominance method • common in stratification research • father or mother whichever dominant (and ft worker) • For example… • nurse mum and consultant dad = dad • (ft) nurse mum and (ft) hospital porter dad = mum

17. YCS Data • YCS cohorts • School leaving years 1990, 1993, 1995, 1997, 1999 • Comprehensive school pupils • Free schooling • No educational selection • Complete information on parental occupation and other measures (n=55120)

18. GCSE Outcome Measures • 5+ GCSEs grades A*-C • Recognised official bench mark • Frequently used outcome measure in research • School league table measure • This measure is still published annually by The Department for Children, Schools and Families (see http://www.dcsf.gov.uk/performancetables/ ) • Government target is 53% with 5+A*-C including Maths & English by 2011 • Number of GCSEs grades A*-C • GCSE score (A/A*=7; G=1) • Capped at 84 point 12 GCSEs Grade A/A* • Standardized GCSE score (A/A*=7; G=1)

19. Descriptive Results • Overall trend • Increasing proportions getting 5+GCSEs (A*-C) • Increasing mean number of A*-C grade GCSEs • Increasing mean GCSE points score • Gender • Female pupils outperforming male pupils • Ethnicity • Some groups doing better than white pupils (e.g. Indians) • Other groups doing worse (e.g. blacks) • Parental Occupation • Observable gradient • Lower levels of GCSE attainment from those pupils with less occupationally advantaged parents

21. What is the relationship between parental occupations and filial educational attainment? • Relatively strong (and persistent) association between a pupil’s GCSE attainment and the occupational position of their parents (net of cohort, gender and ethnicity) • Similar association with any GCSE measure • Similar association with any of the occupational based measures • e.g. NS-SEC, ESeC, RGSC, EGP, but also NS-SEC3, M/NM, Skill, and CAMSIS, NES • The level of association is stronger than gender and ethnicity • The parental occupational gap is more striking • Changing over time? Additional comprehensive analyses required • Ongoing concern about the gender gap • In educational circles and in public discourse (media fuelled) • Ultimate aim is to make a contribution to wider debates within stratification research

22. Which scheme requires some thought... • It is scientifically attractive to try a variety of schemes • Sensitivity analyses • GEODE should help here (www.geode.stir.ac.uk) • In this example broadly similar results at first glance • We doubt the established claim that competing schemes measure different theoretical dimension of social stratification • e.g. does NS-SEC measure employment relations, whilst CAMSIS measures status, Elias’ scheme measure skill? • Simplified measures are less attractive • The difference in explanation may be quite large (e.g. as a proportion of R2) • The difference might be as large as the R2 for the gender effect

23. For many analyses established schemes will be appropriate • We want to further explore (and maybe unpack) relationships between parental occupations and filial attainment • There might be extra insights somewhere between ‘big class categories’ and ‘individual occupations’?

24. Exploring at Occupational Unit Group (OUG) Level NS-SEC No. of SOC90 Occupations* 1.1 Large Employers and higher managers 10 1.2 Higher professional occupations 38 2 Lower managerial and professional occupations 78 3 Intermediate occupations 42 5 Lower supervisory and technical occupations 41 6 Semi-routine occupations 88 7 Routine occupations 74 Total 371 * Employees Possible interesting variations within NS-SEC categories

27. McKnight & Elias (1998) Guide to the 371 DatabaseEarnings distributions in SOC OUG ‘quindeciles?’ Distribution of employment by (highest) qualification SOC OUGRegrettably the micro-data are no longer available

29. There might be extra insights somewhere between ‘big class categories’ and ‘individual occupations’? • Work emerging in sociology… • Jonsson et al 2009 AJS; Grusky & Weeden (2005, 2006) • Between 9 categories and 371 unorganised occupational unit groups, there may be 80-120 microclasses defined by their professional cultures and practices? • ‘Microclass regime.—The microclass approach shares with the big-class model the presumption that contemporary labor markets are balkanized into discrete categories, but such balkanization is assumed to take principally the form of institutionalized occupations (e.g., doctor, plumber, postal clerk) rather than institutionalized big classes (e.g., routine nonmanuals, proprietors)’ (Jonsson et al 2009 pp.982-983)

30. Microclasses The initial appeal is the prospect of • Occupation-Specific Human Capital • Occupation-Specific Cultural Capital • Other Occupation-Specific Mechanisms

