In my response I revisit the question whether internalization should be conceived as representation or as instantiation. Shepard's ingenuity lies partly in allowing both interpretations. The down side of this facile generality of internalization is its immunity to falsification. I describe evidence from 3-D apparent motion studies that speak against geodesic paths in cases of underspecified percepts. I further reflect on the applicability of internalization to normal, well-specified perception, on the superiority of Gestalt principles, as well as on the evolutionary and developmental implications of the concept. The commentaries to the target article reveal an astonishing lack of agreement. This not only indicates that a satisfactory unifying theory explaining perception in the face of poorly specified stimuli does not exist. It also suggests that for the time being we have to be pluralistic and should treat internalization as a source of inspiration rather than as an irrefutable theory.

We reply to Gerbino, Heschl, Hoffman, Jacobs et al., Kurthen, O'Brien & Opie, Todorovic, and Wilson. Several issues are clarified. We concede little.

By and large the commentators express reservations similar to my own concerning Shepard's position. Some focus on the issue of ecological validity, others are skeptical of Shepard's evolutionary thesis. The assumptions and reasons for their criticisms, however, are not always ones I fully accept. In addition, several commentators, although rejecting Shepard's particular claims, support his overall approach. They offer models for motion perception and for phenomena in other domains that they feel are amenable to treatment along Shepard's lines. I examine the pros and cons of the commentators' analyses of Shepard. I also briefly evaluate aspects of their alternative proposals.

We address two kinds of criticisms of our Bayesian framework for generalization: those that question the correctness or the coverage of our analysis, and those that question its intrinsic value. Speaking to the first set, we clarify the origins and scope of our size principle for weighting hypotheses or features, focusing on its potential status as a cognitive universal; outline several variants of our framework to address additional phenomena of generalization raised in the commentaries; and discuss the subtleties of our claims about the relationship between similarity and generalization. Speaking to the second set, we identify the unique contributions that a rational statistical approach to generalization offers over traditional models that focus on mental representation and cognitive processes.

The author does not wish to respond to the Commentators.