So can you break that down for us and help people understand what that means?

Yeah, we spent a lot of time thinking about and debating the pitfalls of forecasting because, of course, with a 75-year time horizon, which is necessary because of some of the threats that are changing slowly and have their big impacts in the future, you know, I think climate change, we depend very much on the forecasts or the scenarios being reasonable.

But we know from the history of forecasting that when your forecast can alter policy priorities, then you are in the territory that's sometimes called reflexivity or self-defeating or self-fulfilling forecasts.

Lots of names in different fields, but a well-understood problem.

And our solution to this was not to say we have a crystal ball and can predict how governments will respond and this is the pathway of the future for sure, but rather that we can do a better job if we bound the range of possible futures by using empirical approaches to say, what's the plausibly worst that can happen? and plausibly best, and it's that zone that we can end up influencing where we land.

And the difference between plausible best and worst we call amenable or amenable burden.

And the plausible part is also really key in that thinking and goes into the notion about amenable burden because we can dream up all sorts of scenarios, terrible scenarios, utopian scenarios, But we want to ground our plausible best and worst in what we've observed across all countries in the past 35 years or so where we have good data.

And how does education shape health and even the size of the world's population?