Information, Communication & Society CLASS ...

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CLASS PLACES AND PLACE CLASSES Geodemographics and the spatialization of class a

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Simon Parker , Emma Uprichard & Roger Burrows

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Department of Politics , University of York , Heslington, York, YO10 5DD, UK E-mail: b

Department of Sociology , University of York , Heslington, York, YO10 5DD, UK E-mail: c

Department of Sociology , University of York , Heslington, York, YO10 5DD, UK E-mail: Published online: 20 Dec 2007.

To cite this article: Simon Parker , Emma Uprichard & Roger Burrows (2007) CLASS PLACES AND PLACE CLASSES Geodemographics and the spatialization of class, Information, Communication & Society, 10:6, 902-921, DOI: 10.1080/13691180701751122 To link to this article: http://dx.doi.org/10.1080/13691180701751122

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Simon Parker, Emma Uprichard & Roger Burrows CLASS PLACES AND PLACE CLASSES Geodemographics and the spatialization


of class

This paper argues that the ‘spatial turn’ in the sociology of class – the clustering of people with a similar habitus into what we might think of as ‘class places’ – is connected in a number of important ways with the ongoing informatization of place, particularly as manifest in the urban informatics technology of geodemographics. This is a technology concerned with the development of the classification of places to commercial and policy ends – the assigning of postcodes to a set of mutually exclusive and exhaustive categories, or ‘place classes’. What interests the authors is the manner in which there is a strong concordance between the conclusions of academic sociologists working on the spatialization of class and those of – what might be thought of as – ‘commercial sociologists’ working in the geodemographics industry. Although the conceptual argot is very different, both have in common an interest in the codification and spatial mapping of habitus, and both arrive at very similar substantive conclusions about contemporary processes of sociocultural spatial clustering. But the authors’ interest is not just in the observation that there is an analytic convergence in academic and commercial concerns with the relationship between ‘class places’ and ‘place classes’; rather, it is in their possible co-construction. They argue that geodemographic classifications are not only sociologically important phenomena but also represent an interesting example of a new form of software-mediated recursive urban ontology. Keywords Geodemographics; software sorting; neighbourhoods; social class; space

Introduction Vernacular systems of classification – the process of assigning elements to classes or categories routinely undertaken by lay people – are fundamental not just to Information, Communication & Society Vol. 10, No. 6, December 2007, pp. 902 – 921 ISSN 1369-118X print/ISSN 1468-4462 online # 2007 Taylor & Francis http://www.tandf.co.uk/journals DOI: 10.1080/13691180701751122


GEODEMOGRAPHICS AND THE SPATIALIZATION OF CLASS

cognition, language and culture, but to the sociospatial construction of reality in general. As such they have long been an important topic for sociological inquiry. At the same time more formal classificatory processes – produced via taxonomies, typologies, ideal types, clustering methodologies and so on – are at the analytic heart of much of the social scientific enterprise and, as such, they are a central resource for social scientific inquiry. This distinction between classifications as both a substantive topic of investigation and, simultaneously, an analytic resource for such investigations, creates one of the central conundrums of the social sciences. The unavoidable ‘double hermeneutic’ (Giddens 1976) relates to the inevitability that the concepts and categories drawn upon by lay actors in their everyday practices are in the end ‘explained’ by sets of concepts and categories developed by social scientists that may or (more likely) may not be recognized by lay actors themselves. Sometimes these concepts and categories are re-appropriated by lay actors into their everyday vernacular. But more often the challenge is to demonstrate how and why the more formal classifications developed by social scientists are in any sense ‘better’ than those used by lay actors to explain their social situations and actions. This tension between vernacular regimes of classification used by lay people and more formal systems of classification to which they are subject is, of course, ubiquitous. But it is not just social scientists who are keen to classify people in ways with which they might or might not concur. The classificatory techniques of academic social science are also widely utilized by the state, commerce, the criminal justice system, the health service and so on. Indeed, some would take the view that we are witnessing a fundamental step-change in both the means and the desire to classify human populations as new and ever more sophisticated classificatory systems are introduced that produce a complex technological machinery designed to create a ‘phenetic fix’ (Lyon 2002; Phillips & Curry 2002) on society. This means that the ability to understand how classification systems are formed, built, implemented and acted upon is likely to become ever more fundamental for understanding how contemporary societies work. Classifications, especially those which become ‘standards’, soon sink from social scientific view unless we remain alert to their functioning. In particular we are now surrounded – immersed even – by systems of classification, standards and protocols that we have come to term ‘software’. For Thrift and French (2002, p. 309) this means that the actual ‘stuff’ that constitutes what we have traditionally thought of as the ‘social’ has ‘changed decisively’; for them, software now increasingly functions in order to provide what they term a ‘new and complex form of automated spatiality’ which has altered the ‘world’s phenomenality’. For Bowker and Star (1999), in their exemplary programmatic call for a revitalized sociology of classification, unless we routinely inspect the social construction of the classifications that have come to dominate our social world, we will systematically miss some of the most

