Journal of Experimental Child Psychology 105 (2010) 198–212
Contents lists available at ScienceDirect
Journal of Experimental Child
Psychology
journal homepage: www.elsevier.com/locate/jecp
What’s in the name? Or how rocks and stones
are different from bunnies and rabbits
Anna V. Fisher *
Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
a r t i c l e
i n f o
Article history:
Received 21 January 2009
Revised 8 November 2009
Available online 14 December 2009
Keywords:
Generalization
Language acquisition
Synonym-based reasoning
Label extension
Polyonomy
Word learning
a b s t r a c t
Labels have been shown to play an important role in inductive generalization; however, the mechanism by which labels contribute to
generalization early in development remains unclear. We investigated two factors that may influence the inductive potential of
labels: semantic similarity and co-occurrence probability. Results
suggested that adults and 6-year-olds rely on semantic similarity
of labels and that their generalizations are not affected by cooccurrence probability. Specifically, generalization patterns were
qualitatively similar for co-occurring semantically similar labels
(e.g., bunny–rabbit) and non-co-occurring semantically similar
labels (e.g., rock–stone) in 6-year-olds and adults. Unlike 6-yearolds and adults, 4-year-olds were likely to generalize co-occurring
labels but not non-co-occurring labels. Possible mechanisms by
which co-occurrence probability may influence label generalization in young children are discussed.
Ó 2009 Elsevier Inc. All rights reserved.
Introduction
Generalization of the known to the unknown is a critically important component of cognition. For
example, learning that a particular cat is a feline can promote generalization of this knowledge to
other cats (a process referred to as categorization), and learning that a particular cat uses enzymes
for digestion can promote generalization of this property to other cats (a process referred to as property induction). The ability to generalize appears to develop early in life. For example, 3- and 4-montholds can learn to categorize artificial dot patterns (Bomba & Siqueland, 1983) as well as naturalistic
stimuli (Quinn, Eimas, & Rosenkrantz, 1993); by 10 months of age, infants are capable of performing
* Fax: +1 412 268 2798.
E-mail address: fi[email protected]
0022-0965/$ - see front matter Ó 2009 Elsevier Inc. All rights reserved.
doi:10.1016/j.jecp.2009.11.001
A.V. Fisher / Journal of Experimental Child Psychology 105 (2010) 198–212
199
simple generalizations about object properties such as pattern of motion and object sounds (Baldwin,
Markman, & Melartin, 1993; Rakison & Poulin-Dubois, 2002); and by 24 months of age, children readily generalize known labels to novel objects (Nelson, 1973).
There is ample evidence that from very early in development, words influence the way children
generalize knowledge. For example, 4-year-olds are more likely to conclude that ambiguously looking
objects belong to the same category and share properties if these objects are referred to by the same
label (e.g., a rabbit and a rabbit) than if these objects are referred to by different labels (e.g., a rabbit and
a squirrel) (Gelman & Markman, 1986; Sloutsky & Fisher, 2004). Furthermore, it has been demonstrated that shared labels influence categorization and property generalization in children as young
as 13 months of age (Graham, Kilbreath, & Welder, 2004). Children’s propensity to rely on matching
labels to generalize knowledge is often explained in terms of children understanding that count nouns
denote categories rather than individual objects and that objects belonging to the same category have
many important properties in common (Gelman & Coley, 1991; Gelman & Markman, 1986; Jaswal,
2004; Welder & Graham, 2001).
A different pattern of results emerged from studies in which children were presented with generalization tasks with taxonomically related labels (e.g., poodle–dog). It has been documented that
young language learners have difficulty in accepting that the same entity can be referred to by multiple labels (Markman, 1989). However, by 3 years of age, children readily accept several labels in reference to the same object for both synonymous labels (e.g., puppy–dog) and taxonomically related
labels (e.g., dog–animal) (Banigan & Mervis, 1988; Blewitt, 1994; Deák & Maratsos, 1998; Deák,
Yen, & Pettit, 2001; Liittschwager & Markman, 1994; Mervis & Bertrand, 1994). Despite this important
achievement, the ability to rely on familiar labels that are organized into taxonomic hierarchies (e.g.,
poodle–dog–animal) in the course of induction does not mature until 7 or 8 years of age (Gelman &
O’Reilly, 1988; Johnson, Scott, & Mervis, 1997).
One way of reconciling results emerging from studies that used identical and taxonomically related
labels is to assume that children’s difficulty in reasoning with taxonomic labels stems not from the
lack of understanding that labels denote categories but rather from the lack of understanding of class
inclusion relations, which children do not generally demonstrate before they reach 7 or 8 years of age
(Deneault & Ricard, 2006; Greene, 1994; Inhelder & Piaget, 1964; Johnson et al., 1997; Klahr &
Wallace, 1972)—the same age at which children become capable of relying on taxonomically related
labels in the course of induction. A straightforward prediction that follows from this assumption is
that children younger than 7 or 8 years of age should be successful in performing generalization tasks
with nonidentical labels if these labels denote entities at the same level of taxonomic hierarchy. In
other words, preschool-age children should be able to perform generalization tasks with semantically
similar (or synonymous) labels.
Although this prediction is quite straightforward, there has been surprisingly little research on children’s ability to generalize knowledge relying on semantically similar labels that denote entities at the
same level of a taxonomic hierarchy (thereby posing no demand on understanding of class inclusion
relations); an extensive literature search revealed only one study that investigated this issue. In that
study, Gelman and Markman (1986, Experiment 2) presented 4-year-olds with a property induction
task in which the children were shown a target item and two test items and asked to generalize properties of the test items to the target item. In the identical labels condition, one of the test items had the
same name as the target item (e.g., a rabbit) and the other test item had a different name (e.g., a squirrel). When both test items looked equally similar to the target item, 4-year-olds generalized the property based on the shared name (e.g., from a rabbit to another rabbit rather than to a squirrel), and this
finding received empirical support in later studies (Sloutsky & Fisher, 2004; Sloutsky, Lo, & Fisher,
2001). Importantly, 4-year-olds correctly generalized properties at above chance level not only in
the identical labels condition but also in the synonymous labels condition, in which one of the test
items was referred to by a label that was semantically similar to that of the target item. For example,
children generalized the property of eating grass from the test item referred to as a bunny to the target
item referred to as a rabbit at above chance level.
Gelman and Markman’s (1986) study described above remains the only study to have investigated
children’s ability to generalize knowledge based on semantically similar labels at the same level of a
taxonomic hierarchy. Results of this study provide support for the hypothesis that young children
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understand that labels denote categories and that their difficulty in relying on taxonomically related
labels may stem from the poor understanding of class inclusion relations.
