Colour categories and category acquisition in Himba and English

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COLOUR CATEGORIES AND CATEGORY ACQUISITION
IN HIMBA AND ENGLISH
DEBI ROBERSON, JULES DAVIDOFF, IAN R.L. DAVIES
& LAURA R. SHAPIRO
University of Essex, Goldsmiths College, University of Surrey
and University of Warwick
For over fifty years, the domain of colour categorization has been used as a
testing ground to investigate the degree to which culture (through language)
might influence thought. While it has been known for many years that different
cultures use different sets of linguistic categories to describe the visible range of
colours, many researchers retain the view, first put forward by Berlin and Kay
(1969) that there is a particular set of basic colour categories, shared between
all humans, named in English by basic colour terms (BCTs) and deriving from
the structure of the visual system (e.g. Guest & Van Laar 2002; Munnich &
Landau 2003). These basic categories (named in English as: red, green, blue,
yellow, black, white, grey, pink, orange, purple and brown) are considered
distinct from other terms (for example, turquoise or maroon) because they are
known to all members of a community, not subsumed within another category
and generally named with mono-lexemic words (Kay, Berlin & Merrifield
1991). This view proposes that the organization of cognitive representations of
colour (the set of possible categories) is tightly constrained by perception, even
though the organization of linguistic categories for colour varies widely.
At the same time, there is a growing body of evidence, from a variety of
other cognitive domains, that interactions between culture, language and
thought are widespread and complex. Gumperz and Levinson (1997) found that
variations in number systems were mirrored by differences in numerical
reasoning, and both Levinson (1996), Levinson, Kita, Haun and Rasch (2002)
and Choi, McDonough, Bowerman and Mandler (1999) found similar results
for cultures whose categories for spatial relations differed. Malt and Johnson
(1998) found that category judgments for artefact categories were made in line
with semantic categories; a result also found for classification by material or
shape by Lucy (1992), for time by Boroditsky (2001), and for modes of motion

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by Gennari, Sloman, Malt and Fitch (2000). Roberson, Davidoff and Shapiro
(2002) found that speakers of a language that does not distinguish basic shape
categories (square, circle, and triangle) were unable to sort stimuli into these
categories, whereas Sera and colleagues (Sera, Berge & Pintado 1994; Sera,
Elieff, Forbes, Burch, Rodriguez & Dubois 2002) have reported differing
effects of grammatical gender on classification across languages. Thus the
weight of evidence in favour of tight links between culture, language, and
thought would make colour a unique field of classification, if cognitive colour
categories can truly be independent of the terms used to describe them.
A series of cross-cultural studies of adult colour categorization have found
consistent differences in a range of perceptual and memory tasks,
systematically linked to the colour categories in each culture (Davidoff, Davies
& Roberson 1999; Roberson, Davies & Davidoff 2000). Most recently,
Roberson, Davidoff, Davies & Shapiro (2005) have shown that, even though
two coding systems may appear to be superficially very similar, speakers of the
two languages encode, remember and discriminate colour stimuli in different
ways. Himba, a language spoken by a semi-nomadic, cattle-herding people in
South West Africa, shows similarity in its number of linguistic categories for
colour to Berinmo, the Papua New Guinean language previously studied by
Roberson et al. (2000). Both languages have five basic colour categories,
according to the criteria of Kay et al. (1991). However, Himba participants
showed categorical perception only for their own linguistic categories and not
for either the supposed universal categories, as occurring in English, or to those
of the Berinmo language.
These findings might be accounted for in several different ways. Firstly, it
might be the case that all adults have a universal set of cognitive categories that
may be innately determined and independent of the terms used to describe
them. Despite this, they might always recruit a culture-specific naming system,
even when making perceptual matching judgements for colour, so that two
items that are called by the same name would always be judged more similar
than two items that are given different names, as suggested by Munnich and
Landau (2003). This seems unlikely, however, for three reasons. Firstly, there is
no correspondence between BCTs and any processes yet found in the visual
system (Boynton 1997; Webster, Miyahara, Malkoc & Raker 2000; Valberg,
2001) that would support such a universal categorization system. Secondly,
nameability has been shown to be an important feature of colour sets,
independent of any perceptual qualities of focality (Guest & Van Laar 2002),
and thirdly, a number of recent cross-cultural studies have found no increased
salience for the proposed universal ‘focal’ colours (Davidoff, Davies &

COLOUR CATEGORIES IN HIMBA AND ENGLISH 3
Roberson 1999; Jameson & Alvarado 2003; Özgen & Davies 1998; Roberson,
Davidoff, Davies & Shapiro 2004; Roberson et al. 2005) around which it has
been suggested such universal categories develop (Rosch Heider 1972).
