Note—This article was accepted by the previous editor, Jonathan Vaughan.
Abstract
Semantic features have provided insight into numerous behavioral phenomena concerning concepts, categorization, and semantic memory in adults, children, and neuropsychological populations. Numerous theories and models in these areas are based on representations and computations involving semantic features. Consequently, empirically derived semantic feature production norms have played, and continue to play, a highly useful role in these domains. This article describes a set of feature norms collected from approximately 725 participants for 541 living (dog) and nonliving (chair) basic-level concepts, the largest such set of norms developed to date. This article describes the norms and numerous statistics associated with them. Our aim is to make these norms available to facilitate other research, while obviating the need to repeat the labor-intensive methods involved in collecting and analyzing such norms. The full set of norms may be downloaded from www.psychonomic.org/archive.
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This work was supported by Natural Sciences and Engineering Research Council Grant OGP0155704 and NIH Grants R01-DC0418 and R01-MH60517 to K.M., an Ontario Graduate Scholarship and a Natural Sciences and Engineering Council Doctoral Fellowship to G.S.C., Grants NICHD 29891 and NIMH K02-01188 to M.S.S., and a SharcNet Graduate Student Fellowship to C.M. When using these norms, please refer both to this article and to the grants that supported it.
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McRae, K., Cree, G.S., Seidenberg, M.S. et al. Semantic feature production norms for a large set of living and nonliving things. Behavior Research Methods 37, 547–559 (2005). https://doi.org/10.3758/BF03192726
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DOI: https://doi.org/10.3758/BF03192726