However, preliminary analysis of the stimuli used in Gelman and Markman’s (1986) study indicated that some of the semantically similar word pairs were likely to co-occur in child-directed
speech, whereas others were not. In particular, analysis of the CHILDES database (MacWhinney,
2000), a database of child-directed speech, indicated that some semantically similar words used in
Gelman and Markman’s study (e.g., bunny–rabbit, puppy–dog) regularly co-occur in the speech of both
children and their parents, whereas other words (e.g., rock–stone, snake–cobra) are unlikely to co-occur
(see Experiment 1 procedure for more details of the CHILDES database analysis below).
It has been suggested that word co-occurrences in both oral and written language give rise to
strong lexical associations (Brown & Berko, 1960; McKoon & Ratcliff, 1992). The strength of lexical
association is typically estimated by using a free association task in which people are presented with
a word and asked to generate another word in response (Jenkins & Palermo, 1964). Strength of association is measured in terms of the probability of the second word in a pair being produced in response
to the first word. Association strength has not been studied extensively in young children; however,
several databases have been created to document lexical association strength in adults (Nelson, McEvoy, & Schreiber, 1998; Wilson, 1988). According to these databases, some words in English are
strongly associated, whereas other words are associated only weakly or not at all. For example, when
people are presented with the words puppy and bunny, the probabilities of obtaining the words dog
and rabbit in response are 71 and 74%, respectively, but when people are presented with the words
rock and snake, only 3 and 0% of adults produce the words stone and cobra in response, respectively
(Nelson et al., 1998).
There are two ways in which co-occurrence of semantically similar labels may influence synonymbased reasoning. First, the ability to rely on semantically similar labels in the course of reasoning requires one to establish mappings between two (or more) different labels and one referent object (e.g.,
this object can be called a bunny and a rabbit). Fig. 1 presents a schematic depiction of such object–label
mappings (shown in black arrows). When semantically similar labels co-occur or are used as a compound noun, it might simplify the task of mapping different labels onto the same object (e.g., compare
the scenarios in Figs. 1A and 1B).
Second, co-occurrence of labels can give rise to strong lexical associations (i.e., the label–label mappings shown in gray lines in Fig. 1) (Brown & Berko, 1960; McKoon & Ratcliff, 1992). In this case, shared
meaning of labels might not be the only factor prompting children to rely on a semantically similar
Fig. 1. Schematic description of possible effects of co-occurrence frequency of semantically similar labels on the strength of
knowledge representations. In panel A, the understanding that the words bunny and rabbit are synonymous is strengthened (as
indicated by solid gray lines) because these words are used simultaneously to refer to the same object. In panel B, the
understanding that words bunny and rabbit are synonymous is weaker (as indicated by dashed gray lines) because children
need to map two different words that occurred at different points in time onto the same object.
A.V. Fisher / Journal of Experimental Child Psychology 105 (2010) 198–212
201
label versus an unrelated label in reasoning tasks; this tendency may be amplified by the activation
spreading from the first word in a pair to prime its associated synonym.
Both of the possibilities described above suggest that effects of semantically similar labels on generalization processes early in development may be amplified or mediated by co-occurrence probability of semantically similar words. The current research was designed to examine effects of semantic
similarity and co-occurrence probability of labels on knowledge generalization in 4-year-olds, 6year-olds, and adults. Finding effects of co-occurrence probability on generalization of familiar labels
in young children may indicate that understanding of labels as markers of category membership continues to develop beyond the age at which children have been traditionally assumed to possess such
understanding (i.e., 2–4 years) (Gelman & Coley, 1991; Gelman & Markman, 1986; Jaswal, 2004;
Welder & Graham, 2001).
In the experiments described below, participants were presented with a label extension task in
which they were asked to generalize object labels. Participants were presented with a set of novel objects consisting of a target item and three test items varying in the degree of similarity to the target.
Participants were told that they would be playing a game in which they needed to guess the names of
objects on a different planet. Participants were presented with pairs of semantically similar labels, told
that the first label in a pair referred to the target item (e.g., ‘‘This one is called a bunny”), and asked
which test item the second label in a pair was likely to refer to (e.g., ‘‘Which one do you think should
be called a rabbit?”). Participants were presented with this generalization task in one of two labeling
conditions: the co-occurring labels condition and the non-co-occurring labels condition (see procedure
below for details).
A label generalization task was chosen instead of a property generalization task because in property generalization tasks it is inferred that because children generalize an unobservable property from
a rabbit to a bunny, they must realize that these words refer to objects of the same kind. This extra
inference is omitted in a label generalization task, in which children are essentially asked whether
or not an object referred to by the word bunny is a similar kind of thing as the object referred to by
the word rabbit (for a similar argument, see Imai & Gentner, 1997). The label generalization task used
in the experiments presented below is based on the assumption that if participants understand that
labels denote categories, they should be more likely to generalize semantically similar labels to perceptually similar items than to perceptually dissimilar items (because items of the same kind typically
look similar to each other) regardless of co-occurrence probability of labels. This assumption was
tested with adult participants in Experiment 1. In Experiments 2 and 3, effects of semantic similarity
and co-occurrence probability of labels were investigated with 4- and 6-year-olds.
Experiment 1
Method
Participants
Participants in Experiment 1 were 38 undergraduate students (mean age = 19.98 years, SD = 2.42,
21 women and 17 men) recruited from the introductory psychology courses at a large university in the
midwestern United States. There were 19 participants in each experimental condition.
Materials and design
Selection of stimuli for Experiment 1 consisted of obtaining ratings of semantic similarity from
adult participants and analyzing co-occurrence frequency of the words that adults judged to be
semantically similar in child-directed speech. To obtain ratings of semantic similarity, a group of 10
adults (none of whom participated in the experiment proper) was asked to rate semantic similarity
of 24 pairs of words on a 7-point scale. Participants were instructed to rate words that can be used
interchangeably (e.g., dog and canine) as 7 and to rate completely unrelated words (e.g., book and sand)
as 1.
Only those words that received a rating of at least 5.0 were chosen as possible stimuli for Experiment 1 and subjected to the co-occurrence frequency analysis. The co-occurrence frequency was
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analyzed using the CHILDES database, a database of child speech and child-directed speech (MacWhinney, 2000). The goal of this analysis was to identify pairs of semantically similar words that have
a high probability and a low probability of co-occurrence in the speech of children and their caregivers. A common method of identifying co-occurring words is ‘‘sliding” a window over the text in a database and counting how many times a given pair of words occurs in each step of the moving window
(Church & Hanks, 1990). In the current analysis, the size of the sliding window was set at five words to
allow for word co-occurrences in the context of compound nouns (e.g., ‘‘Look at this bunny-rabbit”), a
parent explaining word meaning (e.g., ‘‘A pony is a little horse”), and situations in which words may be
connected by a conjunction (e.g., ‘‘Rocks and stones may break your bones . . .”).
