1.Age, gender, and… ethnicity? How to segment populations by a slippery dimension in European multicultural geographies.
Centre for Advanced Spatial Analysis (CASA)
Department of Geography
University College London
p.mateos@ucl.ac.uk
Pablo Mateos
Richard Webber
Int’l Population Geographies Conference
Liverpool
19-21 June 2006
3.Age
The demographic triad
Gender
Ethnicity / Race
Core constituents of a person
(conceived as unmutable over lifecourse)
A model of the main determinants of health (Whitehead, 1995)
4.The demographic triad
Gender & Ethnicity accompany Age in demographic research
5.1 – Defining ethnicity
1 – Defining ethnicity
6.What are human races, and how did they develop? Anthropologists have long argued that race lacks biological reality. But our genetic makeup does vary with geographic origin and as such raises political and ethical as well as scientific questions.
“125 big questions that face scientific inquiry over the next quarter-century”
Ethnicity & Race
1 – Defining ethnicity
7.Biological determinisim
Geography of Races (Mitchell, 1868)
An Eurocentric White man view of the world
1 – Defining ethnicity
8.Modern concepts of Race & Ethnicity
Consensus in that both concepts are socially constructed
The word ‘ethnicity’ derives from the Greek word ethnos, meaning a nation. Thus, the basis of nationalism.
Max Weber (1922)
Race group: A group perceived as having common inherited and inheritable traits that derive from common descent
Ethnic groups: Those human groups that entertain a subjective belief in their common descent because of similarities of physical type or of customs or both, or because of memories of colonization and migration (...)
A firm belief in group’s affinity is required for ethnic groups to be defined in opposition to other groups differently perceived and with whom contact is required (Eriksen, 2002)
The characteristics that define ethnicity are not fixed or easily measured, so ethnicity is imprecise and fluid (Senior & Bhopal, 1994)
1 – Defining ethnicity
9.2 – Measuring ethnicity
2 – Measuring ethnicity
10.Different terms, different ethnicities
219 terms for 8 ‘Ethnic Groups’ in 1,198 articles published in 2 American epidemiology journals 1996-99
(Comstock et al, 2004)
Hispanic black
Latino born
Caribbean Hispanic
Non-White Hispanic
Anglo American Caucasian
European
White/Anglo
Non-Hispanic White
2 – Measuring ethnicity
11.UK 2001 Census Ethnicity Classification
16 Categories
Strongly based on a “skin colour problem”
Confusing question
Source: ONS Census 2001
12.London ‘non-16+ ethnic groups’
Source: 2001 Census GLA commissioned tables
(.../...)
(1.2 million people stated ‘other’ ethnic identities in London 2001 Census)
2 – Measuring ethnicity
13.Sources of Ethnicity data
Current information sources available (UK):
Census of Population (decennial, aggregated)
Official Surveys (few ethnic minorities represented)
Hospital Admissions (low quality)
Problems of collecting ethnicity data:
Sensitive data – low accuracy, low coverage
Changing categorizations
Changing identities
Not always self-assessed (e.g. hospital, deaths)
Tries to measure too many things into one variable
Result in a poor understanding of ethnicity
2 – Measuring ethnicity
14.Muldimensionality of ethnicity
Kinship
Religion
Language
Culture
Shared territory
Nationality
Physical appearance
Ethnicity: A multi-dimensional concept that encompasses different aspects of identity:
Easily inferred from lifecourse Geography
(eg. birthplace)
More difficult to infer from Geography
Surname & Forename Analysis
Enhanced inference of Ethnic group
Ideally each of them to be separately measured
2 – Measuring ethnicity
15.3– Name origin analysis
3- Name origin analysis
16.Names origins & Ethnicity
Identity, though complex, can be encoded in a name (Seeman, 1980)
Names can potentially provide information about:
Used since the 1950s in epidemiological and genetics studies to subdivide populations (Word & Perkins, 1996; Lasker, 1985)
Hispanics, South Asians, Chinese, Muslim Names
3- Name origin analysis
17.Name analysis in genetic research
Surnames generally adopted in the Middle Ages (Europe)
Surnames in genetic studies dates back to 1875; George Darwin (son of Charles Darwin) used surname frequency to study population inbreeding
Today surnames are used to study ancient patrilineal population structures (Manni et al 2005)
Assumptions:
Low intermarriage
Low infidelity
Common origin (monophyletic)
Low name change rate
3- Name origin analysis
18.Cultural Ethnic Linguistic (CEL) classification
250,000 Family Names and 120,000 Personal Names coded by CEL Type
+150 CEL Types aggregated into 15 CEL Groups
3- Name origin analysis
19.World map of CEL types
150 CEL Types
20.Main methods used to classify names
‘Correspondence analysis’ between personal and family names
Census and Geodemographic area data
Geographical distribution & clustering
Text mining
Birthplaces & names
Lists of names by country
‘Googling’ individual names
3- Name origin analysis
21.Issues with Names Analysis
Only reflects patrilineal heritage
Different history of surname adoption, naming conventions & surname change
Name normalisation is required
Family/Household Autocorrelation
Limited names lists, due to temporal & regional differences in name distribution
Lack of consistency in self-conceived identity
(Senior & Bhopal, 1994; Martineau 1998, Word & Perkins, 1996; Jobling 2001)
3- Name origin analysis
22.2004 Electors with ‘Welsh’ surnames
(Webber, 2005)
3- Name origin analysis
23.‘Cornish’ names & Anglosaxon diaspora
(Webber, 2005)
Concentration index
3- Name origin analysis
24.Greek & Greek Cypriot names in London
3- Name origin analysis
25.Turkish names in Greater London
3- Name origin analysis
27.Applications of the CEL classification
UCL analysis
Determining local associations of ethnic inequalities in health Camden PCT (London)
Classifying the UK 1881 Census, UK 2004 electoral roll, and 2004 Spanish Telephone directory.
Measuring ethnic residential segregation in London
Other users in the public sector:
4- Applications & Evaluation
28.Census Vs CEL Black African ethnicity in Camden
4- Applications & Evaluation
29.Census ‘Black African’ by Output Area (OA)
Average Population per OA: 285
4- Applications & Evaluation
30.CEL ‘Black African’ by Postcode
Avg. Population per Postcode: 54
4- Applications & Evaluation
31.CEL ‘Somali’ by Postcode
Avg. Population per Postcode: 54
4- Applications & Evaluation
32.CEL Clusters in London by LSOA
Greek & G. Cypriot
Eastern Europe
Hispanic
Hindu
Sikh
Other Muslim
Somali
Local Indicators of Spatial Association (LISA) (Anselin, 1995) using GeoDA
34.Ethnicity & Migration in Spain
Poland
China
Germany & Austria
Britain & Ireland
4- Applications & Evaluation
Name origins in the telephone directory
35.Correlations CEL vs Census (London)
4- Applications & Evaluation
36.Evaluation at the individual level
Evaluation of the CEL classification through self-reported ethnicity from Hospital Episode Statistics
40,714 patients (20% of total) matched to a unique true ethnic code (1991 Census categories)
Problem of bad quality HES data
4- Applications & Evaluation
37.5 – Conclusions
5- Conclusions
38.Conclusions: Review of CEL methodology
Advantages
Finer spatial, temporal, and nominal scales
Can be applied to Population & Patient Registers, Telephone Directories, etc.
Reveals segregation of very detailed groups in London, such us Sikh, Jewish, Greek, Japanese, or Somali
Challenges
Improvements to some categories in the name classification
CEL overlap for some names
Different CEL allocation for a name in different countries
Mixed ethnicities, name change, etc
5- Conclusions
39.Thank you!Any Questions?
www.casa.ucl.ac.uk/pablo
p.mateos@ucl.ac.uk
The End