Recently I’ve been finding that I really don’t care if I’m right. What I mean is: I don’t care if a hypothesis I’ve come up with turns out to be correct. That theory paper about nonadaptive causes of social competition really brought this up. I do care about formulating a hypothesis well, presenting it clearly, empirically testing it in a way that gives it a fair chance to succeed or to fail, and making sure that my conclusions are justified by my data. But whether a hypothesis turns out to be true? That’s up to nature. The data are what the data are.

The way I see it, if I formulate a hypothesis well, then it’s a reasonable possibility for how things work. If I hadn’t thought of it, I’d want somebody else to. And I’d want to know whether it’s right or wrong whether it was originally my idea or not. That’s one of the main ways we make progress in science—by lining up and knocking down hypotheses until what’s left just won’t fall.

Of course, it’s way easier to publish positive results, so being right makes the mechanics of science productivity a lot simpler. In practice, what usually happens is that a hypothesis is kind of right, in some circumstances, but not the whole story.