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Who is the best judge of a person’s abilities—the person, a knowledgeable informant, or strangers just met in a 3-min speed date? To test this, we collected ability measures as well as self-, informant- and stranger-estimates of verbal, numerical and spatial intelligence, creativity, and intra- and interpersonal emotional competence from 175 young adults. While people themselves were the most accurate about the majority of their abilities, their verbal and spatial intelligence were only estimable by informants or strangers, respectively. These differences in accuracy were not accompanied by differences in the domains’ relevance to people’s self-worth or strangers’ judgment certainty. These results indicate self-other knowledge asymmetries in abilities but raise questions about the reasons behind these asymmetries.
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Journal of Research in Personality 98 (2022) 104226
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Who knows what we are good at? Unique insights of the self,
knowledgeable informants, and strangers into a persons abilities
Gabriela Hofer
, Laura Langmann , Roman Burkart , Aljoscha C. Neubauer
University of Graz, Institute of Psychology, Graz, Austria
Social-emotional competence
Person perception
Self-other knowledge asymmetry
Speed dating
Who is the best judge of a persons abilitiesthe person, a knowledgeable informant, or strangers just met in a 3-
min speed date? To test this, we collected ability measures as well as self-, informant- and stranger-estimates of
verbal, numerical and spatial intelligence, creativity, and intra- and interpersonal emotional competence from
175 young adults. While people themselves were the most accurate about the majority of their abilities, their
verbal and spatial intelligence were only estimable by informants or strangers, respectively. These differences in
accuracy were not accompanied by differences in the domains relevance to peoples self-worth or strangers
judgment certainty. These results indicate self-other knowledge asymmetries in abilities but raise questions about
the reasons behind these asymmetries.
1. Introduction
Nobody knows you better than yourselfis a common piece of folk
wisdom that people tend to believe to be true (Vazire & Mehl, 2008),
even though it might be a misconception: People sometimes have sur-
prisingly little insight into their personality traits (e.g., Vazire, 2010) but
also their abilities (Zell & Krizan, 2014). The latter might be particularly
problematic because an accurate
sense of ones strengths and weak-
nesses can be important. Self-views can inform career decisions and a t
between job demands and actual abilities would be benecial for the
employee and the employer (see also Freund & Kasten, 2012). What is
more, self-estimates are widely used in career counseling, sometimes
even as more economic replacement of psychometric intelligence tests
(Holling & Preckel, 2005). There is also some support that accurate self-
views are associated with higher well-being (Kim et al., 2010; Kim &
Chiu, 2011). Other work found positive (Humberg et al., 2019) or even
overly positive self-views (i.e., self-enhancement; Dufner et al., 2018; He
& Cˆ
e, 2019) to be more benecial. Despite the mixed evidence for the
relative merits of accurate, positive, or inated self-views, in many
areas, the advantages of self-knowledge are likely greater than the costs
(see also Bollich et al., 2011). This raises the following question: How
can we improve our limited knowledge about our abilities?
According to Bollich and colleagues (2011, p. 1), the road to self-
knowledge is likely interpersonal, suggesting feedback from others to
be the most promising avenue towards improving self-knowledge. Ac-
curate ability judgments by others can also be relevant in situations like
job interviews or even at rst dates: Intelligence has been proposed as a
tness indicator that showcases good genes, good health, and good
psychological functioning (G. F. Miller, 2000; Prokosch et al., 2009). It
should, therefore, be both desirable and detectable in potential mates.
Similar arguments have been made for creativity (G. F. Miller, 2000;
Prokosch et al., 2009) and emotional competence (Gignac & Callis,
2020; G. F. Miller, 2007). The high relevance of interpersonal perception
for a species as social as humans likely led us to be good judges of others
(Vazire & Carlson, 2011). And indeed, ability estimates by others can be
similarly or sometimes even slightly more accurate than self-estimates
(e.g., Borkenau & Liebler, 1993; Denissen et al., 2011) and show rele-
vant predictive validity over and above self-estimates (Denissen et al.,
2011; Elfenbein et al., 2015).
Past research indicated that there are personality traits that others
can judge accurately but people themselves cannot, just as there are
traits for which the opposite holds true (Beer & Vazire, 2017; Vazire,
2010; Vazire & Mehl, 2008). The same was observed for ability esti-
mates by adolescents and their schoolmates (Neubauer et al., 2018):
* Corresponding author at: Institute of Psychology, Section for Differential Psychology, University of Graz, Universit¨
atsplatz 2, 8010 Graz, Austria.
E-mail address: (G. Hofer).
Here, accuracy refers to the correlation between judgments and the persons performance on an objective performance measure in the domain in question (see
also Freund & Kasten, 2012; for a discussion on accuracy criteria see Funder, 1995), if not noted otherwise.
Contents lists available at ScienceDirect
Journal of Research in Personality
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Received 21 October 2021; Received in revised form 25 March 2022; Accepted 29 March 2022
Journal of Research in Personality 98 (2022) 104226
While for some abilities, only self-estimates were reasonably accurate,
for other domains only peers provided accurate judgments. Thus,
requesting feedback from others might be particularly helpful for some
abilities but even detrimental for others. It is yet unknown whether these
ndings generalize beyond the school context. Moreover, the level of
acquaintance plays an important role in the accuracy of other-estimates
of personality traits (Paunonen, 1989; Vazire, 2010; Wessels et al.,
2018). Whether this holds true for abilities is still open. The present
investigation aimed to bridge these gaps in the literature. To this end, we
compared the accuracy of perceptions of six different abilities provided
by people themselves, knowledgeable informants, and a set of strangers
just met at a speed-dating event.
1.1. What factors are relevant for accurate interpersonal perception?
Many models of interpersonal perception suggest that both infor-
mational and motivational factors affect accuracy (Vazire, 2010). Ac-
cording to Funders (1995) realistic accuracy model, for accurate
judgments, relevant cues of the trait must not only exist and be available
to the perceiver but also need to be detected and used correctly by them.
While perceivers might be motivated to make accurate judgments, there
are also other motivational forces, like the motivation to think one is
right (Funder, 1995). Correspondingly, many theoretical models (e.g.,
Anusic et al., 2009; Leising et al., 2015; West & Kenny, 2011) consider
that a perceivers judgments of a persons trait are not only driven by the
persons trait levelthe truth”—but also by biases (i.e., factors besides
the truth that affect the judgment; West & Kenny, 2011). Funder (1995)
also proposed that accuracy depends on different types of moderators
pertaining to the trait, the perceiver and the information available to
them, and the target. On the part of the trait, observability (i.e., how
visible the trait is) and evaluativeness (i.e., how socially desirable or
undesirable the trait is) are relevant for accuracy (Funder, 1995; John &
Robins, 1993). More observable traits can be judged more accurately
than less observable ones (John & Robins, 1993), especially if there is a
low level of acquaintance (Paunonen, 1989) or intimacy (Connelly &
Ones, 2010) between the perceiver and the target. Judgments of more
evaluative traits are less accurate, particularly if the perceiver likes the
target (Leising et al., 2015) or if the judgment is a self-rating (John &
Robins, 1993). Highly evaluative traits are thought to be relevant to
peoples self-esteem, making ego-protective mechanisms stand in the
way of accurate self-estimates (see also John & Robins, 1993). The
relationship between perceiver and target can also be a relevant
moderator, as it determines the quality and quantity of information the
perceiver can access (Funder, 1995; see also Wessels et al., 2018).
Vazires (2010) self-other knowledge asymmetry (SOKA) model is a
framework for explaining differences in self- and other-knowledge about
peoples traits. The SOKA model extended the so-called Johari window
(Luft & Ingham, 1955), according to which traits can be assigned to one
of four quadrants based on self- and other-knowledge: The open area
contains traits both targets themselves and others can judge accurately;
the hidden area encompasses traits that only targets can judge; the blind
spot comprises traits that only others can judge; and the unknown area
holds traits that neither targets nor others can judge accurately. Ac-
cording to Vazire, the location of a trait within the Johari window is
determined by two of the aforementioned moderators: observability and
evaluativeness. For other-estimates to be accurate (open area and blind
spot), the trait must be observable, particularly at low levels of ac-
quaintance; for self-estimates to be accurate (open and hidden areas),
the trait must be low in evaluativeness. Results from Vazires (2010)
study conrmed her predictions: Extraversion (high observability, low
evaluativeness) was in the open area, neuroticism (low observability,
low evaluativeness) in the hidden area, and intellect (low observability,
high evaluativeness) mostly in the blind spot. Crucially, the level of
acquaintance was also relevant: Only friendsbut not strang-
ersoutperformed targets in judging their intellect. So far, the SOKA
model has been studied for a variety of characteristics, such as
personality traits (e.g., Beer & Vazire, 2017), personality disorders
(Carlson et al., 2013), and moral behavior (Thielmann et al., 2017).
Neubauer and colleagues (2018) conducted the rst study on the
location of a diverse set of abilitiesverbal, numerical, and spatial in-
telligence, creativity, and intra- and interpersonal emotional manage-
ment abilitiesin the SOKA model/Johari window in 14- and 18-year-
olds. Accuracy was operationalized as the correlation between the ad-
olescents performance in relevant ability tests and ability estimates
provided by themselves and by randomly assigned classmates. Based on
the SOKA model, one might expect that most of these abilitiesperhaps
apart from the two in the emotional domainshould be located in the
blind spot, as they correspond closely to what Vazire (2010) subsumed
under intellect and are likely highly evaluative. This was not the case:
Creativity and numerical intelligence were in the open area, intra- and
interpersonal emotional management abilities were in the hidden area,
verbal intelligence was in the blind spot, and spatial intelligence was
unknown in 14-year-olds and hidden in 18-year-olds. Moreover, Neu-
bauer and colleagues (2018) found no support that the classmatesre-
ported closeness to the targets moderated accuracy, a nding that could
be attributable to the random assignment of peer-raters. It is still unclear
to what extent acquaintance is relevant for an abilitys location in the
model. Equally little is known about the evaluativeness and observ-
ability of abilities and whether they are related to accuracy.
Self- and other-knowledge about abilities might not only be relevant
during adolescence, when important educational and vocational de-
cisions are made (Neubauer et al., 2018), but also later in life. Adults
usually receive less regular feedback on their abilities than pupils, which
might make the maintenance of self-knowledge increasingly difcult.
