Title: Michelle vonAhn, Ruth Lupton and Dick Wiggins
1Population, language, ethnicity and
socio-economic aspects of education
- Michelle vonAhn, Ruth Lupton and Dick Wiggins
2Aims 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
3A big issue in London
4Updating Multilingual Capital
Published in 2000, using pupil data from 1999 to
identify and map languages in London
5Pupil data
But data collection variability makes comparison
difficult
6Language data ambiguity
7Ambiguous language
8Data inconsistency
- Some languages have variants, which are not
consistently used within a local authority or
across London, e.g.
9Language classification
10Geography
- 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
11LSOA map
12MSOA map
13English and Believed to be English
14English and Believed to be English
15Choosing a scale
16Equal counts
- Aims for equal numbers of MSOAs in each category
- Hides extreme values
17Equal ranges
- Aims to divide the whole range into equal
segments - Extreme values dominate
18Natural break
- Elegantly captures both intensity and
distribution - Complex mathematics not made explicit by MapInfo,
and therefore difficult to explain to non-expert
viewers
19Quantiles (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
20Patterns of clustering and dispersal
21South Asian languages
22Bengali/Sylheti, 1999
23Bengali
London 46,681
24Hindi/Urdu, 1999
25Urdu
London 29,354
26Panjabi
London 20,998
London 20,998
27Gujarati
London 19,572
28Tamil
London 16,386
29Persian/Farsi
London 6,959
30Chinese
London 5,905
31Migration patterns over time
- Annual data could show change (if data is
collected in a robust way) - Established or magnet communities
- Recent arrivals
32Turkish, 1999
33Turkish
London 16,778
34Greek
London 3,336
35Polish
London 11,035
36Lithuanian
London 2,974
37Somali
London 27,126
38Somali numbers have increased, but their
distribution has also become more dispersed
39Language 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
40French by ethnic group
London 13,020
41French has an east-west distribution by ethnic
group
smaller numbers
42Spanish by ethnic group
London 8,647
43White Spanish speakers are more likely to be from
Europe, while Other Spanish are probably from
Central and Latin America
44Language, 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?
45Average points at Key Stage 2 by Ethnic Group
(London 2008)
46Linguistic Breakdown for Selected Lower Attaining
Groups
Bangladeshi
Black other
47Linguistic Breakdown for Selected Lower Attaining
Groups
Black African
White other
48Diversity in the Black African group
49Yoruba
London 13,961
50Igbo
London 2,837
51Akan/Twi/Fante
London 8,117
52Diversity in the white other group
53Next 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?
54Data matching
Attainment and language data
Council Tax
GP register of patients
GP register of patients
LLPG addresses
Housing benefit
Electoral Register
PLASC (FSM)
55Consultation
- 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_at_newham.gov.uk
- Tel 020 3373 1659
- Ruth Lupton
- Email r.lupton_at_lse.ac.uk
- Tel 0207 849 4910