We have a real diversity of citizen science programs. Some are very structured and more rigorous, and others are more entry-level programs to engage the next people into science and citizen science. With all of those programs, a unifying factor is that data quality is taken very seriously. There have been hundreds and thousands of scientific papers published citing citizen science data. The reason for that is that it is now broadly accepted that this is high-quality data, and it has become a cornerstone in the biological field.
As an example of what we do internally for our programs, whether they're breeding bird atlases, the Canadian lakes loon survey or eBird—we manage eBird and the Christmas bird count in Canada—we use rigorously tested protocols. We provide intensive training, we incorporate data filters, we regularly review data quality and, very importantly, we implement onboarding for volunteers to move to more challenging programs as they go. All of this is to enhance the experience for the volunteers, but it also allows us to collect rigorous data so we can have an impact on birds. Especially with onboarding and getting more people to take on more complex citizen science programs, that enables us to collect even more relevant and more pertinent data to help make big conservation decisions.