Professor Vernon Gayle, University of Stirling, Scotland

1. Social Stratification and Attitudes to Education in Contemporary Britain:A Multivariate Analysis of the British Youth Panel Professor Vernon Gayle, University of Stirling, Scotland Dr Damon Berridge, Lancaster University, England Dr David Stott, Lancaster University, England

2. In the UK Striking and persistent relationship between children’s socio-economic backgrounds (measured by parents occupations) and educational outcomes (especially school level qualifications) This association is robust and net of other factors Stronger association than gender and ethnicity Association persists whichever socio-economic classification is modelled

3. There is a line of argument that suggests that these observed differences in educational attainment are, in part, due to young people from different social backgrounds having different aspirations and attitudes to education Since the mid 1980s there has been an political assault on schools and teachers to improve standards (mainly examination results and qualifications) Particular focus on the ‘poor’, under-privaledged’, ‘socially excluded’ or whatever terminology is currently popular…

4. Old Sociology of Education Some studies that I was taught about when I was an undergraduate (1987-1990) Willis, P. (1977) Learning to Labour: How working class kids get working class jobs Ethnographic study in West Midlands Corrigan, P. (1979) Schooling the Smash Street Kids Study of working class boys in Sunderland Lacey, C. (1970) Hightown Grammar – The school as a social system Study of a northern grammar school. A study of the ‘disappointing performance of working class boys in grammar schools since the 1944 Education Act’ (p.xi) Rutter, M. et al. (1979) Fifteen Thousand Hours – Secondary schools and their effects on children 15,000 hours the average time spent at school, a study of 12 inner London schools 2,000 pupils tracked though secondary school Douglas, J.W.B. (1964) The Home and the School: A study of ability and attainment in the primary school Douglas, J.W.B. (1970) All our futures Studies of the 1946 birth cohort A study that I have recently read Wedge, P. and Prosser, H. (1973) Born to Fail? Children’s Bureau report on the striking differences in the lives of British children A more recent example Devine, F. (2004) Class Practices – How parents help their children get good jobs A qualitative study of middle class parents in Britain and America

5. The is a popular line of argument that suggests that these observed differences in educational attainment are, in part, due to young people from different social backgrounds having different aspirations and attitudes to education This has an initial ring of plausibility… However, John Goldthorpe is a Fellow of the British Academy, I am not… Is that down to my low aspirations?

6. Educational policy in the UK is in a state of flux (the Departmental website clearly states that the views expressed might not be those of the Government) (Pre May 2010) Government priority breaking the association between social background and educational attainment New Government hint that changing aspirations and attitudes might be key to better educational attainment New Conservative Coalition Government recently appointed a ‘Social Mobility Tsar’, former Labour Government Minister Alan Milburn who is a ‘working class boy made good’

7. This is our first attempt to try to explore some contemporary attitudinal data… BEWARE VERY EARLY STAGES OF WORK IN PROGRESS [Models take an eternity to fit] [and yes of course we would have liked to fit models with age squared and Camsis etc etc.] [Double negative – sorry I cannot promise not to do this]

8. British Household Panel Survey • Major household longitudinal survey • Began in 1991 • Based on an annual interview • Approximately 5,000 household and 10,000 adults • Similar in design to the German Socio-Economic Panel • Has been subsumed and greatly extended – is now a component of the Understanding Society the UK Household Longitudinal Study (40K households)

9. British Household Panel Survey • British Youth Panel is a component of the BHPS • Special questionnaire • Annual interview with young people in the household aged 11-15 • At age 16 they enter the adult survey

10. Structure of the British Youth Panel (BYP)(Rotating Panel)

11. Structure of the British Youth Panel (BYP)(Rotating Panel)

12. BYP Sample Size by AgeWave L (2002) to Q (2007) (Essex Originals)

13. Present analyses are restricted to young people in (original) BHPS household in England • This is because these household have not been over-sampled • The young people are in they same education system and aiming/studying for the same qualifications Observations = 4,424 from n = 1,564 individuals

14. BYP Sample Size by Number of WavesWave L (2002) to Q (2007) (Essex Originals)

16. The next few questions are about how you feel about different aspects of your life. The faces express various types of feelings. Below each face is a number where ‘1’ is completely happy and ‘7’ is not at all happy. Please tick the box that comes closest to expressing how you feel about each of the following things.