Thus, it is essential to investigate whether the ndings of Neubauer and
colleagues replicate in an adult sample. In the present study, we assessed
self- and other-knowledge in the same six domains that Neubauer and
colleagues included since these abilities are related to essential life
outcomes such as professional success or academic achievement (e.g.,
intelligence: Hülsheger et al., 2007; Schmidt & Hunter, 1998, 2004;
Strenze, 2007; creativity: Hennessey & Amabile, 2010; Plucker et al.,
2004; Gajda et al., 2017; emotional competence: Freudenthaler et al.,
2008; Joseph et al., 2015; van der Zee et al., 2002). To test the impact of
acquaintance on accuracy, we compared estimates by well-acquainted
informants to estimates by strangers. Given the lack of literature on
evaluativeness and observability of different types of abilities, we built
our hypotheses on past ndings regarding accuracy (to the extent that
they were available).
1.2. Empirical ndings on self-and other-knowledge of abilities
1.2.1. Self-knowledge of abilities
A large body of research reported rather low accuracy of self-
estimates of abilities (for an overview see Neubauer & Hofer, 2020).
Some studies even showed that self-estimates of abilities share more
variance with personality traits than with the respective measured
ability (Herreen & Zajac, 2018; Neubauer & Hofer, 2021). There appears
to be a pervasive tendency towards overestimation (e.g., Alicke &
Govorun, 2005; Gignac & Zajenkowski, 2019). But some people also
underestimate themselves and still others have a rather accurate self-
view (e.g., John & Robins, 1994). This can be particularly detrimental
to overall accuracy since it disrupts rank-order correlations (Beer &
Vazire, 2017). Accordingly, several meta-analyses (e.g., Freund & Kas-
ten, 2012; Mabe & West, 1982), which were ultimately aggregated into a
metasynthesis (Zell & Krizan, 2014), showed a mean correlation of self-
estimates with respective performance measures of only around 0.3. But
accuracy also varies considerably between different domains (Zell &
Krizan, 2014).
Verbal, numerical, and spatial intelligence are included in most
theories of intelligence by both experts and laypeople (Freund & Kasten,
2012). Out of these three factors, people seem to be best at judging their
numerical intelligence (see also Freund & Kasten, 2012): Here,
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
correlations between self-estimates and performance were consistently
moderate to high
(Furnham, 2001; Neubauer et al., 2018; Neubauer &
Hofer, 2021; Proyer & Ruch, 2009; Rammstedt & Rammsayer, 2002;
Visser et al., 2008). More heterogenous ndings but mostly low corre-
lations were reported for verbal intelligence (Furnham, 2001; Neubauer
et al., 2018; Neubauer & Hofer, 2021; Proyer & Ruch, 2009; Steinmayr
& Spinath, 2009; but cf. Rammstedt & Rammsayer, 2002; Visser et al.,
2008) and spatial intelligence (Furnham, 2001; Neubauer & Hofer,
2021; Proyer & Ruch, 2009; Visser et al., 2008; Rammstedt & Ramm-
sayer, 2002; but cf. Neubauer et al., 2018; Steinmayr & Spinath, 2009).
Many studies have found medium to high associations between self-
estimates and variety of creativity criteria (Ceh et al., 2021; Furnham
et al., 2005; Neubauer et al., 2018; Pretz & McCollum, 2014; but cf.
Neubauer & Hofer, 2021; Vazire, 2010). Less research related self-
estimated emotional management abilities to respective performance
measures. In two studies, Elfenbein and colleagues (2015) found low to
moderate accuracy correlations for emotional management abilities
containing both intra- and interpersonal aspects. Other studies that
distinguished between intra- and interpersonal emotional management
abilities found moderate to high correlations for both domains (Freu-
denthaler & Neubauer, 2005; Neubauer et al., 2018; Neubauer & Hofer,
2021). Taken together, there is considerable evidence that peoples es-
timates of their numerical intelligence, creativity, and intra- as well as
interpersonal emotional management abilities correlate at least
moderately with performance in respective ability tests. Comparatively
lower accuracy was often achieved for verbal and spatial intelligence.
1.2.2. Other-knowledge of abilities
Compared to the large body of literature on self-estimates, studies on
the accuracy of other-estimates of abilities are rather sparse (Neubauer
& Hofer, 2020). According to Vazires (2010) ndings, knowledgeable
informantsin that case friendscan provide moderately accurate
judgments of a persons creativity and intelligence and, in that,
outperform both strangers and targets themselves. But informants are
also subject to biases: Relationship partners overestimate their signi-
cant othersintelligence to a similar degree as they themselves (Gignac
& Zajenkowski, 2019). Of the few studies that looked at informant-
estimates of different types of abilities, many focused on pupils. Par-
ents are moderately accurate about their childrens intelligence on
different facets (verbal, numerical, spatial, and reasoning; Steinmayr &
Spinath, 2009). Both parents and teachers are also reasonably accurate
about childrens intelligence and creativity but less accurate about their
social competence (Sommer et al., 2008). In Neubauer and colleagues
(2018), classmates provided moderately accurate estimates of verbal
and numerical intelligence as well as creativity but were less accurate
about spatial intelligence and intra- as well as interpersonal emotional
management abilities. This relative lack of insight of informants into our
emotional abilities also appears to persist in adulthood: Elfenbein and
colleagues (2015) reported similarly low accuracy for ratings on
different aspects of emotional competence by young adults work col-
leagues and fellow students.
There are also reports of valid intelligence ratings by unknown
others. Strangers can be capable judges of a persons intelligence after
observing them in a short video, with correlations ranging from about
0.2 to up to 0.5 (Borkenau et al., 2004; Borkenau & Liebler, 1993;
Carney et al., 2007; Reynolds & Gifford, 2001). In Borkenau and Liebler
(1993), strangersintelligence estimates were even slightly more accu-
rate than those by targets themselves or their romantic partners. Ratings
of strangers who have interacted with targets appear to be somewhat
less accurate: Denissen and colleagues (2011) investigated the validity
of intelligence estimates in student groups who were just getting to
know each other. After being acquainted for two weeks, peer-estimates
within these groups correlated at around 0.2 with measured intelli-
gence. Vazire (2010) reported low accuracy for intelligence and crea-
tivity ratings by strangers who just had a short conversation with the
targets. We know of no video- or interaction-based zero- or low-
acquaintance studies that investigated accuracy for different intelli-
gence facets or emotional competence.
On the whole, existing studies on other-estimates indicate that it is
worthwhile to distinguish between acquainted and unacquainted others
and between different ability domains when investigating accuracy.
While informants might know a lot about our cognitive abilities,
strangersparticularly those that have just met usmight struggle to
see us accurately. However, based on past research, it is still unclear for
which abilities informants might be more accurate judges than strangers
and for whichif anythe reverse is true.
1.3. The present study
The present study aimed to extend research on self-other knowledge
asymmetries in abilities (Neubauer et al., 2018) to young adults. We put
the potential role of acquaintance to a direct test by including ratings by
knowledgeable informants and strangers. As stranger-estimates, we
collected ratings by people who had just met the targets in speed dates.
The speed-dating design enables naturalistic interactions between per-
ceivers and targets (Finkel et al., 2007) and has mostly been used to
study interpersonal attraction (e.g., Asendorpf et al., 2011; Jauk et al.,
2016; Wu et al., 2019) but also to investigate the accuracy of rst im-
pressions (e.g., Kerr et al., 2020). Intelligence, creativity, and social-
emotional competence are among the highest-ranked attributes in pro-
spective mates (Buss et al., 1990; Gignac et al., 2018). Thus, speed
dating might be a context, in which accurate perceptions of an inter-
action partners abilities are especially relevant.
In our rst research question, we wanted to know how accurate the
self, an informant, and strangers are about a persons abilities. We based
our expectations, which are visualized in Fig. 1, on past ndings
regarding accuracy and theoretical considerations. Specically, we ex-
pected self-estimates to be accurate for numerical intelligence, crea-
tivity, and intra- as well as interpersonal emotional abilities but not for
verbal and spatial intelligence (see Section 1.2.1). We predicted that
informant-estimates would be accurate for verbal and numerical intel-
ligence (Neubauer et al., 2018; Steinmayr & Spinath, 2009) and crea-
tivity (Neubauer et al., 2018; Sommer et al., 2008; but cf. Vazire, 2010)
but not spatial intelligence (Neubauer et al., 2018). Contrary to past
work reporting that schoolmates, fellow students, or work colleagues
had little insight into peoples social-emotional abilities (Elfenbein et al.,
2015; Neubauer et al., 2018; Sommer et al., 2008), we expected our
studys well-acquainted informants to be accurate judges of the targets
intra- and interpersonal emotional abilities. Close others are likely often
on the receiving end of a persons interpersonal emotional management
efforts. Moreover, intrapersonal emotional management abilities
correlate highly with neuroticism (Freudenthaler & Neubauer, 2005),
which friends judged accurately in Vazire (2010). Data on stranger-
estimates were only available for one of our six abilities: In line with
Vazire (2010), we expected low accuracy for stranger-estimates of
creativity. Denissen and colleagues (2011) reported similar accuracy of
intelligence estimates shortly after meeting new classmates and during a
year of getting to know them. Therefore, we mostly based our expec-
tations regarding estimates for intelligence facets on past ndings for
peers (Neubauer et al., 2018), predicting valid stranger-estimates for
verbal but not spatial intelligence. As it seems unlikely that numerical
intelligence is similarly observable in rst dates as it is in school con-
texts, we expected low accuracy in this domain. Based on the low ac-
curacy of stranger-estimates of neuroticism reported by Vazire (2010),
we also expected low accuracy for the related intrapersonal emotional
abilities. Finally, we expected accurate stranger-estimates of interper-
sonal emotional abilities, since speed dating might be a scenario where
these skills are particularly relevant and practical relevance is positively
Here, we follow common effect size guidelines (Cohen, 1992) for quanti-
fying correlations as small (r 0.1), medium (r 0.3), and large (r 0.5).
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
associated with accuracy (Gill & Swann, 2004).
Our second research question referred to potential differences in
accuracy between perspectives. We expected similar accuracy for all
three perspectives for interpersonal emotional abilities (moderate ac-
curacy) and spatial abilities (low to no accuracy). For verbal abilities, we
expected estimates by informants and strangers to be more accurate than
those by targets themselves. For creativity, numerical and intrapersonal
abilities, we expected self- and informant-ratings to be similarly accu-
rate but stranger-ratings to be less accurate than both other perspectives.
