Thanks for that very good question.
We have employed three professors from York University who are experts in this and who have helped us put together this race-based standard. They've looked at it cross-jurisdictionally, internationally, and otherwise as to what is the best way to slice and dice and to have this conversation. We've come up with a draft standard that has a series of categories, which frankly are bringing us more into the 21st century, versus our 19th century nomenclature that we're all stuck with. That's the first thing.
To that, we're adding things like intersectionality. We're adding things like the identity-based information as well. All of this is tied to.... Because the standard is not just about collecting, but about what you do with the information and how you analyze this information, one of the things we're looking at, for example, relative to the black community in our anti-black racism strategy is, how do we reduce disparities?
There are, and I don't want to get too theoretical here, mathematical models and formulas that say given this kind of dataset and given what you're seeing here, if you want to solve this problem, there are disparity indices and so on. There is a science behind this. This is not soft stuff. There are people who are practising this. There's a lot of good evidence in those jurisdictions in the U.S. that I pointed to.
It's not a perfect science. All we're saying is that we need to bring in a new methodology and a framework that recognizes our society today. We then look at these disparities and ask how we remove these disparities. Then there's a very calculated way in which you approach that. The data then adds to your programming, your investments, and so on, and then you reduce those disparities.