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Spatially Integrated Social Science

Spatially integrated social science may be defined as the empirical and theoretical practice where space and place are integrating mechanisms across social science disciplines as well as central considerations both as inputs and as outcomes of theories and models. This definition is rooted in the increasingly implemented practice of examining social, political, and economic data and problems in a spatially explicit context using geographic information systems (GIS), geovisualization, and spatial analysis. Space and place serve as input measures in models and analyses, as spatial concepts (e.g., distance, location, connectivity/topology, proximity) and spatial aggregates of place (e.g., neighborhood and region) are incorporated as units of analysis. In addition, processes that are the targets of inference and models are also very often contingent on space or space-time mechanisms such as diffusion, distance-decay effects, or the creation of social spaces as applications of spatial practice.

Human practices are inherently spatial and create social spaces that take on uses determined by the encompassing society. The connections that link people, institutions, economies, and organizations in geographical space pervade a range of different social contexts that may be conceptualized as general network structures embedded within a social and political context that constitutes the social space. The types, functional scales, and ranges of these connections are generated from spatial practice. Thus, social spaces may consist of everything from political and administrative demarcations referenced directly to geography to transport systems, business and interpersonal interactions, flows, and migrations that occur across a variety of distances and scales, and also global trade and transport networks that may extend over a plethora of network infrastructures. Torsten Hägerstrand's conception of time-geography and space-time behavior prisms as well as his idea of the mean information field are all examples of these social spaces.

Development of Spatially Integrated Social Science

The motivation for spatially integrated social science results from the realization of the necessity of space and geographic context in generating explanations of social, economic, and political phenomena: For example, the processes of trade flow interconnection, migration, capital flows, and compression of space-time due to increased efficiencies of movement have led to the realization of the value of the spatial context in social inquiry. Many practitioners place a growing emphasis on the role of space and place in the activities of analysis and theorizing for contemporary social science. The past 20 years have witnessed a revolution in social science, as geography, space-time, and place/locality have become crucial for understanding the complicated relationships in an increasingly interconnected world.

The social sciences have regularly employed statistical analysis to evaluate hypotheses and make inferences since the halcyon days of the quantitative revolution in the 1960s. However, even when data exhibited a spatial attribution or reference, only rarely was any type of quantitative and cartographic cross-tabulation performed. Partially, this was due to the lack of computer-based cartographic tools (until the advent of SYMAP in 1964 and SYMVU and GRID in the late 1960s) as well as the relative lack of user-ready statistical computer instruments, as most statistical software required some programming for implementation. This situation was further aggravated by the lack of a coherent framework for cogently integrating space and social processes. Social scientists had to wait for the development of integrative computer-based tools such as GIS in the 1980s before spatially referenced data could be readily examined in a geographical context.

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