I think we need to subjugate our data. One of the challenges, and one of my colleagues said this.... For example, I did a study where I looked at the mental health of immigrant and non-immigrant kids in Canada. When you look at all of the data together, everything gets clouded, but then when you start to disaggregate it.... The problem is that when you go, for example, to the Canadian health measures survey, which I try to use, you cannot disaggregate the data. The analysis is just not possible.
When you go to the Canadian community health survey, which has the largest sample size, and in which you may be able to disaggregate the data, they do not collect data on children who are less than 12 years old. Maybe that's one of the places that we need to begin to start collecting data.
My colleague talked about the longitudinal survey of immigrant children and youth, which also provided disaggregated data related to immigrants in Canada, and there was another national study. However, many of those longitudinal studies have been discontinued.
For example, when you look at much of the small-reach longitudinal data across Canada, some of the challenges are that the sample size for the racialized population is so small.
I'm currently doing a study for the Public Health Agency of Canada, looking at how race-based data is collected for black populations in Canada. There are culturally appropriate ways that we must infuse into our race-based data collection to ensure that we have appropriate sample sizes. Right now, at least with the Canadian health measures survey and the Canadian community health survey, the percentage of black, racialized immigrant population interviewed in those surveys is less than the percentage they represent of the Canadian population. That has to change and we need to be able to disaggregate that data.