In our third research question, we investigated the unique predictive
validity of each perspective and the amount of variance in measured
respective abilities all perspectives could explain conjointly (see also
Vazire, 2010). Here, we had no specic expectations.
We also had two exploratory research questions: First, some studies
suggest that gender might be related to the accuracy of ability estimates
(e.g., Herreen & Zajac, 2018; Steinmayr & Spinath, 2009; but cf. Freund
& Kasten, 2012). In the speed-dating design of our study, stranger-
estimates for female targets also only stemmed from men and vice
versa. Therefore, we explored gender as potential moderator of accuracy
with no specic prior expectations. Second, we wanted to collect pre-
liminary data related to the evaluativeness and observability of our
domains of interest. Researchers typically obtain assessments of a traits
evaluativeness and observability by asking external raters (experts or
laypeople) how socially desirable and easily observable the trait is (e.g.,
John & Robins, 1993). These trait-level assessments leave little room to
investigate individual differences. It is reasonable to speculate that most
of the abilities we study are rather desirable and, in that, evaluative (see
also Zell & Krizan, 2014), meaning that their self-worth relevance might
hamper the accuracy of self-estimates (Vazire, 2010). However, as
William James (1890/1950) already suggested, people might differ in
what is important to their self-esteem (see also Zell & Krizan, 2014)a
notion that is in line with the concept of contingencies of self-worth
(Crocker & Wolfe, 2001). To account for these potential interindi-
vidual differences, we let targets directly rate the relevance of each
domain to their self-esteem (i.e., in the form of ability-related self-worth
contingencies) instead of assessing evaluativeness as trait-level social
(un-)desirability. Observability should be particularly relevant in low-
acquaintance perception (e.g., Paunonen, 1989; Vazire, 2010), which
is why we were particularly interested in its relationship to stranger-
estimates. A traits observability reects the availability of valid
behavioral cues indicative of the trait (Funder, 1995; Thielmann et al.,
2017) and this availability can depend on the context (Wall et al., 2013).
For this reason, we found it worthwhile to directly assess observability
within this studys low-acquaintance context (speed dates). At the
speed-dating events, we aimed to collect data with short, intuitive
measures to preserve the validity of this naturalistic setting. When we
conceptualized our measures and discussed them with laypeople, it
became apparent that some struggled to understand the concept of
observability. We, therefore, asked raters instead how certain they were
of each of their judgments. As people tend to report higher judgment
certainty if more cues are available to them (Tsai et al., 2008) and the
availability of cues is at the core of the concept of observability (e.g.,
Funder, 1995), we considered this to be a valid proxy. There is some
evidence that ratersjudgment certainty differs across targets (Praetor-
ius et al., 2013). We, thus, assessed judgment certainty for each indi-
vidual target.
2. Methods
Data for the present study were collected within a larger research
project on abilities, interpersonal perception, and romantic attraction.
Results on another research question focusing on the relationship be-
tween romantic attraction and intelligence, creativity, and emotional
management abilities are reported elsewhere (Hofer et al., 2021). In line
with community standards (Simmons et al., 2012), we report how we
determined our sample size, all data exclusions, and all measures in the
study. This study was preregistered and our code and materials are
openly available to the extent possible
. Data-collection involved mul-
tiple steps: First, targets registered via an online form, where they also
provided the contact of an informant. They then took part in a pre-
testing session and, nally, in a speed-dating event. The study had
been approved by the local ethics committee and all parties provided
their informed consent.
2.1. Participants and power analysis
We determined our target sample size of 180 based on power-
recommendations for our type of social relations model (Kenny et al.,
Fig. 1. Predictions on positions of abilities within the Johari window (Luft & Ingham, 1955)/SOKA model (Vazire, 2010). Other-knowledge by knowledgeable
informants (left) and strangers after 3-min speed dating interactions (right).
In our OSF-project (, we provide our preregistration
as well as a list of any deviations. We share our analysis scripts and all study
material that we are allowed to share (i.e., everything apart from copyright-
protected tests of intelligence and emotional competence). Data for this proj-
ect are available via
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
2006) and to achieve at least 80% power to detect positive correlations
of r 0.2 (n
=153 with
=0.05)an effect size that appears
reasonable given past work in this area (see e.g., Beer & Vazire, 2017; for
a more detailed reasoning see section 2.4; Denissen et al., 2011; Zell &
Krizan, 2014). To counter potential drop-out, registration was open for
210. In the end, 180 people (targets; 50% women) participated in all
parts of the studyincluding a speed-dating event. In speed dating,
people typically meet others of similar age (Back et al., 2011). Thus, to
have relatively age-homogeneous groups, our age limits were 18 to 30
years. Each target attended one of seven heterosexual speed-dating
sessions, where they met between 11 and 14 people (women inter-
acted with men and vice versa). After each of these 1157 interactions,
both speed-dating partners completed ratings about each other (2314
ratings in total). Data from two homosexual participants and one
participant with low compliance
were excluded on the dyadic level
(leaving 2240 ratings). Another two were excluded on the individual
level (i.e., their ratings were still included in their speed-dating partners
stranger-estimates) because they had not completed all performance
measures. The nal sample comprised 175 participants (87 women, 88
men; 2188 ratings) between 18 and 30 years (M =22.51, SD =2.81).
89.7% were university students, 49% of them studying psychology.
79.9% reported A-levels as their highest level of education; 21.1% held a
university degree. 166 were single; 4 were in an open relationship and 5
in a monogamous relationship
. We recruited participants via social
media, mailing lists, and advertisements on campus and in a local
magazine. Participation at the speed dating event was freewith com-
parable commercial offers costing between
15 and
20and psy-
chology students additionally received course credit.
2.2. Procedure
2.2.1. Informant-ratings
We instructed targets to name a person they were close to (e.g., a
good friend, roommate, or sibling) and had known for at least 6 months
as informant. They could also name a second informant to be contacted
as stand-in. We collected ratings by one
informant (108 women, 67
men, age: 1856, M =23.35, SD =5.38) per target via a 15-minute
online survey sent to informants per e-mail. After providing informed
consent, informants indicated the closeness of their relationship to the
target on the one-item Inclusion of Other in the Self Scale (IOS; Aron
et al., 1992). Scores can range from 1 to 7 with higher values for higher
closeness and, on average, informants reported relatively high rela-
tionship closeness (M =5.19, SD =1.41). They then responded to de-
mographic questions. Like targets themselves, informants were highly
educated (66.3% had completed their A-levels and 28% held a univer-
sity degree). 74.3% were university students, 33.1% of them psychology
students. Participants tended to nominate informants of the same
gender: 86.21% of womens informants were women; 62.50% of mens
informants were men. On average, informants had known the targets for
8.44 years (SD =7.39). With 81.1%, most informants were friends.
14.9% were related to the target (e.g., siblings). Three informants were
roommates and another three were romantic partners of the targets. The
last measure completed by informants was a scale assessing their esti-
mates of the targets abilities (see Section 2.3.2).
2.2.2. Pre-testing session
In a 1.5 h-long pre-testing session, participants completed psycho-
metric tests in gender-homogenous groups of between 5 and 25. We rst
collected data on objective performance via a paperpencil intelligence
test battery and computerized measures of creativity and emotional
abilities (see section 2.3.1). Participants then responded to computer-
ized questionnaires on self-estimates of abilities (see section 2.3.2),
ability-related self-worth contingencies (see section 2.3.3), and vari-
ables that are not relevant to the present research (for a full list of all
measures see OSF).
2.2.3. Speed-dating procedure
Each participant attended one of seven speed-dating events that
followed the procedure of past studies (Asendorpf et al., 2011; Jauk
et al., 2016). Assignment to speed-dating events was random within
participants availabilities. The events took place on weeknights in a
baroque chateau on the universitys campus in a relaxed atmospher-
ewith dimmed lights and smooth jazz playing in the background. To
avoid contact before the dates, women and men used separate entrances
to get to separate waiting areas. There, we provided them with a code to
be worn visibly throughout the evening, photographed them under
standardized conditions
, and gave them standardized instructions. The
dates took place in a hall containing 15 speed-dating booths, which were
arranged in a triangular shape and each contained a table and two
chairs. Men entered the hall rst and waited at another set of tables, with
their backs towards the booths. Then, women arrived and sat down in
the booths. The speed dates started with the ringing of a bell, signaling
that men should turn around and join the woman in the booth facing
them for the rst date. The speed-dating partners had 3 min to chat
before another signal indicated for men to return to their tables. Both
parties then completed their score cards, which contained two dichot-
omous items on acquaintanceship (Have you seen this person before?
and Do you know her/him personally?)
, six items to estimate the
other persons verbal, numerical and spatial intelligence, creativity,
intra- and interpersonal abilities (see Section 2.3.2), another six to
measure judgment certainty for the respective abilities (see Section
2.3.3), and other items not relevant to the current study (the full score
card is available on the OSF). Participants also indicated whether they
wanted to meet this partner again. If both partners responded with a yes,
they received each others contact details in the days following the
events (13.71% of all dates). Once everybody had completed their score
cards, another signal indicated for men to go to the next booth. This
procedure was repeated until all men had met all women (and vice
2.3. Main measures
2.3.1. Objective performance measures
We applied three subtests of the well-established German Intelligenz-
Struktur-Test-2000-R (Liepmann et al., 2007)each comprising 20
itemsto measure verbal (similarities), numerical (number series), and
spatial intelligence (gure selection). All subtests were presented within
the time limits and according to the instructions proposed by the test
authors. Internal consistency was good for numerical (
=0.87) and
spatial (
=0.77) intelligence but quite low for verbal intelligence (
We measured creativityoperationalized as divergent thinking-
with a computerized version (Jud, 2018) of the Alternative Uses Task
(Benedek et al., 2013; Guilford, 1967). Here, participants had to nd
Due to this targets negative comments during the speed-dating event and
an informant email address that was conspicuously similar to the targets own
one, we have serious doubts about the quality of their data.
As the majority of these participants indicated to be interested in second
dates or a relationship with some speed-dating partners, we retained them in
the sample to preserve power.
For two participants two informants had completed the survey. In both
cases, the rating that had been completed rst was retained.
These photos were used for physical attractiveness ratings that are not
relevant to the present research questions (for a detailed description see Hofer
et al., 2021).