Alternatively, all humans might be born with a universal set of cognitive
categories, that are later distorted by learning the appropriate set of categories
for their language (Bornstein, Kessen & Weiskopf 1976; Franklin & Davies
2004). Such distortions might arise if learned colour categories were mentally
represented by prototypes and these stored representations acted as perceptual
magnets, distorting the perceived colour space. Some recent studies of
languages having eleven basic categories (Sturges & Whitfield 1997; Guest &
Van Laar 2000; Lin, Luo, MacDonald & Tarrant 2001) have provided some
support for the pre-eminence of category centres, or ‘foci’. Moreover, recent
training studies have shown that new categories can be induced for brightness
(Goldstone 1994) and for hue (Özgen & Davies 2002). However, many recent
studies have suggested that cognitive organization changes in these cases,
because there is a shift in attention to differences at category boundaries that
causes enhanced discrimination of boundary items, relative to category centres
(Özgen & Davies 2002; Roberson & Davidoff 2000; Pilling, Wiggett, Özgen &
Davies 2003; Goldstone 1998). Such a mechanism for category acquisition
would imply less, rather than more attention to category centres, over time.
Finally, it might be the case that there is no single set of categories that is
universal and independent of culture and language, and that all divisions of the
perceived continuum of colour must be learned. In that case, individuals who
have yet to learn the set of categories appropriate to their own culture and
language might still group colours in a principled way, such as by similarity,
but fail to categorize along the lines of the proposed universal set. The tendency
to group by similarity is pervasive, both across cultures and across cognitive
domains. Colour cognition is no exception to this and no culture / language has
yet been reported that violates this principle by grouping together two areas of
colour space (for example, yellow and blue) in a category that excludes the
intermediate area (for example, green).1 Roberson, Davidoff and Braisby (1999)
1 However, McNeill (1972) documents a number of instances of languages in which a term
comes, over time, to be used for either one of opposing colours (red / green or blue / yellow) in
different derivative languages. In the case of Slavonic languages, the same term, plav, at
different times has meant ‘pale yellow / blonde’ in some East Slavonic languages, but ‘pale
blue’ in some South and West Slavonic languages. Fasske, Jentsch and Michalk (1972) suggest
that the original meaning of the term in Proto-Indo-European was ‘pale’ or ‘grey’ and that the
‘yellow / blonde’ meaning came from the ‘pale’ sense, while the ‘pale blue’ meaning came from
the ‘grey’ sense.

4 ROBERSON, DAVIDOFF, DAVIES & SHAPIRO
found that an adult patient with colour anomia, who had lost the ability to
categorize colours, explicitly grouped colours on the basis of perceptual
similarity. If categories are initially formed based on the relative similarity of
stimuli, as Dedrick (1996) and Roberson et al. (2000) have argued, then both
the range of available stimuli in the environment and variability in the need to
communicate about colour should affect the eventual set that a community
arrives at.
A further set of studies examined this question by turning to a new source
of evidence: the acquisition of colour terms by children. Estimates of the age at
which children acquire a minimum colour vocabulary (four basic terms) have
dropped from the 7-8 years of age estimated by Binet and Simon (1916) to 2-3
years (Shatz, Behrend, Gelman & Ebeling 1996; Andrick & Tager-Flusberg
1986), but competent use of a full set of BCTs is acquired relatively late,
compared to other dimensional terms (Bornstein 1985; Mervis, Bertrand & Pani
1995; Soja 1994; Sandhoffer & Smith 1999) even by English-speaking children
for whom the set of basic terms to be acquired would be just those that are
presumed to be universally present before the correct terminology is acquired.
