The blowfish effect: children and adults use atypical exemplars to infer more narrow categories during word learning

Abstract

Learners preferentially interpret novel nouns at the basic level (‘dog’) rather than at a more narrow level (‘Labrador’). This ‘basic-level bias’ is mitigated by statistics: children and adults are more likely to interpret a novel noun at a more narrow label if they witness ‘a suspicious coincidence’ – the word applied to three exemplars of the same narrow category. Independent work has found that exemplar typicality influences learners’ inferences and category learning. We bring these lines of work together to investigate whether the content (typicality) of a single exemplar affects the level of interpretation of words and whether an atypicality effect interacts with input statistics. Results demonstrate that both four- to five-year-olds and adults tend to assign a narrower interpretation to a word if it is exemplified by an atypical category member. This atypicality effect is roughly as strong as, and independent of, the suspicious coincidence effect, which is replicated.

Full text

ARTICLE
The blowfish effect: children and adults use
atypical exemplars to infer more narrow
categories during word learning
Lauren L. EMBERSON, Nicole LONCAR, Carolyn MAZZEI, Isaac TREVES,
and Adele E. GOLDBERG*
Princeton University, USA
*Corresponding author: Princeton University, Psychology Department, Princeton, NJ 08544, USA.
E-mail: adele@princeton.edu
(Received 13 August 2018; revised 12 February 2019; accepted 18 April 2019)
Abstract
Learners preferentially interpret novel nouns at the basic level (‘dog’) rather than at a more
narrow level (‘Labrador’). This ‘basic-level bias’is mitigated by statistics: children and
adults are more likely to interpret a novel noun at a more narrow label if they witness
‘a suspicious coincidence’–the word applied to three exemplars of the same narrow
category. Independent work has found that exemplar typicality influences learners’
inferences and category learning. We bring these lines of work together to investigate
whether the content (typicality) of a single exemplar affects the level of interpretation
of words and whether an atypicality effect interacts with input statistics. Results
demonstrate that both four- to five-year-olds and adults tend to assign a narrower
interpretation to a word if it is exemplified by an atypical category member. This
atypicality effect is roughly as strong as, and independent of, the suspicious coincidence
effect, which is replicated.
Keywords: word learning; suspicious coincidence; atypicality; language
Introduction
Philosophers and psychologists have long marveled at how it is that children learn the
meanings of new words so quickly and so well (Medina, Snedeker, Trueswell, &
Gleitman, 2011; Quine, 1960). To be successful, children ultimately take a number of
factors into account, including an entity’s shape and function, and its linguistic and
non-linguistic contexts. Perhaps the best-known factor is the tendency to interpret
novel nouns as referring to a BASIC taxonomic level (Golinkoff, Mervis, &
Hirsh-Pasek, 1994; Markman, 1989). For example, speakers tend to interpret a novel
word used to refer to a Dalmatian dog as meaning ‘dog’as opposed to ‘Dalmatian’
or ‘animal’; they likewise tend to interpret a novel word applied to a Macintosh
apple as an ‘apple’and not a ‘Macintosh apple’nor ‘fruit’(Hall, 1993; Hall &
Waxman, 1993; Markman, 1989; Rosch et al., 1976; Taylor & Gelman, 1989;
© Cambridge University Press 2019
Journal of Child Language (2019), 46, 938–954
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Waxman, 1990; Waxman, Shipley, & Shepperson, 1991; cf. Callanan, Repp, McCarthy,
& Latzke, 1994). It is well established that basic-level terms tend to be learned earlier
and used more frequently than more narrow (subordinate level) or more broad
(superordinate level) terms.
It is worth considering why a privileged level of description exists. Murphy and
Brownell (1985) make a compelling case that the basic level conveys the appropriate
amount of information in most contexts. For example, knowing that a thing is an
apple tells us a great deal of relevant information, including what kind of shape and
texture it has, what it tastes like, and how to eat it. Knowing that a thing is more
specifically a Macintosh apple only adds a small amount of additional information
and that added information is often not directly relevant to communicative demands;
it simply doesn’t usually matter if one is holding or has eaten a Macintosh or a Fuji
apple. At the other end of the spectrum, knowing that something is a fruit is often
insufficient, since it tells us little about its size, color, taste, or how it is to be eaten.
That is, the level of description that corresponds to the basic level is one that
determines the category’s overall shape, function, and affordances, and it is therefore
the most appropriate term to use in the majority of contexts.