We removed ratings from 55 dates where at least one of the two partners
indicated to know the other.
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
creative ideas that other people would consider original, clever, un-
usual, interesting, or humorousfor alternative uses of a plastic bottle, an
umbrella, and a shoe, each within 2.5 min. They were also told to
emphasize originality over quantity. Six non-expert raters (2 men, 4
women) evaluated the originality of participantsresponses on a scale
from 0 (not creative) to 3 (very creative), after completing a short
training (see also Benedek et al., 2017). Originality was then averaged
across the three highest-rated ideas per object and participant to reduce
the confounding inuence of ideational uency (i.e., the number of
ideas; Benedek et al., 2016, 2017; Smeekens & Kane, 2016). This
resulted in satisfactory inter-rater reliabilities (
=0.88) and internal consistency across objects (
For exploratory purposes, we also calculated mean ideational uency
across objects as an additional creativity measure (
Intra- and interpersonal emotional management abilities were
measured with the typical-performance emotional management test
(TEMT; Freudenthaler & Neubauer, 2005). This situational judgment
test contains 42 short descriptions of emotionally laden situations, 18 of
them requiring intrapersonal and 24 requiring interpersonal emotional
management abilities. Out of four response options, participants are
asked to select the alternative that is closest to how they would typically
react in the given situation. We recoded responses according to their
adequacy (1 =least adequate, 4 =most adequate), based on expert
consensus established during test construction. As often the case with
situational judgment tests (MacCann & Roberts, 2008; McDaniel et al.,
2007; Neubauer & Hofer, 2021)which are inherently heterogeneous
(Libbrecht & Lievens, 2012; McDaniel et al., 2007)internal consis-
tency for both subscales was rather low (intra:
=0.60; inter
0.57). However, a current study (Neubauer and Hofer, 2022) has found
evidence of good testretest reliabilitywhich is considered a more
suitable reliability indicator for these kinds of tests (e.g., McDaniel et al.,
2007)for both subscales (intra: r
=0.83; inter: r
=0.76). We used
mean response adequacy for all analyses.
2.3.2. Self- and other-estimates of abilities
Self- and informant-estimates of verbal, numerical, and spatial in-
telligence, creativity, and intra- and interpersonal abilities were
measured with a questionnaire that was originally constructed for ad-
olescents (Neubauer et al., 2018) and adapted to adults (Neubauer &
Hofer, 2021). Each subscale contained nine to ten items, with all but the
last of them covering different aspects of the pertinent ability (e.g., It is
easy for me to nd a synonym for a word.for verbal abilities). The nal
item reected a more global perspective on the respective ability (e.g., I
am very talented in the verbal domain. for verbal abilities). For
informant-estimates, items included blanks that raters were instructed
to mentally ll with the targets name (e.g., It is easy for _______ to nd a
synonym for a word.). Response alternatives ranged from 1 (strongly
disagree) to 5 (strongly agree). Internal consistencies were satisfactory
to good for both self-estimates (
=0.83) and
informant-estimates (
=0.91). For stranger-
estimates, we only presented the six global items due to time con-
straints at the speed-dating events (e.g., I think this person is generally
very talented in the verbal domain.).
2.3.3. Self-worth relevance and judgment certainty
In line with the concept of self-worth contingencies (Crocker &
Wolfe, 2001), we conceived a six-item measure to assess how relevant
high performance in each of the domains was to the participantsself-
worth (e.g., For my opinion about myself, it is important to be very
talented in the linguistic domain.) with a Likert-like response scale
from 1 (do not agree) to 10 (strongly agree). As an approximation of
observability, we assessed speed-dating partnersjudgment certainty by
asking them on the score cards how certain they were about each of their
ability-estimates. They provided their responses on a 5-point Likert-like
scale ranging from very uncertainto very certain.
2.4. Data analytic strategy
Like past work, we took an effect-size-based approach towards ac-
curacy and differences thereof. We regarded correlations between esti-
mated and measured abilities of at least 0.2 as relevantly accurate (see
also Beer & Vazire, 2017; Neubauer et al., 2018; Vazire & Mehl, 2008).
This corresponds to the average effect in individual difference studies
(Gignac & Szodorai, 2016) and the mostly small to moderate effects in
this line of research (e.g., Denissen et al., 2011; Zell & Krizan, 2014). In
line with earlier studies (Neubauer et al., 2018; Vazire, 2010), we
considered correlational differences of at least 0.15 as indicative of a
relevant difference. Vazire (2010) suggested this approach since 0.15
corresponds to roughly one standard deviation in the distribution of
typical effects in personality and social psychology (see Richard et al.,
2003) and available statistical tests of correlational differences are very
Ratings that are aggregated across raters or items are more reliable
(e.g., Epstein, 1983) andfor purely statistical reasonsmore accurate
than ratings made by single perceivers or on single items (e.g., Nestler
et al., 2012). To benet from maximum reliability, we, therefore,
aggregated self- and informant-estimates across multiple items per
domain and stranger-estimates across multiple raters
. For stranger-
estimates of abilities, we computed target effects within the social re-
lations model (SRM), using the formulae provided by Kenny and col-
leagues (2006). A persons target effect for a given ability represents the
average (group-mean-centered) rating they received for this ability. As
an example, Rons target effect for creativity reects how creative Ron is
viewed across all his speed-dating partners, as compared to the other
members of his speed-dating session. To enable a better comparison
between sources, we also reported accuracy based on disaggregated
data, that is data from single items and perceivers (for the importance of
reporting both single and aggregate perceiver accuracies see Back &
Nestler, 2016). For self- and informant-estimates, we calculated dis-
aggregated accuracy based on the global item (i.e., the item also
included in the score cards), so that estimates by all three sources were
based on the same, single item. Correlations between these single-item
estimates and the respective scale means were between 0.74 and 0.87
for self-estimates and 0.79 and 0.85 for informant estimates. For dis-
aggregated stranger-estimates, we followed Vazires (2010) approach:
We drew a single perceiver for each target and domain and computed
the correlation between their estimate and the targets performance. We
repeated this process 15 times, Fisher-r-to-Z-transformed the 15 corre-
lations, averaged them, and transformed them back to the r-metric.
3. Results
We conducted our main analyses in R (R Core Team, 2021; for a full
list of packages see Appendix 1 on the OSF; Our
scripts are also available on the OSF. When possible, we report
percentile condence intervals based on 2000 bootstrapping samples to
counter violations of assumptions related to non-normality or hetero-
scedasticity of some variables.
3.1. Descriptive statistics, intercorrelations, and variance partitioning
Descriptive statistics (Table A1 on page 7 of Appendix 1) and in-
tercorrelations (Appendix 2) of all main variables can be found on the
OSF. Within the SRM, variance in ratings can be portioned into different
While recruiting multiple informants per target would have likely also
resulted in reliability benets, this would have further increased participant
burden, which was already considerable in this multi-step data collection
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
components (Kenny et al., 2006). We followed the guidelines by
Ackerman et al. (2015) to conduct SRM variance partitioning analyses in
IBM SPSS (for full results see Table A3 in Appendix 1). Importantly,
between 6.91% and 26.66% of the variance in speed-dating ability es-
timates could be attributed to characteristics of the target (target vari-
ance). This target variance was signicant for both genders and all
ability domains (all p .001), indicating a certain consensus in how
perceivers saw the same target. Another 7.20% and 20.02% of variance
pertained to characteristics of the perceiver (perceiver variance). The
remaining 62.58% to 76.18% consisted of dyadic components (rela-
tionship variance) and error variance.
3.2. Accuracy of self-, informant-, and stranger-estimates and differences
between perspectives
To answer our rst research question, we have computed correla-
tions between estimates by the different sources and corresponding
ability measures. The left-hand part of Table 1 shows these correlations
for aggregated estimates (i.e., estimates that are more reliable but less
comparable across sources). In line with our expectations, self-estimates
of numerical intelligence, creativity, and the two social-emotional
abilities showed relevant accuracy (i.e., r 0.2). We had further pre-
dicted that informant-estimates would show relevant accuracy for ver-
bal and numerical intelligence, creativity, and the two emotional
abilities. Results conrmed these expectations for all but intrapersonal
emotional abilities (r 0). Finally, we had expected relevant accuracy
for stranger-estimates of verbal intelligence and interpersonal emotional
abilities. However, only stranger-estimates of spatial intelligence were
accurate, with estimates of numerical intelligence slightly below the
accuracy threshold. Note that the accuracy of self-, informant-, and
stranger-estimates dropped considerably when we used ideational
uency instead of originality as performance criterion for creativity. The
right side of Table 1 shows accuracy correlations based on disaggregated
data (single items for self- and informant-estimates and single raters for
stranger-estimates). Self-estimates again correlated at or above 0.2 with
performance in four of six domains. Informant- and stranger-estimates
based on disaggregated data, by contrast, failed to reach the accuracy
threshold in any domain. Accuracy for creativity was again lower when
ideational uency instead of originality was used as criterion.
To answer our second research question, we determined for which
domains the correlations in Table 1 showed relevant differences be-
tween sources (i.e., r
0.15). For aggregated estimates, the following
differences emerged: Contrary to our prediction, others had no accuracy
advantage over the self for verbal intelligence. Also unexpectedly,
informant-estimates of verbal intelligence were more accurate than
those by strangers. We had expected that both the self and informants
would outperform strangers in estimating numerical intelligence, crea-
tivity, and intrapersonal abilities. However, the relevant comparisons
only surpassed our threshold for self- but not informant-estimates.
Moreover, self-estimates of numerical intelligence and intrapersonal
abilities were also more accurate than corresponding informant-
estimates. Contrary to our expectations that all perspectives would
provide similarly inaccurate estimates of spatial intelligence, stranger-
estimates were more accurate than those by informants. Lastly, we
had expected comparably accurate estimates of interpersonal abilities
by all three sources. However, self-estimates were more accurate than
those by strangers. Findings concerning differences between perspec-
tives differed slightly for disaggregated data: Here, the self was more
accurate than both other sources about numerical intelligence, intra-
personal emotional abilities, and creativity. While informants continued
to be more accurate than strangers in judging verbal intelligence,
strangers were no longer more accurate than informants in judging
spatial intelligence.
