A Domain-General Sense of Confidence
in Children
Carolyn Baer
1
, Inderpreet K. Gill
1
1
, and Darko Odic
1Department of Psychology, University of British Columbia
Palabras clave: confidence, certeza, metacognition, approximate number system, desarrollo
ABSTRACTO
Our minds constantly evaluate the confidence in what we see, think, and remember.
Previous work suggests that confidence is a domain-general currency in adulthood, unifying
otherwise independent sensory and perceptual representations. Aquí, we test whether
children also possess a domain-general sense of confidence over otherwise independent
perceptual dimensions. Six- to 9-year-olds completed either three simple perceptual
discrimination tasks—a number task (“Which group has more dots?"), an area task (“Which
blob is bigger?"), and an emotions task (“Which face is happier?")—or three relative
confidence tasks, selecting which of two trials they are more confident on. encontramos que
while children’s discrimination performance across the three tasks was independent and
constituted three separate factors, children’s confidence in each of three dimensions was
strongly correlated and constituted only a single factor. Our results suggest that confidence is
a domain-general currency even in childhood, providing a mechanism by which disparate
perceptual representations could be integrated.
INTRODUCCIÓN
To learn, representar, and think about the world, our minds constantly deal with uncertainty: Es
my friend angry or surprised? Is it safe to cross the street? To make these decisions, we repre-
sent and reason about our confidence—the subjective probability of an outcome (Mamassian,
2016)—integrating it across different moments, contextos, and timescales. Confidence repre-
sentations in turn guide not only our explicit decisions, but even more automatic, perceptual
unos: when struggling to follow a conversation at a loud cocktail party, Por ejemplo, our eyes
naturally look at a person’s moving mouth to help decode what our ears can’t hear (McGurk &
macdonald, 1976). What is the origin and nature of confidence representations, and how are
they used to compare and integrate information across distinct and independent perceptual
dominios?
Recent work with adults has suggested that perceptual confidence may operate as a com-
mon, domain-general currency, interfacing and integrating across otherwise independent rep-
resentations to guide optimal decision making. Por ejemplo, adults show a strong correlation
in their ability to judge confidence for line orientations versus spatial frequency, even though
these two decisions are behaviorally and neurally independent (De Gardelle & Mamassian,
2014). En la niñez, a domain-general sense of confidence would help in part explain how
children integrate and compare information across distinct and independent sources. por ejemplo-
amplio, a child trying to decide which of two groups is more socially dominant might compare
their confidence in the numerical size of each group against their confidence in the physical
size of each group (Pun, Birch, & Baron, 2016).
un acceso abierto
diario
Citación: Baer, C., Gill, I. K., & Odic, D.
(2018). A Domain-General Sense of
Confidence in Children. Mente abierta:
Descubrimientos en ciencia cognitiva, 2(2),
86–96. https://doi.org/10.1162/opmi_
a_00020
DOI:
https://doi.org/10.1162/opmi_a_00020
Materiales suplementarios:
https://doi.org/10.1162/opmi_a_00020
Recibió: 11 Marzo 2018
Aceptado: 28 Septiembre 2018
Conflicto de intereses: Los autores
declare no conflict of interest in this
trabajar.
Autor correspondiente:
Carolyn Baer
cebaer@psych.ubc.ca
Derechos de autor: © 2018
Instituto de Tecnología de Massachusetts
Publicado bajo Creative Commons
Atribución 4.0 Internacional
(CC POR 4.0) licencia
La prensa del MIT
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Children’s Domain-General Confidence
Baer et al.
