Abstract
In this chapter we focus on a few of the primary spatial concepts that link individuals and their aggregates to one another in space. We also introduce some of the popular statistical methods for taking these spatial relationships into account in sociological research. Here we move beyond the description of relationships to a discussion of geo-sociological (spatially-centered) methods aimed at linking theory and data through explanatory modeling procedures. Underlying the core interests of such analyses is the accounting for spatial relationships in sociological research. In particular, sociology as a discipline is particularly interested in the effect social structure, its changes, and impact of structure and change on human behavior. Given this interest, sociologists have long been focused on the relationship of individuals, and groups of individuals, to specific ecological contexts. These relationships can be conceptualized through a handful of spatial concepts, including proximity, adjacency, and containment. While many other spatial concepts also exist, this chapter examines these key spatial concepts as influential predictors of individual and group behaviors. Each is further related to a popular existing analytic method used by sociologists in an attempt to highlight the relationship between theoretical development and the empirical analysis of spatial relationships.
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Notes
- 1.
For many years, the second author has heard the old standby in statistical analysis, “Oh, I just use SASTM for everything!” It may indeed be that such programs can “do” the appropriate technique once the conceptual work has been done but it shouldn’t be done in reverse. The same applies to other popular software platforms, such as STATATM, SPSSTM, or ArcGISTM, just to name a few. That is, researchers should choose the tool and software implementation after the analytical procedure is appropriately identified.
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Porter, J.R., Howell, F.M. (2012). Spatial Concepts and Their Application to Geo-Sociology. In: Geographical Sociology. GeoJournal Library, vol 105. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-3849-2_7
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DOI: https://doi.org/10.1007/978-94-007-3849-2_7
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