Behavior Research Methods

, Volume 37, Issue 4, pp 547–559 | Cite as

Semantic feature production norms for a large set of living and nonliving things

  • Ken McRae
  • George S. Cree
  • Mark S. Seidenberg
  • Chris Mcnorgan


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


Semantic Memory Semantic Feature Feature Norm Dyslexia Feature Correlation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Psychonomic Society, Inc. 2005

Authors and Affiliations

  • Ken McRae
    • 1
  • George S. Cree
    • 2
  • Mark S. Seidenberg
    • 3
  • Chris Mcnorgan
    • 1
  1. 1.Department of Psychology, Social Science CentreUniversity of Western OntarioLondonCanada
  2. 2.University of TorontoScarboroughCanada
  3. 3.University of WisconsinMadison

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