18. Descriptive Statistics Outcomes 1. Important to get GCSE exams 2. How do you feel about your school 3. How much it means to do well at school 4. I like most of my teachers 5. Teachers are always getting at me 6. How do you feel about school work

19. How important do you think it is for you to get you GCSE exams?

20. The school you go to Please tick the box that comes closest to expressing how you feel about each of the following things BHPS coding scheme

21. How much does it mean to you to do well at school?

22. I like most of my teachers

23. Teachers are always getting at me

24. Your school work Please tick the box that comes closest to expressing how you feel about each of the following things BHPS coding scheme

33. Xttab one-way tabulation and decomposes counts into between and within components in panel dataMeasure of the overall stability – percentages are a normalised between weighted average of the within percentages Important to get GCSE exams 62% How do you feel about your school 33% (3 categories) 56% How much it means to do well at school 53% I like most of my teachers 43% Teachers are always getting at me 44% How do you feel about school work 36% (3 categories) 58%

34. Explanatory Variables Explanatory variables implicated in the sociology of education and youth literature (and available in the data set) • Wave (2002 – 2007) • Age (11 – 16 years) • Gender (males; females) • Family Registrar Generals Social Class [RGSC] (I professional; II managerial & technical; IIIn skilled non-manual; IIIm skilled manual; iv partly skilled; v unskilled) • semi-dominance approach father or mother • Highest Qualification (parents) (higher qualifications [e.g. graduates]; A’ levels; O’level and equivalents; no qualifications) • Parents in a different household (no; yes) • Lone Parent Household [mother] (in addition mother is a lone parent) • Housing tenure [mother] (own/mortgage; local authority rented; housing association rented; other rented)

35. Summary of associations Age – decrease in school happiness; teacher likeability decreases; teacher get a pupils more; happiness with school work declines; Gender (females) – means more to do well; like teachers; don’t feel teachers are getting at them; happier with school work; RGSC (lower groups) smaller proportions think GCSE important; unhappier with school; means less to do well at school; agreement that teacher get at me; less happy with school work; Hi Qual (less) similar to RGSC

36. Statistical Modelling Methodology • Ordered categorical data (proportional odds) • (Univariate) Ordinal random effects models • Possible in gllamm or MLwiN • Could be fitted as a mixed model (e.g in gllamm) • Less satisfactory as responses may not have the same number of ordered categories • Or levels of the categories may have different substantive meanings

37. Statistical Modelling Methodology • New software for bivariate (two outcome) ordered categorical data • Natural extension of the bivariate probit (probit probit)to handle ordinal responses • Estimates two models simultaneously – therefore the model provides two sets of parameter estimates (a mixed approach would only provide a single set) • This is particularly attractive as an effect may vary across outcomes

38. Statistical Modelling Methodology • New software for bivariate (two outcome) ordered categorical data • Correlated responses better controlled for with a parameter estimating the correlation between the two random effects

39. Random Effect Models Not significant - Significant Ö

40. Bivariate Random Effect Models Associations Between Outcome Variables

41. Bivariate Random Effects Model We observe correlations between these outcomes Methodological motivation is to model them simultaneously in a random effects framework • Models estimated using quadrature are extremely slow

42. Bivariate Random Effects Model Joint model of two correlated outcomes ‘feel about your school’ and ‘teachers are always getting at me (Gamma=-.46) Regrettably the initial results are not particularly impressive!

46. Substantive Conclusions • Less switching of attitudes than we anticipated • Overall Satisfaction with the school experience + Importance of GCSEs + Happy with school + Doing well means a lot + Mostly teacher are liked • Over a ¼ agree teachers are get at them + Happy with school work

47. Substantive Conclusions Limited evidence… • Ageing effect, as pupil moves through school – become more less satisfied • Gender – females are more pro-school • Family socio-economic effect for GCSE importance • Family education effect for doing well

48. Moving towards an evaluation of The is a popular line of argument that suggests that these observed differences in educational attainment are, in part, due to young people from different social backgrounds having different aspirations and attitudes to education Quite a long way to go… More sociological thought about the potential relationships between attitudes and education

49. Next Steps • Yesterday estimates for measures of bullying and truancy emerged • Start to model data on educational outcomes • Incorporate ‘parental’ attitudinal data on education • Think more about the precise interpretation of models

50. Next Steps • Think more about this approach • Improve the specification of model (especially alternative measures) • Try to speed up model estimation • Longer term aim – compare and contrast this type of approach with ‘latent class’ style analyses