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- Title
The Case for Spatially-Sensitive Data: How Data Structures Affect Spatial Measurement and Substantive Theory.
- Authors
Chan-Tack, Anjanette M.
- Abstract
Innovations in GIS and spatial statistics offer exciting opportunities to examine novel questions and to revisit established theory. Realizing this promise requires investment in spatially- sensitive data. Though convenient, widely-used administrative datasets are often spatially insensitive. They limit our ability to conceptualize and measure spatial relationships, leading to problems with ecological validity and the MAUP - with profound implications for substantive theory. I dramatize the stakes using the case of supermarket red-lining in 1970 Chicago. I compare the analytical value of a popular, spatially insensitive administrative dataset with that of a custom-built, spatially sensitive alternative. I show how the former constrains analysis to a single count measure and aspatial regression, while the latter's point data support multiple measures and spatially-sensitive regression procedures; leading to starkly divergent results. In establishing the powerful impact that spatial measures can exert on our theoretical conclusions, I highlight the perils of relying on convenient, but insensitive datasets. Concomitantly, I demonstrate why investing in spatially sensitive data is essential for advancing sound knowledge of a broad array of historical and contemporary spatial phenomena.
- Subjects
CHICAGO (Ill.); URBAN sociology; SPATIAL analysis (Statistics); STATISTICAL reliability; GROCERY industry; POVERTY; NEIGHBORHOODS
- Publication
Historical Social Research, 2014, Vol 39, Issue 2, p315
- ISSN
0172-6404
- Publication type
Article
- DOI
10.12759/hsr.39.2014.2.315-346