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important elements of the contemporary functioning of power. This is what Bourdieu (1991) terms the symbolic power of naming that inevitably emerges from the quest to classify populations, be that naming be done by the state, commerce – or even social scientists. Perhaps one of the most important tools of social classification – used by social scientists, the state and commerce (albeit it in different ways and for different reasons) – has long been that of social class. The symbolic power of naming here has, of course, been fundamental. The nomenclature of class is replete with some of the fundamental categories of social life: ‘upper’; ‘middle’; ‘working’; ‘skilled’; ‘semi-skilled’; ‘unskilled’; ‘manual’; ‘non-manual’; ‘bourgeois’; ‘petit bourgeois’; ‘proletarian’; ‘professional’; ‘service’; and so the list goes on. In recent years, however, some influential commentators have come to view it as a classificatory tool that produces nothing other than ‘zombie categories’ (Beck 2004, p. 19) – categorical distinctions devoid of any analytic utility, but which refuse to die. Others, however, have argued that it can still retain some useful analytic life but only if it fundamentally reinvents itself (Savage 2005).

The spatialization of class Savage and his colleagues have suggested that central to this prospective reinvention is the recognition that the idea that occupation and employment position continue to be the fundamental units of class analysis needs urgent reappraisal (Devine et al. 2004; Savage et al. 2005), because increasingly social stratification needs to be viewed as a fundamentally spatial process. The strongest codification of this hypothesis is the suggestion that whereas occupation used to define social class, now it is residential location that increasingly does so, and we are thus witnessing nothing less than the spatialization of class. Savage et al. (2005, p. 207) conclude that: One’s residence is a crucial, possibly the crucial identifier of who you are. The sorting processes by which people chose to live in certain places and others leave is at the heart of contemporary battles over social distinction. Rather than seeing wider social identities as arising out of the field of employment it would be more promising to examine their relationship to residential location. One might expect that this proposition – that class should be thought of as an increasingly spatialized phenomena – would derive fairly clearly from a sociological lineage that harks back to the Chicago school of urban ecology (Park et al. 1925) and then tracks through the urban sociology of Rex and Moore (1967), Pahl (1970) and others on ‘housing classes’. However, this is not so.



Much of the contemporary sociology of place is inspired by the work of Bourdieu (1984) on ‘capital’, ‘habitus’ and ‘field’ as a means of interpreting the preferences, tastes, strategies and actions of metropolitan gentrifiers of various sorts. This ‘Bourdieuian turn’ is especially evident in the work of writers such as Bridge (2006), Butler (Butler with Robson 2003) and, especially, Savage (Savage et al. 2005) – all of whom are concerned to understand the role of the ‘middle classes’ in contemporary patterns of urban change, while at the same time problematizing some of the assumptions about what it means to be ‘middle class’ in a globalized world of polyvalent identities. It is in the work of these authors that one finds the formal codification of a position that draws upon the conceptual armoury of Bourdieu in order to ‘map’ out the habitus of different social groups. It is a concern to understand how people organize themselves and are organized to form distinctive sociocultural spatial clusters that is of analytic concern. For Savage et al. (2005, p. 9) this relates to the observation that people are comfortable when there is a correspondence between habitus and field . . . otherwise people feel ill at ease and seek to move – socially and spatially – so that their discomfort is relieved . . . mobility is driven as people, with their relatively fixed habitus, both move between fields . . . and move to places within fields where they feel more comfortable. Now, this is all very interesting, but what does it have to do with the analytic concerns of this journal and, in particular, the current focus in this issue on the social science of urban informatics? Our argument is that this ‘spatial turn’ in the sociology of class – the clustering of people with a similar a habitus into what we might think of as ‘class places’ – is connected in a number of important ways with the ongoing informatization of place (Burrows & Ellison 2004), particularly as manifest in the urban informatics technology of geodemographics (Harris et al. 2005; Burrows & Gane 2006). This is a technology concerned with the development of the classification of places to commercial and policy ends – the assigning of zip- or postcodes to a set of mutually exclusive and exhaustive categories, or ‘place classes’. What interests us in particular is the manner in which there is a strong concordance between the conclusions of academic sociologists working on the spatialization of class and those of – what we might think of as – ‘commercial sociologists’ working in the geodemographics industry (Burrows & Gane 2006). Although the conceptual argot is very different, both have in common an interest in the codification and spatial mapping of habitus, and both arrive at very similar substantive conclusions about contemporary processes of sociocultural spatial clustering. However, until very recently the common findings of sociologists influenced by this ‘spatial turn’ and those of geodemographers were largely unknown to each other (Burrows & Gane 2006; Webber 2007).