3.3. Unique validity of each perspective and variance explained by all
perspectives combined
To determine the unique and conjoint variance in measured abilities
that estimates by the different sources could explain (research question
three), we ran six multiple regressions (one per domain) with perfor-
mance as outcome and estimates as predictors. We used aggregated data
for this purpose since we were interested in the best possible prediction.
Table 2 shows that the total amount of variance all perspectives
explained conjointly ranged from 0.05 for verbal intelligence to 0.29 for
Table 1
Accuracy correlations for self-, informant-, and stranger-estimates of abilities based on aggregated and disaggregated data.
Aggregated Disaggregated
Domain Self Informant Stranger Self Informant Stranger
Verbal 0.149 0.209
0.143 0.192
[0.018, 0.324] [0.064, 0.363] [0.145, 0.192] [0.002, 0.294] [0.045, 0.339] [0.131, 0.166]
p =.084 p =.011 p =.796 p =.054 p =.016 p =.816
Numerical 0.530
b c
j k
[0.411, 0.634] [0.130, 0.422] [0.054, 0.337] [0.342, 0.583] [0.028, 0.323] [0.032, 0.261]
p <.001 p =.002 p =.007 p <.001 p =.018 p =.123
Spatial 0.179 0.092
0.189 0.117 0.151
[0.045, 0.313] [0.046, 0.226] [0.124, 0.384] [0.037, 0.336] [0.013, 0.243] [0.003, 0.293]
p =.010 p =.188 p =.002 p =.013 p =.080 p =.046
Creativity 0.312
0.222 0.146
l m
[0.170, 0.436] [0.083, 0.359] [0.004, 0.286] [0.178, 0.441] [0.063, 0.206] [0.104, 0.192]
p =.002 p =.002 p =.059 p <.001 p =.289 p =.551
Intrapersonal 0.307
f g
n o
[0.143, 0.452] [0.155, 0.150] [0.196, 0.096] [0.097, 0.392] [0.142, 0.171] [0.180, 0.117]
p <.001 p =.970 p =.474 p =.004 p =.837 p =.673
Interpersonal 0.302
0.223 0.143
0.221 0.086 0.078
[0.148, 0.446] [0.068, 0.376] [0.037, 0.323] [0.079, 0.355] [0.075, 0.242] [0.071, 0.224]
p =.002 p =.005 p =.148 p =.004 p =.307 p =.303
Note. Aggregated estimates are means across multiple items (self and informant) or groupcentered means across multiple raters (target effects; strangers). Dis-
aggregated results are based on single, global items for all three sources and, for strangers, they are the average correlation based on 15 repeated analyses for a single
stranger per target (see Vazire, 2010). Results for creativity are based on originality. Correlations for ideational uency and aggregated data were rSelf =0.152 [0.015,
0.289], rInformant = 0.006 [0.144, 0.134], and rStranger =0.017 [0.127, 0.155] and for disaggregated data rSelf =0.099 [0.059, 0.247], rInformant = 0.065 [0.212,
0.074], and rStranger =0.001 [0.147, 0.150]. Values in brackets represent 95% condence intervals (for all aggregated estimates as well as disaggregated self- and
informant-estimates they are based on 2000 bootstrap samples).
Correlations in bold surpassed our accuracy criterion (r 0.2). Superscripts with the same letter denote accuracy differences of r
0.15 between perspectives.
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
numerical intelligence. Moreover, for each domain, the regression co-
efcient of only one of the three perspectives reached signicance. In 4
out of 6 cases (numerical intelligence, creativity, intra- and interper-
sonal emotional abilities), this was the self, with βs ranging from 0.24
(interpersonal emotional abilities) to 0.59 (numerical intelligence).
Only informant-estimates were a signicant predictor of verbal intelli-
gence (β =0.18) and only stranger-estimates predicted spatial intelli-
gence signicantly (β =0.22).
3.4. The role of gender
Next, we explored whether gender moderated accuracy. None of the
interaction terms for either target gender (self-estimates: all p .231;
informant-estimates: all p .135; stranger-estimates p .398) or
informant gender (all p .094; for detailed results see Tables B1 to B4 of
Appendix 1) reached signicance. Looking at the accuracy correlations
for male and female targets (Tables B5 and B6 of Appendix 1) or in-
formants (Table B7 in Appendix 1) separately yielded somewhat
different patterns. However, given the confounding of target and
perceiver gender, the non-signicant interactions terms for gender, and
Table 2
Unique predictive validities of self-, informant-, and stranger-estimates of abilities.
Verbal Numerical Spatial Creativity Intrapersonal Interpersonal
Predictor b β b β b β b β b β b β
(Intercept) 7.55** 5.37** 8.87** 1.03** 2.55** 2.63**
[4.37, 10.77] [2.64, 8.33] [5.33, 12.68] [0.79, 1.29] [2.16, 2.93] [2.30, 2.97]
Self 0.37 0.09 2.90** 0.59 0.50 0.09 0.11** 0.26 0.19** 0.31 0.11** 0.24
[0.44, 1.16] [2.09, 3.75] [0.36, 1.33] [0.05, 0.17] [0.10, 0.28] [0.02, 0.20]
Informant 0.77* 0.18 0.12 0.02 0.25 0.04 0.05 0.13 0.01 0.03 0.04 0.12
[0.06, 1.42] [0.97, 0.65] [0.57, 1.02] [0.01, 0.10] [0.08, 0.06] [0.02, 0.09]
Stranger 0.33 0.05 0.83 0.10 2.14** 0.22 0.01 0.02 0.06 0.07 0.03 0.05
[1.33, 0.67] [1.99, 0.41] [0.72, 3.55] [0.07, 0.09] [0.20, 0.07] [0.08, 0.13]
R2 0.050* 0.288** 0.076** 0.115** 0.100** 0.107**
[0.01, 0.17] [0.18, 0.42] [0.03, 0.17] [0.05, 0.23] [0.04, 0.22] [0.04, 0.24]
Note. Ratings are based on aggregates across multiple items (self and informant) or multiple raters (target effects; stranger). Results for creativity are based on
originality. With ideational uency as criterion, self-ratings remain the only signicant predictor with β =0.18. Values in brackets represent 95% condence intervals
based on 2000 bootstrap samples. * indicates p <.05. ** indicates p <.01.
Fig. 2. Raincloud plots (Allen et al., 2019) showing mean self-worth relevance (self-rating; A) and judgment certainty (across speed-dating partners; B) per domain
with densities and jittered raw data. Error bars represent 95% within-subject condence intervals with Cousineau-Morey (Cousineau, 2005; Morey, 2008) correction.
Due to a lack of sphericity, condence intervals should be interpreted with caution (Cousineau et al., 2021).
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
the small size of the gender-split subsamples, these correlations and
potential differences between them should be considered with caution.
3.5. The role of self-worth relevance and judgment certainty
To investigate whether some domains were generally more relevant
to targets self-esteem than others, we computed a one-way within-
subject ANOVA. It yielded a signicant (Greenhouse-Geisser corrected)
effect of domain on self-worth relevance, F(3.82, 665.35) =63.58, p <
=0.212, which we followed-up with pairwise comparisons
with Holm-corrections (for detailed statistics see Table B8 in Appendix
1). Panel A of Fig. 2 shows that interpersonal emotional abilities were
rated as more relevant than any other domain (all p <.001), followed by
intrapersonal emotional abilities, in turn being rated more highly than
the other four domains (all p <.001). Spatial intelligence was rated as
least relevant (all p <.001). Creativity and verbal and numerical intel-
ligence fell in between. We analyzed potential differences in judgment
certainty analogously and found a signicant (Greenhouse-Geisser cor-
rected) effect of domain on certainty, F(2.6, 451.84) =100.73, p <.001,
=0.287. Panel B of Fig. 2 shows that, on average, strangers were
most certain about their assessment of the targets interpersonal
emotional abilities (all p <.001). Verbal intelligence received higher
certainty ratings than any of the remaining four domains (all p <.001);
spatial intelligence was associated with the lowest judgment certainty
(all p <.001); and the remaining three domains fell in between (for
detailed statistics see Table B9 in Appendix 1).
We next investigated the potential moderating role of self-worth
relevance on the accuracy of self-estimates in one moderation analysis
per domain. This resulted in a signicant interaction for numerical in-
telligence (b =-0.29, 95% CI [-0.52, 0.09], z =-2.70, p =.007). Simple
slope analyses showed a positive slope between self-estimate and per-
formance for all levels of self-worth relevance of this domain (all p <
.001) but decreasing slope size with increasing relevance (b
=2.52; b
=1.86): The more important it was for a person to
be numerically intelligent, the less accurate their assessment of their
numerical intelligence. Similar patterns of lower accuracy for high levels
of self-worth relevance arose for verbal intelligence, spatial intelligence,
and interpersonal emotional abilities but did not result in signicant
interaction terms (all z -1.71, all p .087). In another six analyses, we
probed potential moderation effects of judgment certainty on the ac-
curacy of stranger-estimates. None of the relevant interactions reached
statistical signicance (all z ±1.33, all ps .182). Detailed results of
all moderation analyses are available in Tables B10 to B13, interaction
plots in Figures B2 and B3 in Appendix 1.
4. Discussion
Who knows what about a persons abilities? Overall, our results
suggest that there might be some truth to the popular belief that people
themselves are their own best judges: In the majority of domains, self-
estimates were the most accurate. However, some abilities were in
peoples blind spots: Verbal and spatial intelligence could only be judged
accurately by informants and strangers, respectively. Conversely, some
abilitiesparticularly those in the social-emotional domainremained
hidden to others. No domain was open or unknown to all three per-
spectives. Similar asymmetries in self- and other-knowledge were re-
ported for various traits (Beer & Vazire, 2017; Carlson et al., 2013; B. K.
Miller & Gallagher, 2016; Thielmann et al., 2017; Vazire, 2010),
including the abilities of adolescents (Neubauer et al., 2018). In line
with the assumptions of Vazires (2010) self-other knowledge asym-
metry (SOKA) model, knowledgeable informants and strangers differed
in what they knew about a persons abilities. According to Vazires
model, self-other knowledge asymmetries should also be determined by
a traits observability and evaluativeness, with highly evaluative traits
presumedly being more relevant to peoples self-worth. We assessed self-
worth relevance of abilities directly and used strangers judgment
certainty as a proxy of observability. Our ndings suggest that self-other
knowledge asymmetries in abilities might not necessarily be determined
by these two factors.
