Michelle vonAhn, Ruth Lupton and Dick Wiggins

1. Population, language, ethnicity and socio-economic aspects of education Michelle vonAhn, Ruth Lupton and Dick Wiggins

2. Aims of the fellowship Analyse and map distribution of language across London What issues does this raise? Conduct some preliminary analysis between language and attainment Analyse the relationship between language, ethnicity and socio-economic indicators Provide guidance and training on the ways language data may be used with other data to answer social and educational research questions

3. A big issue in London

4. Updating Multilingual Capital Published in 2000, using pupil data from 1999 to identify and map languages in London

5. Pupil data But data collection variability makes comparison difficult…

6. Language data ambiguity

7. Ambiguous language

8. Data inconsistency Some languages have variants, which are not consistently used within a local authority or across London, e.g.

9. Language classification

10. Geography • Percentage comparisons are problematic due to data capture variability • Comparative counts of boroughs not suitable due to differences in size • Wards and postcodes also differ in population size • New statistical geographies - Super Output Areas

11. LSOA map

12. MSOA map

13. English and Believed to be English

14. English and Believed to be English

15. Choosing a scale

16. Equal counts • Aims for equal numbers of MSOAs in each category • Hides extreme values

17. Equal ranges • Aims to divide the whole range into equal segments • Extreme values dominate

18. Natural break • Elegantly captures both intensity and distribution • Complex mathematics not made explicit by MapInfo, and therefore difficult to explain to non-expert viewers

19. Quantiles (or in this case, Quintiles!) • Takes total count of pupils and creates target totals for each category – so each category has about 20% of all pupils • A compromise that captures intensity and distribution, relatively easy to explain

20. Patterns of clustering and dispersal

21. South Asian languages

22. Bengali/Sylheti, 1999

23. Bengali London = 46,681

24. Hindi/Urdu, 1999

25. Urdu London = 29,354

26. Panjabi London = 20,998 London = 20,998

27. Gujarati London = 19,572

28. Tamil London = 16,386

29. Persian/Farsi London = 6,959

30. Chinese London = 5,905

31. Migration patterns over time Annual data could show change (if data is collected in a robust way) Established or magnet communities Recent arrivals

32. Turkish, 1999

33. Turkish London = 16,778

34. Greek London = 3,336

35. Polish London = 11,035

36. Lithuanian London = 2,974

37. Somali London = 27,126

38. Somali numbers have increased, but their distribution has also become more dispersed

39. Language is not always enough French speakers 17% White 57% Black 26% Other Arabic speakers 57% Other 15% Black 10% Mixed 9% White 8% Asian • Spanish speakers • 35% White • 4% Black • 61% Other • Portuguese speakers • 54% White • 19% Black • 27% Other

40. French by ethnic group London = 13,020

41. French has an east-west distribution by ethnic group smaller numbers

42. Spanish by ethnic group London = 8,647

43. White Spanish speakers are more likely to be from Europe, while Other Spanish are probably from Central and Latin America

44. Language, ethnicity and attainment How are ethnicity and language related? Can we create useful ethnicity/language categories? How is language related to attainment? Does ethnicity/ language tell us more than ethnicity on its own?

45. Average points at Key Stage 2 by Ethnic Group (London 2008)

46. Linguistic Breakdown for Selected Lower Attaining Groups Bangladeshi Black ‘other’

47. Linguistic Breakdown for Selected Lower Attaining Groups Black African White ‘other’

48. Diversity in the ‘Black African’ group • Higher attaining Lower attaining

49. Yoruba London = 13,961

50. Igbo London = 2,837