Overall, five different databases in the CHILDES corpus were analyzed: the Bates, Brown, Gleason,
HSLLD, and Wells databases. Children’s ages in these five databases ranged from 1.5 to 9 years, and the
total number of words (in all lexical categories) across the databases was 2,264,722. To normalize raw
co-occurrence frequencies, the number of raw co-occurrences was divided by the sum of instances of
each word occurring individually minus the number of times the two words co-occurred. For example,
the word bunny occurred in the analyzed databases 803 times, the word rabbit occurred 579 times,
and these two words co-occurred 103 times. Using the normalization procedure described above,
the probability of the words bunny and rabbit co-occurring was calculated as 0.08 (103 [803 + 579 – 103]).
Word pairs that were selected as stimuli for Experiment 1 are presented in Table 1. These word
pairs were grouped into a co-occurring labels condition and a non-co-occurring labels condition based
on the results of analysis of the CHIDLES database (MacWhinney, 2000). As is shown in the table, the
average probably of co-occurrence of semantically similar words in the co-occurring labels condition
was 0.03. In contrast, words in the non-co-occurring labels condition never co-occurred within the
span of five words in the CHILDES database. The difference in probability of co-occurrence of semantically similar words in the co-occurring labels and non-co-occurring labels conditions was marginally
significant, independent-samples t(8) = 2.11, p = .067. The average ratings of semantic similarity of the
chosen word pairs were similar in the two co-occurrence conditions (5.77 and 5.95 in the co-occurring
labels and non-co-occurring labels conditions, respectively).
Table 1 also presents the strength of lexical association of the chosen word pairs in the lexicon of
adults. Co-occurrence probabilities and forward association strength presented in the table provide
support to the argument that words regularly co-occurring in written or oral language might become strongly associated (these findings, of course, do not rule out other means by which words
may become associated such as thematic relatedness). The average forward association strengths
of the words in the co-occurring labels and non-co-occurring labels conditions were 0.46 and
0.038, respectively, and this difference was statistically significant, independent-samples
t(8) = 3.71, p < .01.
Table 1
Label pairs used in Experiments 1 to 3.
Co-occurring
labels
(Experiments
1 and 2)
Probability
of cooccurrence
Forward
association
strengtha
Non-cooccurring
labels
(Experiments
1 and 2)
Probability
of cooccurrence
Forward
association
strength
Non-cooccurring
labels
(Experiment 3)
Probability
of cooccurrence
Forward
association
strength
Bunny–rabbit
Puppy–dog
Pony–horse
Kitty–cat
Ship–boat
.081
.010
.003
.031
.021
.74
.71
.32
.31
.20
Couch–sofa
Child–kid
Rock–stone
Hat–cap
Cup–mug
.000
.000
.000
.000
.000
.08
.04
.03
.02
.02
Tree–bush
Child–kid
Rock–stone
Dolphin–whale
Frog–toad
.000
.000
.000
.000
.000
.01
.04
.03
.05
.14
Average
Standard
deviation
.029
.030
.46
.25
Average
Standard
deviation
.000
.000
.038
.025
Average
Standard
deviation
.000
.000
.054
.050
a
Forward association strength (FAS) is measured in terms of the probability of the second word in a pair being produced in response to the
first word. FAS values presented in the table were taken from the Nelson et al. (1998) and Wilson (1988) databases.
A.V. Fisher / Journal of Experimental Child Psychology 105 (2010) 198–212
203
Ratings of lexical association strength for the stimuli used in this research are not available with
young children; however, Bjorklund and Jacobs (1984) demonstrated that associative strength between pairs of words undergoes minimal changes with development. In particular, Bjorklund and Jacobs (1984) asked participants between 8 and 27 years of age to rate association strength of 70 word
pairs, and the results indicated that correlations between child and adult rankings ranged from .91 to
.98 for the majority of label pairs used in that study.
Visual stimuli in Experiment 1 consisted of eight picture sets composed of novel objects. Each set
contained a target item and three test items that varied in the degree of similarity to the target: a similar test item, a less similar test item, and a dissimilar test item (see Fig. 2 for an example of the visual
stimuli). The position of the test items relative to the target item (directly below, below and to the left,
or below and to the right) was randomized on each trial.
Procedure
Each label pair was randomly paired with each picture set on each trial. Participants were randomly assigned to the co-occurring labels and non-co-occurring labels conditions. The order of trials
was randomized for each participant. Picture sets were presented on a computer screen. In Experiment 1, and in all experiments reported below, participants were told that they would be guessing
what various things are called on a far-away planet. Participants were presented with the first picture
set, told what the target object was called on the far-away planet, and asked which test object would
be called by a synonymous label. For instance, participants could be told, ‘‘This one is called a rock on
the far-away planet. Which one of these do you think is called a stone on the far-away planet?” Participants were tested individually in a laboratory on campus by hypothesis-blind researchers.
Results
The proportion of choices of each test item was calculated for each participant and averaged across
participants (see Table 2). Initial analyses evaluated whether participants generalized semantically
similar labels to the similar items at a rate greater than expected by chance alone (33%) using single-sample t tests. Participants in both the co-occurring and non-co-occurring labels conditions generalized semantically similar labels to the similar items significantly above chance (90 and 85%,
respectively), both ts > 10.89, ps < .001. Furthermore, the means in the two conditions were not significantly different from each other, independent samples t(36) < 1.70, p > .40.
Fig. 2. Examples of object sets used in Experiments 1 to 3.
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Table 2
Proportions of choices of similar, less similar, and dissimilar items in Experiments 1 to 3.
Similar items
Experiment 1
Adults
Experiment 2
6-yearolds
4-yearolds
Experiment 3
Adults
6-yearolds
4-yearolds
Less similar items
Dissimilar items
Cooccurring
labels
Non-cooccurring
labels
Cooccurring
labels
Non-co-occurring
labels
Cooccurring
labels
Non-cooccurring
labels
.90 (.18)
.85 (.21)
.08 (.15)
.12 (.14)
.02 (.04)
.03 (.14)
.67 (.32)
.70 (.27)
.14 (.18)
.16 (.18)
.18 (.24)
.14 (.14)
.65 (.28)
.38 (.31)
.15 (.13)
.32 (.19)
.19 (.20)
.31 (.25)
–
–
.82 (.17)
.71 (.31)
–
–
.12 (.13)
.21 (.23)
–
–
.06 (.09)
.08 (.13)
–
.42 (.28)
–
.29 (.19)
–
.29 (.23)
Note. Standard deviations are in parentheses.
In both labeling conditions, adults were unlikely to generalize semantically similar labels to the
less similar items or the dissimilar items (see Table 2). This pattern of generalization (based on the
criterion of at least four of five generalizations to the similar items, binomial p < .05) was found in
16 of 19 participants (or 84%) in both the co-occurring and non-co-occurring labels conditions.
