This blogpost doesn't say anything new – it just uses a new analogy (at least new to me) to make a point about the value of null results from well-designed studies. I was thinking about this after reading this blogpost by Anne Scheel.
Think of science like prospecting for kryptonite in an enormous desert. There's a huge amount of territory out there, and very little kryptonite. Suppose also that the fate of the human race depends crucially on finding kryptonite deposits.
Most prospectors don't find kryptonite. Not finding kryptonite is disappointing: it feels like a lot of time and energy has been wasted, and the prospector leaves empty-handed. But the failure is nonetheless useful. It means that new prospectors won't waste their time looking for kryptonite in places where it doesn't exist. If, however, someone finds kryptonite, everyone gets very excited and there is a stampede to rush to the spot where it was discovered.
Contemporary science works a bit like this, except that the whole process is messed up by reporting bias and poor methods which lead to false information.
To take reporting bias first: suppose the prospector who finds nothing doesn't bother to tell anyone. Then others may come back to the same spot and waste time also finding nothing. Of course, some scientists are like prospectors in that they are competitive and would like to prevent other people from getting useful information. Having a competitor bogged down in a blind alley may be just what they want for their rivals. But where there is an urgent need for new discovery, there needs to be a collaborative rather than competitive approach, to speed up discovery and avoid waste of scarce funds. In this context, null results are very useful.
False information can come from the prospector who declares there is no kryptonite on the basis of a superficial drive through a region. This is like the researcher who does an underpowered study that gets an inconclusive null result. It doesn't allow us to map out the region with kryptonite-rich and kryptonite-empty areas – it just leaves us having to go back and look again more thoroughly. Null results from poorly designed studies are not much use to anyone.
But the worst kind of false information is fool's kryptonite: someone declares they have found kryptonite, but they haven't. So everyone rushes off to that spot to try and find their own kryptonite, only to find they have been deceived. So there are a lot of wasted resources and broken hearts. For a prospector who has been misled in this way, this situation is worse than just not finding any kryptonite, because their hopes have been raised and they may have put a disproportionate amount of effort and energy into pursuing the false information.
Pre-registering a study is the equivalent of a prospectors declaring publicly that they are doing a comprehensive survey of a specific region, and will declare what they have found, so that the map can gradually be filled in, with no duplication of effort.
Some will say, what about exploratory research? Of course the prospector may hit lucky and find some other useful mineral that nobody had anticipated. If so, that's great, and it may even turn out more important than kryptonite. But the point I want to stress is that the norm for most prospectors is that they won't find kryptonite or anything else. Really exciting findings occur rarely, yet our current incentive structures create the impression that you have to find something amazing to be valued as a scientist. It would make more sense to reward those who do a good job of prospecting, producing results that add to our knowledge and can be built upon.
I'll leave the last word to Ottoline Leyser, who in an interview for The Life Scientific said: "There's an awful lot of talk about ground-breaking research…. Ground-breaking is what you do when you start a building. You go into a field and you dig a hole in the ground. If you're only rewarded for ground-breaking research, there's going to be a lot of fields with a small hole in, and no buildings."