With constant intensive training, children as young as 1.5 years can produce
and use some colour terms accurately (Cruse 1977; Mervis, Catlin & Rosch
1975), but hundreds of training trials are required to reach such early
competence (Rice 1980), compared to the single presentation learning
demonstrated for object terms (Carey 1978). With choices restricted to only two
widely separated colours (for example, red and green), young children may
show the same degree of success as for dimensions such as size or form
(Pitchford & Mullen 2001) but, without intensive input, estimates of the age at
which children acquire a full set of colour terms fall between two and six years,
depending on the number of terms examined and the measures of knowledge
taken. Our studies examined naming and comprehension systematically over a
three-year period in order to establish a reliable measure of children’s colour
term acquisition.
The study also examined whether colour term acquisition might differ in
speakers of different languages. In the framework of a presumed innate,
universal fixed set of colour categories, Bornstein (1985) predicted that
acquiring colour terms would be even more difficult for children learning a
language in which the innate universal set must be over-written by a new set,
even if there were fewer terms to be learnt. They might have to assimilate their
existing hue-based universal categories into a new and orthogonal set of
semantic categories based on another dimension, such as lightness in the case of
the Dani reported by Rosch Heider (1972). Similarly, Bowerman and Choi

COLOUR CATEGORIES IN HIMBA AND ENGLISH 5
(2003) suggest that, the more robust and pre-potent the pre-linguistic
organization of the perceived world is, the greater the resistance that language
acquisition would have to overcome, in order to re-structure mental life. Thus,
the acquisition of a set of named categories that are different to the presumed
set of innate, universal categories might show a different developmental pattern
to that of English-speaking children.
Roberson et al. (2004) addressed these questions in a study that included a
group of young English children, who were tested initially before they entered
pre-school and, subsequently, through three years of formal education, and a
group of Himba children from northern Namibia, few of whom received any
formal education during the period of the study. Himba has five BCTs
according to the criteria of Kay et al. (1991). Children’s colour term knowledge
and memory for colours were tested at six-month intervals over three years. At
the first test, 32 English three-year-olds and 36 four-year-olds were tested,
along with 42 Himba three-year-olds and 27 Himba four-year-olds. In the
longitudinal sample, 28 of the English three-year-olds and 63 of the Himba
children completed all six tests. All had normal colour vision. Color Aid matte
stimuli were used (best examples of black, white, grey, red, orange, yellow,
green, blue, pink, purple and brown, together with eleven intermediate colours).
The children completed a colour term listing task (“tell me all the colours that
you know”), colour naming (“what colour is this?”), colour term
comprehension (“can you find a red one?”) and a recognition memory task in
each of the six testing sessions. Full details of the methodology can be found in
Roberson et al. (2004).
Despite the considerable environmental, linguistic and educational
differences between the two groups, there were some noticeable similarities in
our data. Considering the order in which colour terms were learned, the order of
acquisition observed over time differed according to the measure used and
showed great individual variation. However, no measure showed the pattern,
predicted by universalist theory, in which primary colour terms (in English: red,
blue, green and yellow) are learned before non-primary terms, a finding
consistent with other recent studies. Over the course of the longitudinal study,
neither population showed a predictable order of acquisition, and there were
considerable individual differences in term acquisition, such that terms for
brown and grey were acquired very early by some children, although the
English group, as a whole, acquired the terms brown and grey later than other
terms (consistent with Pitchford & Mullen 2002). The present study supported
previous findings of the lack of a predictable order of term acquisition in both
languages (e.g. Macario 1991; Mervis et al. 1975; Pitchford & Mullen 2002;

6 ROBERSON, DAVIDOFF, DAVIES & SHAPIRO
Shatz et al. 1996).
Considering the trajectory of colour term acquisition in the two cultures,
the longitudinal results suggested that children continue to refine their
conceptual colour categories for some years after they first show evidence of
term knowledge for ‘focal’ colours. Previous cross-sectional studies have found
conflicting evidence about the age at which children reliably produce and use
colour terms appropriately. This could be due to the wide range of
methodologies used, the number of colour terms assessed, or to increased
developmental variability introduced by the use of chronological, rather than
language age as a measure, as suggested by Pitchford and Mullen (2003). A
further possibility, uncovered by repeated testing in the present study, is the
tendency of children to subsequently fail either to name or to comprehend a
BCT that they had previously used correctly (the mean subsequent failure rate
was 8% for both groups). Such error-prone performance may help to explain
the inconsistency of previous estimates based on a single test of knowledge.
