Is a question I thought as dead as a Dodo. When I came upon it in an undergraduate philosophy of science class the drums had been muffled and the mourners called. Nevertheless, there are still those who persist in resuscitating the corpse (see here for a recent example) and those, who for noble reasons, indulge them by responding.
There were, and are two good reasons for why this question should be left to rot in peace. The first is that the comparisons made to arrive at a demarcation are problematic. If Science were a country, Physics might be its capital. If one were to ask whether History is a Science, the customary thing to do is to measure the proximity of History to Science’s capital city. Why proximity to the capital and not to one of its outlying settlements like Geology and Archaeology? The second, better reason, is that the question, `is X a science?’ is of interest only if we believe that scientific knowledge should be privileged in some way. Perhaps it alone is valid and useful while nonscientific knowledge is not. If that is the case, the correct question should not be whether X is a science, but whether X produces knowledge that is valid and useful. Now we have something interesting to discuss: what constitutes useful or valid knowledge?
One might point to accurate prediction, but this alone cannot be the touchstone. How would we feel about the laws of Newtonian motion if we came upon them via regression? I suspect many of us would find such a theory to be incomplete, not least because of the concern with out of sample prediction. By the way, if you think this outlandish, I first learnt Newton’s laws by sending little carts down inclines with bits of ticker tape attached to them to so that we might, by induction, learn a linear relationship between velocity and acceleration. Truth be told, the Physics was sometimes lost in the enormous fun of racing the carts when the master’s back was turned. What if prediction is probabilistic rather than deterministic? In earlier posts on this blog you will find lengthy discussions of the problems associated with evaluating the accuracy of such predictions. I mention all this to hint at how difficult it is to pin down precisely what constitutes useful, reliable or valid knowledge.