The Dictionary of Human Geography (163 page)

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Authors: Michael Watts

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methods have often been conceived as opposite or even opposed to quantitative methods, this is an unproduct ive way of conceiving the distinction. Critical eealism was one important moment for think ing of the two approaches as compatible: (NEW PARAGRAPH) extensive methods (often quantitative) were seen to be especially useful for describing pat terns, and intensive methods (typically quali tative ones) more effective for studying causal processes (cf. extensive eeseaech; intensive eeseaech). More recently, the call of mixed methods has been tied to the concept of tri angulation, which involves exploring processes from different angles using different methods, in order to assess the validity of each data source and method, and more fully under stand the process. Nightingale (2003) links the utility of mixed methods to the concept of situated knowledge: she suggests that a mix of qualitative and quantitative methods allows the researcher to better understand the limits of knowledge acquired through any one methodological approach. Different approaches resonate with different audiences for instance, state funding bodies and policy makers are typically more convinced of the ?scientific merit? of quantitative techniques, which they sometimes designate as ?evidence based? research (Mountz, Miyares, Wright and Bailey, 2003). Blending qualitative and quantitative methods may allow a researcher to reach different audiences in more authori tative ways. gp (NEW PARAGRAPH) Suggested reading (NEW PARAGRAPH) Hay (2000); Limb and Dwyer (2001). (NEW PARAGRAPH)
quality of life
A concept linked to that of social well being, which is based on the ar gument that the human condition should be evaluated on a wider range of indicators than just income whether at the individual level or through national aggregates (such as geoss national peoduct and geoss domestic peoduct). Work on the quality of life was introduced to geographers in the 1970s in studies of territorial social indicators (Smith, 1973; Knox, 1975), which focused on separ ate dimensions of collective well being, such as income, wealth and employment, the built environment, physical and mental health, edu cation, social disorganization, social belong ing, and recreation and leisure. maps of these indicators, at a variety of spatial scales from the international to the inter urban, provided evidence on geographical variations in well being, with which researchers could address the question of ?who gets what, where?? (Smith, 1977). (NEW PARAGRAPH) Other concepts, such as freedom (cf. human eights) and happiness, are frequently related to measures of the quality of life that individuals and societies experience, although (NEW PARAGRAPH) much work on happiness shows that to the extent that it can be measured it does not increase above a certain threshold income: people may be more content and live more comfortable lives with higher incomes, but they do not feel any happier (Layard, 2005). rj (NEW PARAGRAPH)
quango
An acronym for quasi autono mous non governmental organizations. These are established and financed by governments to perform public functions in areas of policy such as education and health care. Quango members are appointed rather than elected, and are drawn from private, public and third sectors. Since the 1970s, quangos have grown both numerically and in terms of the areas of the world in which they can be found. This growth reflects a general trend in national gov ernments changing how they govern, involving new forms of organizations in their activities. The incorporation of these organizations into the state apparatus raises issues of account ability, democracy and transparency in public decision MAking. kwa (NEW PARAGRAPH) Suggested reading (NEW PARAGRAPH) Ridley and Wilson (1995). (NEW PARAGRAPH)
quantitative methods
Mathematics has al ways been a foundation of geographical prac tices. For many centuries, it underpinned the development of cartography, providing the techniques (notably geometrical and trigono metrical) deployed in map making in estab lishing exact locations (increasingly through the universally adopted graticule of latitude and longitude and the national surveying sys tems based on that matrix) and in portraying those locations in map form. With the latter, for example, much effort was (and still is) expended on the development of map projec TioNs with which to portray a spherical reality on to a two dimensional surface. Increasingly, however, this work has been separated from academic geographical practices into separate disciplines (such as geodesy). (NEW PARAGRAPH) Although, as with almost all changes within a discipline, earlier exemplars can be identi fied, the post 1945 decades saw a major shift in geographical practices associated with a widespread adoption of quantitative methods in huMAN and physical geography a period widely known as the discipline?s quantitative revoLution and very much linked to the adoption of an explicitly theoretical approach to the discipline?s subject matter. This shift was associated with scholars located at a number of institutions, initially in the USA and then also in the UK (Johnston and Sid away, 2004a), but the dominant core was lo cated at the Department of Geography in the University of Washington, Seattle, in the early to mid 1950s, when a number of graduate students coalesced around two individuals Edward Ullman and, especially, William Gar rison. Their core concern was the application and development of Location theory (espe cially that based in neo cLassicaL econoM ics), with quantitative methods identified as in other social sciences, notably economics and sociology at the time as a means of both expressing theories in a formal language and empirically testing hypotheses. (NEW PARAGRAPH) These two core activities drew on different quantitative MethodoLogies: the expression of theories involved mathematical argumen tation and representation (including ModeL Ling), whereas hypothesis testing used statistical procedures, expressing the outcome of empirical research in probabilistic terms. In some cases, mathematical modelling preceded empirical