Children know that a set of terms refer to ‘colour’ and can select colour as
a property on which to match objects as early as two years of age (Soja 1994).
In the present study, three-year-olds in both cultures listed only colour terms
when asked, demonstrating their understanding of colour as a dimension.
However, even at the end of the study, some children from both language
groups could not correctly apply all their BCTs (even though the English
children had had three years of specific instruction). Despite the similarities in
learning trajectory across the two populations, English children acquired their
first colour words earlier than the Himba. Greater exposure to coloured objects
and the increased cultural salience of colour in Western society may contribute
to an earlier conceptual understanding of colour as a separable dimension.
However, from then on, the differences between the groups are less marked
than the similarities, which are clearly seen in their performance on the
recognition memory tasks.
At the first time of testing, for both Himba and English children who knew
no colour terms, the pattern of memory errors was very similar, and, crucially,
neither pattern resembled that derived from the eleven basic categories of
English. Both appeared to be based on perceptual distance rather than a
particular set of predetermined categories. Additionally, for this group of
children, there was no advantage in memory for the stimuli that were central
(focal) to the BCTs in either language. This finding supports the hypothesis that
the eleven basic categories that exist in English are not cognitive universals,
and conflicts with the findings of some studies of infant colour categories
(Bornstein, Kessen & Weiskopf 1976; Franklin & Davies 2004). We return to

COLOUR CATEGORIES IN HIMBA AND ENGLISH 7
this issue later in the discussion.
In our longitudinal study, from an initial reliance on perceptual similarity,
an advantage for the (language appropriate) set of focal colours became evident
as soon as children acquired colour terms. Of those children knowing one or
more colour terms at the first time of testing, English children showed superior
memory performance for the items that are focal to English, but not to Himba
categories, while Himba children showed the reverse pattern. Such rapid
divergence in the cognitive organization of colour for the two groups, from the
time that the first terms are learnt, suggests that cognitive colour categories are
learned rather than innate. Thus, these data, like those for adult Himba and
Berinmo speakers, argue against an innate origin for the eleven basic colour
terms in English.
For both populations, once colour terms were acquired, memory
performance was determined by the number of terms known. Children made
more correct identifications of focal items for terms that they knew than for
terms that they did not, regardless of the absolute number of terms known.
Thus, the effect of term knowledge on memory cannot be an artefact of superior
memory, and language skills of children with higher general intelligence;
children who knew more terms got the same proportion of the items they knew
correct as those who knew few. Knowledge of even one colour term appears to
change the cognitive organization of colour, and from this point on there are
language-dependent differences between the two groups. Once knowledge is
acquired, it appears to restructure the cognitive organization of colour in a
reliable way, and this restructuring relates to term acquisition per se, not to
maturation or educational input. Additionally, the type of recognition errors
made changed over time. The perceptual distance of memory errors decreased
as children learned more BCTs and, in most cases, more within-category than
across-category errors were made at later tests.
Acquisition of term knowledge caused a reduction of memory errors, and
these changed in nature over time. The effects of naming were particularly
evident in the case of two items that were called by the same name in one
language and by different names in another, such as navy blue, or dark orange.