Pero, while a domain-general sense of confidence is an appealing mechanism, existing
work has not found a correlation in children’s confidence across independent perceptual di-
mensions. Vo, li, Kornell, Pouget, and Cantlon ( 2014), Por ejemplo, measured 5- to 8-year-old
children’s confidence by having them bet on getting a question right or wrong, and found that
children’s betting in a simple number perception game (p.ej., which box has more dots) y
their betting on an emotion recognition game (p.ej., which face looks happier) did not corre-
late. Sin embargo, tasks requiring children to explicitly rate or gamble on their confidence have
long been known to conflate two key components of children’s confidence representations:
their sensitivity to confidence (the ability to differentiate between states of confidence; p.ej.,
Salles, Ais, Semelman, Sigman, & Calero, 2016), and their response biases, including a gen-
eral tendency to be overconfident (Butterfield, nelson, & Peck, 1988; Lipowski, Merriman, &
Dunlosky, 2013; nelson & Narens, 1980). While both components contribute to confidence
judgments, response biases across tasks (p.ej., overconfidence in one domain and underconfi-
dence in another, as reported by Vo et al., 2014) might influence the detection of underlying
similarities in confidence sensitivity. To eliminate these response biases and focus uniquely on
sensitivity to confidence, we adapted a method used in the adult visual perception literature
that measures participants’ confidence acuity independent of their response biases by ask-
ing them to decide on which of two trials they are relatively more confident, rather than rate
how confident they are on any single trial (Baer & Odic, 2018; De Gardelle & Mamassian,
2014).
Aquí, we use this novel and accessible measure to test children’s confidence acuity in
three distinct perceptual dimensions: number, área, and emotion perception (Odic, 2018; Vo
et al., 2014). We first confirm the domain-specificity of these dimensions in children aged 6 a
9, then investigate whether confidence sensitivity in these dimensions nonetheless correlates,
signaling domain-generality, or if children’s confidence representations are domain-specific
before formal schooling and become domain-general as they develop.
METHOD
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Participantes
Eighty-one 6- to 9-year-old children (m = 7;11 [año; meses], range = 6;0–10;0, 42 girls)
participated in the study, meeting our a priori goal of 40 children per condition and therefore
allowing for adequate psychophysical model fits (Halberda & Feigenson, 2008). Three addi-
tional children participated but were removed from the sample because they failed to complete
al menos 90% of the trials. Participants were tested in a quiet room at an on-campus lab or in
a quiet area of their schools in Vancouver, British Columbia. All children spoke English and
most came from middle-class families.
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Materials and Procedure
Children saw custom-made stimuli on an 11.3 en. Apple MacBook Air laptop using
Psychtoolbox-3 (Brainard, 1997) scripts, which are available online for free use at http://odic.
psych.ubc.ca/scripts/domaingeneralconfidence.zip. Children saw three types of stimuli, de-
scribed in detail below and shown in Figure 1: blue and yellow dots (Número), blue and
yellow blobs (Area), and two emotional expressions (Emoción). Children randomly assigned
to the Confidence condition (norte = 40) were asked to reason about their relative confidence in
answering two questions, while children in the Discrimination condition (norte = 41) were simply
asked to answer the questions. The Discrimination condition therefore allowed us to confirm
the domain-specificity of the perceptual discriminations in these three dimensions, así como
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Children’s Domain-General Confidence
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Cifra 1. Stimuli and results for the Discrimination condition. Children were shown randomly intermixed trials from the three tasks at one
de 5 ratios. As shown in panels a–c, accuracy improved as ratios increased (error bars represent 95% CI). Panels d–f show the correlations
between dimensions. Correlations in brackets are controlling for age. No correlations here are significant.
control for the possibility that correlations between dimensions in the Confidence condition
are due to other domain-general comparison or task-comprehension abilities.
In the Discrimination condition, children saw a Number, Area, o
Discrimination Condition.
Emotion trial in a random, intermixed order. This both prevented order effects between the
three stimuli types and made the task more interesting for children. To remove the influence
of their developing motor skills and inhibitory control, children were asked to either verbalize
their answer or point to one side of the screen, and the experimenter pushed a corresponding
button. Children received feedback after each trial in the form of a prerecorded female voice
that would either give positive feedback (p.ej., “That’s right!") or negative feedback (“Oh no,
that’s not right”). Ocasionalmente, the experimenter would give additional feedback to encourage
the child to stay engaged in the task (p.ej., “That’s okay, let’s do another one”). After completing
12 practice trails that familiarized children with each dimension (4 per dimension), niños
completed a total of 60 ensayos (20 per dimension).