It could be argued that this pattern of results could stem from adults matching similar pictures
regardless of the semantic similarity of labels. To control for this possibility, a separate group of 15
undergraduate students was presented with the same label generalization task as in Experiment 1;
however, semantically similar words were substituted with unrelated labels (i.e., horse–sky, lamp–
cup, spoon–cat, key–skirt, and bag–bird); the average semantic similarity rating for these word pairs
was 1.47, and the average forward association strength was .01. The results of this control experiment
indicated that adults were unlikely to generalize unrelated labels to the similar items (M = 0.09) and
less similar items (M = 0.37); however, adults were above chance (33%) in generalizing unrelated labels to the dissimilar items (M = 0.54), single-sample t(15) = 3.84, p < .005.
Overall, the results of Experiment 1 provide support to the hypothesis that adults assume that
semantically similar words should refer to perceptually similar items regardless of the probability
of co-occurrence of these words in the lexicon. These results also support previous research indicating
that adults understand the symbolic nature of labels and treat labels as markers of category membership (Gelman & Markman, 1986; Yamauchi & Markman, 2000). Experiment 2 tested whether 4- and 6year-olds possess a similar understanding of the symbolic nature of labels. If young children’s understanding of category labels is similar to adults’ understanding of category labels, then children should
exhibit a pattern of results that is qualitatively similar to that of adults; in other words, children
should be likely to generalize familiar semantically similar words to perceptually similar objects
and there should be no differences in the rate of generalization of semantically similar words in the
co-occurring labels and non-co-occurring labels conditions.
Experiment 2
Method
Participants
Participants in Experiment 2 were 35 4-year-olds (mean age = 4.59 years, SD = 0.43, 13 girls and 22
boys) and 28 6-year-olds (mean age = 6.86 years, SD = 0.54, 13 girls and 15 boys) recruited from day
care centers and preschools in a large midwestern city.
A.V. Fisher / Journal of Experimental Child Psychology 105 (2010) 198–212
205
Materials
Materials of Experiment 2 were identical to those of Experiment 1. Prior to the experiment proper,
all label pairs were calibrated with a separate group of 4-year-olds to establish that even the youngest
children tested in Experiment 2 were familiar with the words used in the current research and treated
these words as semantically similar. A separate experiment was conducted with another group of 4year-olds to calibrate visual similarity of the test items to the target items. These calibration studies
are described below.
Label calibration. A group of 20 4-year-olds was recruited for label calibration (mean age = 4.79 years,
SD = 0.31). During calibration, children were presented with a test analogous to the Peabody Picture Vocabulary Test (Dunn & Dunn, 1997). Specifically, children were presented with picture cards
on the screen of a laptop computer, and each card contained four pictures: one target item, one critical
lure, and two unrelated items. Children were asked to point to the picture of an object named by the
experimenter. For example, the experimenter might have asked, ‘‘Can you find a sofa?” The critical
lures consisted of items that belonged to the same superordinate category as the target items (e.g.,
for the target item ‘sofa’ the critical lure was a picture of a chair) and the unrelated items consisted
of items that belonged to a different ontological category than the target items (e.g., for the target item
‘sofa’ unrelated items consisted of pictures of a man and a giraffe). The location of the target objects on
the screen (i.e., top right quadrant, top left quadrant, bottom right quadrant, or bottom left quadrant)
was counterbalanced across trials.
Label pairs used in Experiments 1 to 3 were included in the calibration: 10 label pairs from Experiments 1 and 2 and an additional 3 label pairs from Experiment 3. Therefore, there was a total of 13
critical picture cards. Importantly, children were presented with these picture cards twice (the location of each target item was changed from the first presentation to the second presentation of each
picture card) and asked to identify the same objects using both labels in the synonym pairs from Experiments 1 to 3. For example, children could be first presented with a picture card and asked to point to a
sofa and later presented with the same set of items (with locations of items counterbalanced between
the two presentations of the card) and asked to point to a couch. Therefore, children were presented
with a total of 26 critical picture cards. An additional 24 picture cards were included as fillers, resulting in a total of 50 trials in label calibration. Participants were presented with the cards in one of two
pseudorandom orders, and no feedback was provided.
The results of label calibration indicated that even the youngest children in this research were well
familiar with the labels that were used in Experiments 1 to 3. In particular, children identified pictures
corresponding to labels in the co-occurring labels condition with a mean accuracy of 99% and identified pictures corresponding to labels in the non-co-occurring labels condition with a mean accuracy of
95%. In addition, these results suggest that 4-year-olds not only are familiar with all of the labels used
in Experiments 1 to 3 but also understand that these different labels can be readily applied to the same
objects.
Similarity calibration. In a separate calibration experiment, a new group of 15 4-year-olds (mean
age = 4.76 years, SD = 0.35) was presented with the stimuli from Experiment 1 organized into triads.
There were five triads consisting of a target item, a similar item, and a less similar item as well as five
triads consisting of a target item, a less similar item, and a dissimilar item. The experimenter told the
children, ‘‘Look at this one [pointing to the target]. Which of these [pictures below] looks like this
one?” The results of the similarity calibration indicated that 4-year-olds judged similar items as looking more like the target items than less similar items 96% of the time. In the absence of similar items,
children judged less similar items as looking more like the target items than dissimilar items 65% of
the time, above chance, single-sample t(14) = 3.94, p < .001. Overall, the results of the calibration indicated that similarity of the test items in comparison with the target items was as follows: similar
items > less similar items > dissimilar items.
Design and procedure
Experiment 2 had a 2 (Age: 4-year-olds vs. 6-year-olds) by 2 (Labeling Condition: co-occurring
labels vs. non-co-occurring labels) between-participant design. The task and procedures were
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identical to those of Experiment 1. Children were tested individually in their preschools or day care
centers by hypothesis-blind researchers.
Results
The proportion of choices of each test item was calculated for each participant and averaged across
participants (see Table 2). A two-way analysis of variance (ANOVA) was conducted on the proportions
of choices of the similar items, with age (4-year-olds vs. 6-year-olds) and condition (co-occurring labels vs. non-co-occurring labels) as between-participant factors. This analysis revealed a main effect of
age, F(1, 59) = 5.15, p < .05 g2p ¼ :08, qualified by an age-by-condition interaction, F(1, 59) = 4.23,
p < .05, g2p ¼ :07. This interaction was further explored using a set of planned comparisons reported
below.
The proportions of generalizations of semantically similar labels to the similar items were compared with chance (33%) using single-sample t tests. In the co-occurring labels condition, both 4and 6-year-olds reliably generalized semantically similar labels to the similar items at above chance
level (65 and 67%, respectively), both ts > 3.99, means not different from each other, independentsamples t(30) < 1, ns. In the non-co-occurring labels condition, 6-year-olds reliably generalized
semantically similar labels to the similar items (70%) at above chance level, t(13) = 5.14, p < .0001.