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But our interest is not just in the observation that there is an analytic convergence in academic and commercial concerns with the relationship between ‘class places’ and ‘place classes’; rather, it is in their possible co-construction. In the remainder of the paper, we want to argue that geodemographic classifications are not only interesting and sociologically important phenomena, they also represent an interesting example of a new form of software-mediated recursive urban ontology (Thrift & French 2002; Backhaus & Murungi 2005). However, before we tackle this issue we need to briefly outline the objects that are of concern to us here, and provide some examples of their operation.

Geodemographic classifications In the UK, it is possible to identify a number of competing geodemographic classifications (Harris et al. 2005) including, inter alia, systems such as: Acorn; Cameo; Censation; Likewise; Locale; Mosaic; P2: People & Places; PRIZM; and SONAR. The most widely used system is the Mosaic classification owned by the global data corporation Experian, and designed by Richard Webber (Burrows & Gane 2006). The Mosaic system classifies each of the 1.7 million postcodes in the UK to one of 11 different Mosaic Groups and 61 different Mosaic Types. By way of illustration this schema is shown in Table 1, which also includes the proportion of households in the UK placed in each Mosaic Type. The Mosaic system is a classification schema which now has a global reach. There are parallel Mosaic schemas for: Australia; China (at least for Beijing, Guangzhou and Shanghai); Denmark; Finland; France; Germany; Greece; Hong Kong; Japan; the Netherlands; New Zealand; Norway; the Republic of Ireland; Spain; Sweden; and the USA. At the time of writing schemas are also in development in: Austria; Canada; the Czech Republic; Italy; and Switzerland. There is also a Global Mosaic system which maps all of these national Mosaic systems to a set of supposedly common global sociospatial classes (Burrows forthcoming). Thus, although our focus here is on the UK, what we have to say may clearly have a much wider global applicability. Given our interest in the sociology of classification and the manner in which the social sciences have so often been implicated in generating classifications, we thought it analytically beneficial to use a recent sociological attempt to classify social space as a crude template for selecting some case study neighbourhoods in order to examine the relationship between ‘ground truths’ (Pickles 1995) and the digitized ascribed categorizations of place that geodemographic classifications generate. We could have used any number of such attempts, but given that the classification offered by Lash

GEODEMOGRAPHICS AND THE SPATIALIZATION OF CLASS TABLE 1 The Mosaic Classification # Experian. group description symbols of success


happy families

suburban comfort

ties of community

urban intelligence

welfare borderline

type description

per cent

global connections

0.72

cultural leadership

0.92

corporate chieftains

1.12

golden empty nesters

1.33

provincial privilege

1.66

high technologists

1.82

semi-rural seclusion

2.04

just moving in

0.91

fledgling nurseries

1.18

upscale new owners

1.35

families making good

2.32

middle-rung families

2.86

burdened optimists

1.96

in military quarters

0.17

close to retirement

2.81

conservative values

2.84

small-time business

2.93

sprawling subtopia

3.08

original suburbs

2.41

Asian enterprise

1.02

respectable rows

2.65

affluent blue collar

3.12

industrial grit

3.82

coronation street

2.81

town centre refuge

1.13

south Asian industry

0.88

settled minorities

1.62

counter-cultural mix

1.36

city adventurers

1.27

new urban colonists

1.36

caring professionals

1.08

dinky developments

1.10

town–gown transition

0.76

university challenge

0.26

bedsit beneficiaries

0.71

metro multiculture

1.67

(Table continued )

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908


TABLE 1 Continued group description


municipal dependency

blue-collar enterprise

twilight subsistence

grey perspectives

rural isolation

type description

per cent

upper floor families

1.72

tower block living

0.49

dignified dependency

1.34

sharing a staircase

0.50

families on benefits

1.21

low horizons

2.64

ex-industrial legacy

2.86

rustbelt resilience

3.00

older right to buy

2.67

white van culture

3.17

new town materialism

2.17

old people in flats

0.83

low-income elderly

1.63

cared-for pensioners

1.43

sepia memories

0.75

childfree serenity

1.34

high-spending elders

1.53

bungalow retirement

1.26

small-town seniors

2.71

tourist attendants

0.30

summer playgrounds

0.29

greenbelt guardians

1.74

parochial villagers

1.64

pastoral symphony

1.31

upland hill farmers

0.41

(2002) in his Critique of Information is also concerned to understand the rezoning of space in the light of some of the urban technologies that concern us here, it seemed reflexively appropriate to use this as a basis for our case study selection. For Lash, social geography is becoming fragmented as a result of the interplay between two main drivers: the variable density of ‘information flows’ and the prior nature of the ‘identity spaces’ that such flows envelop. Lash (2002, pp. 28 –29) draws a distinction between what he calls ‘live’ and ‘dead’ zones in the fluid ‘infoscapes’ emerging across the globe. Live zones are where such flows are at their most dense, and dead zones are where the flows are lightest. However, for Lash, this contemporary ‘infoscape’ intersects in variable ways


