The Importance of Religious Displays for Belief Acquisition and Secularization

Both the sociology and the cognitive science of religion seek to explain the acquisition of religious beliefs. In this article, I offer an account of the acquisition and distribution of religious beliefs using the findings of both fields. In the process, I seek to illustrate the potential of interdisciplinary dialogue for improving our understanding of religion and its absence. More specifically, I present a prima facie case—based on existing work in the social and cognitive sciences, exploratory online surveys, and participant observation—that witnessing actions attesting to religious claims is one of the most crucial variables determining whether or not an individual will explicitly believe such claims. Further, I argue that the connection between action and belief can help produce an improved account of secularization and non-theism, defined here as the lack of explicit belief in the existence of non-physical agents.

Strudel: A corpus-based semantic model based on properties and types

Computational models of meaning trained on naturally occurring text successfully model human performance on tasks involving simple similarity measures, but they characterize meaning in terms of undifferentiated bags of words or topical dimensions. This has led some to question their psychological plausibility (Murphy, 2002; Schunn, 1999). We present here a fully automatic method for extracting a structured and comprehensive set of concept descriptions directly from an English part-of-speech-tagged corpus. Concepts are characterized by weighted properties, enriched with concept-property types that approximate classical relations such as hypernymy and function. Our model outperforms comparable algorithms in cognitive tasks pertaining not only to concept-internal structures (discovering properties of concepts, grouping properties by property type) but also to inter-concept relations (clustering into superordinates), suggesting the empirical validity of the property-based approach. Copyright © 2009 Cognitive Science Society, Inc. All rights reserved.