Theory before the test: How to build high-verisimilitude explanatory theories in psychological science
SourcePerspectives on Psychological Science, 16, 4, (2021), pp. 682-697
Article / Letter to editor
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SW OZ DCC AI
Perspectives on Psychological Science
SubjectCognitive artificial intelligence
Drawing on the philosophy of psychological explanation, we suggest that psychological science, by focusing on effects, may lose sight of its primary explananda: psychological capacities. We revisit Marr's levels-of-analysis framework, which has been remarkably productive and useful for cognitive psychological explanation. We discuss ways in which Marr's framework may be extended to other areas of psychology, such as social, developmental, and evolutionary psychology, bringing new benefits to these fields. We then show how theoretical analyses can endow a theory with minimal plausibility even before contact with empirical data: We call this the theoretical cycle. Finally, we explain how our proposal may contribute to addressing critical issues in psychological science, including how to leverage effects to understand capacities better.
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