If learners treat basic-level interpretations as a default, as prior work suggests,
then the question arises as to when and why they ever decide to assign a more
narrow interpretation to a novel word. It is easy to see how witnessing multiple
exemplars from distinct categories can encourage learners to generalize to a higher
level. For example, if Macintosh, Fuji, and Granny Smith apples are all labeled the
same way, then the label cannot refer to any of these subtypes and is instead more
likely to mean ‘apple’. Likewise, if an apple, a banana, and a peach are all labeled
with the same word (e.g., fruit), then the word must refer to an even higher level
of generalization. Learners’ability to interpret words more narrowly than the basic
level, however, is not accounted for as simply (Jenkins, Samuelson, Smith, &
Spencer, 2015). The tendency to interpret words at the basic level helps us learn
the words dog,apple,andtable, and witnessing a word applying to a variety of
exemplars encourages more broad generalizations, but these factors are decidedly
unhelpful for learning words such as Dalmatian,Granny Smith,orcoffee table.
One recognized situation in which a more narrow interpretation is encouraged is
when a new term properly includes a basic-level term: a coffee table is a more
narrow type of table and a Granny Smith apple is a special type of apple, and both
children and adults are sensitive to this (Clark, Gelman, & Lane, 1985;Waxman&
Hatch, 1992).
Recent work has also found that the statistics of the input results in more narrow
interpretations. Specifically, Xu and Tenenbaum (2007) found that when adults and
three- to five-year-old children were shown a single exemplar of a category (e.g., a
picture of a Dalmatian dog labeled a fep), they exhibited the basic-level bias and were
generally willing to extend the label to any instance of the corresponding basic level
category ( fep =‘dog’). But after witnessing three different feps, each of which referred
to a different exemplar of a Dalmatian, participants were much more likely to apply
the term only to other Dalmatians (i.e., a more narrow category) and NOT to other
types of dogs. Xu and Tenenbaum suggest that children and adults are aware that
witnessing three exemplars of a narrow category presents the learner with a
‘suspicious coincidence’, because in ostensive contexts people assume exemplars are
chosen purposely to be representative of the intended category (an assumption of
STRONG SAMPLING). The coincidence is resolved by assuming that the label only refers
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to members of the narrower category ‘Dalmatian’. Thus different statistics of the input
(i.e., witnessing multiple exemplars of a novel word) appear to play a role in
determining which level of categorization a novel term applies to (see also Gweon,
Tenenbaum, & Schulz, 2010; Lawson, 2014; Xu & Denison, 2009; Lewis & Frank,
2018; but cf. Spencer, Perone, Smith, & Samuelson, 2011).
In this paper, we investigate a different way in which learners may be led to a more
narrow interpretation of a novel word. Specifically, we investigate whether the CONTENT
of a single exemplar plays a role in whether learners interpret a novel word at a basic or
more narrow taxonomic level. Specifically, we investigate whether the typicality of the
illustrating exemplar leads to the application of a more narrow interpretation.
Importantly, the rationale described above for preferring basic-level descriptions does
necessarily hold for ATYPICAL exemplars of a category (Murphy & Brownell, 1985).
Atypical exemplars of basic-level categories (e.g., bowling ball,race car) often have
highly salient or relevant properties that distinguish them from other members of the
basic-level category. For example, unlike other balls, bowling balls are heavy and
cannot be thrown; unlike other cars, race cars are usually found on race tracks, are
driven by specially trained drivers, and don’t have car seats for children. Therefore, it
is often pragmatically appropriate to refer to these entities with more specific labels
in order to convey highly relevant information. If the reason basic-level terms are
used most frequently stems from the fact that they provide the appropriate amount
of information, we predict that a novel label for an atypical exemplar should be more
likely to be interpreted as referring to a more narrow taxonomic level, since the
narrower interpretation is more relevant in the case of atypical exemplars. Our
hypothesis can also be construed as resolving a different type of ‘suspicious
coincidence’as follows. Bayesian inference of a word’s meaning involves comparing
hypotheses about the word’s distribution, based on the likelihood of the exemplar(s)
being generated from each distribution, given prior knowledge. Our prior knowledge
tells us that the distribution of category members is not uniform. Some types of
exemplars are more common than others, and atypical exemplars tend to be rare.
Given this, the selection of an atypical exemplar to illustrate the meaning of a word
that refers to an entire basic-level category is unlikely, presenting a type of suspicious
coincidence based on the content of the exemplar rather than the number of similar
exemplars. On the other hand, an atypical exemplar is NOT unlikely if the novel word
refers only to the narrower category. Thus the suspicious coincidence can be
eliminated if the learner assumes that the novel word refers to the more narrow
category. In the experiment reported below, we investigate whether child and adult
learners use the typicality of exemplars to infer the appropriate level of description
for novel words.
It is well known that typicality plays a role in categorization tasks (Larochelle &
Pineau, 1994; McCloskey & Glucksburg, 1978; Murphy, 2004; Murphy & Brownell,
1985; Rips, Shoben, & Smith, 1973; Van Overschelde, Rawson, & Dunlosky, 2004).
