Encyclopedia of Geography

Barney Warf

Hardcover

University of Kansas University of Kansas, USA 30-09-2010

ISBN: 9781412956970

£590.00

3560 Pages

TABLE OF CONTENTS Economic Geography Spatial Analysis Popular Culture, Geography and Population, Geography of Historical Geography Foreign Direct Investment Automobile Industry Film, Geography and Infrastructure Brownfields Trade Quantitative Methods Kropotkin, Peter Enlightenment Applied Geography Industrial Districts Industrialization Transportation Geography Aviation and Geography Terrorism, Geography of Radical Geography Real Estate, Geography and Critical Geopolitics Agro-Food System Harley, Brian Segregation and Geography Actor-Network Theory Citizenship Human Rights, Geography and Mitchell, Don Sexuality, Geography and/of  Commodity Chains Geomancy Conference of Latin Americanist Geographers

Trevor Barnes, Jayme Walenta Paul Longley Jason Dittmer Ezekiel Kalipeni Phil Birge-Liberman Sharmistha Bagchi-Sen, Dipti Saletore James Rubenstein Christopher Lukinbeal Igor Vojnovic Linda McCarthy Dean Hanink Brian Ceh Ray Bromley Mariselle Melendez Sonya Glavac Ronald Kalafsky Ronald Kalafsky Julie Cidell John Bowen Samuel Nunn Peter Hossler Grant Thrall Jason Dittmer John Grimes Dennis Reinhartz David Kaplan Fernando Bosco Thomas Chapman Thomas Chapman Thomas Chapman Thomas Chapman Deborah Leslie David Nemeth David Robinson

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Encyclopedia of Geography Poverty Nuclear Energy Symbolism and Place Columbus, Christopher Spatial Inequality Association of American Geographers Disability, Geography of Non-representational Theory Social Construction of Nature Immigration Urban Land Use Art, Geography and Urban Sustainability Travel Writing, Geography and Medical Geography Gender and Geography Commonwealth of Independent States Communications, Geography of Council for Mutual Economic Assistance (COMECON) Queer Theory Rural Development Gentrification Geopolitics Extreme Geography Redistricting Fordism Homelessness Urban Underclass Psychoanalysis, Geography and African Union National Council on Geographic Education Whiteness Vision and Geography Geographic Education Accessibility Sequent Occupance Boundaries and Borders Nomadic Herding Nomadism Social Justice Crime, Geography of Krummholtz Biodiversity Desert Varnish Urban and Regional Development Food and Agriculture Organization

Pascale Joassart Lisa Marshall Briavel Holcomb Santa Arias Huhua Cao Douglas Richardson Valorie Crooks Ian Shaw Kevin Archer Ines Miyares Jeffrey Richetto Deborah Che Meg Holden Jamie Winders Jordan Lisa Ann Oberhauser Darren Purcell Darren Purcell Darren Purcell Tiffany Muller Soren Larsen Martin Phillips Klaus Dodds David Nemeth Toby Moore Bruce Pietrykowski Jeff May, Alan Walks David Wilson Jesse Proudfoot Garth Myers Martha Sharma Euan Hague Nazanin Naraghi Michael Solem Joe Weber John Pipkin Gabriel Popescu Douglas Johnson Douglas Johnson Christopher Merrett James LeBeau Kathy Hansen Bob Voeks Ron Dorn Mark de Socio Alan Grainger

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Encyclopedia of Geography Spatial Inequality

Contributors: Barney Warf Print Pub. Date: 2010 Online Pub. Date: September 01, 2010 Print ISBN: 9781412956970 Online ISBN: 9781412939591 DOI: 10.4135/9781412939591 Print pages: 2641-2646 This PDF has been generated from SAGE knowledge. Please note that the pagination of the online version will vary from the pagination of the print book.

