A clustering methodology needs to be developed to group continuous proximity measures produced by Statistics Canada.
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Even in a world that is rapidly shifting toward digital technologies, evidence has shown that physical proximity between entities, social and economic actors, or consumers and providers of a service, remains a relevant driver of socioeconomic outcomes. Physical proximity to services and amenities has a determinant contribution to economic performances of businesses, quality of life for individuals, and location decisions for people and businesses alike.
The Data Exploration and Integration Lab (DEIL) at Statistics Canada is creating a new set of granular measures that assess local access to a variety of amenities such as libraries, parks, educational facilities, hospitals, and more. The measures are generated out of a gravity model approach, where the cost of transportation is weighted by the magnitude or importance of the entity they travel to. The measures are calculated at the dissemination block level in Canada. That is, around 500,000 unique geo-located units. The challenge for the UBC Capstone students will be to implement a clustering algorithm methodology for the segmentation of the measures.
- Proximity measures dataset --> Continuous numerical proximity scores for each of the 10 services/amenities, for each dissemination block in Canada.
- Index of Remoteness --> Continuous numeric remoteness score for each census subdivision in Canada.
Data Exploration and Integration Lab (DEIL), Statistics Canada