Socio-economic

Geodemographics and surnames

Lots of potential for analysis here though I am not entirely convinced of the validity of this approach on the microscale.

Geodemographic schemes use census and private data to create a profile of a neighbourhood. These profiles serve as a likely indication of the area’s relative affluence, and the possible life-style of its inhabitants. A classification scheme is used to assign profiles into a hierarchical order. Two well-known geodemographic products are Acorn and Mosaic:

Acorn – A Classification  of  Residential Neighbourhoods				Mosaic – (used by the credit agency, Experian)
UK 2001 Classification (Main classes)		est % Uk Pop		Main classes	52 sub-groups
Wealthy achievers	Wealthy executives Affluent greys Flourishing families	8.6 7.7 8.8		High income familes Suburban semis	Professionals and wealthy people living in very affluent suburbs includes satellite villages as well as suburbs
Urban prosperity	Prosperous Professionals Educated Urbanites Aspiring singles	2.2 4.6 3.9		Blue Collar Low rise council Council flats	Least expensive owner-occupied housing; includes junior white-collar Local authority or housing association tenants includes municipal overspill estates
Comfortably Off	Starting out Secure families Settled suburbia Prudent pensioners	2.5 15.5 6.0 2.6		Victorian low status Town houses/flats Stylish singles	Wide mix of lifestyles for mainly young families and childless elderly Lower and middle income- typically junior admin grades Typically inner-city; well-educated occupants
Moderate Means	Asian communities Post Industrial families Blue collar roots	1.6 4.8 8.0		Independent elders Mortgaged families	Owner-occupiers or sheltered accommodation: low incomes Typically newly-built private housing; young families on town peripheries
Hard Pressed	Struggling families Burdened singles High rise hardship Inner-city adversity	14.1 4.5 1.6 2.1		Country dwellers Institutional areas	Outside the commuter belt; wide range of lifestyles & affluence A catch-all category for militayr housing, boarding schools, hospitals etc
Unclassified		0.3		Mosaic has recently been revised e.g. to accommodate changing affluence/lifestyles e.g. in the Asian community
Census variables: {Age, sex, socioeconomic status, Occupation, tenure}				Census variables: {Age, marital status, recent movers, household composition & size, employment type, travel to work, unemployment, car ownership, housing tenure, amenities, housing type, socioeconomic status} Non-census variables: {County Court Judgements, Credit activity, Electoral Roll, Postcode Address File, Directors, Retail accessibility. c 350 variables (census and non-census) in all
source used for table %				Photographs [link no longer available] that illustrate areas deemed to be typical in Mosaic.
				On average there are 3.1 different household level Mosaic types in a postcode : Only 22% postcodes consist entirely of 1 Mosaic type at household level : A maximum of 18 different types in a postcode (Source: Richard Webber)
More detailed classification for both schemes on their websites Useful source; Presentations to the MRS Census and Geodemographics Group

Of the two, Acorn is the more usable to the surname analyst, as the profile assigned to a unit postcode is readily available.

A One-namer could obviously tabulate the current overall socio-economic status of their name. Although a minimum number of name-holders would be needed (100+?). If a name is still predominantly located within a specific region, such an analysis would divulge what percentage are rural/urban; associated with town centres, suburbs etc.

• Ideally, the results should be plotted on a map – with an icon/ different coloured spot for each occurrence.
  (Genmap has this facility, though one needs to convert postcodes into grid refs)
• Is there a correlation beween the distribution and the neighbourhood type?

This is such a new area, that I am wary that there must be pitfalls in applying a scheme to find the socio-economic value of a surname. And would such a profile have any validity?

• Schemes such as Acorn and Mosaic are built around census data. In the inter-census period, an influx of new residents with education levels, employment and ages that differed from established residents, may cause a mismatch.
• Classification schemes are one-dimensional. A unit postcode could actually encompass several lifestyles. A postcode may be split 55% : 45% between classes, and yet will be assigned to the former. Or it may be wrongly assigned. For example the postcode of my large employer (the only building in the road) is designated as low-income tenants, rather than institutional . Almost right- the flats are 2 streets away. (Incidentally, each census output area encompasses between 5 to 10 postcodes).
• Though new schemes are being developed with fuzzy classifications, and a resulting contour-line representation.

Perhaps of more significance would be to define a group of names, and to perform the same profiling. This has been done for the names traditionally associated with one small region (i.e. ‘local’ surnames). The analysis (of this unpublished academic study) found that ‘local’ names were more associated with lower status profiles. and neighbourhoods.
To see what can be achieved in this area of name pattern analysis using geodemographics, then read Richard Webber’s Neighbourhood segregation and social mobility among the descendants of Middlesbrough’s 19th century immigrants (CASA Working Paper- 88)

Note:

• Although unstated, this approach does rely upon the correct classification of a name (and that is contentious in itself), and the classification scheme seems to be based upon an analysis of modern-day forms and distribution, and not a historical approach. Although on the large-scale of this study, an occasional mis-classification is not significant.
• The MAUP could also be a distorting factor i.e. when surname figures are being compared between different spatial areas in different periods.

This type of approach needs to be repeated for other parts of the country. The following are possible areas for socio-economic surname studies:

Above-average concentrations of financially privileged and socially excluded, in close proximity:-	Camden, Haringey, Westminster Aberdeen, Edinburgh, Stirling
High proportions of elderly people living in council accommodation	Nottingham, Barking, Dagenham
Eclectic ethnic mixes (London postcodes)	London -E7, E12, EC1N,W2,W3,W1BN17, London-N15,SE15,SE8,SW9,SW5,SW7,SW8, UB1

Source: J. of targeting, measurement and analysis for marketing (2001) vol 10, 1 p64.

Portsmouth would be an interesting case-study. It is unique in the UK as being an island city, with a strong-sense of place, and a clannishness associated with long-established families. See Phil’s Portsmouth study [link no longer available].