PropertyValue
?:about
?: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. (xsd:string)
?:contributor
?:dateModified
  • 2014 (xsd:gyear)
?:datePublished
  • 2014 (xsd:gyear)
?:doi
  • 10.12759/hsr.39.2014.2.315-346 ()
?:duplicate
?:hasFulltext
  • true (xsd:boolean)
is ?:hasPart of
?:inLanguage
  • en (xsd:string)
?:isPartOf
?:issn
  • 0172-6404 ()
?:issueNumber
  • 2 (xsd:string)
?:linksDOI
?:linksURN
is ?:mainEntity of
?:name
  • The case for spatially-sensitive data: how data structures affect spatial measurement and substantive theory (xsd:string)
?:provider
?:publicationType
  • Zeitschriftenartikel (xsd:string)
  • journal_article (en)
?:sourceInfo
  • GESIS-SSOAR (xsd:string)
  • In: Historical Social Research, 39, 2014, 2, 315-346 (xsd:string)
rdf:type
?:url
?:urn
  • urn:nbn:de:0168-ssoar-384875 ()
?:volumeNumber
  • 39 (xsd:string)