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Best practices for measuring community resources across Canada: A comparison of coding classifications
Authors:Marisa Young  Sean Leipe  Diana Singh
Affiliation:1. Department of Sociology, McMaster University, Hamilton, Ontario, Canada;2. McMaster University, Ontario, Canada
Abstract:Social scientists, geographers, criminologists, and health scientists are often tasked with finding data to best capture the impact of “community context” on individual outcomes, including residential services, physical resources, and social institutions. One outlet for such data in Canada is Digital Map Technologies Inc. (DMTI) Spatial, which offers a national repository of over one million businesses and recreational points of interest. The database is generated through CanMap Streetfiles, which includes geocodes of each point's precise location. These data are available to researchers from their university data library and Esri Canada, but primarily available to private sector and government markets. That said, the goal of the current paper is to encourage researchers to access this rich yet under-utilized data source. Each service, business, or resource in the DMTI Spatial database is assigned to a respective category using Standard Industrial Classification codes and North American Industrial Classification System codes. It is not clear, however, which is the more reliable coding criteria. We provide an overview of our review of DMTI Spatial data and take-away suggestions for using this valuable resource for future research on meso-level residential markers.
Keywords:community data  DMTI Spatial data  North American Industrial Classification System codes  Standard Industrial Classification codes  données spatiales DMTI  données communautaires  codes de la classification industrielle standard  codes de la classification industrielle nord-américaine
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