Gender differences in colour naming

Mylonas, Dimitris; Paramei, Galina V.; MacDonald, Lindsay W.

doi:10.1075/z.191.15myl

Cited by 20 publications

(48 citation statements)

References 32 publications

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“…, p 95). Greater response latencies for written recording of color names are indirectly confirmed by results of the online color‐naming experiments which recorded onset RTs for typing a term, with median RTs for BCTs varying between 3 and 5 sec …”

Section: Resultsmentioning

confidence: 68%

“…Further 11 non‐BCTs were used consistently by at least one subject: fucsia, celeste, ocra, lilla, bordeaux, magenta, vinaccia, violetto, amaranto, salmone , and panna . This number of consistently used non‐BCTs is comparable to English sources: 13, 10, or 14 . Notably, the consistently used English non‐BCTs include turquoise, peach, beige, olive, and lime , but this is not the case for their Italian counterparts used inconsistently: turchese “turquoise,” pesca “peach,” beige, oliva “olive,” and lime .…”

Section: Resultsmentioning

confidence: 73%

“…The relatively low number of elicited non‐BCTs in the present study—and, as a corollary, higher consistency of their use—may be attributed to two factors: (i) overrepresentation of males (12 out of 16 subjects), manifesting a gender effect in color naming, i.e., significantly lower usage of non‐BCTs by men compared to women [cf. almost equal gender split in Refs.…”

Section: Resultsmentioning

confidence: 90%

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Color naming in Italian language

Paggetti

Menegaz

Paramei

2015

Color Research & Application

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The present study investigated Italian basic color terms (BCTs). It is an extension of our previous work that explored Italian basic color categories (BCCs) using a constrained colornaming method, with 11 Italian BCTs allowed, including blu for naming the BLUE area. Since a latter outcome indicated a categorization bias, here monolexemic color-naming method was employed, enabling also use of azzurro, deeply entrenched Italian term that designates light blue. In Experiment 1, colors (N=367), sampling the Munsell Mercator projection, were presented on a CRT; color names and reaction times of vocalization onset were recorded. Naming consistency and consensus were estimated. Consistency was obtained for 12 CTs, including the two blue terms; consensus was found for 11 CTs, excluding rosso 'red'. For each consensus category, color with the shortest RT was considered focal. In Experiment 2, consensus stimuli (N=72) were presented; on each trial, observers indicated the focal color ("best example") in an array of colors comprising a consensus category. For each of the 12 Italian CCs, centroid was calculated and focal color (two measures) estimated. Compared to English color terms, two outcomes are specific to Italian color naming: (i) naming of the RED-PURPLE area is highly refined, with consistent use of emergent non-BCTs; (ii) azzurro and blu both perform as BCTs dividing the BLUE area along the lightness dimension. The findings are considered in the framework of the weak relativity hypothesis. Historico-linguistic, environmental and pragmatic communication factors are discussed that conceivably have driven the extension of the BCT inventory in Italian.

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Section: Resultsmentioning

confidence: 68%

Section: Resultsmentioning

confidence: 73%

Section: Resultsmentioning

confidence: 90%

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Color naming in Italian language

Paggetti

Menegaz

Paramei

2015

Color Research & Application

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“…Gender differences in color lexicon have been demonstrated in numerous English‐language studies (for recent reviews see refs. and ). Women possess a more extensive color vocabulary than men .…”

Section: Introductionmentioning

confidence: 96%

An online color naming experiment in Russian using Munsell color samples

2017

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Russian color naming was explored in a web-based experiment. The purpose was 3-fold: to examine (1) CIELAB coordinates of centroids for 12 Russian basic color terms (BCTs), including 2 Russian terms for "blue", sinij "dark blue", and goluboj "light blue", and compare these with coordinates for the 11 English BCTs obtained in earlier studies; (2) frequent nonBCTs; and (3) gender differences in color naming. Native Russian speakers participated in the experiment using an unconstrained colornaming method. Each participant named 20 colors, selected from 600 colors densely sampling the Munsell Color Solid. Color names and response times of typing onset were registered. Several deviations between centroids of the Russian and English BCTs were found. The 2 "Russian blues", as expected, divided the BLUE area along the lightness dimension; their centroids deviated from a centroid of English blue. Further minor departures were found between centroids of Russian and English counterparts of "brown" and "red". The Russian color inventory confirmed the linguistic refinement of the PURPLE area, with high frequencies of nonBCTs. In addition, Russian speakers revealed elaborated naming strategies and use of a rich inventory of nonBCTs. Elicitation frequencies of the 12 BCTs were comparable for both genders; however, linguistic segmentation of color space, employing a synthetic observer, revealed gender differences in naming colors, with more refined naming of the "warm" colors from females. We conclude that, along with universal perceptual factors, that govern categorical partition of color space, Russian speakers' color naming reflects language-specific factors, supporting the weak relativity hypothesis. K E Y W O R D Scentroids, CIELAB, color naming, color space, gender differences, linguistic segmentation, Russian, webbased experiment | I NT ROD UCTI ONAccording to its color, a visual stimulus is assigned to a certain color category. Identified by a linguistic label (in adult humans), language-specific concepts enable attention to be drawn to certain perceptual attributes of reality. Color names, like other groups of semantically related words, are systems in which one word's position influences the positions of all others.

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“…In particular, they access a larger vocabulary when describing hue samples (Mylonas & Paramei & MacDonald 2014); these reports are not restricted to English-speaking samples (Rätsep 2013;Ryabina 2009). We therefore expected to find a gender difference in the number of terms each participant listed.…”

Section: Discussionmentioning

confidence: 99%

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2016

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Gender differences in colour naming

Cited by 20 publications

References 32 publications

Color naming in Italian language

Color naming in Italian language

An online color naming experiment in Russian using Munsell color samples

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