For example, Meints, Plunkett, and Harris (1999) showed that one-year-olds restrict
their understanding of many common categories to typical exemplars only, gradually
including atypical exemplars over their second year of life. In a mouse-tracking study
by Dale, Kehoe, and Spivey (2007), adults displayed more competition from a
competing category (fish) when required to classify atypical exemplars of a category
(e.g., whale as a mammal). A particularly relevant demonstration of typicality effects
comes from Mervis and Pani (1980), who found that adults and five-year-old
children generalized within novel categories better and more accurately when shown
940 Emberson et al.
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typical exemplars of the categories compared to atypical exemplars (see also Rips,
1975). Overall, typicality is recognized to affect categorization with both known
categories and in the context of category learning in adults and young children.
While we know that children are sensitive to typicality effects, whether exemplar
typicality plays a role in the context of word learning has not been examined. The
present study asks whether learners interpret labels of a single atypical exemplar
more narrowly than they do if the label applies to a typical exemplar. Following the
rationale from Murphy and Brownell (1985), the basic level is the most contextually
appropriate level of description for typical exemplars in most contexts, but it is not
the most appropriate level of description for atypical exemplars. Are word learners
sensitive to what constitutes the contextually appropriate level of description vis-à-vis
exemplar typicality? Do both adults and children expect speakers to adjust their
labels when a different taxonomic level is more appropriate?
Our goal was to identify whether manipulating exemplar typicality affects word
learning in four- to five-year-old children and adults. Specifically, we hypothesized
that illustrating a novel word with an atypical exemplar would lead learners to
narrow the interpretation of the novel word (e.g., as meaning ‘blowfish’rather than
‘fish’). We also manipulated whether one or three exemplars of a category were
witnessed in order to compare any effect of typicality with the expected effect of the
number of exemplars on participants’tendency to assign a more narrow
interpretation to novel nouns (Xu & Tenenbaum, 2007).
Participants were shown one or three exemplars, which were referred to by a novel
label (e.g., “This is a fep”). Exemplars were either typical or atypical exemplars. The
pictures of exemplars were separately normed for typicality as members of dog, fish,
flower, and bird categories as described in the ‘Methods’section below. Participants
were shown an array of eight entities and asked to “check the box(es) for any other
feps that you find in the pictures below”. The eight pictures always included two
subordinate-level matches (e.g., two additional golden retrievers, if the first exemplar
was a golden retriever), two basic-level matches (e.g., a Labrador and a beagle), and
four distractors (pictures of other categories). The order of the pictures included in
each display was randomized across participants.
In a subsequent task, children were tested on all four categories in order to
determine whether they were able to recognize that the atypical exemplars were
members of the intended categories. Clearly children cannot be expected to interpret
a label at a higher level of categorization if they do not recognize it is a member of
the higher-level category. Children’s performance was therefore reanalyzed considering
only those trials in which the child correctly recognized that the atypical exemplars
WERE instances of the intended basic-level categories. If exemplar typicality does affect
learners’pattern of generalization, it will demonstrate that learners are selectively
altering the level at which a novel word is interpreted, depending on the content of
witnessed exemplar(s).
Methods
Participants
Children
Forty (40) monolingual English-speaking children aged four and five years (26 female,
M= 4;9, range = 4;0–5;10; SD = 6 months) were recruited from the local area through a
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variety of means: during visits to the Baby Lab, community children’s events, or at a
local preschool (N= 17). Monolingual exposure was defined as hearing 80%
English or greater by parental report (language exposure for the included sample:
M= 96.68%, SD = 5.12%, range: 80–100%). An additional 5 children were tested but
not included because of technical errors or a failure to finish all trials in the
experiment (N= 2) or because they did not meet our criteria for being monolingual
(N= 3). No children were excluded on the basis of their selections during the test or
categorization trials (discussed below). Those who took part in the experiment in the
lab setting were given a T-shirt and children’s book for their visit. Those who
participated in the school setting were given a children’s book. Caregivers provided
consent for participation prior to the beginning the study.
Adults
Participants were 43 undergraduate students between the ages of 18 and 25 years (32
females, M= 21 years, SD = 2.56, 95.8% exposure to English), recruited at the student
campus center and compensated with a cookie or cupcake. Participation was preceded by
an explicit consent procedure, and participants were debriefed about the study afterwards.
Stimuli
Visual stimuli
We investigated the role of exemplar typicality and number of exemplars in both children
and adults, using an interactive touch-screen tablet (iPad). Each trial contained either one
or three exemplars of the same narrow (subordinate) category, and the exemplar(s) were
either typical or atypical. Images of dogs, fish, birds, and flowers were used. The stimuli
were extensively normed for typicality as reported in separate work by Emberson and
Rubinstein (2016). Specifically, 62 participants rated how typical the pictures were on a
scale of 1–5 across three experiments (i.e., “How typical is this picture? 1 for not
typical, 5 for very typical”). In each experiment, participants reported significantly
higher ratings for typical than the atypical exemplars employed (typical exemplars
were given an average rating of 4 and atypical exemplars were given ratings averaging
between 2 and 3). The examples of typical and atypical stimuli used in the present
experiments are provided in Figure 1.