work, providing the formal basis for hypothesis generation; in others, statistical an alysis was either based on more informal forms of argument leading to some form of expected empirical outcome, or involved exploration of numerical data without any clear expectation as to the likely outcome (cf. expLoratory data anaLysis). These two approaches (espe cially that involving statistical analysis) spread rapidly through the 1960s and 1970s from the core institutions in Seattle and other US centres, alongside parallel and linked develop ments in the UK (Barnes, 2004b, 2008b; Johnston, Fairbrother, Hoare, Hayes and Jones, 2008): according to Burton (1963), geography?s ?quantitative revolution? had suc ceeded by the early 1960s, although circum stantial evidence suggested that it never dominated human geography (Wheeler, 2002). (NEW PARAGRAPH) Much of the mathematical modelling underpinning quantitative work in human geography has focused on either spatial pat terns such as the distribution of settlements, as in ceNTraL place Theory or spaTiAL iNTeracTioN (notably various forms of Migra TioN and communication). The goal was to express the subject matter under consideration in mathematical terms. At the core of much work on spatial interaction, for example, was an analogy with Newton?s famous formula tion, which posited that the volume of inter action between two places was positively related to some index of the generating cap acity at each place and negatively related to the distance between them (the so called dis tance decay hypothesis based on assumed frictions of distance). This could be ex pressed as a simple formula (as in the well known gravity model), but the formulation was later extended to present a more realistic representation through the adoption of entropy maximizing modeLs. Similar ap proaches presented the spatiaL structure being investigated as a system, with nodes (such as towns) and links (transport routes). They modelled various aspects of those sys tems the optimum number and location of warehouses in a distribution network, for ex ample, or the shortest route involving visits to three or more nodes on the network using a variety of mathematical techniques, such as graph theory and Linear programming (cf. optimization modeLs). Changes of and to those structures were also analysed, notably through models of spatial diffusion. (NEW PARAGRAPH) Many of these early approaches relied on a relatively simple conception of spatiaL struc ture, in which distance was the foundational variable to which many of the key relationships were linearly related (albeit through non linear transformations in some cases: see Cox, 1976). More sophisticated mathematical modelling procedures were later adopted, in corporating non linear relationships between elements within the system (such as catas trophe theory and chaos theory). (NEW PARAGRAPH) Most statistical analyses undertaken by human geographers are based on the generaL Linear modeL notably those components that identify either the relationship of one vari able to another (regression, which indicates the degree of change in one variable relative to the amount of change in another) or the strength of such relationships (shown by cor reLation coefficients). Their introduction as exemplified by the first textbook on using stat istical methods in geography (Gregory, 1962) was initially presented by some simply as the proper way to present quantitative material and relationships (Gregory, 1971), with for mal statements replacing the vagueness of ordinary language (Cole, 1969: see also process). But statistical procedures soon be came the predominant means whereby ana lysts tested hypotheses about spatial patterns and processes, with the findings expressed as probability statements the likelihood either that what had been observed in a sample of observations also held in the population from which that sample was drawn (cf. sampLing) or that the relationship identified could have occurred by chance rather than as the result of some assumed causal sequence whereby changes in x stimulated changes in y (where, for example, x is the distance between a pair of towns and y is the number of migrants be tween them). Thus applications of statistical methods involved combining reasoning methods that are both deductive (formal hy potheses regarding the size, strength and dir ection of relationships among variables are stated and those expectations compared against empirical data) and inductive (pat terns are identified in data sets that suggest ordered behaviour). (NEW PARAGRAPH) By the 1960s, some geographers had become aware of potential difficulties of ap plying standard statistical procedures (such as those derived from the general linear model) to geographical data because of the issue of spatial auTocorreLATioN, whereby the as sumed independence of observations could not be sustained. Tobler (1970), for example, had posited a ?first law of geography? that ?everything is related to everything else, but near things are more related than distant ones?. Thus the value of an observation at one place the level of unemployment, for example might well be related to the value at adjacent places, and incorporating all of these values into an unadjusted regression or similar model could violate its foundational assumptions and generate unreliable estimates (NEW PARAGRAPH) of, say, the relationship between unemploy ment levels and house values across a set of counties. Techniques for analysing spatial data that take such autocorrelation into account and provide reliable estimates were thus devel oped forming the basis of an approach to spatial data analysis increasingly widely adopted across the social sciences and known as spatial ecoNomeTrics. Those, and many other, approaches have been increasingly fa cilitated by the development and availability of geographical iNforMATioN systems. (NEW PARAGRAPH) By the 1970s, the approach to human geography widely known as spatial science or locational ANALysis was coming under increasing criticism from a number of direc tions. Many were associated with the assumed link between quantitative analysis and the phiLosophy of positivism the goals of spatial science, it was argued, involved a search for laws of spatial order, in terms of both patterns on the ground and the behaviour