with zones of another sort – what he terms ‘tame’ and ‘wild’ zones. He writes:


the live and dead zones of economic spaces refer to the presence (or relative absence) of the flows and the identity spaces refer to what social actors do with them. (Lash 2002, pp. 28 –29) These two sets of distinctions (live/dead and tame/wild) allow Lash to identify four different types of sociospatial zone. A summary and discussion of some of the supposed characteristics of four zones which emerge have been discussed previously in the pages of this journal (Burrows & Ellison 2004) and elsewhere (Ellison & Burrows 2007). Using this crude analytic template as a guide – and after much debate, walking the streets and staring at statistics – we selected four neighbourhoods that we felt epitomized each of these ideal-typical characterizations of social space: .

. .

.

a street in central York in Northern England, as an example of a live/tame zone; a street in Hoxton in East London, as an example of a live/wild zone; a street in Howden, a small market town in the East Riding of Yorkshire in the North of England, as an example of a dead/tame zone; and a street in the west of York as an example of a dead/wild zone.

We interviewed a total of 42 residents (between 10 and 12 in each street). They were asked various questions about: how they came to be living in the area; their perceptions of the neighbourhood, of their neighbours and of themselves in relation to their neighbours; and their initial reactions to the geodemographic classifications of their neighbourhood that we presented them with. We also interviewed: local estate agents (10 in total); people with community and neighbourhood responsibilities in the relevant local authorities (four interviews); and local shopkeepers (six interviews). We also spent time undertaking observations in the neighbourhoods. By a combination of means, then, we managed to build up a qualitative understanding of the ‘ground truth’ (and its variability) within each neighbourhood. For each street we also ‘audited’ the range of classificatory schemas to which each was subject. In what follows we briefly compare and contrast the immanent lay perceptions of place that pertained within each neighbourhood with a range of abstract digitally derived ascribed categorizations to which each was subject.

A live/tame zone Our first case study street is in central York on one of the rather grand thoroughfares into the city. It is covered by two different postcodes. Average

909


910


house prices at the time the data were collected were close to £400,000. It is made up of very large terraced houses, some of which have been converted into apartments. It is leafy and has an almost cosmopolitan feel. The volume of traffic moving through is heavy, and if one did not know where one was it would be possible to mistake the street for somewhere in London. How is this place classified? According to the official Indices of Multiple Deprivation (IMD)1 both postcodes are contained within the 18,675th (out of 32,482) most deprived area in England (the 53 percentile). So, in the statistical sense of the term, this is ‘middle England’. However, according to the Acorn classification this is an area of Urban Prosperity made up of Prosperous Professionals who are further classified as Older Professionals in Detached Houses and Apartments. According the P2 People & Places system both postcodes are instances of Urban Professionals who are Qualified Metropolitans, whilst for the Cameo system this is an area classified as Urban Living Professional Singles and Couples. According to Mosaic both postcodes are within the Symbols of Success group and the Cultural Leadership type. In the Mosaic classification, each of the 61 types is underpinned by 12 dense pages of text, photos, graphs and charts under the headings of: sociology and environment; culture and consumer psychology; stereotype; who we are; how we make a living; where we live; our home lives; weltanschauung; time use; and measures of deprivation. Space precludes a detailed summary here but the following gives a flavour. These areas are classified as being populated by ‘well-to-do professionals, living in traditional family units in exclusive suburbs’. The names ‘Jacob’ and ‘Annabel’ are suggested as emblematic. They are considered to hold ‘orthodox values’, to be ‘private’, to be ‘powerful decision makers’, who are ‘well educated’, living in ‘expensive family houses’, and who are ‘rooted in the UK’.

A dead/wild zone Less than one mile to the west of this zone of ‘cultural leadership’ is a very different sort of place. This is our example of a dead/wild zone – a long street of rundown postwar council houses, a few now in owner occupation, which does not fulfil any of the stereotypical images of York as a cultural heritage city. Average house prices here are currently £130,000. The gardens are unkempt, crime levels are high, drugs are perceived to be a major problem and many of the symbols of contemporary cultures of poverty are all too readily apparent in the clothes, demeanour and language of the predominantly white youths on small bikes who populate many of the public spaces of the area. Older residents also live here but many are fearful and few populate the urban mise-en-sce`ne. This street is covered by three postcodes. How are they characterized? According to the IMD the first postcode is within an area that is the 7,152 (20th percentile) most deprived in England. However, towards the top end of