Figure 2 presents two representative trials. During the initial introduction to Mr
Frog, participants saw a simple animation of a jumping frog. This same animation
was used prior to the categorization phase at the end of the experiment.
Auditory stimuli
The current study used prosody intended to engage children, recorded by a female
native English speaker. The four novel words that were used throughout the
experiment were fep,zak,lat, and galt, which all obey English phonotactic
constraints. The volume was set to 65% of the total iPad volume and was held at a
constant level for every child in order to ensure that it was not too loud, but that
they could hear the instructions clearly.
A categorization task followed the novel word interpretation task, as described
below. During the categorization phase, children were asked to select examples of the
English categories dog, flower, fish, and bird (e.g., “Can you show Mr Frog the dogs?”).
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Procedure
The experiment was administered using an iPad (Swift, 3.1). Children were generally
seated beside the experimenter, who held the iPad screen at an angle that allowed
the children to view and select the images. Children used a pair of child-sized
headphones that allowed them to hear the instructions while attenuating any
background noise.
The experiment had three phases: an orientation phase, a test phase, and a
categorization phase. The orientation phase was included to familiarize the children
with the on-screen testing method, as well as with the fact that they were able to
select either a single image or multiple images in each trial. This phase consisted of
two trials, each of which was repeated as many times as necessary until the child
correctly completed them. The first of these trials consisted of an array of twelve
images, all of which were primary shapes (e.g., squares, circles, etc.) of varying
colors. The child was then asked by the experimenter to select all of the blue circles
on the screen, of which there were three. If the child did not select all three blue
circles, the experimenter would refresh the screen and ask them to try again. Once
completed without error, children continued to the second orientation trial by
selecting the arrow on the screen. In the second trial the experimenter asked the
children to “find the queen”from a myriad of individuals depicting stereotypical
occupational garb (e.g., a doctor, a king, a queen, a fireman, etc.). Once again, this
trial was repeated until the child selected the single, correct image. Upon completing
this trial, the children were prompted to move on to the test trials by pressing an
orange arrow on the top right of the screen.
The test phase included four trials to test children’s generalization of novel words to
typical and atypical exemplars. We also tested any effects of typicality in relation to the
effect of exemplar number. As in Xu and Tenenbaum (2007, Experiment 2), exemplar
number was manipulated between-subjects. Exemplar typicality was manipulated
within-subjects with typical exemplars presented first and atypical exemplars
presented second, for reasons described in the ‘Supplementary Materials’(available
Figure 1. Representative stimuli.
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at < https://doi.10.1017/S0305000919000266>). We have since reversed the order with a
new group of children and found the same effects (see ‘Supplementary Materials’). Each
child participated in four test trials: the first two consisted of typical target exemplars
while the third and fourth trials consisted of atypical target exemplars.
The number of exemplars presented was manipulated between groups of
participants, so that each person saw only 1-exemplar trials or only 3-exemplar trials.
Within each trial, the child was first introduced to the exemplar(s) at the top of the
screen, paired with a novel verbal label (i.e., “This is a fep”or “These are three
feps”). The child then pressed the arrow at the top of the screen which added an
array of twelve images below the exemplars: 8 distractors (i.e., unrelated to the category
of the exemplar), 2 basic-level matches; 2 subordinate-level matches (Figure 2). The
child was then asked, “Can you find the feps?”and was prompted to select as many of
the images in the array as they wanted to, at their own pace, before proceeding to the
next trial by pressing the arrow again. The order of the four categories of the
Figure 2. Sample selection screens for the single exemplar (top) and multiple exemplars (bottom) conditions.
Children first witnessed only the exemplar(s), which would appear at the top of the screen while paired with a
novel, verbal label. After pressing the orange arrow, they were shown an array of 12 images: 4 distractors as well
as 2 subordinate-level matches and 2 basic-level matches. They could select as many pictures as they wanted.
Note that this Figure only shows 8 images for visual clarity but an additional 4 distractors were presented.
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exemplars –fish, birds, dogs, and flowers –was counterbalanced across participants so
each participant saw each category in one condition only.