In contrast, generalization of non-co-occurring semantically similar labels to the similar items in 4year-olds (38%) did not exceed chance, t(16) < 1, ns. Furthermore, 4-year-olds were more likely to generalize semantically similar labels to the similar items in the co-occurring labels condition (65%) than
in the non-co-occurring labels condition (38%), independent-samples t(33) = 2.81, p < .001, Cohen’s
d = .90, whereas 6-year-olds exhibited similar patterns of responses in both conditions (67 and 70%
of generalizations to the similar items, respectively), independent-samples t(26) < 1, ns.
Analyses of the individual patterns of responses were in agreement with the group-level analyses.
In the co-occurring labels condition, the proportions of children making at least four of five generalizations to the similar items (binomial p < .05) were similar across 4- and 6-year-olds. Specifically, 7 of
18 children in the 4-year-old group (or 39% of the sample) and 7 of 14 children in the 6-year-old group
(or 50% of the sample) made at least four of five generalizations to the similar items, Fisher’s exact
p > .72. However, in the non-co-occurring labels condition, only 2 of 17 children in the 4-year-old
group (or 11% of the sample) exhibited this pattern of responding, whereas 6 of 14 children in the
6-year-old group (or 43% of the sample) did so; the association between age and individual response
pattern was marginally significant, Fisher’s exact p = .09.
The proportions of choices of similar items across both labeling conditions in Experiments 1 and 2
are presented in Fig. 3. Overall, responses of 6-year-olds were more variable than those of adults;
across both labeling conditions, adults averaged 88% of generalizations to the similar items, whereas
6-year-olds averaged 68% of generalizations to the similar items, independent-samples t(64) = 2.27,
p < .05, Cohen’s d = .75. However, as shown in Fig. 3 and Table 2, the pattern of performance observed
in 6-year-olds was qualitatively similar to that of adults in Experiment 1; both adults and 6-year-olds
generalized semantically similar labels to perceptually similar items at above chance level. Critically,
for both adults and 6-year-olds, there was no difference in the rate of generalization of semantically
similar labels to the similar items in the co-occurring and non-co-occurring label conditions. A
different pattern of results emerged with 4-year-olds,1 who generalized semantically similar labels
to perceptually similar items at above chance level in the co-occurring labels condition but not in the
non-co-occurring labels condition.
1
A separate group of 17 4-year-olds (mean age = 4.64 years, SD = 0.38) was tested to replicate effects observed in generalization
of co-occurring semantically similar labels. The findings of this follow-up experiment fully replicated the findings reported in
Experiment 2; children averaged 62% of generalizations to similar items, above chance (33%), single-sample t(16) = 3.65, p < .005.
At the same time, children were unlikely to generalize semantically similar co-occurring labels to less similar and dissimilar items
(20 and 18% of generalizations, respectively). The proportion of choices of similar items in this replication was statistically
equivalent to that in the co-occurring labels condition of Experiment 2 (65% of responses), independent-samples t(33) < 1. The
individual patterns of responses were also highly similar to those observed in Experiment 2, with 39% of participants (or 7 of 18
children) in Experiment 2 and 41% of participants (or 7 of 17 children) in the replication experiment generalizing co-occurring
semantically similar labels to similar items on at least four of five trials, Fisher’s exact p > .99.
A.V. Fisher / Journal of Experimental Child Psychology 105 (2010) 198–212
207
Fig. 3. Proportions of choices of similar items in the co-occurring and non-co-occurring labels conditions in Experiments 1 and
2. The dashed line represents chance level. Error bars represent the standard error of the mean.
Overall, these results suggest that co-occurrence probability influenced label generalization in 4year-olds but not in older children and adults. However, it could be counterargued that results presented above could stem from greater attenuation of the mutual exclusivity bias in the co-occurring
labels condition than in the non-co-occurring labels condition. In particular, young children are biased
to interpret novel words as referring to novel entities rather than familiar entities—a tendency referred to as mutual exclusivity (Markman & Wachtel, 1988). Therefore, in Experiment 2, once children
learned that the target object had a particular name, they might have expected synonymous labels to
refer to objects that looked dissimilar from the target. Furthermore, it is possible that this tendency
was greater in the non-co-occurring labels condition than in the co-occurring labels condition.2 However, mutual exclusivity has been shown when children are presented with a mixture of familiar and novel objects and labels. For example, when children are presented with an apple (familiar object) and a
stethoscope (novel object) and asked which of these objects is a dax (novel label), children are likely
to choose the novel object, presumably because they already know the label for the familiar object
(Markman & Wachtel, 1988). At the same time, all labels used in Experiment 2 were familiar to children,
whereas all objects were novel. Therefore, it is unclear whether mutual exclusivity would arise under
these conditions.
To examine this possibility, a separate group of 11 4-year-olds (mean age = 4.36 years) was asked
to perform the label extension task with pairs of unrelated labels (the same labels that were used in a
control follow-up condition to Experiment 1: horse–sky, lamp–cup, spoon–cat, key–skirt, and bag–bird).
If children exhibit mutual exclusivity when presented with familiar labels and novel objects, then children should not perform at chance with unrelated labels but rather should show a tendency to choose
the dissimilar items. Results of this follow-up experiment suggested that the rates of choices of similar, less similar, and dissimilar items were 35, 31, and 34%, respectively; the proportion of generalizations to similar items was not different from chance, t(10) < 1, ns. This result suggests that 4-year-olds
did not exhibit mutual exclusivity when presented with familiar labels and novel objects. Therefore, it
is unlikely that results of Experiment 2 can be explained by 4-year-olds having a stronger mutual
exclusivity bias in the non-co-occurring labels condition than in the co-occurring labels condition.
Another alternative explanation of the results reported in Experiment 2 is that the performance of
4-year-olds was influenced by the composition of the stimulus lists rather than by co-occurrence
probability of labels. In particular, the stimulus list in the co-occurring labels condition was composed
mainly of natural kind items (with the exception of the ship–boat word pair), and the stimulus list in
the non-co-occurring labels condition was composed mainly of artifacts (with the exception of the
rock–stone and child–kid word pairs). The uneven distribution of natural kind and artifact items in different conditions was not intentional; all items were chosen on the basis of semantic similarity ratings
and co-occurrence probability in the CHILDES database. It appears that words with overlapping meanings are more likely to co-occur (at least in the English language) if these words refer to natural kind
items than to artifacts. This phenomenon is not unique; the use of different language patterns for natural kind items and artifacts has been reported previously. For example, it has been observed that
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people are more likely to use generic sentence structures when talking about natural kind items (e.g.,
birds fly) than when talking about artifacts (e.g., woks are for cooking) (Gelman, Goetz, Sarnecka, &
Flukes, 2008).
