Not just empirically but scientifically

This came up in a recent post:

We should be understanding them [prediction markets] empirically–or, I should say, scientifically, combining empirics and theory, since neither alone will do the job–, not just blindly following pro- or anti-market ideology. As Rajiv says, the markets are out there already, and we can learn from them.

What I want to highlight here is not the topic of prediction markets, interesting as it is, but rather the distinction between “empirically” and “scientifically.” We’ll typically talk about empirical evaluation and empirical understanding, but the data just about never stand alone: you need a model to tie them to the underlying questions you’re asking.

So I’d prefer to talk about evaluating and understanding systems “scientifically” rather than “empirically.”

This is not just words! I think that framing the problem as scientific rather than empirical can also change how we do things, by putting some of the focus on theory. So much of the discussion of the replication crisis is about data, but consider all the problems that arise from absent or defective theory.