that gave rise to those patterns. Some of these criticisms emanated from adherents to a marxisT or rad ical geography, who argued that a focus on the spatial superstructure (cf. iNfrasTruc ture) ignored the true processes involved in the creation/re creation of geographies of un even development and the (class based) powee relations that underpinned them. Other critiques emanated from what became known as humanistic geogeaphy and the var iety of approaches to social and cultueal geogeaphy that emerged in subsequent dec ades, which focused on spatial science?s impli cit characterization of decision making as either deterministic (and thus denying the free will inherent in human agency) or influ enced by economic factors only, thereby ig noring the social and cultural contexts of decision making not least those associated with gendee and ethnicity. (NEW PARAGRAPH) To some extent, these critiques were antici pated by geographers working with quantita tive methods in the spatial science genre. Many soon became aware that the complexity of contemporary society meant that the rela tively simple locational models that they were applying were insufficiently sophisticated to incorporate the wide range of contextual and other variables that can influence spatial be haviour. They therefore shifted their focus away from those models that portrayed a rigid, geometrical spatial order towards more general models of locational decision making that emphasized context what became known as behavioueal geogeaphy. They sought order common patterns of decision making in non deterministic situations, much as suggested in the attempt through steuctueation theoey to eliminate the bin ary dualism between structure and agency. Behavioural geography?s core argument is not that people are irrational decision makers but, rather, that they are boundedly (as against perfectly) rational: the boundedness reflects the limits to their information, their ability to process it and the utility functions that they apply when evaluating options. This does not mean that everybody has to be treated as both unique (having characteristics that nobody else shares in total) and singular (sharing no characteristics with others), so that no general patterns can be found and theories developed. Rushton (1969) makes this point in contrast ing studies of behaviour in space for example, mapping individual journey to work routes with those identifying rules of spatial behaviour, the general patterns within all those choices that can be uncovered from the individual pieces of data using quantitative procedures, to suggest common behavioural decisions. The reasons for such commonalities can then be explored by, for example, identifying shared information underpinning such de cisions, as in Peter Gould?s pioneering work on mental maps, the spatial depictions that we use when evaluating the places we want to visit, move to and so on (Gould and White, 1993 [1974]). (NEW PARAGRAPH) This general approach characterizes the contemporary use of quantitative methods in human geography. Although some have claimed that such work is now virtually absent from human geography?s portfolio and pro spectus, much work using quantitative methods continues to be reported in the dis cipline?s general and specialist journals. As with its predecessors, it concentrates on aggre gate patterns in space and their generating processes: the description, explanation and (in some cases) prediction of general patterns of spatial behaviour and their reflection in the landscape. (Note, however, the recent emer gence of a ?new economic geogeaphy? within economics, and the creation of a journal Journal of Economic Geography to explore commonalities between that approach and the work of geographers who continue to undertake theoretically inspired quantitative work.) (NEW PARAGRAPH) Much contemporary work follows the be havioural geography rather than the original spatial science paeadigm, therefore. Most of it is theory driven, based on generalized hy potheses of how people behave, but much of the analysis involves exploring data assembled to identify patterns rather than explicit hypothesis testing. This very largely reflects the ?immaturity? of such studies: our know ledge of how people make spatially relevant decisions and behave is limited, and so the best we can come up with at this stage is broad expectations. In electoeal geogeaphy, for example, there are theoretical arguments that self interest influences how people vote, with economic concerns underpinning that self interest. But it may be expressed in differ ent ways: some may vote sociotropically, according to their views of the national, re gional and/or local economic situation (voting for the governing party[ies] if they are optimis tic about the economic situation but against if they are pessimistic); some may vote egocen trically, according to their perceived personal financial situation; and some vote altruistic ally, in the interests of their (geographical) neighbours even when these don?t coincide with their own (Johnston and Pattie, 2006). Those theoretically based expectations gener ate testable hypotheses but as with the grav ity model they cannot predict in advance the size of the relevant coefficients for each type of voting, because of the many other contingent factors (some of them spatial in nature) that influence electoral behaviour. (NEW PARAGRAPH) This example illustrates the dominant focus within contemporary quantitative human geography, not as it was 50 years ago on the orderly arrangement of points and lines in the landscape, and of people, ideas and com modities flowing through those spatial struc tures (as postulated by Haggett, 1965), but rather on common patterns of behaviour in similar contexts or common realizations of human agency within particular contextual settings. The emphasis has shifted between two of geography?s fundamental concepts, from a focus on space to one on pLace. Within that changed emphasis has come the adoption of new quantitative procedures that emphasize the important role ofplace as context such as geographicaL aNaLysis MachiNe, geograph icaL expLaNaTioN MachiNe, LocaL sTaTisTics, geographicaLLy weighTed regressioN, MuLTi LeveL ModeLLiNg, the ModifiabLe areaL uNiT

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