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Canada up close: What we can learn from disaggregated data

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Released: 2020-09-10

With the COVID-19 pandemic and global protests at the forefront of the news, there is a greater sense of urgency to gathering data on the most vulnerable populations.

Now more than ever, there is a need for disaggregated data on visible minority groups.

This month, the StatCan Blog features an article, "Canada up Close: What We Can Learn From Disaggregated Data," on how Statistics Canada has been working to leverage the power of disaggregated data to collect key information on vulnerable groups.

  Note to readers

Aggregated data refers to large-scale data summaries and reports. Disaggregated data is data that has been divided into categories, such as region, gender and ethnicity. Providing this type of data can reveal inequalities between different population groups that aggregated data cannot.

The following articles, which are based on disaggregated data, are available: "Experiences of violent victimization and unwanted sexual behaviours among gay, lesbian, bisexual and other sexual minority people, and the transgender population, in Canada, 2018," "Perceptions of personal safety among population groups designated as visible minorities in Canada during the COVID-19 pandemic," "Economic impact of COVID-19 among Indigenous people" and "Changes in the socioeconomic situation of Canada's Black population, 2001 to 2016."

More information is also available online in Statistics Canada and disaggregated data, the Gender, Diversity and Inclusion Statistics Hub and COVID-19: A data perspective.


The article, "Canada up Close: What We Can Learn From Disaggregated Data" is now available on the StatCan Blog.

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