A fundamental question in the study of human cognition is how people learn to predict the category membership of an example from its properties. Leading approaches account for a wide range of data in terms of comparison to stored examples, abstractions capturing statistical regularities, or logical rules. Across three experiments, participants learned a category structure in a low‐dimension, continuous‐valued space consisting of regularly alternating regions of class membership (A B A B). The dependent measure was generalization performance for novel items (...) outside the range of the training space. Human learners often extended the alternation pattern––a finding of critical interest given that leading theories of categorization based on similarity or dimensional rules fail to predict this behavior. In addition, we provide novel theoretical interpretations of the observed phenomenon. (shrink)

Huttenlocher et al. (J Exp Psychol Gen 129:220–241, 2000) introduce the category adjustment model (CAM). Given that participants imperfectly remember stimuli (which we refer to as “targets”), CAM holds that participants maximize accuracy by using information about the distribution of the targets to improve their judgments. CAM predicts that judgments will be a weighted average of the imperfect memory of the target and the mean of the distribution of targets. Huttenlocher et al. (2000) report on three experiments and conclude that (...) CAM is “verified”. We attempt to replicate the conditions in Experiment 3 from Huttenlocher et al. (2000). We analyze judgment-level data rather than averaged data. We find evidence of a bias toward a set of recent targets rather than a bias toward the running mean. We do not find evidence of learning. The judgments in our dataset are not consistent with CAM. We discuss other defects in HHV—including dividing by zero. It seems that evidence for CAM is a statistical artifact that appears when researchers analyze data averaged across trials and do not consider a recency bias. (shrink)

A vexing problem in contemporary epistemology—one with origins in Plato’s Meno—concerns the value of knowledge, and in particular, whether and how the value of knowledge exceeds the value of mere true opinion. The recent literature is deeply divided on the matter of how best to address the problem. One point, however, remains unquestioned: that if a solution is to be found, it will be at the personal level, the level at which states of subjects or agents, as such, appear. We (...) take exception to this orthodoxy, or at least to its unquestioned status. We argue that subpersonal states play a significant—arguably, primary—role in much epistemically relevant cognition and thus constitute a domain in which we might reasonably expect to locate the “missing source” of epistemic value, beyond the value attached to mere true belief. (shrink)