Finally, the categorization phase was included to determine whether each child
recognized the intended category in the case of atypical exemplars. In this task,
children were shown the animation of Mr Frog again and asked to teach Mr Frog
words from their language (English). This phase also consisted of four trials where a
single, typical image was provided of each category, and children were asked to select
“the dogs”(or fish, flowers, or birds) from a set of 12 pictures: 8 distractors, 2
typical, and 2 atypical images for that category. Thus in addition to the
categorization task being used to determine whether children recognized atypical
exemplars as members of the intended categories, the task was also useful as a check
that any reduction in responses for later trials in the main task would not arise from
fatigue or distraction. If any children grew weary or distracted by the end of the
experiment, this would be evident in the final categorization trials as well.
With adult participants, the procedure was identical, except for an explanation that
the experiment was intended for young children. Adult participants were allowed to
hold the iPad themselves.
Results
Children’s and adults’generalization to the basic level was modulated by both exemplar
typicality and by the number of target exemplars provided. We employed a logistic
regression to predict the number of basic-level responses (out of 2) for each
participant based on two fixed effects, the number of exemplars (1 vs. 3) and
exemplar typicality (atypical vs. typical), as well as their interaction. Given the
within-subjects design, category was included as a random effect in order to control
for any differences in generalization across categories. The binary variable of
typicality had a reference level of typical and was contrast coded (–1 to 1, for typical
to atypical). The binary variable of number of exemplars (1 vs. 3) used the reference
level of 1-exemplar and it was also contrast coded (–1 to 1, for 1 to 3 exemplars).
We constructed separate models for child (Figure 3) and adult (Figure 4)
participants as well as a combined model to investigate systematic differences across
age groups.
We find an effect of typicality in adults’tendency to generalize (β=–0.586, Ζ=–4.39,
p< .001). Importantly, we also find a similarly robust effect of typicality in children
(β=–0.460, Ζ=–2.82, p< .01). We also replicate the effect of number of exemplars
by finding a significant difference in generalization between single and multiple
exemplars for children (β=–0.579, Ζ=–3.013, p< .01), as well as for adults (β=–0.450,
Ζ=–3.53, p< .01). The effects of the number of exemplars and typicality are again
of roughly the same size, and no interaction is evident in either children (p=.37)
or adults (p= .56).
In addition, we sought to determine whether there were differences between the
children and adults. We augmented the models that had been employed for children
and adults separately to include age group (child vs. adult) as a fixed effect. We
conducted this analysis separately for exemplar number and exemplar typicality as
we find no interaction between these effects in either age group and these models are
more straightforward to interpret. The model for exemplar typicality continues to
find a robust effect (β=–0.524, Z=–4.96, p< .001). We find a small but significant
main effect of age group with children generalizing to the basic level less than adults
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(β= 0.226, Z= 2.14, p= .03). Importantly, we find no interaction between age and
exemplar typicality in the selection of basic-level pictures (p= .51), indicating that
there is no modulation of this effect by age. We find the same results for exemplar
number: In the pooled sample across children and adults, we continue to find a
robust effect of exemplar number (β=–0.476, Z=–4.59, p< .001) and the same small
main effect of age (β= 0.253, Z= 2.44, p= .015), but no interaction of exemplar
number and age (p= .81). Thus, we confirm that exemplar typicality as well as
number of exemplars modulates word learning similarly in children and adults;
specifically, the presentation of an atypical exemplar during word learning results in
a narrower interpretation of the novel word.
Child and adult performance were also consistent with task demands (Table 1).
During test trials, children reliably selected the narrow (subordinate-level) matches
(M= 1.64, SD = 0.66, out of two possible, averaged over all trial types), and rarely
selected distractors (M= 0.21, out of 8 possible, SD = 0.76, averaged over all trial
types). Adults’subordinate selections for test trials were near ceiling (M= 1.98, out
of two possible, SD = 0.19), and they virtually never selected distractors (M= 0.02,
out of 8 possible, SD = 0.13).
We also confirmed that the experimental manipulations (e.g., exemplar typicality)
were not found in selections at the subordinate level in either group. Using the same
models as above but applied to subordinate-level responses, we find all Z-values are
less than the absolute value of 0.4 and all p-values are greater than .7 for children.
We also apply these methods to the distractor responses. We find no effect of
number of exemplars shown on the selection of distractors ( p= .7). However, we
find a marginal effect of the typicality of the exemplar on the numbers of distractors
chosen (β=–0.3688, Ζ=–1.93, p= .054), with more distractors chosen when typical
Figure 3. Children’s mean # of basic-level selections (out of 2) when asked to find matches of a novel word (e.g.,
galt) when witnessing 1 or 3 typical or atypical exemplars. Error bars represent standard deviations.
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exemplars are presented than when atypical exemplars are chosen. Further examination
of this data revealed that, on one trial, one subject selected 6 distractors (a clear outlier).
We conducted this analysis again removing this subject and found no effect of typicality
on distractor selection (p= .28), suggesting that this is not a group-level finding but one
biased by this single trial. Adults also exhibited no differences in subordinate or
distractor selections based on exemplar typicality or number of exemplars (Zs < |0.6|,
ps > .5).