the street the other two postcodes both fall in an area classified as the 3,324th (9th percentile) most deprived. According to the Acorn classification this is an area made up of two different groups of Hard Pressed people: a group of Burdened Singles living as Single Parents and Pensioners in Council Terraces and a group of Struggling Families further classified as Low Income, Routine Jobs, Terraces and Flats. According to Mosaic the first two postcodes are both classified as Municipal Dependency: Ex-Industrial Legacy whilst the one at the far end of the street (where younger people tend to live) is classified as Municipal Dependency: Low Horizons. According to Global Mosaic all of the postcodes are made of what it terms Metropolitan Strugglers – a category that covers almost 16 per cent of households in the UK, almost 25 per cent in the USA, 9 per cent in New Zealand but only 6 per cent in Australia. According to the Global Mosaic handbook the category Metropolitan Strugglers contain people who live in less sought after neighbourhoods in large population centres and who often battle against high levels of crime, drug addiction and social disorder as well as difficult physical environments. Often poorly paid in low skill service jobs such as office cleaners, parking attendants, security staff, transport workers, these people are seldom able to afford to buy their own homes and typically live in cramped rented apartments, very often in social housing schemes.

A tame/dead zone Eighteen miles or so to the south of York is the small market town of Howden, with a population of about 4,000 people. Here we find a long suburban street that forms our third case study. The houses are all detached or semi-detached and were mostly built in the 1950s. Some have extensions. Many have had their original windows and doors replaced with uPVC versions. They have well-kept small front gardens and large back gardens. Almost all have cars on the drive. There are very few children living here, and those that are, are in their late teens or early twenties. The average price of a house here is just over £240,000. Those towards the outskirts are slightly larger and slightly more expensive. How is this street classified? The street crosses two different SOAs. Towards the town centre the street is classified as being part of the 26,252th (74th percentile) most deprived area in England by the IMD, whilst towards its far end towards the outskirts of the town it is classified as being in the 17,660th (50th percentile). The street is also covered by two postcodes. Acorn classifies both as instances of Wealthy Achievers, but of two rather different types. At one end of the street they are classified as Affluent Greys who are also Older Affluent

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Professionals, whilst at the other end they are Flourishing Families who are Welloff Managers, detached houses. Mosaic broadly concurs: both are examples of Suburban Comfort but one group are Close to Retirement whilst the other is Small Time Business. This latter group is characterized as ‘local professionals and small business proprietors in quiet residential areas’. The keys features of the groups are considered to be: self-reliance; small businesses; small market towns; higher incomes; local networks; grown up children; local professionals; and of older working ages.


A wild/live zone Wild/live zones, as characterized by Lash, are pretty thin on the ground in Yorkshire. So our final case study took us to a street not very far from Hoxton Square in the East End of London – an area often characterized as the epitome of certain sort of ‘cool’. Here we find a street about as far removed from the one in Howden, just described, as it is possible to imagine. This is a densely populated, multi-ethnic, noisy and dynamic environment. The buildings are a complex mixture of low-rise 1960s council estate, trendy modern apartments and flats and small new-build houses. This is a street close to where Jarvis Cocker used to live. At the corner at one end is an off-licence and at the other there is a plethora of small shops, bars and takeaways. Those properties in owner occupation are relatively expensive – flats often being over £300,000 and houses closer to £400,000. How is the complexity of this street classified? The street cuts across five different postcodes (reflecting the density of the population here) and two different SOAs. At the more ‘trendy’ end of the street the IMD classifies it as in the 3,992th (11th percentile) most deprived place in England, whilst at the other (predominantly low-rise council estate) as the 1,824th (5th percentile) most deprived. This division is mirrored in more detail in the various geodemographic classifications to which the street is subject. Acorn classifies three contiguous postcodes as instances of Urban Prosperity of a particular form – Educated Urbanites – and even more specifically as Prosperous young professionals, flats. Their neighbours, at the poorer end of the street are, however, classified very differently, as instances of the Hard Pressed of a particular form – Inner City Adversity – or more specifically as Multi-ethnic purpose built estates. Mosaic offers a slightly more nuanced characterization still. The first three postcodes are all considered to be instances of Urban Intelligence, the first two postcodes are considered to be City Adventurers, whilst the third – a sort of zone of transition perhaps – is considered an instance of Counter Cultural Mix, whilst the last two postcodes are classified as part of the Welfare Borderline group and the Metro Multi-culture type. City Adventurers are ‘High-salaried, twenty-something singles in smart flats in inner urban areas’. The names Tim and Claudia are emblematic. The key



characteristics of this Mosaic type are listed as: 20-something singles; individuality; high flyers; high salaries; smart studio flats; fashionable; London; and pressured jobs. The Counter Cultural Mix type, by contrast, is described as ‘Young, mobile population in a mix of jobs either in the service economy or in professional employment, in run-down urban areas’. The names Jose and Ana are emblematic. The key characteristics of this Mosaic type are listed as: stylish and creative; individual; some in good jobs; some lower incomes; well informed; live for today; tuned in to marketplace; trendy city dwellers; and young professionals. Their neighbours in the Metro Multiculture type are described as ‘Welfare Borderline Tenants of public housing in inner city areas, with a high proportion belonging to minority communities’. The names Abdul and Fatima are emblematic. The key characteristics of this Mosaic type are listed as: TV popular; multi-storey flats; many children; mixture of ethnicity; high unemployment; relaxed and carefree; modest incomes; and singles and cohabiting couples.

