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Michelle vonAhn, Ruth Lupton and Dick Wiggins
Population, language, ethnicity and socio-economic aspects of education
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Aims of the fellowshipAnalyse and map distribution of language across
LondonWhat 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
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A big issue in London
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Updating Multilingual CapitalPublished in 2000, using pupil data from 1999 to identify and map languages in London
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Pupil data 1999 2008
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
Geography Boroughs mainly, some postcodes
Boroughs and MSOAs
Missing data Bromley and Havering did not collect data – synthetic data used
Variable data collection between schools and local authorities
But data collection variability makes comparison difficult…
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Language data ambiguityCategories include: % of London total
Missing data 0.6%
Not obtained 0.4%
Classification pending 0.3%
Refused 0.1%
Other language 0.4%
Other than English 4.5%
Believed to be other than English 1.3%
Believed to be English 0.8%
Total ambiguous 8.4%
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Ambiguous language
Borough Total pupils % ambiguous
Westminster 16,086 27.9%
Brent 43,120 21.1%
Waltham Forest 38,500 15.6%
Haringey 35,056 14.5%
Hounslow 35,203 14.0%
Newham 50,402 12.4%
…
Havering 33,526 2.5%
Ealing 46,511 2.3%
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Data inconsistencySome languages have variants, which are not consistently used within a
local authority or across London, e.g.
Bengali Panjabi Arabic Chinese
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)
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Asian
(South)Asian (East)
Asian (W/C)
Turkish
African (North)
Africa (West)
Africa (E/C/S)
European Union
European Other
International/ Transnational Other
Bengali
Urdu
Panjabi
Gujarati
Tamil
Hindi
Malayalam
Nepali
Other
Chinese
Viet-namese
Japanese
Korean
Tagalog/Filipino
Other
Persian/ Farsi
Kurdish
Pashto/Pakhto
Other
Somali
Tigrinya
Amharic
Other
Yoruba
Akan/Twi-Fante
Igbo
Other
Lingala
Swahili/ Kiswahili
Luganda
Shona
Other
Greek
Italian
Dutch/Flemish
German
Polish
Lithuanian
Other
Albanian/Shqip
Russian
Serbian/Crotian/Bosnian
Other
Arabic
French
Portu-guese
Spanish
CaribbeanCreoles
Oceania/S/C America
Unspeci-fied
>5000pupils
Language classification
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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
LSOA MSOA
4765 in London 983 in London
About 1500 people About 7500 people
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LSOA map
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MSOA map
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English and Believed to be English
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English and Believed to be English
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Choosing a scale
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Equal counts
Aims for equal numbers of MSOAs in each category
Hides extreme values
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Equal ranges
Aims to divide the whole range into equal segments
Extreme values dominate
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Natural break
Elegantly captures both intensity and distribution
Complex mathematics not made explicit by MapInfo, and therefore difficult to explain to non-expert viewers
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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
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Patterns of clustering and dispersal
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South Asian languages
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Bengali/Sylheti, 1999
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Bengali
London = 46,681
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Hindi/Urdu, 1999
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Urdu
London = 29,354
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Panjabi
London = 20,998London = 20,998
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Gujarati
London = 19,572
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Tamil
London = 16,386
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Persian/Farsi
London = 6,959
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Chinese
London = 5,905
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Migration patterns over timeAnnual data could show change (if data is collected in a
robust way)Established or magnet communitiesRecent arrivals
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Turkish, 1999
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Turkish
London = 16,778
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Greek
London = 3,336
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Polish
London = 11,035
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Lithuanian
London = 2,974
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Somali
London = 27,126
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Somali numbers have increased, but their distribution has also become more dispersed
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Language is not always enoughFrench speakers
17% White57% Black26% Other
Arabic speakers57% Other15% Black10% Mixed9% White8% Asian
Spanish speakers
35% White4% Black61% Other
Portuguese speakers54% White19% Black27% Other
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French by ethnic group
London = 13,020
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French has an east-west distribution by ethnic group
smaller numbers
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Spanish by ethnic group
London = 8,647
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White Spanish speakers are more likely to be from Europe, while Other Spanish are probably from Central and Latin America
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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?
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Average points at Key Stage 2 by Ethnic Group (London 2008)
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Linguistic Breakdown for Selected Lower Attaining Groups
Language N % of total
Bengali 3725 92%
Other than English 205 5%
Believed to be English 69 2%
Others ( 10 or less each) 47 1%
Bangladeshi
Language N % of totalEnglish/Believed to be English 1097 66%
French 86 5%
Other than English 68 4%
Portuguese 61 4%
Yoruba 57 3%
Somali 49 3%
Arabic 37 2%
Akan 30 2%
Swahili variants 18 1%
Creoles and Pidgins 14 1%
Lingala 14 1%
Unknown 12 1%
Others (10 or less each) 118 7%
Black ‘other’
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Language N % of total
English/Believed to be English 2481 25%
Somali 2079 21%
Yoruba 1245 13%
Akan 682 7%
French 502 5%
Lingala 259 3%
Igbo 220 2%
Arabic 181 2%
Swahili variants 183 2%
Luganda 112 1%
Portuguese 131 1%
Black African
Language N % of total
English/Believed to be English 1887 26%
Turkish 1184 16%
Polish 757 11%
Albanian/Shqip 559 8%
Portuguese 505 7%
Greek 263 4%
Spanish 199 3%
Lithuanian 237 3%
French 116 2%
Italian 151 2%
Arabic 119 2%
Serbian/Croatian/Bosnian 100 1%
Russian 107 1%
White ‘other’
Linguistic Breakdown for Selected Lower Attaining Groups
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Lower attaining Higher attaining
Diversity in the ‘Black African’ group
70 75 80 85 90
Chinese
Indian
Black AfricanIgbo
White British
Black AfricanYoruba
Black AfricanEnglish
All
70 75 80 85 90
All
Black African Luganda
Bangladeshi
Pakistani
Black African Akan
Black African Arabic
Other White
Other
Black African all
Black Caribbean
Black Other
Black African Swahili variants
Black African Somali
Black African Portuguese
Black African French
Black African Lingala
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Yoruba
London = 13,961
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Igbo
London = 2,837
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Akan/Twi/Fante
London = 8,117
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Higher attaining
Diversity in the ‘white other’ group Lower attaining
70 75 80 85 90
White Other French
Chinese
White Other Italian
White Other Serbian Croatian Bosnian
White Other Greek
White Other English
Indian
White Other Spanish
White British
All
70 75 80 85 90
All
White Other Arabic
White Other Russian
Bangladeshi
Pakistani
White Other Albanian
White Other Arabic
Other White
Other
White Other Lithuanian
White Other Portuguese
White Other Turkish
White Other Polish
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Next stagesHow are ethnicity/language categories related to socio-
economic status?Explore FSM, IDACI, using London ASCMatching 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?
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Data matching
GP register of patients
GP register of patients
Council Tax
Housing benefit
Electoral RegisterPLASC
(FSM)
LLPG addresses
Attainment and
language data
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ConsultationLocal 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
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Michelle vonAhnEmail: [email protected]: 020 3373 1659
Ruth LuptonEmail: [email protected]: 0207 849 4910