This task was modeled after dozens of studies exploring children’s
Number Discrimination.
approximate number system (ANS), an early sense of number that is broadly shared with other,
nonhuman animals (Halberda & Feigenson, 2008). Children saw a set of yellow and blue
dots, with the yellow dots on the left and the blue dots on the right (Cifra 1) para 1,000 ms—
preventing them from counting—and were asked to identify “which side has more dots.” We
varied difficulty by manipulating the ratio of blue to yellow dots, showing children one of five
ratios on each trial: 3.3 (p.ej., 33 yellow dots and 10 blue dots), 2.1, 1.4, 1.1, y 1.05.
MENTE ABIERTA: Descubrimientos en ciencia cognitiva
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Children’s Domain-General Confidence
Baer et al.
This task was modeled after studies exploring children’s early ability to
Area Discrimination.
discriminate area (Odic, 2018). Children were shown a yellow amorphous blob on the left
and a blue amorphous blob on the right (Cifra 1) para 1,000 EM, and were asked to identify
“which blob is bigger.” We varied difficulty by manipulating the ratio of pixels in the blue
and yellow blobs, showing children one of five ratios on each trial: 3.3 (p.ej., 119,130 yellow
pixels and 36,100 blue pixels), 2.1, 1.4, 1.1, o 1.05.
This task was modeled after studies exploring children’s emotion dis-
Emotion Discrimination.
crimination (Vo et al., 2014). Children saw two female faces that differed in emotion on a
spectrum from happy to angry for 1,000 EM (Cifra 1), and were asked to identify “which face
is happier.” To generate the stimuli, we took a 100% happy and a 100% angry face from four
different female models—two Caucasian and two Asian—and blended the two faces using the
FantaMorph software (Abrosoft, 2007). We blended faces in 6.67% intervals, creating eight
total blends varying from 100% happy (es decir., 0% angry), a través de 53.3% happy (es decir., 46.7%
angry). We varied difficulty by presenting two faces whose difference was either easy to tell
apart (p.ej., 93.3% happy vs. 60% happy, a ratio of 1.56) and some that are very difficult (p.ej.,
73.3% happy vs. 66.7% happy, a ratio of 1.1). This resulted in five different binned ratios: 1.09,
1.2, 1.31, 1.43, y 1.57.
This task used identical stimuli to the Discrimination condition,
Confidence Condition.
with one simple, but major, cambiar: rather than showing children a single trial and asking
them to choose the correct answer, we presented two trials simultaneously and asked chil-
dren to choose which of two trials they wanted to answer (Baer & Odic,2018; De Gardelle &
Mamassian, 2014; Cifra 2). Because we rewarded children for their accuracy through positive
comentario, we expected that children would maximize their chances of success by choosing
the more certain (es decir., easier) pregunta. By varying the difference in difficulty between the two
ensayos, we can identify children who can tell apart only large differences between their confi-
dencia (p.ej., the difference between “very sure” and “not sure”) versus children who can tell
apart even small differences in their internal confidence (p.ej., between “very sure” and “some-
what sure”), giving us a measure of individual differences to compare across domains. Este
relative confidence task is extensively used in the adult perception literature, as it eliminates
the possibility of response biases (p.ej., saying “very confident” on every trial).
Después 12 practice discrimination-only trials, evenly distributed between each dimension,
children completed 45 confidence trials (15 per dimension). On each trial, children were pre-
sented with a pair of stimuli made up of either dots (Número), blobs (Area), or faces (Emoción)
trials used in the Discrimination condition (note that children only saw pairs of stimuli from a
single dimension at a time). As in the Discrimination condition, these stimuli were presented
in a random, intermixed order. Children were asked to identify “which of these two ques-
tions would you like to do.” The trial would stay on the screen until children responded by
verbalizing or pointing to their answer, and the experimenter pushed a corresponding but-
tonelada. To keep children motivated to choose the easier question, the selected trial would then
expand to fill the screen, and children answered the question as in the Discrimination condi-
ción (p.ej., judging which side has more dots in the case of Number). After choosing the answer
for the selected discrimination trial, children received feedback in the form of a prerecorded
female voice. As in the Discrimination condition, the experimenter would occasionally pro-
vide additional feedback to encourage the child to stay engaged in the task (p.ej., “That’s okay,
let’s do another one!"), but the child never received feedback on whether they had successfully
selected the easier question (see Smith, Beran, Couchman, & Coutinho, 2008).
