Memory Errors Reveal a Bias to Spontaneously Generalize to Categories

Autor/inn/en	Sutherland, Shelbie L.; Cimpian, Andrei; Leslie, Sarah-Jane; Gelman, Susan A.
Titel	Memory Errors Reveal a Bias to Spontaneously Generalize to Categories
Quelle	In: Cognitive Science, 39 (2015) 5, S.1021-1046 (26 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0364-0213
DOI	10.1111/cogs.12189
Schlagwörter	Memory; Bias; Generalization; Classification; Cognitive Processes; Difficulty Level + Suchen Sie Ihr Suchwort? Gedächtnis; Classification system; Klassifikation; Klassifikationssystem; Cognitive process; Kognitiver Prozess; Schwierigkeitsgrad
Abstract	Much evidence suggests that, from a young age, humans are able to generalize information learned about a subset of a category to the category itself. Here, we propose that--beyond simply being able to perform such generalizations--people are "biased" to generalize to categories, such that they routinely make spontaneous, implicit category generalizations from information that licenses such generalizations. To demonstrate the existence of this bias, we asked participants to perform a task in which category generalizations would distract from the main goal of the task, leading to a characteristic pattern of errors. Specifically, participants were asked to memorize two types of novel facts: quantified facts about sets of kind members (e.g., facts about "all" or "many stups") and generic facts about entire kinds (e.g., facts about "zorbs" as a kind). Moreover, half of the facts concerned properties that are typically generalizable to an animal kind (e.g., eating fruits and vegetables), and half concerned properties that are typically more idiosyncratic (e.g., getting mud in their hair). We predicted that--because of the hypothesized bias--participants would spontaneously generalize the quantified facts to the corresponding kinds, and would do so more frequently for the facts about generalizable (rather than idiosyncratic) properties. In turn, these generalizations would lead to a higher rate of quantified-to-generic "memory errors" for the generalizable properties. The results of four experiments (N = 449) supported this prediction. Moreover, the same generalizable-versus-idiosyncratic difference in memory errors occurred even under cognitive load, which suggests that the hypothesized bias operates unnoticed in the background, requiring few cognitive resources. In sum, this evidence suggests the presence of a powerful bias to draw generalizations about kinds. (As Provided).
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Update	2020/1/01