Recall that the subsequent categorization task asked participants to indicate all of the
pictures that matched each familiar basic-level label (e.g., ‘dog’). For each of the four
categories, they were presented with 2 typical, 2 atypical exemplars, and 8 distractors.
As expected, adults reliably included atypical selections when asked to indicate all of
the pictures that matched each basic-level label (M= 1.86, out of 2 possible, SD =
0.25), virtually never included any distractors (M= 0.01, out of 8 possible, SD = 0.11),
and selected atypical exemplars at a greater rate than distractors (t(42) = 50.79,
p< .001). Children also reliably selected atypical exemplars (Figure 5). Specifically,
children were much more likely to include atypical exemplars (M= 1.49, out of 2
possible, SD = 0.77) than distractors (M= 0.25, out of 8 possible, SD = 1.03; paired
samples t-test: t(39) = 10.17, p< .0001). Thus, even though many more distractors
were available for selection than atypical exemplars, children selected atypical
exemplars that matched their familiar basic-level label far more reliably.
At the same time, there is evidence of a typicality effect forchildren inthe categorization
task insofar as they selected the typical exemplars more often than the atypical exemplars
(typical exemplars: M= 1.76, out of 2 possible, SD = 0.53, t(39) = 3.48, p=.001).Sincewe
cannot expect a child to interpret fep as ‘fish’when shown a blowfish if the child failed to
recognize that the blowfish was a fish, we re-ran the analysis for children, excluding test
trials in which the child subsequently failed to include atypical exemplars as
Figure 4. Adults’mean number of basic-level selections (out of 2) when asked to find matches of a novel word
(e.g., galt) when witnessing 1 or 3 typical or atypical exemplars. Error bars represent standard deviations.
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Table 1. Selections of all types for both children (left) and adults (right) in all conditions. Two basic-level options were provided on each trial, so, e.g., 0.66= 33%.
Children Adults
Exposure
Basic-level
matches
(out of 2)
Subordinate- level
matches
(out of 2)
Other
(out of 8) Exposure
Basic-level
matches
(out of 2)
Subordinate- level
matches
(out of 2)
0ther
(out of 8)
1-typical M = 0.66 M = 1.63 M = 0.32 1-typical M = 1.14 M = 2.0 M = 0.02
SD = 0.91 SD = 0.67 SD = 1.10 SD = 0.95 SD = 0.0 SD = 0.15
3-typical M = 0.28 M = 1.60 M = 0.26 3-typical M = 0.50 M = 1.93 M = 0.02
SD = 0.59 SD = 0.77 SD = 0.83 SD = 0.77 SD = 0.34 SD = 0.15
1-atypical M = 0.32 M = 1.76 M = 0.07 1-atypical M = 0.38 M = 1.98 M = 0.02
SD = 0.66 SD = 0.43 M = 0.27 SD = 0.78 SD = 0.15 SD = 0.15
3-atypical M = 0.07 M = 1.59 M = 0.19 3-atypical M = 0.12 M = 2.0 M = 0.0
SD = 0.34 SD = 0.70 SD = 0.64 SD = 0.45 SD = 0.0 SD = 0.0
948 Emberson et al.
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members of the basic-level category in the categorization task. Recall that 40 children
each received four categorization trials for a total of 160 trials. Children failed to
select at least one of these subordinate level pictures on 27 of these trials (17% of
total trials). To determine the effectiveness of this approach, we confirmed that we
do not find any difference in picture selection between typical and atypical
exemplars at test (t(37) = 0.74, p= .47). Even so, the effect of atypicality on
children’s generalization remained significant (β=–0.480, Ζ=–2.64, p< .001), as
did the effect of the number of exemplars (β=–0.750, Ζ=–3.65, p< .01). Thus,
the reduction in basic-level responses after seeing an atypical exemplar cannot be
attributed to children not understanding which category the atypical exemplar
refers to, as this effect is persistent, and even appears to be strengthened, when we
only include trials where children demonstrate knowledge of the atypical exemplars
for a given category.
In addition, we ran an exploratory analysis to determine how category knowledge
related to the effects of exemplar number and typicality. Jenkins et al. (2015) found
that increases in category knowledge resulted in a decrease of the effect of multiple
exemplars on children’s generalization. This finding was contrary to the predictions
of the Bayesian model by Xu and Tenenbaum (2007). We conducted an exploratory
analysis to determine whether category knowledge as assessed during categorization
trials had an effect on children’s use of exemplar typicality and number on their
generalization to the basic level. To quantify category knowledge, we summed correct
responses to the typical and atypical exemplars for each category trials (4 possible
across 4 trials, for a total possible score of 16, M= 13.03, SD = 3.11, median = 13.5,
range = 4–16). This category knowledge score had sufficient variance to separate
Figure 5. Average number of selections made by
children of typical exemplars, atypical exemplars,
and distractors during categorization trials. There
were 2 possible typical and atypical exemplars
and 8 possible distractors. Children were asked
to select all of the members of each category
(i.e., “Can you find all of the dogs?”). Children
selected significantly more atypical matches
than distractor images, but significantly fewer
than typical images.