By the time children were six years old, the few errors that were made to these
tiles were to within- rather than cross-category items, regardless of perceptual
distance. It was not simply the case that improving memory allowed children to
make fewer and less distant errors. There were two cases, however, in which
perceptual and categorical errors could be directly contrasted. One was the navy
blue tile, which lies perceptually between English focal blue and black. For
English speakers, this tile is in the same category as the focal blue tile. For

8 ROBERSON, DAVIDOFF, DAVIES & SHAPIRO
Himba speakers, however, it is in the same category as the black tile (and both
are equally focal). Within the test set, there was also a closer perceptual
alternative than either of these; the English focal purple tile. If choices were
only influenced by perceptual similarity, the purple tile should have been a
more frequent erroneous choice than either the lighter blue or the black tile for
both populations. A similar comparison was carried out for children’s
performance on the dark orange tile, which lies perceptually between English
focal red and focal orange. For English speakers, this tile is in the orange
category. For Himba speakers, however, it is in the same category as the red tile
(and also focal). The red tile is also the closest perceptual alternative within the
set. If choices were only influenced by perceptual similarity the most frequent
erroneous choice for both populations would be the red tile. In both cases,
errors in early tests were very varied, for both groups of children. In later tests,
although there were fewer errors, these diverged and, within each language
group, were significantly more likely to be made in connection with the best
example of the category into which the tile fell. For example, by the sixth test,
the only errors made by English children for the navy blue tile were to the focal
blue tile. Over the same period, Himba children’s errors narrowed until the only
errors made were to the (within-category) black tile
The advantage for items central (focal) to children’s native language
categories also increased throughout the longitudinal study. Thus, the
importance that Rosch gave to focality in establishing categories seems justified
from the present data; nevertheless, it is important to stress that the focality is
not universal but, as shown both at first testing and longitudinally, it is language
dependent. For English children, this effect may be unsurprising since these are
just the colours that are taught from the earliest age, and most readily available
in their playthings. For Himba children, focality was determined on the basis of
adult naming agreement. Those targets deemed focal were those for which over
90% of adults agreed on the name. Other targets received little adult naming
agreement. Himba children do not encounter constant presentation, through
printing, dyeing and screen images of best example, highly saturated colours. In
their environment only muted, natural colours are encountered, for which adult
naming might often disagree. Children should then learn more quickly those
colours that adults reliably call by the same name, hence the more accurate
results for ‘focal’ colours.
Himba, like many other traditional cultures, has fewer than eleven basic
categories, each containing a wide range of exemplars, each extending to very
desaturated colours, and with little inter-individual agreement among adults on
where the best examples of categories are located (Roberson et al. 2000;

COLOUR CATEGORIES IN HIMBA AND ENGLISH 9
MacLaury 1987; Rosch Heider & Olivier 1972). Without the full range of
saturated stimuli that can be artificially produced, traditional communities may
have no need of the finer categorical distinctions required when a wider variety
is available, and thus lack the motivation to refine their colour lexicon further.
However, a large proportion of the world’s major languages have the same
number of colour categories, and one may ask why. It is possible that the
eleven-colour organization yields the optimal combination of discriminability
and cognitive economy for recognition and representation of large numbers of
colours. If so, languages with fewer terms would gain by introducing /
borrowing new terms, when increasing technological advances or contact with
other cultures introduced a greater need to communicate more precisely about
colour. Nevertheless, even if the eleven-term organization were found to be
optimal, and eventually adopted by all cultures, it need not be innate.
Early studies by Bornstein and colleagues (Bornstein, Kessen & Weiskopf
1976; Sandell, Gross & Bornstein 1979) suggested that categorical divisions
between red, green, blue and yellow might be innate and perceived
categorically by both infants and other primates. However, there were
methodological issues with these studies (Banks & Salapatek 1981; Werner &
Wooten 1985) and, under controlled conditions, Davidoff, Goldstein and Fagot
(2004) found qualitatively different colour categorization in humans and
primates. Franklin and Davies (2004), using a preferential looking technique,
found that 4-month-old infants showed categorical novelty preferences for a
wide range of colour categories, both across hue boundaries (such as that
between blue and green) and across brightness boundaries (such as that between
pink and red), but there are reasons to be cautious of interpreting infant
‘categorization’ as resembling that acquired later in life.
Infants show remarkable abilities to form short-term dynamic ‘on line’
categories, within a preferential looking paradigm, for a wide range of stimuli
such as cats and lions (Quinn & Eimas 1997), but these categorizations are
labile and can change when the perceptual features of the input are changed
(Rakison & Butterworth 1998a, 1998b). Moreover, recent work by Bremner
and others (Bremner & Bryant 2001; Bremner & Mareschal 2004) suggests that
colour and location information are processed separately in infants, and that
dorsal and ventral streams of visual processing are not integrated until much
later in development. This has been proposed as an explanation as to why
children of 2-3 years of age often fail on other categorization tasks that infants
appear to have passed, since it is around this age that children begin to try to
integrate information about colour, shape, texture and location of stimuli. Xu
and Carey (1996; Xu, Carey & Quint 2004) have also shown that, even at 12

10 ROBERSON, DAVIDOFF, DAVIES & SHAPIRO
months of age, infants fail to represent perceptual features of objects such as
colour, size or pattern and they suggested that infants’ representational systems
only begin to distinguish kinds and properties of objects towards the end of the
first year of life.
