Overview
For years, Statistics Canada has been providing Canadians with big picture statistics on a variety of topics impacting people across the country. However, the big picture can hide key differences in the experiences of specific population groups.
While inequities across population groups have long been recognized, the COVID-19 pandemic highlighted how a single event can be experienced differently across various groups, revealing uneven social and economic realities. This underscored the importance of having more detailed and representative data.
In response to this need for more granular evidence, the Government of Canada announced and funded the Disaggregated Data Action Plan (DDAP) through Budget 2021, establishing a long-term commitment to improving disaggregated and intersectional data across the federal system. Led by Statistics Canada, the DDAP is a whole-of-government initiative to increase and improve the availability of detailed statistics on diverse populations, and to support more representative data collection methods.
These increased and improved disaggregated statistics will give all levels of government, businesses, policy specialists, data users, non-for-profit organizations, and all Canadians the level of detail they need to make evidence-based decisions. By informing policy and program development, this work supports ongoing efforts to address systemic racism, gender gaps and other inequities to help create a more equitable Canada.
DDAP target audience
The DDAP targets the four employment equity groups:
- Indigenous Peoples (First Nations, Métis and Inuit)
- Women
- Racialized populations (various subgroups)
- Persons with disabilities (various subgroups)
However, where relevant and possible, disaggregation is extended to other groups, such as, but not limited to, sexual orientation, children and youth, seniors, official language minority communities, immigrants, low-income Canadians.
DDAP's four guiding principles
Disaggregation:
Data will be disaggregated at the lowest level of population detail possible, while including Gender-based Analysis Plus (GBA Plus) considerations and respecting quality and confidentiality.
Intersectionality:
Analysis will focus on intersectionality (e.g., young, Black, women) as opposed to dual combinations (e.g., young, women).
Standards:
Statistics Canada's approved standards will be used for disaggregation across all programs.
Geography:
Data will be released at the lowest level of geography possible.
How do we produce more detailed data?
First, Statistics Canada securely combines its census and survey data with data already collected by federal, provincial or territorial organizations. Data from other organizations are called 'administrative data' and this process of data combination is called 'data linkage'. Data linkages create an opportunity to access more accurate information and conduct comprehensive analyses. They also reduce the number of surveys Canadians are asked to complete.
After creating data linkages, data are then broken down (or disaggregated) into sub-categories according to a combination of gender, race, sexual orientation, disability, and geography. Through this disaggregation, Statistics Canada can increase insights on diverse groups of people, to support evidence-based decision-making.
Keeping your data safe
All information collected through Statistics Canada's censuses and surveys, as well as administrative data from third parties, is protected by law under the Statistics Act, the Access to Information Act and the Privacy Act. We take the confidentiality and privacy of Canadians very seriously.
