The division of cognitive labor is fundamental to all cultures. Adults have a strong sense of how knowledge is clustered in the world around them and use that sense to access additional information, defer to relevant experts, and ground their own incomplete understandings. One prominent way of clustering knowledge is by disciplines similar to those that comprise the natural and social sciences. Seven studies explored an emerging sense of these discipline-based ways of clustering of knowledge. Even 5-year-olds could cluster knowledge in a manner roughly corresponding to the departments of natural and social sciences in a university, doing so without any explicit awareness of those academic disciplines. But this awareness is fragile early on and competes with other ways of clustering knowledge. Over the next few years, children come to see discipline-based clusters as having a privileged status, one that may be linked to increasingly sophisticated assumptions about essences for natural kinds. Possible mechanisms for this developmental shift are examined.

A number of researchers and scholars have stressed the importance of disconfirmation in the quest for the development of scientific knowledge (e.g., Popper, 1959). Paradoxically, studies examining human reasoning in the laboratory have typically found that people display a confirmation bias in that they are more likely to seek out and attend to data consistent rather than data inconsistent with their initial theory (Wason, 1968). We examine the strategies that scientists and students use to evaluate data that are either consistent or inconsistent with their expectations. First, we present findings from scientists reasoning "live" in their laboratory meetings. We show that scientists often show an initial reluctance to consider inconsistent data as "real." However, this initial reluctance is often overcome with repeated observations of the inconsistent data such that they modify their theories to account for the new data. We further examine these issues in a controlled scientific causal thinking simulation specifically developed to examine the reasoning strategies we observed in the natural scientific environment. Like the scientists, we found that participants in our simulation initially displayed a propensity to discount data inconsistent with a theory provided. However, with repeated observations of the inconsistent data, the students, like the scientists, began to see the once anomalous data as "real" and the initial bias to discount that data was significantly diminished. Science ... warns me to be careful how I adopt a view which jumps with my preconceptions, and to require stronger evidence for such belief than for one to which I was previously hostile. My business is to teach my aspirations to conform themselves to fact, not to try and make facts harmonize with my aspirations.

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