Given the difficulty in interpreting infant performance on preferential
looking tasks, Roberson et al.’s (2004) study set out to examine when and how
children acquire a set of colour categories appropriate to their own language
and culture. The results suggest that children gradually acquire the organization
of such categories, and progress gradually from an uncategorized organization
of colour based on perceptual similarity (where dimensions are viewed as
continua) to a structured organization of categories that varies across languages
and cultures. The increase in the influence of linguistic categorization on
memory for colours is progressive and cumulative in both groups. Moreover,
without intensive adult input, colour category acquisition is universally slow
and effortful.
References:
Andrick, G. R. & H. Tager-Flusberg. 1986. “The Acquisition of Colour Terms”.
Journal of Child Language 13.119-134.
Banks, M. S. & P. Salapatek. 1981. “Infant Pattern Vision – a New Approach
Based on the Contrast Sensitivity Function”. Journal of Experimental Child
Psychology 31.1-45.
Berlin, B. & P. Kay. 1969. Basic Color Terms: their Universality and
Evolution. Berkeley: University of California Press.
Binet, A. & T. Simon. 1916. The Development of Intelligence in Children.
Baltimore: Williams & Wilkins.
Bornstein, M. H. 1985. “On the Development of Color Naming in Young
Children: Data and Theory”. Brain and Language 26.72-93.
—, W. Kessen & S. Weiskopf. 1976. “Color Vision and Hue Categorization in
Young Human Infants”. Journal of Experimental Psychology: Human
Perception and Performance 2.115-129.
Boroditsky, L. 2001. “Does Language Shape Thought?: Mandarin and English
Speakers’ Conceptions of Time”. Cognitive Psychology 43.1-22.
Bowerman, M. & S. Choi. 2003. “Space under Construction: Language-specific
Spatial Categorization in First Language Acquisition”. Language in Mind:
Advances in the Study of Language and Thought ed. by D. Gentner & S.
Goldin-Meadow, 387-429. Cambridge, Mass.: MIT Press.
Boynton, R. M. 1997. “Insights Gained from Naming the OSA Colors”. Color
Categories in Thought and Language ed. by C. L. Hardin & L. Maffi, 135-
150. Cambridge: Cambridge University Press.

COLOUR CATEGORIES IN HIMBA AND ENGLISH 11
Bremner, A. & P. Bryant. 2001. “The Effect of Spatial Cues on Infants’
Responses in the AB Task, With and Without a Hidden Object”.
Developmental Science 4.408-415.
— & D. Mareschal. 2004. “Reasoning … What Reasoning?” Developmental
Science 7.419-421.
Carey, S. 1978. “The Child as Word Learner”. Linguistic Theory and
Psychological Reality ed. by J. Bresnan, G. Miller & M. Halle, 264-293.
Cambridge, Mass.: MIT Press.
Choi, S., L. McDonough, M. Bowerman & J. Mandler. 1999. “Early Sensitivity
to Language-specific Spatial Categories in English and Korean”. Cognitive
Development 14.241-268.
Cruse, D. A. 1977. “A Note on the Learning of Colour Names”. Journal of
Child Language 4.305-311.
Davidoff, J., I. Davies & D. Roberson. 1999. “Colour Categories of a Stone-
Age Tribe”. Nature 398.203-204, 402, 604.
—, J. Goldstein & J. Fagot. 2004. “Monkeys Categorise Colours Differently to
Humans”. Poster presented at PICS 04: Progress in Colour Studies.
Dedrick, D. 1996. “Color Language Universality and Evolution: on the
Explanation of Basic Color Terms”. Philosophical Psychology 9.497-524.
Fasske, H., H. Jentsch & S. Michalk, eds. 1972. Sorbischer Sprachatlas, vol. 4.
Bautzen: Domowina.
Franklin, A. & I. R. L. Davies. 2004. “New Evidence for Infant Color
Categories”. British Journal of Developmental Psychology 22.349-377.
Gennari, S. P., S. Sloman, B. Malt & W. T. Fitch. 2000. “Motion Events in
Language and Cognition”. Cognition 83.49-79.
Goldstone, R. 1994. “Influences of Categorization on Perceptual
Discrimination”. Journal of Experimental Psychology: General 123.178-
200.
