creating measures of theoretically relevant neighborhood attributes at multiple spatial scales

Growing interest in accurately measuring attributes in neighborhood environments allows researchers to study the influence of neighborhoods on individual-level outcomes. Researchers working to improve measurement of neighborhood attributes generally advocate doing so in one of two ways: improving the theoretical relevancy of measures and correctly defining the appropriate spatial scale. The data required by the first, ``ecometric'' neighborhood assessments on a sample of neighborhoods, are generally incompatible with the methods of the second, which tend to rely on population data. In this paper, we describe how ecometric measures of theoretically relevant attributes observed on a sample of city blocks can be combined with a geostatistical method known as kriging to develop city block level estimates across a city that can be configured to multiple neighborhood definitions. We us a cross-validation study with data data from a 2002 systematic social observation of physical disorder on 1,663 city-blocks in Chicago, we show that this method creates valid results. We then demonstrate, using neighborhood measures aggregated to three different spatial scales, that residents' perceptions of both fear and neighborhood disorder vary substantially across different spatial scales.

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