Alice says: the p-value for the drug effectiveness is X. This means that there is X% probability that the results we see arose entirely by chance while the drug has no effect at all.
No. You don't understand null hypotheis testing. It doesn't measure whether the results arose entirely by chance. It measures whether a specifc null hypothsis can be rejected.
I hate to disappoint you, but I do understand null hypothesis testing. In this particular example the specific null hypothesis is that the drug has no effect and therefore all observable results arose entirely by chance.
For those who haven't heard, NIH and NSF are no longer processing grants, leading to many negative downstream effects.
I've been directing my attention elsewhere lately and don't have anything informative to say about this. However, my uninformed intuition is that people who care about effective altruism (research in general, infrastructure development, X-risk mitigation, life-extension...basically everything, actually) or have transhumanist leanings should be very concerned.
The consequences have already been pretty disastrous. To provide just one, immediate example, the article says that the Center for Disease Control and Prevention has shut down. I think that this is almost certain to directly cause a nontrivial number of deaths. Each additional day that this continues could have huge negative impact down the line, perhaps delaying some key future discoveries by years. This event *might* be a small window of opportunity to prevent a lot of harm very cheaply.
So the question is:
1) Can we do anything to remedy the situation?
2) If so, is it worth doing it? (Opportunity costs, etc)