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children into two groups with low category knowledge (Mcategory knowledge = 10.8,
range = 4–13, age = 4;8, n = 20, 12 female) and high category knowledge (Mcategory
knowledge = 15.25, range = 14–16, age = 4,9, n = 20, 14 female). Category knowledge
is not correlated with age in this sample (r(39) = 0.05, p= .76).
We ran models separately for each to determine the presence or absence of the
effects of exemplar typicality and number on their generalization to the basic level
and then compared performance across groups based on category label. Note that
this is an exploratory analysis and the dataset is divided in two; it is much less
powered than our planned analyses. Overall, we find that the typicality effect that we
report here is present in both groups (high category knowledge: β= 0.490, Z=–1.95,
p= .05; low category knowledge: β=–0.430, Z=–1.977, p= .05), and there is no
difference between groups (all children together, typicality: β=–0.470, Z=–2.81,
p< .01; category label (low vs. high, contrast coded): β=–0.17, Z=–1.01, p= .31;
interaction of typicality and category label: β=–0.027, Z=–0.16, p= .87). However,
we find that category knowledge has an effect on children’s suspicious coincidence
effect (i.e., their generalization after seeing 1 or 3 exemplars). The high category
knowledge group has the suspicious coincidence effect (β=–1.15, Z=–3.04, p< .01),
but the low category knowledge group does not (β=–0.23, Z=–1.16, p= .24). When
considering all children together, we find an effect of category knowledge on the
number of basic-level pictures chosen regardless of trial type (β=–0.43, Z=–2.0,
p< .05), and an interaction of the number of basic-level pictures selected and the
number of exemplars children viewed (β=–0.46, Z=–2.15, p< 0.5; Figure 6).
Discussion
The present results find evidence of the widely assumed basic-level bias only when a
novel label is illustrated by a typical exemplar of the basic-level category. When an
atypical exemplar is provided, novel labels instead tend to be interpreted more
narrowly. That is, when witnessing an unusual dog labeled as a fep, both adults and
four- to five-year-old children are likely to interpret fep to apply narrowly to only
the same type of unusual dog, not to dogs more generally. We find that the effect of
witnessing an atypical exemplar affects both adults and four- to five-year-old
children to roughly the same extent. Both groups generalize a single atypical
exemplar to basic-level pictures less than 20% of the time. We also replicated the
‘suspicious coincidence effect’(Xu & Tenenbaum, 2007), in which witnessing a novel
label applied to multiple examples of the same narrow subcategory encouraged a
narrow interpretation. Moreover, the two effects were roughly equally strong and
independent of one another in both child and adult learners. While we have long
known that children as well as adults distinguish typical and atypical exemplars of
various categories (e.g., Rosch et al.,1976), the present results demonstrate that
children specifically make use of exemplar typicality in their interpretation of novel
words, mitigating the tendency to interpret new words at the basic level. Thus, this
work establishes a new source of information that learners use to make
generalizations of novel words that are narrower than the basic level.
The present findings run counter to the idea that children necessarily assume that
novel words should be interpreted at the basic level, at least if interpreted as a
context-blind bias (Bloom, 2001). Instead, our findings suggest that young children
as well as adults attribute more narrow meanings to novel labels when presented
with unusual or atypical exemplars. We addressed the possibility that children simply
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did not recognize the atypical members as members of the intended categories with the
categorization study results. The categorization task followed the word learning test
phase and asked children to select “all of the dogs (fish, flowers and birds)”.
Children demonstrated high, but not ceiling level accuracy. We therefore considered
performance in the word learning task only on trials in which the same child
accurately selected BOTH atypical exemplars as instances of the intended basic-level
category during the following categorization task. Results demonstrated that, in fact,
children who were shown a blowfish labeled as a fep interpreted fep to mean
‘blowfish’rather than ‘fish’, even when they demonstrably recognized that the
blowfish was in fact a fish in the categorization task. Thus, the blowfish effect
remains in this conservative case and with substantially reduced statistical power
(due to the rejection of 35% of total trials).
Recall that typicality was treated as a within-subjects variable and atypical trials
always followed typical trials, used so that children would need to retreat from an
anticipated basic-level bias upon witnessing atypical examples. We have seen that, in
fact, children did select fewer basic-level items as members of the novel category for
atypical items. Concerns about this order were addressed in a follow-up replication
that we performed with a new group of children who all witnessed atypical
exemplars first. Once again, children treated a novel term introduced with an
atypical exemplar as only applying to the subordinate category, while they treated a
novel term introduced by a typical exemplar as more likely to refer to the basic level
(see ‘Supplementary Materials’).
