Enumeration of small collections violates Weber's law.

In a phenomenon called subitizing, we can immediately generate exact counts of small collections (one to three objects), in contrast to larger collections, for which we must either create rough estimates or serially count. A parsimonious explanation for this advantage for small collections is that noisy representations of small collections are more tolerable, due to the larger relative differences between consecutive numbers (e.g., 2 vs. 3 is a 50 % increase, but 10 vs. 11 is only a 10 % increase). In contrast, the advantage could stem from the fact that small-collection enumeration is more precise, relying on a unique mechanism. Here, we present two experiments that conclusively showed that the enumeration of small collections is indeed "superprecise." Participants compared numerosity within either small or large visual collections in conditions in which the relative differences were controlled (e.g., performance for 2 vs. 3 was compared with performance for 20 vs. 30). Small-number comparison was still faster and more accurate, across both "more-fewer" judgments (Exp. 1), and "same-different" judgments (Exp. 2). We then reviewed the remaining potential mechanisms that might underlie this superprecision for small collections, including the greater diagnostic value of visual features that correlate with number and a limited capacity for visually individuating objects.