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The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Russian blues reveal effects of language on color discrimination

Open access
Winawer, Jonathan, Witthoft, Nathan, Frank, Michael C., Wu, Lisa, Wade, Alex R., Boroditsky, Lera·2007·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.0701644104
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Abstract

English and Russian color terms divide the color spectrum differently. Unlike English, Russian makes an obligatory distinction between lighter blues (“goluboy”) and darker blues (“siniy”). We investigated whether this linguistic difference leads to differences in color discrimination. We tested English and Russian speakers in a speeded color discrimination task using blue stimuli that spanned the siniy/goluboy border. We found that Russian speakers were faster to discriminate two colors when they fell into different linguistic categories in Russian (one siniy and the other goluboy) than when they were from the same linguistic category (both siniy or both goluboy). Moreover, this category advantage was eliminated by a verbal, but not a spatial, dual task. These effects were stronger for difficult discriminations (i.e., when the colors were perceptually close) than for easy discriminations (i.e., when the colors were further apart). English speakers tested on the identical stimuli did not show a category advantage in any of the conditions. These results demonstrate that (i) categories in language affect performance on simple perceptual color tasks and (ii) the effect of language is online (and can be disrupted by verbal interference).

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Metadata

Authors
Winawer, J., Witthoft, N., Frank, M. C., Wu, L., Wade, A. R., & Boroditsky, L.
Venue
Proceedings of the National Academy of Sciences
Publisher
Proceedings of the National Academy of Sciences
Published
2007-05-08
Volume
104
Issue
19
Pages
7780-7785
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.0701644104
OpenAlex
W2140053249
Cited by
1,021
References
25
FWCI
38.80
Type
journal article
Language
en
Open access
green

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