Mateos - Age, gender, and… ethnicity, How to segment populations by
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- 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
- 2.Contents Defining ethnicity Measuring ethnicity Name origin analysis Applications & evaluation Conclusions
- 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
- 26.4 – Applications & Evaluation 4- Applications & Evaluation
- 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
- 33.Distribution of Non-British Surnames 1881-1998 1998 1881 4- Applications & Evaluation www.spatial-literacy.org
- 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
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