Summary In these four instances we found a high level of concordance between the detailed characterizations offered by the various classifications we examined. We have only given illustrative descriptions here, but we found no instances of major disagreements between the various schemas we examined. We also found that, for the most part, the characterizations on offer ‘rang true’ for us as ethnographic observers of the places we were studying. They were reasonable descriptions of the people and places they purported to represent. The residents of these streets we spoke to were often first shocked by the level of detail that these ideal types presented about their localities. Next they began to point out where the characterizations failed, and finally they would often conclude that although the classification was incorrect about them, it was not at all bad at describing their neighbours! So, in general, these things ‘work’ and allow us to know something about who lives where. They offer reasonable ideal typical socioeconomic and cultural characterizations of neighbourhoods. What interests us most about this particular form of urban informatics is its application and impact as a software social sorting technology on ‘ground truth’ and vice versa. As Graham (2005, p. 2) has argued, ‘new technologies are intimately involved in the fine-grained and subtle transformations or “remediations” of place – and space-based social worlds’ – and, in his view, ‘the coded worlds of the “virtual” actually work to continually constitute structure and facilitate the place-based practices of the material world’. But, of course, these new urban informatics technologies are also themselves continually co-constructed in knowledge practices of the material world. It is this recursive relation between ‘class places’ and ‘place classes’ that is our focus here.

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Geodemographic co-constructions Detailed descriptions of how a range of different geodemographic classifications are produced and utilized can be found elsewhere (Harris et al. 2005), as can some initial assessments of their sociological significance (Burrows & Gane 2006; Ellison & Burrows 2007). The specific algorithms that are used to create them are largely proprietary, but most share a common methodological approach. A large number of spatially referenced data items – usually about half from the Census and the other half from other (mostly commercial) sources – are subject to different forms of cluster analysis, which are basically techniques that sort out cases into selfsimilar clusters based on a chosen set of relevant attributes. The final (and perhaps most sociologically interesting) stage is then to ‘label’ or ‘name’ each type of place in a manner that is taken to epitomize its dominant sociocultural characteristics. This done, a detailed descriptive narrative is produced which is aimed at characterizing the ‘sort of people’ who reside within the ‘types of places’ so classified. The geodemographic methodology, therefore, conveniently summarizes large amounts of information by producing classifications that have the potential to be both useful and meaningful. To the extent that classifications offer the potential to be both of these things, they are also constructed in ways that maximize the probability that this will be facilitated. It is the manner in which this ‘optimization’ is achieved that invokes issues of co-construction in the form of a recursive loop. Whilst clusters of similar entities are produced through cluster analysis, it is the case that different cluster methods can, and do, produce different results (Aldenderfer & Blashfield 1984); so there is no ‘right’ or ‘wrong’ cluster production. This is not to say that all cluster results are equally meaningful, but they are re-crafted according to their meaningfulness and utility. Therefore, the fact that the final geodemographic classifications are meaningful and useful is not so much a ‘surprise’ of the method as it is a deliberate part and aim of the method. It is a circular argument. They are both meaningful and useful because they are made to be both meaningful and useful; they are increasingly used because they are useful; and they are increasingly meaningful because they are increasingly used. In turn, and as we have already hinted, which classifications become ‘useful’ and who decides that this is the case is not simply a technical matter, but a deeply political and ethical one. And it is not just in the statistical procedures that we find such processes at work. We find it also in the data to which they are applied. As we have noted above, geodemographic classifications tend to rely on a mixture of both national census data and other administrative and commercial databases (Harris et al. 2005). Wherever data ‘come from’ and however they