Children tended to include all category members when asked to select all of the fish,
dogs, flowers, or birds, and selected many more pictures than in the atypical test trials.
And when we only considered trials in which children successfully selected BOTH
atypical pictures as instances of the basic level category (e.g., both pictures of
blowfish were selected as ‘fish’), children nonetheless did not treat the novel label as
a basic-level description. That is, they did not interpret the novel label assigned to a
blowfish as if it meant ‘fish’. Thus, the selection of fewer entities in the main task
cannot be attributed to fatigue.
Figure 6. Left panel: suspicious coincidence effect by category knowledge. Right panel: blowfish effect by
category knowledge.
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One might worry that the present results hinge on the fact that children at this age
already have words for these particular basic-level terms and that THIS is why they tend
to interpret the novel terms at the subordinate level; that is, it is possible that children
interpret fep as something other than ‘fish’because they already have the word fish.
While we know that children do avoid multiple labels for a given concept, this
possibility would not explain the difference between atypical vs. typical examples,
nor would it address the fact that three instances of a subordinate category
were interpreted differently than one (as established in other studies; e.g., Xu &
Tenenbaum, 2007). That is, the idea that a fep should refer to something other than
‘fish’may have reduced basic-level interpretations across the board, but it cannot
predict the especially strong avoidance of basic-level interpretation for atypical
exemplars reported here.
To explain the origin of the blowfish effect, at least three alternatives present
themselves. The explanation we favor was alluded to in the ‘Introduction’: learners
may use Bayesian reasoning to infer that an atypical exemplar was unlikely to be
generated from a category that included many more typical exemplars. Alternatively,
since typical exemplars tend to be labeled with basic-level terms and atypical
exemplars tend to be labeled with more narrowly circumscribed terms (Murphy &
Brownell, 1985), it could be that this specific correlation in our language input is
learned through experience and implicitly affects learners’future interpretations of
novel word labels. This explanation would suggest that the blowfish effect is
dependent on a certain amount of language experience; we might then expect that
adults would exhibit a stronger atypicality effect than children, but we did not find
evidence of this. It remains possible that the atypicality effect is learned as a
correlation if little data is needed to observe the relationship between atypical
exemplars and specific terms, possibly because the correlation is strongly present in
the input that a child receives. Analyses of child language corpora or studies of
naturalistic word learning scenarios would be useful to determine whether caregivers
consistently provide more specific (or modified) basic-level terms when presenting
atypical exemplars to their children (“Look at the greyhound’s long legs. I bet he
runs faster than other dogs.”). Finally, it is possible that a lower-level, attentional
explanation is involved, insofar as the more unusual features of atypical exemplars
may attract more attention, which may in turn lead to a more specific, narrower
interpretation. This explanation would be consistent with Spencer et al.’s(2011)
interpretation of the suspicious coincidence effect; they argued that the reason three
instances are more likely to lead to a subordinate interpretation of a novel word is
that witnessing three instances of the same category leads to increased attention to
the instances’shared attributes. It is possible that both high-level reasoning, language
experience, and low-level attentional factors are involved to different degrees and/or
at different stages of language learning. Clearly more work is needed to draw firm
conclusions as to why exemplar typicality has such a strong effect on word learners’
interpretation of the meanings of novel labels.
Overall, the present results demonstrate that the TYPICALITY of an exemplar plays a
role in which taxonomic level is inferred from a novel label even in young children.
Learners tend to restrict the interpretation of a novel label if it is illustrated by an
atypical exemplar of a higher-level category, even when they recognize that the
atypical exemplar is an instance of the higher-level category. This effect is
independent of, and as strong as, witnessing multiple exemplars of the same subtype:
the suspicious coincidence effect documented by Xu and Tenenbaum (2007). Thus,
952 Emberson et al.
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we have replicated the finding that galt is likely to be interpreted as ‘fish’if it labels a
single salmon, while it tends to be interpreted as ‘salmon’if it is illustrated by three
salmon. The present work highlights a strong and independent effect: if galt labels
even a single ATYPICAL fish –a blowfish –it is quite likely to be interpreted as
‘blowfish’rather than ‘fish’.
Supplementary materials. For Supplementary materials for this paper, please visit <https://doi.org/10.
1017/S0305000919000266>.
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Cite this article: Emberson LL, Loncar N, Mazzei C, Treves I, Goldberg AE (2019). The blowfish effect:
children and adults use atypical exemplars to infer more narrow categories during word learning.
Journal of Child Language 46, 938–954. https://doi.org/10.1017/S0305000919000266
954 Emberson et al.
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