4.1. Accuracy of self-, informant-, and stranger-estimates of abilities
Fig. 3 shows each ability domains location within the Johari win-
dow (Luft & Ingham, 1955)/SOKA model (Vazire, 2010) according to
our correlational results. Results for self- and informant-estimates were
mostly in line with our expectations (visualized in Fig. 1): Numerical
intelligence, creativity, and interpersonal emotional abilities were open
to both, targets and informants; targets were blind to their verbal in-
telligence but informants were not; spatial intelligence was unknown to
both parties. Only the location of intrapersonal emotional abilities in the
hidden instead of the open area was unexpected. Results for self- and
stranger-estimates were less consistent with our expectations: Creativity
and numerical intelligence were in the hidden area, as expected, but the
same was also true for interpersonal emotional abilities that we had
expected in the open area. Compared to our predictions, spatial and
verbal intelligence exchanged places so that spatial intelligence was in
the blind spot and verbal intelligence was in the unknown area. Fig. 3
also demonstrates that the placement of two abilities within the same
quadrant does not necessarily mean that they were judged with the same
degree of accuracy: While all informant- or stranger-estimates that
surpassed our accuracy criterion were indeed rather similarlyand at
most moderately (rs 0.210.28)accurate, self-estimates in the nu-
merical domain were (at least descriptively) considerably more accurate
(r =0.53) than those of creativity and intra- and interpersonal abilities
(rs 0.300.31).
Peoples lack of insight into their own verbal and spatial intelligence
remains striking, particularly when compared to their knowledge about
their numerical intelligence. While recent work reported somewhat
higher accuracy (rs around 0.3) for self-estimates of spatial (Hofer,
Mraulak, et al., 2022) or both verbal and spatial intelligence (Hofer,
Macher, et al., 2022), the nding that people can judge their own nu-
merical intelligence more accurately than the other two facets conforms
with the majority of studies in this area (Furnham, 2001; Hofer, Macher,
et al., 2022; Hofer, Mraulak, et al., 2022; Neubauer et al., 2018; Neu-
bauer & Hofer, 2021; Proyer & Ruch, 2009; Rammstedt & Rammsayer,
2002; Steinmayr & Spinath, 2009; Visser et al., 2008). One potential
explanation for these differences between facets could be (lack of) fa-
miliarity with the respective tasks (see for example Zell & Krizan, 2014):
Most tasks that measure numerical intelligence consist of basic mathe-
matical operations that people encounter in a similar form at school. The
same cannot be said for many tests of verbal intelligence (e.g., nding
similarities between words) or spatial intelligence (e.g., the mental
rotation of objects). However, in the present study, self-estimates were
completed after the performance tests. Thus, as targets had just been
exposed to the tasks, a lack of familiarity is likely not well-suited to
explain our results. Interestingly, high schoolers self-estimates in the
spatial domain have often been more accurate (e.g., Neubauer et al.,
2018; Steinmayr & Spinath, 2009) than what we or other studies found
for adult populations (e.g., Furnham, 2001; Visser et al., 2008). Unlike
the majority of adults, high school pupils likely receive regular feedback
on aspects of their spatial abilities (e.g., in geometry) and feedback is
often discussed as essential for accurate self-views (e.g., Bollich et al.,
2011). Thus, future work could explore increasing task familiarity and
providing feedback as ways to move self-estimates of verbal and spatial
intelligence out of the blind spot.
Others could complement the selfs blind spots: Informants were the
only ones with relevant insights into peoples verbal intelligence and
strangers were the only ones with relevant insights into peoples spatial
intelligence. Together with past results on peers (Neubauer et al., 2018),
parents (Steinmayr & Spinath, 2009), and recently also romantic part-
ners and close friends (Hofer, Macher, et al., 2022), these ndings
support that acquainted others can judge a persons verbal intelligence
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
validly. Strangersinsight into the targets spatial intelligence was more
surprising. Given the unexpected nature of this result, it will be espe-
cially important to replicate it. However, some potential explanations
already come to mind: Strangers might have based their judgments on
different cues and cues can differ in their validity (e.g., Borkenau &
Liebler, 1995). As an example, speed-dating partners likely talked about
their jobs or studies. Since people with higher spatial intelligence are
more likely to seek education or employment in a STEM-related eld
(Shea et al., 2001), those cues likely had some validity. It seems plau-
sible that informants and targets, who both arguably have access to a
much larger number of cues about the target, have relied on other,
potentially less valid cues. Coming back to the argument about task
familiarity, it should be considered that all perceivers who provided
stranger-estimates also took part as main participants and had, there-
fore, completed a test of spatial intelligence before providing stranger-
estimates. If increased task familiarity indeed helped participants to
form more accurate judgments of their speed-dating partners spatial
intelligence, what remains puzzling is that (1) this familiarity was not
accompanied by more accurate self-estimates and (2) stranger-estimates
were rather inaccurate in all other domains. A comparison of how task
familiarity might affect both self- and other-estimates of different abil-
ities could shed more light on this issue.
Others knew less about a persons social-emotional abilities than we
had anticipated. While well-acquainted informants were more accurate
in the interpersonal domain than classmates in the past (Neubauer et al.,
2018), they still lacked accuracy in the intrapersonal domain (r 0). In
that, well-acquainted others might face similar struggles as peers
(Neubauer et al., 2018), work colleagues and supervisors (Elfenbein
et al., 2015), and teachers (Sommer et al., 2008). Notably, in a recent
study, acquaintances and close friends also had relatively little insight
into peoples intrapersonal emotional abilities while romantic partners
were at least moderately accurate (Hofer, Macher, et al., 2022). Thus,
knowing a persons intrapersonal emotional abilities might require high
levels of emotional intimacy. Strangers had no relevant insight into
either of the two social-emotional domains. Thus, contrary to our ex-
pectations, interpersonal emotional abilities do not appear to be esti-
mable after rst, short dates. Interestingly, stranger-estimates of both
intra- and interpersonal emotional abilities correlated highly with
stranger-estimates of verbal intelligence (r 0.640.66; see intercorrela-
tion matrix in Appendix 2). Participants may have relied on invalid
speech-related cues (e.g., condent speech; Breil et al., 2021) for judg-
ments in the verbal and/or social-emotional domains. Similarly, social-
emotional components or other, more general characteristics of the
interaction could have contributed to all these estimates. Indeed, speed-
dating ratings of liking, which we reported on elsewhere in more detail
(Hofer et al., 2021), correlated at between 0.5 and 0.7 with stranger-
estimates of verbal, intrapersonal, and interpersonal abilities (and
considerably less with estimates of numerical, spatial, and creative
abilities). The interconnectedness of strangersperceptions of a persons
verbal and social-emotional abilities and their relation to liking is an
interesting topic for future research.
Apart from their surprising insight into peoples spatial intelligence,
strangers were rather inaccurate. These ndings stand in contrast to the
accuracy correlations reported for stranger-estimates of intelligence in
some video-based studies (e.g. up to r 0.5 in Borkenau et al., 2004; up
to r 0.4 in Borkenau & Liebler, 1993; but around r 0.2 in Carney
et al., 2007). Notably, stranger-estimates of abilities after short, non-
romantic real-life interactions seem to be less accurate (e.g., r 0.1
for intelligence and r 0.0 for creativity in Vazire, 2010). What is more,
rst impressions on speed dates tend to be less accurate than those in
more platonic contexts (Kerr et al., 2020). In line with this, another
speed-dating study reported an accuracy of intelligence estimates of
only around 0.1 (Driebe et al., 2021). This might be unexpected at the
rst moment, given that person perception tends to be particularly ac-
curate in pragmatically relevant domains (Gill & Swann, 2004) and that
evolution-based theories (e.g., G. F. Miller, 2000, 2007) and cross-
cultural studies (e.g., Buss et al., 1990; Walter et al., 2020) suggest
that intelligence, creativity, and emotional competence are important in
mating contexts. However, current ndingsbased on data reported
here (Hofer et al., 2021) and another speed-dating study (Driebe et al.,
2021)suggest that these abilities might play a lesser role for initial
attraction. Instead, easily observable characteristics like physical
attractiveness might be more important at rst interactions, with abili-
ties potentially becoming relevant at a later stage (see also G. F. Miller &
Fig. 3. Placement of abilities in the Johari window (Luft & Ingham, 1955)/self-other knowledge asymmetry model (Vazire, 2010) with other-estimates by known
others (informant; left) and previously unknown others after 3-min speed dating interactions (strangers; right). Intra =intrapersonal abilities. Inter =inter-
personal abilities. For self- or other-knowledge of any domain to be classied as ‘high, the respective estimate*performance correlation must be at least 0.2. A
position farther left on the x-axis indicates more accurate self-estimates; a higher position on the y-axis indicates more accurate other-estimates. All correlations are
based on aggregated data for maximum reliability. N =175.
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
Todd, 1998). The centrality of physical attractiveness at rst, short dates
might have further impeded accuracy: Stranger-estimates in the ma-
jority of ability domains showed positive correlationssome of them as
high as 0.6 to 0.7with those of physical attractiveness (for detailed
results see Hofer et al., 2021). Thus, participants might have equated
their interaction partners attractiveness with their cognitive, creative,
and emotional abilities, irrespective of whether they were actually
competent in these domains (see also Langlois et al., 2000). Such halo
errors (Thorndike, 1920)i.e., assigning a person various positive
characteristics based on a positive impressioncould also be one reason
behind the high correlations between stranger-estimates in different
domains. Additionally, targets might have also been motivated to
convey a specic, likely very positive, image of themselves to their
interaction partners, which could have also impeded accuracy.
Accuracy was further reduced when we disaggregated ratings. This
was particularly true for stranger-estimates: The mean accuracy of a
single strangers rating of spatial intelligence was only 0.15 (compared
to 0.26 for the aggregate) and accuracy varied greatly between raters
(from -0.02 to 0.29). While aggregation across strangers offers benets
for reliability and, thus, better possible predictions (see also Back &
Nestler, 2016; Epstein, 1983), one should keep in mind that it might not
always reect real-life person perception: At rst dates or job interviews
ability perceptions often stem from a single source. It will, therefore,
remain crucial to investigate how accurate single strangers are in their
judgments. Vazire (2010) suggested that aggregating across raters might
still reect real-life contexts to a certain degree: While there is only one
person you can ask for self-estimates, you could, at least theoretically,
address multiple people for other-estimates. Thus, aggregated stranger-
estimates could be viewed as a meaningful measure of the general
impression that strangers have of a persons abilities. In a similar vein,
informant-estimates would have likely also benetted from aggregation
across raters, although it is, again, unclear to what extent this would
reect related real-life scenarios (e.g., how many and what kind of close
others would people consult before making important decisions?). In-
formants responses to single, global items about the targets abilities
were considerably less accurate than aggregates across multiple items.