However, this correlation between co-occurrence probability and ontological status of an object
complicates interpretation of the results of Experiment 2. It is unclear whether 4-year-olds were unlikely to generalize semantically similar words to perceptually similar objects in the non-co-occurring
labels condition because young children conceptualize artifacts in a different way from natural kind
objects or because these words were unlikely to co-occur in the speech of children and their caregivers. The previous research has shown that children younger than 7 or 8 years of age show little differentiation between artifacts and natural kind objects in property induction and other reasoning tasks
(DiYanni & Kelemen, 2005; Gelman & O’Reilly, 1988). Nonetheless, this possibility was directly examined in Experiment 3.
Experiment 3
To isolate effects of co-occurrence probability from effects of ontological status on label generalization, in Experiment 3 the stimulus list was composed exclusively of non-co-occurring semantically similar labels referring to natural kind items. If 4-year-olds are likely to generalize semantically similar
labels to perceptually similar items for natural kind items but not for artifacts, then they should be likely
to generalize semantically similar labels to perceptually similar items in Experiment 3, where the stimulus list is composed solely of natural kind items. However, if 4-year-olds are likely to generalize semantically similar labels to perceptually similar items for words that tend to co-occur in the speech of
children and their caregivers but not for words that are unlikely to co-occur, then 4-year-olds should
be unlikely to generalize semantically similar labels to perceptually similar items in Experiment 3.
Method
Participants
Participants in Experiment 3 were 13 undergraduate students recruited from introductory psychology classes (mean age = 20.25 years, SD = 1.16, 5 women and 8 men), 18 4-year-olds (mean age = 4.53
years, SD = 0.28, 7 girls and 11 boys), and 15 6-year-olds (mean age = 6.98 years, SD = 0.62, 7 girls and
8 boys) recruited from day care centers and preschools in a large midwestern city.
Materials and procedure
Visual materials in Experiment 3 were identical to those in Experiments 1 and 2; however, a different set of word pairs was used. Word pairs in Experiment 3 consisted of semantically similar natural kind items that were unlikely to co-occur in the CHILDES database (MacWhinney, 2000). The
following five word pairs were chosen based on the semantic similarity ratings from a separate group
of 18 undergraduate students and analysis of co-occurrence frequencies: child–kid, rock–stone, dolphin–whale, tree–bush, and toad–frog. The average semantic similarity rating for this group of words
was 5.58 (on a 1–7 scale), which was comparable to the semantic similarity ratings of the word pairs
used in Experiments 1 and 2 (5.77 and 5.95 for word pairs in the co-occurring and non-co-occurring
conditions, respectively). The analysis of co-occurrence probabilities was conducted in the same way
as in Experiment 1; none of the words within the chosen pairs co-occurred in the speech of children
and their caregivers in the CHILDES database (see Table 1). The calibration experiment described in
the Method section of Experiment 2 established that all words used in Experiment 3 were well familiar even to the youngest participants in this experiment; the 4-year-olds were 98% correct in identifying pictures of objects using semantically similar labels used in Experiment 3.
Results
The proportion of choices of each test item was calculated for each participant and averaged across
participants (see Table 2). Similar to the previous experiments, proportions of generalization of
A.V. Fisher / Journal of Experimental Child Psychology 105 (2010) 198–212
209
semantically similar labels to the similar items were compared with chance (33%) using single-sample
t tests. The proportion of generalizations to the similar items in adults (82%) was above chance,
t(12) > 10.14, p < .0001. Similar to adults, 6-year-olds generalized semantically similar labels to the
similar items (71%) at above chance level, t(14) = 4.69, p < .001. A different pattern of generalization
emerged in 4-year-olds; unlike 6-year-olds and adults, the proportion of generalizations to the similar
items in 4-year-olds (42%) did not exceed chance, t(17) = 1.38, p > .182.
The proportions of choices of the similar items were entered into a one-way ANOVA with age as a
factor. The results of this analysis confirmed that there was a significant difference in the proportion of
generalizations to the similar items in Experiment 3, F(2, 43) = 9.22, p < .001, g2p ¼ :30. Post hoc Tukey’s tests indicated that the performance of 4-year-olds was different from that of 6-year-olds and
adults, both ps < .05, whereas there was no difference in the proportion of generalizations to the similar items between 6-year-olds and adults, p > .53.
The above analysis was supported by the analysis of the individual patterns of responses. In particular, the proportions of participants who reliably (i.e., on at least four of five trials) generalized semantically similar non-co-occurring labels denoting natural kind items to perceptually similar objects
were as follows: 69% of adults (or 9 of 13 participants), 60% of 6-year-olds (or 9 of 15 participants),
and 17% of 4-year-olds (or 3 of 18 participants). The association between age and performance was
statistically significant, v2(2) = 10.25, p < .01. Follow-up analyses indicated that individual patterns
of responses of 4-year-olds differed from those of adults and 6-year-olds, both v2s > 4.90, ps < .05.
At the same time, individual patterns of responses were not different between 6-year-olds and adults,
v2(1) < 1, ns.
The results of Experiment 3 replicated the findings of Experiment 2, suggesting that, unlike most
older children and adults, the majority of 4-year-olds do not generalize semantically similar labels
to visually similar objects if these labels do not co-occur in child-directed speech. These results
indicate that different ontological status of label pairs in Experiment 2 cannot account for different
patterns of generalization in the co-occurring labels and non-co-occurring labels conditions in
4-year-olds.
It could be argued, however, that children had less familiarity with labels in the non-co-occurring
condition than with labels in the co-occurring condition and were generally less likely to generalize
labels with which they were less familiar. For instance, when a target object is introduced as a toad
and children are asked to find another toad among the test items, children might be less likely to
choose the perceptually similar test items compared with the situation where the target object is
introduced as a bunny and children are asked to find another bunny.3 To address this possibility, a separate group of 18 4-year-olds was recruited to participate in the label extension task with identical labels. Children were randomly assigned to the identical/co-occurring condition (n = 9, mean age = 4.62
years) or the identical/non-co-occurring condition (n = 9, mean age = 4.54 years). There were eight nonco-occurring synonym pairs used in Experiments 2 and 3; therefore, the identical/non-co-occurring condition consisted of a total of 16 trials (e.g., on one trial children were asked about a frog, and on another
trial children were asked about a toad). There were five co-occurring synonym pairs used in Experiment
2; therefore, the identical/co-occurring condition consisted of a total of 10 trials (e.g., on one trial children were asked about a bunny, and on another trial children were asked about a rabbit). In both conditions, trials were presented in one of two pseudorandom orders such that semantically similar labels
were not used on successive trials. Results indicated that in the identical/co-occurring condition, the proportion of choices of similar items was 80%, above chance, single-sample t(8) = 4.30, p < .005. These data
suggest that in the three-alternative forced-choice label extension task used in the current research,
choosing similar items approximately 80% of the time is a functional ceiling for 4-year-olds. In the identical/non-co-occurring condition, the proportion of choices of similar items was 83%, above chance, single-sample t(8) = 5.30, p < .005. Most important, the difference between conditions was not significant,
independent-samples t(16) < 1, ns. These results suggest that children were no more likely to generalize
labels used in the co-occurring condition than to generalize labels used in the non-co-occurring condition when the task involved generalization of identical labels. Recall also that in the label calibration
3
I thank an anonymous reviewer for pointing out this possibility.
