Canada up Close: What We Can Learn From Disaggregated Data
If you watch enough television, you might believe that we live in a violent world. Nightly entertainment is packed with stories about murder and violence, particularly gun violence.
But the statistics tell a different story—homicide rates have been falling across Canada since the 1970s.
What the overall statistics do not tell you is that Toronto had the most homicides of any Canadian city in 2018. Nor do they tell you that the majority of homicides in Canada are committed by an acquaintance (34%) or a family member (33%). They do not tell you that the rate of Indigenous homicide victims remains approximately five times higher than the rate of non-Indigenous victims.
Unless you are able to filter and sift through the sea of data, you may be under the assumption that crime is pretty much the same everywhere.
Similarly, if you looked at the data available on COVID-19 from across Canada, you would be able see patterns—infections, hospitalizations, deaths—emerge as a big, national picture. But you would not know what was happening at your local hospital.
Early COVID-19 data clearly showed that some groups are much more vulnerable to the virus than other groups. As the pandemic progressed, the inequities became more apparent and the need to address them more urgent.
What if you need more detail?
Within that big national picture are many, many smaller pictures of communities, ethnic groups, life stages, gender and occupations. Different groups—big, small and all sizes in between—each have different experiences, and each may experience varying levels of crime, homelessness, mental health concerns, poverty, domestic violence, academic success or tendency to a specific illness.
The aggregate national picture encompasses tales from across the country to tell a big complete story.
To get a more specific small picture, statisticians disaggregate the data.
That means taking carefully gathered and aggregated data—the critical step to make sure that everyone's data is lumped together and kept anonymous—and stepping back to look at data for various populations by breaking down large-scale datasets into sub-categories such as region, gender or ethnicity or a combination of these sub-categories.
The secret in the exercise is to make sure to maintain people's anonymity, even as you are finding the stories that only disaggregated data can tell about the gaps and inequities that may exist in our society.
Disaggregation is all made possible by evolved statistical techniques and standards to ensure data comparability.
Statistics Canada has been working to leverage the power of disaggregated data to come up with a nuanced picture of the diverse groups of people who share the same characteristics.
Otherwise, you are only making inferences about individuals based on the inferences about the larger group.
Ramping up efforts
Statisticians must ask the right questions and collect data effectively so that the data can be accurately disaggregated.
If you are a Métis, First Nations or Inuit leader, you need disaggregated data to get a clear picture of how your specific community is affected by a sudden jolt to the labour market. A member of the LGBTQ2 community can use the agency's disaggregated data to look at issues of gender and equality. Immigration analysts can find information to understand how refugees are faring economically relative to their Canadian-born counterparts.
And, criminal justice experts can track how the justice system serves people from different ethnocultural backgrounds so that policies can be developed that best serve the needs of each community.
Good policy and informed decisions come from understanding how each member of the diverse Canadian family is affected by their changing world. The big picture is important, but sometimes it may be hiding inequities and differences that, if not addressed, make some Canadian communities more challenged than others.
The current advances in disaggregation are but one example of how Statistics Canada continues to review its data programs to ensure that they remain relevant to the evolving interests of all Canadians.
To learn more, check out Statistics Canada and disaggregated data.
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