Even though we used virtually the same questionnaire for informant-
and self-estimates, self-estimates suffered less from disaggregation.
Whether this discrepancy was driven by the selfs greater familiarity
with the performance measures or whether there were other mecha-
nisms at work remains open. Overall, the attempt of a fair comparison
between the perspectivesthat is one that is based on single items
responded to by single ratersleft the self as the only perspective with
relevant insight into any of the domains.
4.2. Self-worth relevance and judgment certainty
Based on Vazires SOKA model (2010), people struggle when judging
their own evaluativei.e., neither desirable nor undesirabletraits, as
those are tied to their self-esteem (see also John & Robins, 1993). In
accordance, the low accuracy of self-estimates of verbal and spatial in-
telligence could be due to a high general relevance of these domains to
peoples self-worth. Our data do not support this reasoning: On average,
spatial intelligence was viewed as least relevant. Even though verbal
intelligence was rated as more relevant, the two social-emotional
domainsreceiving moderately accurate self-estimateswere the
most relevant for peoples self-esteem. Thus, high general self-worth
relevance of a domain does not necessarily go hand in hand with inac-
curate ratings. There was also considerable variance in how relevant
people rated the different abilities (see Fig. 2), suggesting substantial
individual differences rather than a general self-worth relevance or
desirability of domains. The idea that people differ in what is tied to
their self-worth is in line with the concept of self-worth contingencies
(Crocker et al., 2003; Crocker & Wolfe, 2001) and ideas already pro-
posed by William James (1890/1950). People, who saw a domain as
more relevant also gave higher self-estimates in this domain (see
intercorrelations in Appendix 2). However, moderation analyses indi-
cated that higher self-worth relevance could also be related to less ac-
curacy, at least in the numerical domain: The more importance a person
placed on their numerical intelligence, the less accurate they were in
estimating it. Simple slopes for three other domainsverbal intelli-
gence, spatial intelligence, and interpersonal emotional abilitiessh-
owed similar patterns, although the interaction terms did not reach
According to the SOKA model (Vazire, 2010), one would further
expect othersparticularly strangersto require high observability of a
trait to judge it accurately. Strangersaccurate estimates of the targets
spatial intelligence should, therefore, be accompanied by high observ-
ability of this domain. We would have expected this to be reected in
high judgment certainty. However, strangers were actually the least
certain about their ratings in the spatial domain. What is more, verbal
intelligence was among the domains associated with the highest general
judgment certaintyright behind interpersonal abilitiesbut was only
judged with negligible accuracy. Thus, more observable abilitiesat
least when operationalized as judgment certaintymight not neces-
sarily be accompanied by more accurate judgments. Like with self-worth
relevance, it is also possible that observability affects accuracy not on
the domain- but the individual-level: Perhaps some people make it easier
to observe specic abilities in them, allowing for higher judgment cer-
tainty. There were highly positive correlations between how certain
strangers were about their rating of a given targets ability and how
competent they viewed this target in the respective domain (see in-
tercorrelations in Appendix 2). In another set of moderation analyses,
we explored whether this affected accuracy. However, none of these
moderation analyses yielded support for effects of judgment certainty on
4.3. Implications for theory, research, and practice
When we view our results in the context of the self-other knowledge
asymmetry model (Vazire, 2010), the following conclusions can be
drawn: Like for many other traits (Beer & Vazire, 2017; Carlson et al.,
2013; B. K. Miller & Gallagher, 2016; Thielmann et al., 2017; Vazire,
2010), we found asymmetries in what the self and others know about a
persons abilities: The self seems to be a valid source for estimates of
numerical intelligence, creativity, and social-emotional abilities. In-
formants can provide accurate insights into a persons verbal and nu-
merical intelligence, creativity, and interpersonal emotional abilities.
The majority of these ndings are in line with an earlier study on pupils
and their peers (Neubauer et al., 2018). Our study added to that by
showing that others who differ in their level of acquaintance to a person
also differ in how well they can judge the persons abilities: While
strangers were overall less accurate than informants, they could provide
unique insight into the targets spatial intelligence. In that, our study
also complements a recent one that found differences in what romantic
partners, close friends, and acquaintances knew about a persons abili-
ties (Hofer, Macher, et al., 2022). Even though a more direct and
comprehensive assessment of ability domainsobservability and eval-
uativeness is needed for a more denite conclusion, it is notable that our
results were not in line with the SOKA models predictions about the role
of these characteristics for accuracy.
While evaluativeness and observability are included in many models
of person perception (e.g., Funder, 1995; John & Robins, 1993; Leising
et al., 2015; Paunonen, 1989), their associations to self-other knowledge
asymmetriesparticularly those in abilitieswarrant further investi-
gation. In a recent loss-of-condence statement, Vazire noted that her
original results (2010) were at least partly based on research practices
that likely overstated the relevance of observability and evaluativeness
for accuracy (for the full statement see Rohrer et al., 2021). Our results
suggest that individual differences in a domains relevance for peoples
self-worth might show more promise in explaining accuracy than the
domains general desirability. A closer look at perceiver- and/or target-
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
level individual differences in observability and evaluativeness (or other
related characteristics) might, therefore, shed more light on accuracy
(for an example of such a more comprehensive modeling approach see
Leising et al., 2015). This would also be in line with individual differ-
ences in accuracy itself: If all people over- or underestimated themselves
(or others) to a similar degree, we would see higher accuracy correla-
tions as estimates would keep their rank-order validity (see also Vazire,
2010). Past research on individual differences in the accuracy of self-
estimates showed associations with broad personality traits (Jacobs
et al., 2012), specic personality traits like honesty-humility (Hilbig
et al., 2014), and the underlying ability level (e.g., Kruger & Dunning,
1999; von Stumm, 2014; but cf. Gignac & Zajenkowski, 2020; Hofer,
Mraulak, et al., 2022). There is also evidence of individual differences in
the accuracy of other-estimates of abilities: Several studies have re-
ported individual differences in how accurately teachers can judge
studentsabilities (for an overview see Machts et al., 2016). This is also
in line with the different accuracy correlations that we have found for
different single strangers. Thus, even though it is unclear whether the
SOKA models predictions on evaluativeness and observability are valid
for knowledge about abilities, we do consider it worthwhile to continue
investigating self-other knowledge asymmetries. Future work on this
topic would likely benet from considering potential individual differ-
ences in accuracy and other characteristics that might account for them.
Our ndings regarding overall self- and other-knowledge about a
persons abilitiesor sometimes rather lack thereofhave implications
that are relevant in both empirical and practical contexts. Even though
the self was the most accurate source in the majority of domains, the
underlying accuracy correlations were only moderate in most cases (see
also Freund & Kasten, 2012; Zell & Krizan, 2014). Therefore, in situa-
tions that require an accurate assessment of a persons abilitiesbe it
before educational or job decisions or in researchthe self should not be
the (sole) source to rely on. At least in some domains, others could
complement what we know about our abilities (see also Hofer, Macher,
& Neubauer, 2022; Neubauer, Pribil, Wallner, & Hofer, 2018): In
particular, it might make sense to ask someone who knows us relatively
well about our verbal intelligence. Moreover, we found rstand yet to
be replicatedindication that strangers might have relevant insight into
our spatial intelligence after short interactions. Importantly, however,
this insight could only be achieved across a group of strangers. Together
with the generally rather low accuracy of strangers, this also leads us to
warn against using stranger-estimates as a stand-in for the pertinent
ability (e.g., like in past studies on mate appeal Fisman et al., 2006;
Karbowski et al., 2016). The low accuracy of ability-estimates by su-
pervisors or colleagues (e.g., Elfenbein et al., 2015) shows that it might
also not be wise to rely on other-estimates in professional contexts. We
conclude that, in any situation where knowledge of a persons abilities is
truly required, psychometrically sound performance tests should be
conducted (see also Neubauer et al., 2018).
4.4. Limits of generalizability and future directions
Even though the present study could provide relevant insights into
self- and other-knowledge about peoples abilities, there are limits to
how far our ndings should be generalized. First, we did not distinguish
between different types of informants. As the majority of informants
were friends of the targets, it is open whether family members or
romantic partners would show similar other-knowledge (for recent
ndings on partners, friends, and acquaintances accuracy see Hofer,
Macher, & Neubauer, 2022). Second, the perception of new acquain-
tances within the dating context might be characterized by specic
motivations and biases, which are not necessarily generalizable to other
judgments at rst encounters (Kerr et al., 2020). It would be interesting
to see how good strangers are at judging a persons abilities in other
settings with practical relevance (e.g., job interviews). Third, we found
some indication for potential gender differences in accuracy. However,
our design does not enable us to clearly disentangle possible effects of
the gender of the target (i.e., are women or men rated more accurately?)
from those of the gender of the perceiver (e.g., are women or men more
accurate raters?). For this, future research including ratings by both
female and male perceivers for the same targets is warranted. Fourth,
this study only assessed self-worth relevance and judgment certainty as
proxies for evaluativeness and observability. It is yet unclear whether
our ndings are generalizable to other, more direct measures of these
characteristics. Additionally, the potential moderation effects should be
revisited in a larger sample as interaction terms are often less powerful
than linear terms (Perugini et al., 2018). Fifth, our results are based on a
highly educated sample and should not be generalized beyond that. As
some have suggested that associations between self-estimated and
measured abilities might be lower at the lower end of the ability spec-
trum (Kruger & Dunning, 1999; but cf. Gignac & Zajenkowski, 2020;
Hofer, Mraulak, et al., 2022), the potentially high cognitive abilities of
our sample could have increased accuracy. However, our samples in-
telligence quotients were neither conspicuously high nor restricted in
dispersion (verbal IQ: M =97.75, SD =12.46; numerical IQ: M =
104.01, SD =14.18; spatial IQ: M =98.83, SD =16.18). Finally, it has
yet to be determined to what extent the ndings based on our young
sample generalize to other age groups.