—. 1998. “Perceptual Learning”. Annual Review of Psychology 49.585-612.
Guest, S. & D. L. Van Laar. 2000. “The Structure of Colour Naming Space”.
Vision Research 40.723-734.
— & D. L. Van Laar. 2002. “The Effect of Name Category and
Discriminability on the Search Characteristics of Colour Sets”. Perception
31.445-461.
Gumperz, J. J. & S. C. Levinson. 1997. “Rethinking Linguistic Relativity”.
Current Anthropology 32.613-623.
Jameson, K. A. & N. Alvarado. 2003. “Differences in Color Naming and Color
Salience in Vietnamese and English”. Color Research and Application
28.113-138.
Kay, P., B. Berlin & W. Merrifield. 1991. “Biocultural Implications of Systems

12 ROBERSON, DAVIDOFF, DAVIES & SHAPIRO
of Color Naming”. Journal of Linguistic Anthropology 1.12-25.
Levinson, S. C. 1996. “Language and Space”. Annual Review of Anthropology
25.353-382.
—, S. Kita, D. B. M. Haun & B. H. Rasch. 2002. “Returning the Tables:
Language Affects Spatial Reasoning”. Cognition 84.155-188.
Lin, H., M. R. Luo, L. W. MacDonald & A. W. S. Tarrant. 2001. “A Cross-
cultural Colour-naming Study, Part I: Using an Unconstrained Method”.
Color Research and Application 26.40-60.
Lucy, J. A. 1992. Language and Diversity of Thought: a Reformulation of the
Linguistic Relativity Hypothesis. Cambridge: Cambridge University Press.
Macario, J. F. 1991. “Young Children’s Use of Colour in Classification: Foods
and Canonically Coloured Objects”. Cognitive Development 6.17-46.
MacLaury, R. E. 1987. Color and Cognition in Mesoamerica: Constructing
Categories as Vantages. Austin: University of Texas Press.
Malt, B. C. & E. C. Johnson. 1998. “Artifact Category Membership and the
Intentional-historical Theory”. Cognition 66.79-85
McNeill, N. B. 1972. “Colour and Colour Terminology”. Journal of Linguistics
8.21-33.
Mervis, C. B., J. Bertrand & J. R. Pani. 1995. “Transaction of cognitive-
linguistic Abilities and Adult Input: a Case-study of the Acquisition of
Color Terms and Color-based Subordinate Object Categories”. British
Journal of Developmental Psychology 13.285-302.
—, J. Catlin & E. Rosch. 1975. “Development of the Structure of Color
Categories”. Developmental Psychology 11.54-60.
Munnich, E. & B. Landau. 2003. “The Effects of Spatial Language on Spatial
Representation: Setting Some Boundaries”. Language in Mind: Advances
in the Study of Language and Thought ed. by D. Gentner and S. Goldin-
Meadow, 113-156. Cambridge, Mass.: MIT Press.
Özgen, E. & I. R. L. Davies. 1998. “Turkish Color Terms: Tests of Berlin and
Kay’s Theory of Color Universals and Linguistic Relativity”. Linguistics
36.919-956.
— & I. R. L. Davies. 2002. “Acquisition of Categorical Color Perception: a
Perceptual Learning Approach to the Linguistic Relativity Hypothesis”.
Journal of Experimental Psychology: General 131.477-493.
Pilling, M., A. Wiggett, E. Özgen & I. R. L. Davies. 2003. “Is Color
Categorical Perception Really Perceptual?” Memory and Cognition 31.538-
551.
Pitchford, N. J. & K. T. Mullen. 2001. “Conceptualization of Perceptual
Attributes: a Special Case for Color?” Journal of Experimental Child
Psychology 80.289-314.

COLOUR CATEGORIES IN HIMBA AND ENGLISH 13
— & K. T Mullen. 2002. “Is the Acquisition of Basic-colour Terms in Young
Children Constrained?” Perception 31.1349-1370.
— & K. T. Mullen. 2003. “The Development of Conceptual Colour Categories
in Pre-school Children: Influence of Perceptual Categorization”. Visual
Cognition 10.51-77.
Quinn, P. C. & P. D. Eimas. 1997. “A Re-examination of the Perceptual-to-
conceptual Shift in Mental Representations”. Review of General
Psychology 1.271-287.