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described in Experiment 2, 4-year-olds exhibited near ceiling accuracy in using both co-occurring and
non-co-occurring synonyms to identify referent objects (e.g., to identify the same picture as both frog
and toad). Taken together, the results of the label calibration and label extension with identical labels
suggest that differential familiarity of labels is an unlikely explanation for different patterns of generalization of co-occurring and non-co-occurring labels.
General discussion
Results of the three experiments reported above point to several novel findings. First, adult participants were likely to generalize semantically similar labels to perceptually similar items regardless of
the co-occurrence probability of these labels in the lexicon (Experiment 1). Similar to adults, 6-yearolds were likely to generalize semantically similar labels to perceptually similar items regardless of
the co-occurrence probability of these labels in child-directed speech (Experiment 2). Unlike 6year-olds and adults, 4-year-olds were unlikely to generalize familiar semantically similar labels to
perceptually similar items unless these labels regularly co-occurred in the speech of children and their
caregivers (Experiment 2). Finally, these results likely stem from the differences in co-occurrence
probability of semantically similar labels rather than from differences in the ontological status of
the label pairs used in the co-occurring and non-co-occurring labels conditions (Experiment 3).
Results reported here suggest that lack of understanding of class inclusion relations might be the
major reason why 6-year-olds have difficulty in performing reasoning tasks relying on taxonomic labels (e.g., animal–cat). In the current research, the majority of 6-year-olds treated labels as category
markers, as evidenced by children’s reliance exclusively on semantic similarity in the label generalization task regardless of the co-occurrence probability of labels. At the same time, the results suggest a
possibility that younger children’s difficulty in relying on taxonomically related labels in reasoning
tasks might not stem solely from the lack of understanding of class inclusion relations. In particular,
in 4-year-olds, reliance on semantic similarity of labels was mediated by the co-occurrence probability
of semantically similar labels, suggesting that 4-year-olds’ conceptualization of linguistic labels was
different from that of older children and adults. This finding adds to the growing body of evidence
(Fisher & Sloutsky, 2004; Matlen & Fisher, 2008; Sloutsky & Fisher, 2004; Sloutsky et al., 2001) suggesting that understanding of linguistic labels as category markers has a protracted developmental
course and is not yet complete by the time it has traditionally been assumed to have matured—2 to
4 years of age (Gelman & Coley, 1991; Jaswal, 2004; Welder & Graham, 2001).
As stated in the Introduction, there are two ways in which co-occurrence of semantically similar
labels may increase children’s ability to use semantic similarity of labels in reasoning tasks. First,
co-occurrence of semantically similar words may simplify the task of mapping two different labels
onto the same object. In other words, co-occurrence might aid children in establishing the label–object
mappings (see Fig. 1). Second, it is often suggested that semantic knowledge is organized into networks of simple units, with strength of connections among the units being a function of similarity
or relatedness among various features and concepts. Activation of one node in a network is assumed
to spread activation to the interconnected nodes (e.g., activating the node representing the word bird
might activate nodes representing has wings, flies, robin, etc.) (Anderson, 1983; Plaut & Booth, 2000;
Rogers & McClelland, 2004). Lexical associations (i.e., the label–label mappings in Fig. 1) formed as
a result of word co-occurrences in the natural language may amplify children’s reliance on semantically similar labels in reasoning tasks by means of spreading activation. For example, in a property
induction task (Gelman & Markman, 1986), when children are told that a bunny has a particular property and are then asked whether this property would be true of a rabbit or a squirrel, children’s answers might be based not on the understanding that bunnies and rabbits are the same kind of
animal but rather on the fact that activation in the semantic network spread from the word bunny
to activate the word rabbit, whereas the word squirrel received little to no activation from the word
bunny.
The results from the label generalization task presented in this article suggest that the above explanation is a viable alternative to the explanation proposed by Gelman and Markman (1986), namely,
that children realize that bunny is the same kind of animal as rabbit and, therefore, generalize from
bunny to rabbit and not from bunny to squirrel. In particular, if 4-year-olds did not rely on lexical
A.V. Fisher / Journal of Experimental Child Psychology 105 (2010) 198–212
211
associations but instead reasoned that objects denoted by semantically similar labels belong to the
same kind, then 4-year-olds should have generalized semantically similar labels to perceptually similar objects regardless of the co-occurrence probability of labels in the current research. However, unlike 6-year-olds and adults, the success of 4-year-olds on the label generalization task was dependent
on the co-occurrence probability of semantically similar labels.
The experiments presented above examined children’s ability to rely on semantically similar labels
in the context of a label generalization task. Based on the results of these experiments, it is reasonable
to hypothesize that young children might be sensitive to co-occurrence probability in the context of
other generalization tasks such as categorization and property induction. This prediction remains to
be tested in future research; however, preliminary findings suggest that children are more likely to
rely on co-occurring semantically similar labels than on non-co-occurring semantically similar labels
in the context of a property induction task (Matlen & Fisher, 2008).
Overall, the results reported in this article point to a novel finding that co-occurrence probability of
semantically similar labels plays an important role in children’s reliance on semantic similarity of labels in label generalization tasks. These results begin to fill the gap in our knowledge of children’s ability to use semantic similarity of labels under various conditions. These results also indicate that
understanding of labels as markers of category membership continues to develop beyond the age
when children have traditionally been assumed to possess such understanding.
Acknowledgments
I thank Vladimir Sloutsky and David Rakison for their helpful comments on the earlier version of
this article. I also thank Vladimir Sloutsky for providing visual stimuli for this study. These stimuli
were first used in Sloutsky, Kaminski, and Heckler (2005) study.
References
Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning and Verbal Behavior, 22, 2–32.
Baldwin, D. A., Markman, E. M., & Melartin, R. L. (1993). Infants’ ability to draw inferences about nonobvious object properties:
Evidence from exploratory play. Child Development, 64, 711–728.
Banigan, R. L., & Mervis, C. B. (1988). Role of adult input in young children’s category evolution: An experimental study. Journal
of Child Language, 15, 493–504.
Bjorklund, D. F., & Jacobs, J. W. (1984). A developmental examination of ratings of associative strength. Behavior Research
Methods, Instruments, and Computers, 16, 568–569.
Blewitt, P. (1994). Understanding categorical hierarchies: The earliest level of skill. Child Development, 65, 1279–1298.
