The same cognitive mechanism underlies reasoning about the features of kinds and the traits of individuals
Year: 2014
Type: article
Abstract: Learning about categories of things in the world (e.g., that lions have manes) and learning about the individuals around us (e.g., that the new neighbor is friendly) are both crucial cognitive tasks whose output enables people to behave adaptively in many novel circumstances. Aside from their importance to our lives, however, these two tasks seem to have little in common: Reasoning about the features of categories appears to rely on a set of computations that is entirely distinct from those involved in reasoning about the traits of individuals. Consistent with this impression, these judgments have been studied in near-complete isolation. Here, however, we propose that inferences about the features of kinds and the traits of individuals are in fact computed by the same cognitive mechanism. To test this hypothesis, we investigated whether kind-feature and individual-trait inferences share two distinctive signatures: namely, whether they are both facilitated by features/behaviors that are (1) threatening or (2) unique. Five experiments provided evidence for this prediction. The results also suggested that these signatures were not shared by other types of inferences. That is, the information that facilitated participants’ kind-feature and individual-trait inferences did not similarly facilitate quantified inferences concerning whether all/some members of a kind display a feature and whether an individual always/sometimes performs a behavior. By suggesting that inferences about the features of kinds and the traits of individuals share a cognitive source, these studies open possibilities for dialogue between the independent research traditions that have investigated these important aspects of human thought.
Author: Lin Bian
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2593201455