Rakison, D. H. & G. E. Butterworth. 1998a. “Infants’ Use of Object Parts in
Early Categorization”. Developmental Psychology 34.49-62.
— & G. E. Butterworth. 1998b. “Infants’ Attention to Object Structure in Early
Categorization”. Developmental Psychology 34.1310-1325.
Rice, M. 1980. Cognition to Language: Categories, Word Meanings, and
Training. Baltimore: University Park Press.
Roberson, D. & J. Davidoff. 2000. “The Categorical Perception of Colours and
Facial Expressions: the Effect of Verbal Interference”. Memory and
Cognition 28.977-986.
—, J. Davidoff & N. Braisby. 1999. “Similarity and Categorization: Neuro-
psychological Evidence for a Dissociation in Explicit Categorization
Tasks”. Cognition 71.1-42.
—, J. Davidoff, I. R. L Davies & L. R. Shapiro. 2004. “The Development of
Color Categories in Two Languages: a Longitudinal Study”. Journal of
Experimental Psychology: General 133.554-571.
—, J. Davidoff, I. R. L Davies & L. R. Shapiro. 2005. “Color Categories:
Evidence for the Cultural Relativity Hypothesis”. Cognitive Psychology
50.378-411.
—, J. Davidoff & L. Shapiro. 2002. “Squaring the Circle: the Cultural
Relativity of Good Shape”. Journal of Cognition and Culture 2.29-53.
—, I. Davies & J. Davidoff. 2000. “Colour Categories Are Not Universal:
Replications and New Evidence from a Stone-Age Culture”. Journal of
Experimental Psychology: General 129.369-398.
Rosch Heider, E. 1972. “Universals in Color Naming and Memory”. Journal of
Experimental Psychology 93.10-20.
— & D. C. Olivier. 1972. “The Structure of the Color Space in Naming and
Memory for Two Languages”. Cognitive Psychology 3.337-354.
Sandell, J. H., C. G. Gross & M. H. Bornstein. 1979. “Color Categories in
Macaques”. Journal of Comparative and Physiological Psychology 93.626-
635.
Sandhoffer, C. M. & L. B. Smith. 1999. “Learning Color Words Involves a
System of Mappings”. Developmental Psychology 35.568-679.

14 ROBERSON, DAVIDOFF, DAVIES & SHAPIRO
Sera, M. D., C. Berge & J. del Castillo Pintado. 1994. “Grammatical and
Conceptual Forces in the Attribution of Gender by English and Spanish
Speakers”. Cognitive Development 9.261-292.
—, C. Elieff, J. Forbes, M. C. Burch, W. Rodriguez & D. P. Dubois. 2002.
“When Language Affects Cognition and When it Does Not: an Analysis of
Grammatical Gender and Classification”. Journal of Experimental
Psychology: General 131.377-397.
Shatz, M., D. Behrend, S. A. Gelman & K. S. Ebeling. 1996. “Colour Term
Knowledge in Two-year-olds: Evidence for Early Competence”. Journal of
Child Language 23.177-199.
Soja, N. N. 1994. “Young Children’s Concept of Color and its Relation to the
Acquisition of Color Words”. Child Development 65.918-937.
Sturges, J. & T. W. A. Whitfield. 1997. “Salient Features of Munsell Colour
Space as a Function of Monolexemic Naming and Response Latencies”.
Vision Research 37.307-313.
Valberg, A. 2001. “Unique Hues: an Old Problem for a New Generation”.
Vision Research 41.1645-1657.
Webster, M. A., E. Miyahara, G. Malkoc & V. E. Raker. 2000. “Variations in
Normal Color Vision, II: Unique Hues”. Journal of the Optical Society of
America, A: Optics, Image Science and Vision 17.1545-1555.
Werner, J. S. & Wooten, B. R. 1985. “Unsettled Issues in Infant Color
Development”. Infant Behavior and Development 8.99-107.
Xu, F. & S. Carey. 1996. “Infants’ Metaphysics: the Case of Numerical
Identity”. Cognitive Psychology 30.111-153.
—, S. Carey & N. Quint. 2004. “The Emergence of Kind-based Object
Individuation in Infancy”. Cognitive Psychology 49.155-190.