Russian blues reveal the limits of language influencing colour discrimination

Jasna Martinovic*, Galina V. Paramei, W. Joseph MacInnes

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
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Chromatic stimuli across a boundary of basic colour categories (BCCs; e.g. blue and green) are discriminated faster than colorimetrically equidistant colours within a given category. Russian has two BCCs for blue, sinij ‘dark blue’ and goluboj ‘light blue’. These language-specific BCCs were reported to enable native Russian speakers to discriminate cross-boundary dark and light blues faster than English speakers (Winawer et al., 2007, PNAS, 4, 7780-7785). We re-evaluated this finding in two experiments that employed identical tasks as in the cited study. In Experiment 1, Russian and English speakers categorised colours as sinij/goluboj or dark blue/light blue respectively; this was followed by a colour discrimination task. In Experiment 2, Russian speakers initially performed the discrimination task on sinij/goluboj and goluboj/zelënyj ‘green’ sets. They then categorised these colours in three frequency contexts with each stimulus presented: (i) an equal number of times (unbiased); more frequent (ii) either sinij or goluboj; (iii) either goluboj or zelënyj. We observed a boundary response speed advantage for goluboj/ zelënyj but not for sinij/goluboj. The frequency bias affected only the sinij/goluboj boundary such that in a lighter context, the boundary shifted towards lighter shades, and vice versa. Contrary to previous research, our results show that in Russian, stimulus discrimination at the lightnessdefined blue BCC boundary is not reflected in processing speed. The sinij/goluboj boundary did have a sharper categorical transition than the dark blue/light blue boundary, but it was also affected by frequency and order biases, demonstrating that “Russian blues” are less wellstructured than previously thought.
Original languageEnglish
Article number104281
Pages (from-to)1-15
Number of pages15
Early online date7 Apr 2020
Publication statusPublished - Aug 2020

Bibliographical note

JM’s work was partly supported by the DAAD re-invitation programme for former scholarship holders. The authors are grateful to Alexander Belokopytov and Galina I. Rozhkova for their generous colorimetric assistance and to Karin Tuur, Daria Tusheva and Carl Wollter for help with data collection. JM would like to thank Agnieszka Konopka and Matt Craddock for advice on data analysis and plotting in R and Christoph Witzel for suggesting the analyses of RT distributions. Finally, we would like to thank Jonathan Winawer, two other, anonymous, reviewers, and Jacob Feldman, Associate Editor, for constructive comments that greatly helped in improving our work.

CRediT authorship contribution statement
Jasna Martinovic:Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration, Funding acquisition.Galina V. Paramei:Conceptualization, Methodology, Writing - review & editing.W. Joseph MacInnes:Validation, Formal analysis, Investigation, Resources, Writing - review & editing, Visualization, Supervision.


  • colour categorisation
  • cross-linguistic
  • Russian blues
  • Whorfian effect
  • lightness
  • hue
  • Cross-linguistic
  • Lightness
  • Colour categorisation
  • Hue
  • HUE


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