  The present paper is concerned with the question of how falsifiable a single
proposition is in the short and long run. Formal Learning theorists such as
Schulte and Juhl have argued that long-run falsifiability is characterized by
the topological notion of nowhere density in a suitable topological space. I
argue that the short-run falsifiability of a hypothesis is in turn
characterized by the VC finiteness of the hypothesis. Crucially, VC finite
hypotheses correspond precisely to definable sets in NIP structures. I end the
chapter by giving rigorous foundations for Mayo's conception of severe testing
by way of a combinatorial, non-probabilistic notion of surprise. VC finite
hypotheses again appear as the hypotheses with guaranteed short-run surprise
bounds. Therefore, NIP theories and VC finite hypotheses capture the notion of
short-run falsifiability.