are ‘produced’, they have already been subject to a string of identification and classification processes that are themselves necessarily historically, socially and politically contingent. This point is made well by Desrosie`res (1998), whose work on the construction of statistical information and measurement processes illustrates the contingent, historical, political and cognitive processes involved in making statistical representations ‘hold’. His argument is that ‘Statistical information did not fall from the sky like some pure reflection of a pre-existing “reality”‘(Desrosie`res 1998, p. 325). On the contrary, he suggests, taxonomy and classifications are made to ‘hold’ because they themselves are ‘tools for classifications and encoding, linked to action and decision making, and cannot be separated from the social network into which they are introduced’ (1998, pp. 245 –246). There is, therefore, a recursive interaction between the classifications produced by geodemographics and the data that are used to construct them. Furthermore, there is a recursive interaction between the world that geodemographic classifications are designed to represent, and classifications already entrenched in both the world and the research practices used to know that world. As Hacking (2002a, p. 344) would have it, ‘classifications interact with the classified’. In one sense, the clustering algorithms that underpin the construction of the classifications can operate quite happily without any of the visualizations or text that make geodemographic classifications meaningful to their users – as Hansen (2000, p. 19) puts it, software ‘does not rely on the activity of thinking for its ontogenesis’ (cited in Thrift 2005, p. 157). But in another, it is precisely the ‘human narrative’ that acts as the transmission belt of what Hacking (2002b) calls the ‘feedback loop’ – the labels, the classificatory descriptors – which provide the hermeneutic gateway through which a recursive traffic of classifiers and the classified shifts backwards and forwards. While our research found this place-making reflexive ontogenesis to be relatively under-developed in the areas of the case study (with the possible exception of the live/wild zone of Hoxton in London), residential location decisions have a much greater degree of interactivity in the United States through the availability of web technologies which allow personal profiles to be matched to ideal spatial fixes based on the education, income, household type, and even religious and political convictions of the existing inhabitants. Sites such as Sperling’s Best Places (http://www.bestplaces.net) offer chapter and verse on how to select not just the perfect city, but the ideal neighbourhood in which to raise your family. Like the popular UK Internet based neighbourhood information system (IBNIS) upmystreet.co.uk, in the United States there is a strong focus on folksonomic data feeds from ‘on the ground’ inhabitants (or former inhabitants) that can either confirm or contrast the hard data rankings and classifications devised by the professional geodemographers. Findyourspot.com, for example, encourages the user to take

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on an online questionnaire that will then match you with your ideal location, but the site requires a good deal of personal information to be keyed in before it will unveil your 24 ‘hottest spots’. These ‘data trades’ are an increasingly important part of the recursive relay of informational capitalism in general and the proprietary domain of the geodemographics industry in particular, and this new informational economy is made possible precisely because growing numbers of Web 2.0 users are becoming trained to present themselves as assemblages of discrete socioeconomic, cultural and political categories, which in turn are linked to place. Hacking argues against the idea that ‘classifications may grow or be revised, but once in place they are basically fixed and do not interact with what is classified’. Instead he proposes a different kind of nominalism— which he terms ‘dynamic nominalism’. This idea depends on the belief that there is a relationship between how we describe things and how we act towards them. As Hacking puts it, ‘if new modes of description come into being, new possibilities for action come into being in consequence’ (Hacking 2002b, p. 110). The geodemographic assemblages described in this paper provide an example of this. They represent a complex set of relations between recursive ontologies, social sorting and the automatic production of space. These software-mediated processes are novel to the extent that they achieve ‘a standardization and classification of urban situations in ways which were formerly impossible’ (Thrift 2005, p. 173). The same author also points out that even as traditional ‘guns and barbed wire’ capitalism continues to forcibly commodify what is left of the ecosphere: A new kind of productive commotion is being achieved through an active refiguring of space and time, which has the effect of making knowledge into a direct agent of the technical-artistic transformation of life: knowledge and life become inextricable. (Thrift 2006, pp. 280 – 281) Whilst this may be the case, as real as all these co-constructions are in themselves and in their consequences, we need to avoid becoming caught up in them in a way that overlooks the importance of urban ontology. How might we describe the ontological properties of the sociospatial urban world that facilitate and make possible the co-constructing and constructed geodemographic classifications? We might think about the implications of this in respect of the nature of the case (whatever the case) and cluster analysis (whatever the specific cluster method), and suggest that whilst cluster analysis is structure imposing, the structure it imposes is likely to be congruent to the ontology of the case (Uprichard 2008). Perhaps, as we discussed at the outset of this paper, one reason put forward for why geodemographics



