> This isn't high risk though. It's low risk.
I meant "high risk" in the sense that the return has a high variance, with all of it being concentrated in a thin sliver of the probability; apologies if I've misused a technical term.
> The problem here is that you could make this same argument about almost anything, a la Pascal's Wager.
I'd call it a consequence of expected return being a widely-applicable calculation, rather than a "problem" per se. Even if we knew the expected returns, we'd still need a decision procedure to perform the allocation.
My point is that it's uncontroversial to avoid putting all funding into the most promising project (e.g. other Physics research doesn't wait until we're "finished" with the LHC), so there's certainly scope for allocating a small budget to more "fringe" research like the EmDrive. I'm not in charge of research budgets, but as a simplified argument we might imagine allocating funding on an exponential scale, based on expected return and risk: the most promising projects compete for a chunk of half the funds, the "second tier" projects for a quarter, and so on. Projects with lower impact are lower tier, projects with lower probability of success are lower tier. We stop once we've rounded-up an allocation to the smallest unit of funding, hence avoiding Pascal's Wager.
Also note that there are only a finite number of options to choose from, because there are only a finite number of submitted research proposals.