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

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 19992008 Pupils>850,000, attending state schools in London >1,100,000, resident in London, attending a state school Languages>350, including dialects and variants 322 categories collected, 239 without variants GeographyBoroughs mainly, some postcodes Boroughs and MSOAs Missing dataBromley and Havering did not collect data – synthetic data used Variable data collection between schools and local authorities But data collection variability makes comparison difficult…

6. Language data ambiguity Categories include:% of London total Missing data0.6% Not obtained0.4% Classification pending0.3% Refused0.1% Other language0.4% Other than English4.5% Believed to be other than English1.3% Believed to be English0.8% Total ambiguous8.4%

7. Ambiguous language BoroughTotal pupils% ambiguous Westminster16,08627.9% Brent43,12021.1% Waltham Forest38,50015.6% Haringey35,05614.5% Hounslow35,20314.0% Newham50,40212.4% … Havering33,5262.5% Ealing46,5112.3%

8. Data inconsistency Some languages have variants, which are not consistently used within a local authority or across London, e.g. BengaliPanjabiArabicChinese Bengali (Any other)Panjabi (Any other)Arabic (Any other)Chinese (Any other) Bengali (Sylheti)Panjabi (Gurmukhi)Arabic (Algeria)Chinese (Cantonese) Bengali (Chittagong/Noakhali)Panjabi (Mirpuri)Arabic (Iraq)Chinese (Hokkien/Fujianese) Panjabi (Pothwari)Arabic (Morocco)Chinese (Hakka) Arabic (Sudan)Chinese (Mandarin/Putonghua) Arabic (Yemen)

9. >5000 pupils 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 LSOAMSOA 4765 in London983 in London About 1500 peopleAbout 7500 people

11. LSOA map

12. MSOA map

13. 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

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 LanguageN% of total Bengali372592% Other than English2055% Believed to be English692% Others ( 10 or less each)471% Bangladeshi LanguageN% of total English/ Believed to be English109766% French865% Other than English684% Portuguese614% Yoruba573% Somali493% Arabic372% Akan302% Swahili variants181% Creoles and Pidgins141% Lingala141% Unknown121% Others (10 or less each)1187% Black ‘other’

47. LanguageN% of total English/ Believed to be English248125% Somali207921% Yoruba124513% Akan6827% French5025% Lingala2593% Igbo2202% Arabic1812% Swahili variants1832% Luganda1121% Portuguese1311% Black African LanguageN% of total English/ Believed to be English188726% Turkish118416% Polish75711% Albanian/Shqip5598% Portuguese5057% Greek2634% Spanish1993% Lithuanian2373% French1162% Italian1512% Arabic1192% Serbian/Croatian/Bosnian1001% Russian1071% White ‘other’ Linguistic Breakdown for Selected Lower Attaining Groups

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

49. Yoruba London = 13,961

50. Igbo London = 2,837

51. Akan/Twi/Fante London = 8,117

52. Higher attaining Diversity in the ‘white other’ group Lower attaining

53. Next stages How are ethnicity/language categories related to socio- economic status? Explore FSM, IDACI, using London ASC Matching to local authority data (e.g. housing benefits, Council tax band), for a case study borough (Newham) How is the attainment of ethno-linguistic groups related to indicators of socio-economic status?

54. Data matching GP register of patients Council Tax Housing benefit Electoral Register PLASC (FSM) LLPG addresses Attainment and language data

55. Consultation Local authority views of the practical, legal, technical and ethical issues for data matching within and across authorities Identifying practical uses of matched data Goal: to prepare guidance for other data users

56. Michelle vonAhn Email: michelle.von.ahn@newham.gov.ukmichelle.von.ahn@newham.gov.uk Tel: 020 3373 1659 Ruth Lupton Email: r.lupton@lse.ac.ukr.lupton@lse.ac.uk Tel: 0207 849 4910