‘work’ is because of the supposed observation that ‘birds of a feather flock together’. Does this reflect urban ontology? Certainly at least two ontological properties of cities as complex systems have been noted (Byrne 1998, 2001; Batty 2005) that might suggest why this cliche´ might function as well as it does: ‘self-organization’ and ‘fractal formation’. Self-organization is, as the term suggests, the idea behind what ‘makes’ birds fly in flocks, fish swim in schools, and similar people cluster together in cities (Johnson 2001; DeLanda 2006). It refers to self-organization without a ‘top-down’ control system, but instead from local ‘bottom-up’ behaviour. Similarly, whilst the methodological procedures behind the construction of geodemographic classifications produce self-similar clusters, ‘fractal formations’ are also understood to be present in complex places. Fractals are geometrical patterns, structures or set of points, which are self-similar on different scales. Kelly and Allison (1998, p. 15) offer a simple, but useful, explanation of these complex patterns as ‘those in which the nested parts of a system are shaped into the same patterns as the whole’. Cities then are, arguably, fractal in character, as Pumain explains more fully: [the urban space] is fragmented, self-similar in the sense that the same patterns, like the dilution from a centre towards a periphery, can be observed at several scales, and hierarchical, including many more small centres than large ones, as well as a [sic] many more small narrow roads than very large ones, or many more urban squares than very large plazas. The same differentiation processes have produced more or less gradients in building, population and activities densities around the centres towards the peripheries, at local scales as well as at regional or higher scales, according to various degrees of accessibility. (Pumain 2003, p. 11) Thus, even though geodemographic classification produces self-similar clusters, and the method imposes this structure, it is possible that geodemographic methods work as well as they do because the structure they seek to produce is self-similar to that which ‘exists’ anyhow, and that the descriptive narrative that emerges from these classification processes is constructed to reflect that ontology. So whilst geodemographic classifications are fundamentally sociospatial representations, the ways in which these representations are constructed involve recursive loops which are both methodological and epistemological, which in turn interact recursively with the spatialization of class at an ontological level. Class places people into different types of places, which in turn results in the spatialization of class. The application and impact of geodemographic classifications recursively reinforces this spatialization of class. In addition, the construction of geodemographics classifications involves the

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use of sociospatial data that are ‘made’ in the world by particular groups of people, from particular classes, who are ultimately involved in determining which types of people and places are classified, and where particular classes are placed. In other words, the pace and extent of the automatic production of classified space requires a fateful synergy on the supply side of coders and narrators of habitus; and on the demand side a sufficiency of ontologically recursive, resourceful and geographically mobile knowledge-bearing agents in order to achieve the ‘co-creation’ of commodified or commodifiable locales (Thrift 2006, p. 282). Our study found ample evidence that all the conditions for the successful technical-artistic transformation of neighbourhood classifications are already well established and in place. What is lacking, with the possible exception of the live/wild zone of Hoxton, is the sort of demandside recursive ontogenesis that is transforming the nature of the US upscale habitus into what for some has been sold as the modern equivalent of the earthly paradise; while those left outside the gates (Atkinson 2006) find their spatial ontologies ever more segregated and circumscribed by a splintering urbanism (Graham & Marvin 2001) in which they are not so much ‘cocreative’ subjects as ‘re-mediated’ objects of classification, surveillance and control (Ellison & Burrows 2007).

Acknowledgement This paper was written under the auspices of a research project funded by the ESRC (L341250006).

Note 1

The IMD (Noble et al. 2004) is itself a sophisticated classificatory schema, but one that is rather different from the geodemographic classifications that are our focus here. Whilst they are based on postcode geography, the IMD is based on census geography. Within this England is divided into 32,482 areas – called super output areas (SOAs) – of roughly equal population size, and each is assigned a score and a rank. The IMD score is constructed using a large number of data items covering seven different domains of deprivation: income deprivation; employment deprivation; health deprivation and disability; education, skills and training deprivation; barriers to housing and services; living environment deprivation; and crime. A rank of 1 is assigned to the SOA with the highest levels of multiple deprivation and a rank of 32,482 to the SOA with the lowest levels.



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Thrift, N. (2006) ‘Re-inventing invention’, Economy & Society, vol. 35, no. 2, pp. 279 – 300. Thrift, N. & French, S. (2002) ‘The automatic production of space’, Transactions of the Institute of British Geographers, vol. 27, no. 4. Uprichard, E. (2008) ‘Introducing cluster analysis: what can it teach about the case?’, in D. Byrne & C. Ragin (eds) Handbook of Case-Based Methods, Sage Publications, London. Webber, R. (2007) ‘The metropolitan habitus: its manifestations, locations, and consumption profiles’, Environment and Planning A, vol. 39, no. 1, pp. 182–207. Simon Parker is a Senior Lecturer in the Department of Politics at the University of York. His research interests include: Italian politics; comparative European politics; comparative urban politics; and political sociology. He is author of Urban Theory and the Urban Experience: Encountering the City (Routledge 2004). Address: Department of Politics, University of York, Heslington, York YO10 5DD, UK. [email: [email protected]] Emma Uprichard is a Lecturer in Sociology at the University of York. She has research interests in: social research methods (including computer simulation methods); children and childhood (especially children’s geographies); cities and urban change; complexity theory; and the sociology of time and space. Address: Department of Sociology, University of York, Heslington, York YO10 5DD, UK. [email: [email protected]] Roger Burrows is Professor of Sociology in the Department of Sociology at the University of York. He has research interests in: urban and housing studies; the sociology of health and illness; and social informatics. Address: Department of Sociology, University of York, Heslington, York YO10 5DD, UK. [email: [email protected]]

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