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Children’s Domain-General Confidence
Baer et al.
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Cifra 2. Stimuli and results for the Confidence condition. Children were shown randomly intermixed pairs of trials from one of the three
tasks and asked which question they wanted to answer. Entonces, the screen zoomed in on their selected question and they answered it, just as
in the Discrimination trials. As shown in panels a–c, accuracy improved as ratios increased (error bars represent 95% CI). Panels d–f show the
correlations between dimensions. Correlations in brackets are controlling for age. ** denotes p < .01, *** denotes p < .001.
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To vary the difficulty and estimate individual differences in the precision with which
children could tell apart levels of confidence, we varied the difference in the relative difficulty
between the two presented trials (i.e., the “metaratio”—the larger numerical ratio divided by
the smaller one). For example, children were shown one Number trial with a ratio of 3.3 on the
left (e.g., 33 yellow to 10 blue dots), and a ratio of 1.1 on the right (e.g., 22 yellow to 20 blue
dots), yielding a metaratio of 3.0 (3.3 / 1.1). The difference in difficulty between the two trials
becomes harder to detect as the metaratio approaches 1.0, much like the difficulty in telling
apart two quantities becomes harder to detect as the ratio approaches 1.0. Children were
presented with three metaratios per dimension: 3.0, 2.0, and 1.33 (for Number and Area), and
1.44, 1.31, and 1.1 (for Emotion; e.g., an easy 1.57 ratio vs. a hard 1.09 ratio yields a metaratio
of 1.44).
In previous research, we have shown that children generally want to maximize their
chance of success in relative confidence tasks and therefore choose the trial in which they
have more confidence, producing a metaratio effect: the larger the difference between two
presented ratios, the more likely children are to indicate the easier trial as the one they are
more confident in (Baer & Odic, 2018). However—we also found that, given that we used
wording that uses simple vocabulary and avoids advanced mentalistic terms (i.e., “which trial
do you want to do,” rather than “which trial are you more confident on”), some of the children
in our sample had significant below chance performance in which they consistently selected
OPEN MIND: Discoveries in Cognitive Science
90
Children’s Domain-General Confidence
Baer et al.
the harder of the two trials. Indeed, many of these children would subsequently tell us that
they chose the harder trials in order to challenge themselves. While these children’s consis-
tent preference for the harder ratios clearly demonstrates the ability to differentiate between
their confidence states (which is what we are ultimately interested in), their data also create
a bimodal accuracy distribution, leading to violations of several statistical assumptions. For
this reason, all children’s data were fit both by a psychophysical model assuming that chil-
dren select the easier of the two trials (see Results), and an inverted version of the same model
whereby we assume that children select the harder of the two trials. By using model com-
parison, we identified 10 children whose data clearly show a preference for harder trials: 3
children showed this behavior across all three dimensions, while 6 children showed this be-
havior on only one of the three dimensions. For these children, we treated their inverted model
as the dependent variable (e.g., a child with accuracy of 10% was modeled to have accuracy of
90%). Although our conclusions remain the same with these 10 children removed or modeled
with the noninverted model, we also include a complete report of our analyses with only the
noninverted model in the Supplemental Materials (Baer, Gill, & Odic, 2018).
RESULTS
We first report results from the Discrimination condition, which serves as a control condition,
allowing us to detect any preexisting correlations between perceptual representations or task
understanding in number, area, and emotion perception. Subsequently, we conduct identical
analyses on the Confidence condition to see whether confidence acuity correlates across the
three dimensions.