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10.4135/9781412939591.n1066 The study of inequality seeks to analyze the causes, contexts, conditions, and outcomes of disparities between two or more groups over a given number of variables. It differs from a study of difference insofar as the former assumes a quantifiable progression from worse off to better off in some respects relevant to the human sciences. Inequality is most commonly explained with reference to genetic predisposition, individual action, and social forces, or some combination of the three that leads to disparities between two or more unequal individuals or groups. The means of quantifying inequality are often quite sophisticated and are consistently used to analyze the development of a given group relative to its own past and relative to the situation of others within a specific time frame. Spatial inequality is a particular form of inequality. Inequality is more generally the study of “who gets what and why.” Adding a spatial characteristic means integrating an element of “where,” enriching the concept by seeking to explain how social, political, economic, and cultural discrepancies relate not only to ideas, structure, and agency but also to the specific attributes of space in the material world. Spatial inequality is a concept that seeks to explain and illustrate discrepancies among populations regarding outcomes, conditions, and/or opportunities across different spaces and spatial scales. It shows inequality in terms of different spatially located demographics and their relationship to a given set of variables. Spatial inequality occurs for a number of reasons, including the formation and operation of class; racism and/or prejudice toward cultural, ethnic, or minority groups; and other discriminative views and practices (e.g., based on gender, religion, age, or sexuality). Equally important, however, is a clustering among socioeconomic lines, which is a general feature of spatial inequality. Figure 1 shows the level of intra- and intercountry economic disparity among four countries. Economic disparities are a useful and common way of measuring inequality. The graphic shows that while Brazil's richest people are as rich as those of France, its poorest are poorer than the poorest in rural Indonesia. Clearly, this kind of analysis is useful in understanding the massive discrepancies on two different spatial scales, in this case national and global.

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Spatial inequality can also be considered in terms of the unequal distribution in goods or services depending on an area or location. Inequality in services, for instance, means that the provision of medical aid or education will differ among spaces. Figure 2 shows the results of a study that found a correlation between nonattendance rates [p. 2641 ↓ ] and school densities in counties in Gansu province, China. The map shows that counties with a relatively weak density of lower-secondary schools have a higher girls’ nonschooling rate than counties with high densities of lower-secondary schools. This study demonstrates that the longer the distance from schools, the higher the opportunity cost of acquiring education and the greater the gender disparities in the school attendance rate. Figure 1 World income distribution by percentile across four countries, 2005

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Source: Malanovic, B. (2006). Global income inequality: What it is and why it matters. World Economics, 7(1), 19. Spatially, inequality can be examined globally, regionally, nationally, and locally. It can be measured between the global North and the global South, between Asia and North America, between the United States and China, or between New York and Shanghai. Within countries, spatial inequality studies can evaluate the difference in outcome, condition, and/or opportunity on an interurban scale (e.g., New York vs. San Francisco), an intra-urban scale (e.g., the Lower East Side vs. Harlem), an urbanrural scale (e.g., the Atlantic Northeast vs. the Midwest), and a rural-rural scale (e.g., Page 4 of 10

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Appalachia vs. the Midwest). Many other scales are also open to comparison in studies of spatial inequality. Figure 3 shows an example of intraprovincial spatial inequality. We can observe the disparity between per capita [p. 2642 ↓ ] income in Kolkata and in other districts of West Bengal in 2004–2005. No other district in the province had a per capita income that was even half that of Kolkata, not even those that are contiguous to or located near the capital. More than half the districts had per capita incomes of around one third (or less) that of West Bengal's capital. It should also be noted that for almost every district, the per capita income gap with respect to Kolkata has actually widened since 1999–2000, indicating that the recent pattern of economic growth has accentuated spatial inequalities within the state. Figure 2 Spatial distribution of girls’ nonschooling rates and density of lower-secondary schools in Gansu, China, 2000

Source: Cao, H. (2008). Spatial inequality in children's schooling in Gansu, Western China: Reality and challenges. Canadian Geographer, 55(3), 346. Page 5 of 10

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Studies of spatial inequality are well suited to representing the dynamic process of change across different spatial scales. They can offer a more nuanced perspective of migratory patterns, remittances, and the impact of global and national flows of capital, goods, and services on local, regional, and national demographics. Spatial inequality is a useful focus for mapping migrants or the dynamics of slum settlements as they relate to increasing urbanization in the global South and the processes of change of large metropolitan cities such as gentrification and redevelopment. Figure 4 demonstrates the relationship between income discrepancies and slum population in a number of countries in the global South. As an example of spatial inequality, it is successful in demonstrating the linkages between national and local spatial scales through a common pattern of economic outcomes. For instance, Sierra Leone has both the highest income ratio and the highest population of slum dwellers as a proportion of its urban population. The correlation does not hold across all countries, however, as Honduras has high income inequality but a low percentage of slum dwellers. Studies of the spatial differentiation of outcomes, conditions, and opportunities between [p. 2643 ↓ ] different demographics are applicable to every field of study in the human sciences. The use of such a method of study arose out of a need to address the spatial dynamics of change that occur in tandem with economic and political changes and shifts in the cultural and social outlook among populations. Recent spatial inequality research has sought to study spatial inequality for manufacturing wages in five countries in Africa and the process of periurbanization in Albania, among others. Table 1 shows some unmet basic needs for urban and rural Albania as well as for the capital, Tirana, demonstrating a clear urban bias, which becomes more pronounced for the capital. Tirana clearly acts as a hub of social and economic activity, to which the provision of social goods is a response. Figure 3 Per capita income in West Bengal districts, India, as a percentage of Kolkota's in 2004–2005