In addition to the future directions mentioned throughout the dis-
cussion, research on self-other knowledge asymmetries in abilities might
particularly benet from assessing the validity and usage of cues related
to abilities, like done in past video-based studies on stranger-estimates
(e.g., Borkenau et al., 2004; Borkenau & Liebler, 1995; Carney et al.,
2007). Different sources could use differentand differently val-
idcues when judging a persons abilities. A cue-based perspective
might, therefore, contribute to nding answers to questions like: Are
self-estimates of verbal intelligence less accurate than those of other
domains or those by informants because people use invalid cues when
judging their own verbal intelligence?. This type of research could also
be particularly interesting in speed dating or other real-life zero-ac-
quaintance settings and might shed some light on why strangers appear
to be better at judging targets after viewing videos of them than after
actually meeting them. Compared to scripted videos, spontaneous real-
life interactions involve a plethora of cues, out of which some may be
valid indicators of abilities, but others may impede accurate judgments.
In a study by Hughes et al. (2021), targets expressed somewhat valid
cues of intellect-related aspects of openness in dyadic real-life in-
teractions with strangers and strangers judgments also showed some
correspondence to these cues. However, whether this generalizes to
measured cognitive abilities is yet unknown. A recent meta-analysis
reported thatat least in video-based studiesonly few of the cues
that strangers use in their intelligence-estimates are also valid (Breil
et al., 2021).
4.5. Conclusion
When it comes to judging what we are good at, it appears that for
some of our abilities, there truly is nobody who knows us better than
ourselves. People are not uniformly blind to their own abilities or even
those summarized under intellect (i.e., intelligence and creativity;
Vazire, 2010). Instead, it is important to distinguish between different
abilities and intelligence facets. Here, verbal and spatial intelligence
were indeed in peoples blind spot but accessible to well-acquainted or
even just-encountered others. Feedback in these areas likely has the
most potential of being the road to self-knowledge. Bollich and col-
leagues (2011, p.4) proposed that the search for self-knowledge likely
requires the active involvement of close others to help ll in our blind
spots.In the case of abilities, however, the overall rather low accuracy
of all perspectives suggests that the involvement of yet another
perspective (i.e., objective ability measures) is necessary.
CRediT authorship contribution statement
Gabriela Hofer: Conceptualization, Methodology, Formal analysis,
G. Hofer et al.
Journal of Research in Personality 98 (2022) 104226
Writing original draft, Project administration. Laura Langmann:
Conceptualization, Investigation, Methodology, Writing review &
editing. Roman Burkart: Investigation, Methodology, Writing review
& editing. Aljoscha C. Neubauer: Conceptualization, Supervision,
Writing review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
We want to thank Angelina Felber for her contribution to data
collection. The authors acknowledge the nancial support by the Uni-
versity of Graz.
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... Effective teaching applies to all teachers at all levels (Finefter-Rosenbluh et al., 2021), including elementary schools with special needs. Learning is helping human resources to a higher level (Hofer et al., 2022) and making people who are intelligent, knowledgeable, and expected to become leaders in their field of business (Hofer et al., 2022). Therefore, education administrators at that level are responsible for ensuring the support of teaching and learning activities that are appropriate for the development of their schools. ...
... Effective teaching applies to all teachers at all levels (Finefter-Rosenbluh et al., 2021), including elementary schools with special needs. Learning is helping human resources to a higher level (Hofer et al., 2022) and making people who are intelligent, knowledgeable, and expected to become leaders in their field of business (Hofer et al., 2022). Therefore, education administrators at that level are responsible for ensuring the support of teaching and learning activities that are appropriate for the development of their schools. ...
The relevance and challenges of clinical supervision for effective teaching and learning in Elementary schools with special needs exploring through descriptive survey research. We collected data using twenty questionnaire items from 429 respondents consisting of principals and teachers and analyzed them using t-test statistics. The research findings reveal several relevancies of clinical supervision in teaching and learning: improving teacher classroom behavior and supporting students' clinical learning. Clinical management has challenges, including disagreements on collaboration between teachers and principals, lack of trained supervisors, inadequate supervisors in various areas of specialization, and time constraints. Based on these findings, this study recommends that the Management Board of elementary schools with special needs requires clinical supervision at least once a month.
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How much do our partners, close friends, and acquaintances know about our abilities, as compared to ourselves? This registered report aimed to investigate asymmetries in these perspectives’ knowledge of a person’s verbal, numerical, and spatial intelligence, creativity, and intra- and interpersonal emotional abilities. We collected self-estimates and performance measures of these abilities from 238 targets. Each target’s abilities were also rated by their romantic partner, a close friend, and an acquaintance. Results showed knowledge-asymmetries but also similarities between perspectives. People themselves were at least moderately accurate across all six domains. However, partners achieved similar accuracy and both partners and friends could provide unique insights into some abilities. We discuss these results with regard to Vazire’s self-other knowledge asymmetry model.
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People’s perceptions of their intelligence correlate only moderately with objective intelligence measures. On average, people overestimate themselves. According to the popular Dunning–Kruger effect, this is particularly true for low performers: across many domains, those in the lowest quartile overestimate their abilities the most. However, recent work using improved statistical approaches found little support for a Dunning–Kruger effect in general intelligence. We investigated accuracy and Dunning–Kruger effects for self-estimates of general, verbal, numerical, and spatial intelligence—domains that differed in how well they can be judged in the past. A total of 281 participants completed self-estimates and intelligence measures online. Self-estimates showed mostly moderate correlational accuracy that was slightly higher for numerical intelligence and lower for verbal intelligence. Across domains, participants rated their intelligence as above average. However, as their intelligence was indeed high, this was not an overestimation. While standard analyses indicated Dunning–Kruger effects in general, verbal, and spatial intelligence, improved statistical methods only yielded some support for one in verbal intelligence: people with lower verbal intelligence tended to have less self-knowledge about it. The generalizability of these findings is limited to young, highly educated populations. Nevertheless, our results contribute to a growing literature questioning the generality of the Dunning–Kruger effect.
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Plotting the data of an experiment allows researchers to illustrate the main results of a study, show effect sizes, compare conditions, and guide interpretations. To achieve all this, it is necessary to show point estimates of the results and their precision using error bars. Often, and potentially unbeknownst to them, researchers use a type of error bars—the confidence intervals—that convey limited information. For instance, confidence intervals do not allow comparing results (a) between groups, (b) between repeated measures, (c) when participants are sampled in clusters, and (d) when the population size is finite. The use of such stand-alone error bars can lead to discrepancies between the plot’s display and the conclusions derived from statistical tests. To overcome this problem, we propose to generalize the precision of the results (the confidence intervals) by adjusting them so that they take into account the experimental design and the sampling methodology. Unfortunately, most software dedicated to statistical analyses do not offer options to adjust error bars. As a solution, we developed an open-access, open-source library for R— superb—that allows users to create summary plots with easily adjusted error bars.
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Creativity research crucially relies on creativity evaluations by external raters, but it is not clear what properties characterize good raters. In the present study, we investigated whether rater personality and rater creativity are related to discernment (i.e., the ability to distinguish creative from uncreative responses) when evaluating others’ responses. To this end, 166 novice raters evaluated a pre‐selected set of responses from the alternate uses task for creativity. We further assessed the rater’s creativity and personality and explored the role of task factors such as rating motivation and rating time. We found that creativity in terms of creative potential and creative achievement independently predicted rater discernment. At the level of personality, openness to experience was related to higher discernment, but not any other Big‐Five factors or dark triad traits. Rater discernment also increased with rating time, rating motivation, and rater leniency (i.e., the tendency to appreciate creative responses). Finally, we seized the large rater sample to estimate to what extent inter‐rater reliability depends on rater number and how dependable ratings are across the rating scale. Together, these findings highlight relevant factors at person, task, and method level predicting individual discernment, which should be considered to ensure good inter‐rater reliability in creativity ratings.
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Are intelligent, creative, and emotionally competent people more desirable? Evolution-based theories and studies on the ideal partner suggest that they are. We aimed to assess whether verbal, numerical, and spatial intelligence, creativity, and intra- and interpersonal emotional competence are associated with higher real-life mate appeal. In speed dates, 87 women and 88 men met up to 14 members of the opposite sex (2188 observations). While only one measured ability—women’s creativity—was significantly associated with mate appeal, ability perceptions by speed-dating partners could broadly predict mate appeal. Effects of perceived and measured abilities were substantially reduced after controlling for physical attractiveness. These results suggest that the investigated abilities play a lesser role in initial attraction than proposed in the past.
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In this chapter, we summarize research on nonverbal expressions of behavior (nonverbal cues) and how they contribute to the accuracy of personality judgments. First, we present a conceptual overview of relevant nonverbal cues in the domains of facial expressions, body language, paralanguage, and appearance as well as approaches to assess these cues on different levels of aggregation. We then summarize research on the validity of nonverbal cues (what kind of nonverbal cues are good indicators of personality?) as well as the utilization of nonverbal cues (what kind of nonverbal cues lead to personality impressions?), resulting in a catalogue of those cues that drive judgment accuracy for different traits. Finally, we discuss personal and situational characteristics that moderate the expression and utilization of nonverbal cues and give an outlook for future research.
Situational judgments tests (SJTs) offer many advantages over traditional trait questionnaires but often show low internal consistency, presumably due to heterogeneity of the underlying constructs (Lievens et al., 2008; Whetzel & McDaniel, 2009). Some have suggested test-retest-reliability (TRT) as better-suited reliability indicator for SJTs. Here, we analyzed the TRT of the typical-performance emotional management test (TEMT, Freudenthaler & Neubauer, 2005)—an emotional management SJT. We additionally report validity evidence with respect to a maximum-performance emotional management SJT (STEM, MacCann & Roberts, 2008) and the widely-used Trait Emotional Intelligence Questionnaire (TEIQue, Petrides & Furnham, 2003). For a 2 week-interval, we found satisfying TRT for both scales of the TEMT (inter- and intrapersonal emotional management; 0.76 and 0.83, respectively). Intrapersonal ability correlated moderately to highly with all four TEIQue main factors and the total score, whereas interpersonal ability showed low to medium relations. Correlations with the STEM were smaller. Our results support that SJTs can show good reliabilities—when assessed via TRT—and emphasize the importance of distinguishing between typical- and maximum-performance tests of emotional abilities.