Discrimination Condition
Children in the Discrimination condition performed above chance for all three dimensions (see
Table 1 for means and tests against chance), and performed significantly better at Area com-
pared to Number (replicating Odic, 2018), and at Number compared to Emotion, F(2, 80) =
14.67, p < .001, η2
= .27. We also found that children’s accuracy on the Emotion trials
p
increased with age, r(39) = .32, p = .04, but found no age effects for the Area or Num-
(39) = −.26, p = .099, most likely due to our
ber trials, r
truncated age range compared to past research in these areas (e.g., Odic, 2018). Additionally,
children’s accuracy varied as a function of ratio in each of the three dimensions (Figure 1a–c):
Number: F(3.23, 129.01) = 24.66, p < .001, η2
= .38; Area: F(1.95, 78.16) = 59.57, p < .001,
p
η2
p
= .60; Emotion: F(3.67, 146.61) = 16.45, p < .001, η2
p
(39) = .07, p = .685, r
= .29.
Num
Area
Table 1. Descriptive statistics, tests against chance, and average estimates of fit to the Weber model.
Dimension
M [95% CI]
t
p
d
# Fit
w [95% CI]
Lapse rate [95% CI]
Discrimination condition
Number
Area
Emotion
81.44 [78.57, 84.30]
85.58 [83.42, 87.74]
73.86 [69.83, 77.90]
Confidence condition
Number
Area
Emotion
75.67 [71.05, 80.29]
82.00 [77.00, 87.00]
67.33 [63.27, 71.40]
22.18
33.30
11.95
11.24
12.95
8.63
<.001
<.001
<.001
<.001
<.001
<.001
3.46
5.20
1.87
1.78
2.05
1.36
41
41
39
37
37
36
.23 [.17, .30]
.10 [.10, .10]
.30 [.16, .44]
.53 [.35, .71]
.32 [.16, .48]
.31 [.19, .43]
.02 [.00, .03]
.01 [.00, .03]
.08 [.02, .14]
.11 [.08, .17]
.13 [.07, .19]
.21 [.13, .28]
OPEN MIND: Discoveries in Cognitive Science
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Children’s Domain-General Confidence
Baer et al.
To simplify data on each child’s accuracy as a function of ratio, we fit children’s accuracy
data to a standard two-parameter psychophysical model widely used in the literature, yielding
an estimate of each child’s Weber fraction (w): the underlying precision of their number, area,
and emotion representations independent of guessing (Halberda & Feigenson, 2008; Odic,
2018; Pica, Lemer, Izard, & Dehaene, 2004). Weber fractions can also be interpreted as the
smallest change in a stimulus that can be reliably detected, thus smaller w estimates indicate
better acuity. This model assumes that the underlying representations of number, area, and
emotion are normally distributed tuning curves with the single parameter w indexing their
standard deviation (i.e., precision; for review, see Halberda, Odic, & Koepke, 2014). On top
of this standard assumption, the model fits the lapse rate, which accounts for a constant per-
centage of trials that participants may have been guessing (e.g., a lapse rate of 0.10 indicates
that participants were randomly guessing on 5% of trials, independent of ratio). More formally,
Weber fractions and lapse rates were estimated using the equation:
Accuracy = (1 − lapse) ∗ Φ
(cid:2)
Ratio − 1
√
1 + Ratio2
w ∗
(cid:3)
+
lapse
2
where Φ is the Gaussian cumulative distribution function. This model was fit to each partici-
pant’s data for each task using R’s optim function (R Core Team, 2018) under the assumption
of normally distributed errors, converging on the best-fit parameters by minimizing the neg-
ative log-likelihood value. We successfully fit the data of all children except for two in the
Emotion Discrimination condition (a typical cut-off of w = 3 was used to fit data; Halberda &
Feigenson, 2008; Odic, 2018; accuracy data for these children were still included in all accu-
racy analyses). The estimated w values for the three dimensions are shown in Table 1, and
replicate previously established values for children of this age (Halberda & Feigenson, 2008;
Odic, 2018).
Finally, we found that children’s performance on the three dimensions were independent
of each other; how well children did on the Number trials did not correlate with how well
they did on Area or Emotion, and vice-versa (Figure 1d–f). This result held for both accuracy
and w data, and held when we controlled for the effects of age (see Table 2). Thus, we can
conclude, consistent with previous work (Odic, 2018; Vo et al., 2014), there is evidence for
domain-specificity in children’s number, area, and emotion perception.
Table 2. Correlations between tasks with and without controlling for age.
