Similarity is universally acknowledged to be central in transfer, but recent research suggests that its role is complex. The present research attempts to isolate and compare the determinants of similarity-based access to memory and the determinants of the subjective soundness and similarity of a match. We predicted, based on structure-mapping theory, that subjective soundness would depend on the degree of shared relational structure, particularly higher-order structure such as causal bindings. In contrast, we predicted that memory retrieval would be highly sensitive to surface similarities such as common object attributes. To assess retrievability, in three studies, subjects were asked to read a large set of stories and were later given a set of probe stories that resembled the original stories in systematically different ways; e.g., purely relational analogies, surface-similarity matches, or overall (literal similarity) matches. Subjects were told to write out any of the original stories that came to mind. To assess subjective soundness, independent subjects (and also the same reminding subjects) were asked to rate the inferential soundness of each pair; i.e., how well inferences true of one story would apply to the other. As predicted, subjective soundness was highly related to the degree of common relational structure, while retrievability was chiefly related to the degree of surface similarity. Ratings of the similarity of the pairs did not predict the retrievability ordering, arguing against the possibility that the retrieval ordering simply reflected overall similarity. Further, a fourth study demonstrated that subjects given a forced-choice recognition task could discriminate between possible matches on the basis of relational structure, ruling out the possibility that the poor relational retrieval resulted from forgetting or failing to encode the relational structure. We conclude that there is a dissociation between the similarity that governs access to long-term memory and that which is used in evaluating and reasoning from a present match. We describe a model, called MAC/FAC ("Many are called but few are chosen"), that uses a two-stage similarity retrieval process to model these findings. Finally, we speculate on the implications of this view for learning and transfer.