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Source: Adapted from Chandrasekhar, C. P., & Ghosh, J. (2008, May 12). Recent growth in West Bengal (Table 2). MacroScan. Retrieved January 19, 2010, from http:// www.macroscan.org/fet/may08/fet120508West_Bengal.htm. Studies of spatial inequality have developed rigorous methodologies for mapping the discrepancies of different variables across demographics in different spaces and at differing spatial scales. Methodologically, they are strongly related to quantitative analysis, which has been aided by the development of geographic information systems (GIS). The study of spatial inequality can be constrained by the ability of the researcher to amass data relevant to both a given spatial scale and the variable(s) being studied. For example, large-scale surveys, particularly in poor countries, are not always a Page 7 of 10

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reliable source of information. Moreover, the breadth of studies of spatial inequality risks revolving primarily around studies that relate to economic well-being, when inequality [p. 2644 ↓ ] [p. 2645 ↓ ] may reflect an underlying bias that resides more in geographical, social, or cultural predilections than in overt political or economic exclusion or weakness. Thus, qualitative studies of spatial inequality should be used to place the results gleaned from research into a larger context of human activity and geographic space using various theoretical models. Figure 4 Income ratio relative to slum population in 16 countries in the global South, 2006

Source: Adapted from Hall, P. (2007). Urban land, housing, and transportation: The global challenge. Global Urban Development, 3(1), 6, Table 3. Table 1 Comparative indicators of unmet basic needs (UBN) in Albania, 2003

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Source: Deda, L., & Tsenkova, S. (2006). Poverty and inequality in Greater Tirana: The reality of periurban areas. In S. Tsenkova & Z. Nedovic-Budic (Eds.), The urban mosaic of post-socialist Europe: Space, institutions and policy (pp. 151–170). Heidelberg, Germany: Physica. HuhuaCao

10.4135/9781412939591.n1066 See also Further Readings (2008). Spatial inequality in children's schooling in Gansu, Western China: Reality and challenges. Canadian Geographer vol. 55 no. (3) pp. 331–350. http:// dx.doi.org/10.1111/j.1541-0064.2008.00216.x Cao, H.

(2005). Fragments of inequality: Social, spatial, and evolutionary analyses of income distribution. Oxford, UK: Routledge. Chakravorty, S.

(2008). Recent growth in West Bengal. MacroScan. Retrieved January 19, 2010, from http://www.macroscan.org/fet/may08/ fet120508West_Bengal.htm Chandrasekhar, C. P. Ghosh, J.

Deda, L.,

& Tsenkova, S. (2006). Poverty and inequality in Greater Tirana: The reality of periurban areas. In S. Tsenkova, ed. & Z. Nedovic-Budic (Eds.), The urban mosaic of post-socialist Europe: Space, institutions and policy (pp. pp. 151–172). Heidelberg, Germany: Physica. (2007). Urban land, housing, and transportation: The global challenge. Global Urban Development vol. 3 no. (1) pp. 1–11. Hall, P.

Kanbur, R.,

& Venables, A. (2005). Spatial inequality and development. Oxford, UK: Oxford University Press. http://dx.doi.org/10.1093/0199278636.001.0001

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Lobao, L., Hooks, G.,

& Tickamyer, A. (2007). The sociology of spatial inequality. New York: State University of New York Press. (2002). Spatial inequality and diversity as an emerging research area. Rural Sociology vol. 67 pp. 497–511. http://dx.doi.org/10.1111/ j.1549-0831.2002.tb00116.x Lobao, L. Saenz, R.

(2006). Global income inequality: What it is and why it matters. World Economics vol. 7 no. (1) pp. 1–35. Milanovic, B.

(2000). Space matters! Spatial inequality in future sociology. Contemporary Sociology vol. 29 no. (6) pp. 805–813. http://dx.doi.org/10.2307/2654088 Tickamyer, A.

Willem te Velde, D.,

& Morrissey, O. (2005). Spatial inequality for manufacturing wages in five African countries. In R. Kanbur, ed. & A. Venables (Eds.), Spatial inequality and development (pp. pp. 349–378). Oxford, UK: Oxford University Press.

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