31. Jonsson et al 2009 p.986

33. Examples of the Composition of Microclasses Health ProfessionalsHealth Semi-Professionals 220 Medical practitioners 222 Ophthalmic opticians 221 Pharmacists / pharmacologists 340 Nurses 223 Dental practitioners 314 Midwives 224 Veterinarians 342 Medical radiographers 343 Physiotherapists Workers in religion 344 Chiropodists 292 Clergy 345 Dispensing opticians 347 Occupational and speech therapists Elementary and Secondary teachers 348 Environmental health officers 233 Secondary school teachers 349 Other health associated professionals 234 Primary school teachers 235 Special education 239 Other teaching

34. Examples of the Composition of Microclasses Bricklayers, carpenters, and related construction workers 500. Bricklayers, masons fixer 501. Roofers, slaters, tilers, sheeters 502. Plasterers fibrous foreman 503. Glaziers firm 504. Builders, building contractors 505. Scaffolders, stagers, steeplejacks 506. Floorers, floor coverers, carpet f 509. Other construction trades 570. Carpenters and joiners 896. Construction and related operative 921. Mates to building trades workers 922. Rail construction maintenance track 923. Road construction and maintenance 924. Paviors, kerb layers 929. Other building and civil engineering

37. Least Squares Dummy Variable Models GCSE Score Controls - Cohort; Gender; Ethnicity n=55120

38. Tentative Conclusions • Strong and persistent association between parental occupations and filial GCSE attainment • Irrespective of how GCSEs are measured • Irrespective of how occupations are measured

39. Tentative Conclusions “Nevertheless a large proportion of the social origins influence is adequately measured by quite simplified occupation-based schemes. This suggests that much, but not all, of the social origins influence of occupations is a direct function of average position within the stratification structure. However, contrary to claims that different stratification measures measure different things (cf. Rose and Harrison, 2010), the divergences between schemes are minimal and have little correspondence to the theoretical foundations of different measures (cf. Lambert and Bihagen, 2007)” Gayle and Lambert 2011

40. Tentative Conclusions • Strong and persistent association between parental occupations and filial GCSE attainment • Empirically stronger when specific occupations are recognised (difference between secondary school teachers and publicans)

41. Tentative Conclusions “The results presented clearly favour the arguments developed by Jonsson et al. (2009) and Grusky and Weeden (2006; 2005; 2002). Amongst the range of measures used, fine-grained occupation-based schemes such as the original SOC units or the microclass scheme bring a substantial, parsimonious improvement to the empirical description of parental influences upon educational attainment, and the differences from occupation to occupation seem predictable and consistent with an emphasis on the impact of particular occupational cultures” Gayle and Lambert 2011

42. Tentative Conclusions • In the UK many educational initiatives have attempted to target the underachievement of specific groups • In our view plagued by poor measures (e.g. free school meals, neighbourhood) • Some based on ‘big class’ analyses • Big classes are heterogeneous and this might obviate the intended beneficiaries of these initiatives

43. More beyond…

44. References Dale, A., Middleton, E. and Schofield, T. (2005) ‘New Earnings Survey variables added to the SARs’, SARs Newsletter, 6. Grusky. D. and Weeden, K. (2006) ‘Does the Sociological Approach to Studying Social Mobility Have a Future?’, in Morgan, S., Grusky, D. and Fields, G., Mobility and Inequality, Stanford University Press. Jarvis, S. and Jenkins, S.P. (1997) ‘Low income dynamics in 1990s Britain’, Fiscal Studies, 18: 1-20. Jonsson, J., Grusky, D., Di Carlo, D., Pollak, R. and Brinton. M (2009) ‘Micoclass Mobility: Social Reproduction in Four Countries’, American Journal of Sociology, 114: 977-1036. Lambert, P.S., Bihagen, E. (2007) “Concepts and Measures: Empirical evidence on the interpretation of ESeC and other occupation-based social classifications”, International Sociological Association Conference, Research Committee 28 Social Stratification and Mobility, Montreal. Rose, D. and Harrison, E. (2010) (eds) Social Class in Europe: An Introduction to the European Socio-economic Classification, Routledge. Rose, D. and Pevalin, D. (2003) A Researcher’s Guide to the National Statistics Socio-economic Classification, Sage. Weeden, K. and Grusky, D. (2005) ‘The Case for a New Class Map’, American Journal of Sociology, 111:141-212.