Best practices for measuring community resources across Canada: A comparison of coding classifications

CANADIAN GEOGRAPHIES-GEOGRAPHIES CANADIENNES(2024)

引用 0|浏览0
暂无评分
摘要
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.
更多
查看译文
关键词
community data,DMTI Spatial data,North American Industrial Classification System codes,Standard Industrial Classification codes
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要