Accuracy (r)
w(ρ)
Area
Emotion
Area
Emotion
−.16 (−.15)
.06 (.04)
.00 (.09)
.02 (.02)
.00 (.00)
.23 (.29ˆ)
Discrimination condition
Number
Area
Confidence condition
Number
Area
.46** (.46**)
.59*** (.60***)
.43** (.43**)
.34ˆ (.34ˆ)
.66** (.66**)
.20 (.20)
Note. Accuracy data are correlated using Pearson’s r, while model fit estimates are correlated
using Spearman’s ρ. Correlations controlling for age are shown in brackets. ˆ p < .10, ** p < .01,
*** p < .001.
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Confidence Condition
Children in the Confidence condition also performed above chance for all three dimensions
(see Table 1 for means and tests against chance), choosing the easier of the two trials on 75% of
trials (95% CI[71.44, 78.78], t(39) = 13.84, p < .001, d = 2.19), suggesting that they reasoned
about their relative confidence in the two questions. As in the case of Discrimination, we found
that children were best on the Area trials and worst on the Emotion trials, F(2, 78) = 20.50,
p < .001, η2
= .35. And, much as in the Discrimination condition, we found no correlations
p
between accuracy and age, all rs < .09, potentially due to our restricted range.
Replicating past work using this measure of confidence with Number stimuli, we found
that children were more likely to choose the easier question when the metaratio was higher,
F(2, 78) = 10.00, p < .001, η2
= .20 (Baer & Odic, 2018). In other words, children’s confi-
p
dence discrimination was itself ratio-dependent. But, critically, we also found the same meta-
ratio effect for Area, F(1.53, 59.70) = 5.19, p = .014, η2
= .12, and Emotion, F(2, 78) = 18.57,
p
p < .001, η2
= .32 (see Figure 2a–c), suggesting that it is not merely an effect of number
p
perception, and suggesting that this confidence task can be successfully and reasonably used
across a variety of stimuli types.
Because performance in the Confidence condition was metaratio-dependent, we fit chil-
dren’s confidence data to the same psychophysical model as the one used in the Discrimination
condition, estimating each child’s confidence acuity (the precision with which they can distin-
guish their internal confidence states) separately from their guessing behavior. We successfully
fit all but eight children on all three tasks and all but one child on at least two tasks using the
same criteria of w < 3 as in the Discrimination condition, but retain all children’s accuracy
data for all subsequent analyses. The fit w data are presented in Table 1.
Finally, and most importantly, we found strong correlations between Number, Area,
and Emotion confidence discrimination for accuracy, and slightly weaker correlations with w
(Figure 2, see Table 2). This result stands in strong contrast to the Discrimination condition and
suggests an important degree of domain-generality in confidence perception that is not present
when children are merely discriminating each dimension.
To further confirm the domain-generality of children’s confi-
Principal Component Analyses.
dence perception, we ran two principal component analyses (PCAs), which attempt to simplify
a set of variables into factors that explain the maximum possible variance (Hair, Black, Babin,
& Anderson, 2009): one for accuracy and Weber estimates for all three dimensions in the Dis-
crimination condition, and one accuracy and Weber estimates for all three dimensions in the
Confidence condition.
In the Discrimination condition, there were three components identified in the scree plot
and associated eigenvalues, clustered by dimension. To improve interpretability, the factor
loadings (i.e., the correlations between variables and the extracted components) were varimax-
rotated. Number, Area, and Emotion each uniquely mapped onto separate components, consis-
tent with the interpretation that each dimension is independent (see Table 3 for factor loadings).
In contrast, only one component was identified in the Confidence condition, consis-
tent with a domain-general system. Factor loadings are shown in Table 3 (because only one
component was extracted, these could not be varimax-rotated). An additional analysis in
the Supplemental Materials (Baer et al., 2018) also shows that the two PCAs extracted signifi-
cantly different proportions of variance. In sum, despite strong evidence that the underlying
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Table 3. Factor loadings of measures by dimension.
