Policy Intensity Analysis Example

Using a machine learning algorithm, our team will leverage CivicInquire’s policy database to search for and analyze the policy intensity (e.g., alignment in scope, strategies, goals/outcomes) of the relevant housing and homelessness data. Outputs will allow advocates, practitioners, policymakers, and the public to:

Examine alignment between local/regional and provincial government to specific homelessness/housing policy strategies and governance approaches (e.g., emergency housing, community housing).

Comparatively explore points of convergence and divergence between housing/homeless policy approaches, strategies, goals etc. (e.g., policy time horizons, involved community partners) across Canadian cities of varied sizes.

Quantify policy alignment in reference to the inclusion and consideration of various intersectional factors relevant to housing/homelessness (e.g., family structure, gender, veteran/immigrant status).