Bomba, P. C., & Siqueland, E. R. (1983). The nature and structure of infant form categories. Journal of Experimental Child
Psychology, 35, 294–328.
Brown, R., & Berko, J. (1960). Word association and the acquisition of grammar. Child Development, 31, 1–14.
Church, K. W., & Hanks, P. (1990). Word association norms, mutual information, and lexicography. Computational Linguistics, 16,
22–29.
Deák, G. O., & Maratsos, M. (1998). On having complex representations of things: Preschoolers use multiple words for objects
and people. Developmental Psychology, 34, 224–240.
Deák, G. O., Yen, L., & Pettit, J. (2001). By any other name: When will preschoolers produce multiple labels for a referent? Journal
of Child Language, 28, 787–804.
Deneault, J., & Ricard, M. (2006). The assessment of children’s understanding of inclusion relations: Transitivity, asymmetry, and
quantification. Journal of Cognition and Development, 7, 551–570.
DiYanni, C., & Kelemen, D. (2005). Time to get a new mountain? The role of function in children’s conceptions of natural kinds.
Cognition, 97, 325–335.
Dunn, L. M., & Dunn, L. M. (1997). Peabody picture vocabulary test–third edition: Manual. Circle Pines, MN: American Guidance
Services.
Fisher, A. V., & Sloutsky, V. M. (2004). When mats meow: Phonological similarity of labels and induction in young children. In
Poster presented at the 26th Annual Conference of the Cognitive Science Society. Chicago.
Gelman, S. A., & Coley, J. D. (1991). Language and categorization: The acquisition of natural kind terms. In S. Gelman, E. Byrnes, &
P. James (Eds.), Perspectives on language and thought: Interrelations in development (pp. 146–196). New York: Cambridge
University Press.
Gelman, S. A., & Markman, E. (1986). Categories and induction in young children. Cognition, 23, 183–209.
Gelman, S. A., & O’Reilly, A. W. (1988). Children’s inductive inferences within superordinate categories: The role of language and
category structure. Child Development, 59, 876–887.
Gelman, S. A., Goetz, P. J., Sarnecka, B. W., & Flukes, J. (2008). Generic language in parent–child conversations. Language Learning
and Development, 4, 1–31.
Graham, S. A., Kilbreath, C. S., & Welder, A. N. (2004). Thirteen-month-olds rely on shared labels and shape similarity for
inductive inferences. Child Development, 75, 409–427.
212
A.V. Fisher / Journal of Experimental Child Psychology 105 (2010) 198–212
Greene, T. (1994). What kindergarteners know about class inclusion hierarchies. Journal of Experimental Child Psychology, 57,
72–88.
Imai, M., & Gentner, D. (1997). A crosslinguistic study of early word meaning: Universal ontology and linguistic influence.
Cognition, 62, 169–200.
Inhelder, B., & Piaget, J. (1964). The early growth of logic in the child. London: Routledge & Kegan Paul.
Jaswal, V. K. (2004). Don’t believe everything you hear: Preschoolers’ sensitivity to speaker intent in category induction. Child
Development, 3, 279–300.
Jenkins, J. J., & Palermo, D. S. (1964). Word association norms. Minneapolis: University of Minnesota Press.
Johnson, K. E., Scott, P., & Mervis, C. B. (1997). Development of children’s understanding of basic subordinate inclusion relations.
Developmental Psychology, 33, 745–763.
Klahr, D., & Wallace, J. G. (1972). Class inclusion processes. In S. Farnham-Diggory (Ed.), Information processing in children
(pp. 144–172). New York: Academic Press.
Liittschwager, J. C., & Markman, E. M. (1994). Sixteen- and 24-month-olds’ use of mutual exclusivity as a default assumption in
second-label learning. Developmental Psychology, 30, 955–968.
MacWhinney, B. (2000). The CHILDES project: Tools for analyzing talk (3rd ed.). Mahwah, NJ: Lawrence Erlbaum.
Markman, E. M. (1989). Categorization and naming in children. Cambridge, MA: MIT Press.
Markman, E. M., & Wachtel, G. F. (1988). Children’s use of mutual exclusivity to constrain the meaning of words. Cognitive
Psychology, 20, 121–157.
Matlen, B., & Fisher, A. V. (2008). Development of synonym-based induction. In Poster presented at the 30th Annual Meeting of the
Cognitive Science Society. Washington, DC.
McKoon, G., & Ratcliff, R. (1992). Spreading activation versus compound cue accounts of priming: Mediated priming revisited.
Journal of Experimental Psychology: Learning, Memory, and Cognition, 18, 1155–1172.
Mervis, C. B., & Bertrand, J. (1994). Acquisition of the novel name–nameless category (N3C) principle. Child Development, 65,
1646–1662.
Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (1998). The University of South Florida word association, rhyme, and word fragment
norms. Available from: http://www.usf.edu/FreeAssociation.
Nelson, K. (1973). Structure and strategy in learning to talk. Monographs of the Society in Child Development, 38, 1–135.
Plaut, D. C., & Booth, J. R. (2000). Individual and developmental differences in semantic priming: Empirical and computational
support for a single-mechanism account of lexical processing. Psychological Review, 107, 786–823.
Quinn, P. C., Eimas, P. D., & Rosenkrantz, S. L. (1993). Evidence for representations of perceptually similar natural categories by
3-month-old and 4-month-old infants. Perception, 22, 463–475.
Rakison, D. H., & Poulin-Dubois, D. (2002). You go this way and I’ll go that way: Developmental changes in infants’ attention to
correlations among dynamic features in motion events. Child Development, 73, 682–699.
Rogers, T. T., & McClelland, J. L. (2004). Semantic cognition: A parallel distributed processing approach. Cambridge, MA: MIT Press.
Sloutsky, V. M., & Fisher, A. V. (2004). Induction and categorization in young children: A similarity-based model. Journal of
Experimental Psychology: General, 133, 166–188.
Sloutsky, V. M., Kaminski, J., & Heckler, A. F. (2005). The advantage of simple symbols for learning and transfer. Psychonomic
Bulletin and Review, 12, 508–513.
Sloutsky, V. M., Lo, Y.-F., & Fisher, A. V. (2001). How much does a shared name make things similar? Linguistic labels and the
development of inductive inference. Child Development, 72, 1695–1709.
Welder, A. N., & Graham, S. A. (2001). The influences of shape similarity, and shared labels on infants’ inductive inferences about
nonobvious object properties. Child Development, 72, 1653–1673.
Wilson, M. D. (1988). The MRC Psycholinguistic Database: Machine Readable Dictionary, Version 2. Available: http://
www.psych.rl.ac.uk.
Yamauchi, T., & Markman, A. B. (2000). Inference using categories. Journal of Experimental Psychology: Learning, Memory, and
Cognition, 26, 776–795.