Discrimination condition
Confidence condition
Component 1 Component 2 Component 3
Component 1
.126
.046
−.966
.971
−.146
−.023
2.07
35%
.953
−.961
−.048
.028
.186
.146
1.87
31%
.009
.037
−.047
.073
−.871
.900
1.44
24%
−.804
.958
−.820
.865
−.841
.908
4.52
75%
Measure
Number
Accuracy
w
Area
Accuracy
w
Emotion
Accuracy
w
Eigenvalue
Variance Explained
Note. Lower w values indicate better precision.
perceptual discriminations are domain-specific, confidence discriminations are domain-general
from at least the age of 6.
GENERAL DISCUSSION
Our data are the first to show evidence of domain-generality in 6- to 9-year-old children’s
sense of confidence: while children’s perceptual discrimination of number, area, and emotion
were dissociated, their confidence judgements over these same dimensions are strongly corre-
lated and constitute a single factor, extending previous work in adults (De Gardelle, Le Corre, &
Mamassian, 2016; De Gardelle & Mamassian, 2014). We find, therefore, that children as young
as age 6 share a domain-general sense of confidence with adults, suggesting that confidence
is either domain-general throughout development, or else is combined before children begin
formal schooling.
Our results hold several
implications about
the nature and origin of confidence
representations.
First, a domain-general sense of confidence should allow children and adults to compare
information across perceptual boundaries. Under many models, and consistent with our dis-
crimination data, perceptual magnitudes are represented on distinct scales (e.g., Odic, 2018),
making cross-magnitude comparison difficult. A domain-general sense of confidence could,
therefore, act as a universal translator between magnitudes: given that confidence in each
dimension could be represented on a scale that is shared broadly across all magnitudes, ob-
servers should be able to easily compare and decide which information is most reliable in a
given context. For example, if our friend says a word that sounds like “noodle” while talking to
a friend about dogs, we can use a domain-general sense of confidence to compare the auditory
cues to the social cues and determine that they must have said “poodle.” Similarly, an observer
faced with a spontaneous discrimination task in which number is easier to discriminate than
area should prioritize numerical information over other magnitudes (e.g., Cantlon, Safford, &
Brannon, 2010).
Second, our results suggest the domain-general confidence scale is itself subject to indi-
vidual differences and that any intervention that helps teach an individual how to make more
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precise confidence decisions should impact confidence across the board, helping or hinder-
ing children’s confidence across perceptual magnitudes. Furthermore, because we find that
confidence precision is correlated even in children, these findings support the view that confi-
dence itself is represented in a domain-general format (De Gardelle et al., 2016; De Gardelle
& Mamassian, 2014), though future work will need to uncover whether this pattern holds at
even younger ages.
In conclusion, we find that children as young as 6—much like adults—have a domain-
general sense of confidence that crosses otherwise independent perceptual representations.
Our work places confidence in a broader developmental context and shows continuity
between adults and developing children’s minds.
ACKNOWLEDGMENTS
We would like to acknowledge the support of the families and schools that participated in this
project.
FUNDING INFORMATION
Carolyn Baer, Social Sciences and Humanities Research Council of Canada (http://dx.doi.org/
10.13039/501100000155), Canada Graduate Scholarship—Doctoral. Darko Odic, Social Sciences
and Humanities Research Council of Canada (http://dx.doi.org/10.13039/501100000155),
Insight Development Grant.
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AUTHOR CONTRIBUTIONS
Carolyn Baer: Conceptualization: Lead; Data curation: Equal; Formal analysis: Lead; Funding
acquisition: Supporting; Investigation: Supporting; Methodology: Equal; Project administra-
tion: Lead; Resources: Equal; Software: Supporting; Visualization: Lead; Writing – original
draft: Lead; Writing – review & editing: Equal. Inderpreet K. Gill: Investigation: Lead; Method-
ology: Equal; Resources: Equal; Writing – review & editing: Equal. Darko Odic: Conceptual-
ization: Supporting; Data curation: Equal; Formal analysis: Supporting; Funding acquisition:
Lead; Methodology: Equal; Resources: Lead; Software: Lead; Supervision: Lead; Visualization:
Supporting; Writing – original draft: Supporting; Writing – review & editing: Equal.
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