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Abstract

Although bullshit is common in everyday life and has attracted attention from philosophers, its reception (critical or ingenuous) has not, to our knowledge, been subject to empirical investigation. Here we focus on pseudo-profound bullshit, which consists of seemingly impressive assertions that are presented as true and meaningful but are actually vacuous. We presented participants with bullshit statements consisting of buzzwords randomly organized into statements with syntactic structure but no discernible meaning (e.g., “Wholeness quiets infinite phenomena”). Across multiple studies, the propensity to judge bullshit statements as profound was associated with a variety of conceptually relevant variables (e.g., intuitive cognitive style, supernatural belief). Parallel associations were less evident among profundity judgments for more conventionally profound (e.g., “A wet person does not fear the rain”) or mundane (e.g., “Newborn babies require constant attention”) statements. These results support the idea that some people are more receptive to this type of bullshit and that detecting it is not merely a matter of indiscriminate skepticism but rather a discernment of deceptive vagueness in otherwise impressive sounding claims. Our results also suggest that a bias toward accepting statements as true may be an important component of pseudo-profound bullshit receptivity.
Judgment and Decision Making, Vol. 10, No. 6, November 2015, pp. 549–563
On the reception and detection of pseudo-profound bullshit
Gordon Pennycook
James Allan Cheyne
Nathaniel Barr
Derek J. Koehler
Jonathan A. Fugelsang
Abstract
Although bullshit is common in everyday life and has attracted attention from philosophers, its reception (critical or ingen-
uous) has not, to our knowledge, been subject to empirical investigation. Here we focus on pseudo-profound bullshit, which
consists of seemingly impressive assertions that are presented as true and meaningful but are actually vacuous. We presented
participants with bullshit statements consisting of buzzwords randomly organized into statements with syntactic structure but
no discernible meaning (e.g., “Wholeness quiets infinite phenomena”). Across multiple studies, the propensity to judge bull-
shit statements as profound was associated with a variety of conceptually relevant variables (e.g., intuitive cognitive style,
supernatural belief). Parallel associations were less evident among profundity judgments for more conventionally profound
(e.g., A wet person does not fear the rain”) or mundane (e.g., “Newborn babies require constant attention”) statements. These
results support the idea that some people are more receptive to this type of bullshit and that detecting it is not merely a matter
of indiscriminate skepticism but rather a discernment of deceptive vagueness in otherwise impressive sounding claims. Our re-
sults also suggest that a bias toward accepting statements as true may be an important component of pseudo-profound bullshit
receptivity.
Keywords: bullshit, bullshit detection, dual-process theories, analytic thinking, supernatural beliefs, religiosity, conspiratorial
ideation, complementary and alternative medicine.
1 Introduction
“It is impossible for someone to lie unless he thinks he
knows the truth. Producing bullshit requires no such con-
viction. Harry Frankfurt
In On Bullshit, the philosopher Frankfurt (2005) defines
bullshit as something that is designed to impress but that
was constructed absent direct concern for the truth. This
distinguishes bullshit from lying, which entails a deliberate
manipulation and subversion of truth (as understood by the
liar). There is little question that bullshit is a real and con-
sequential phenomenon. Indeed, given the rise of commu-
nication technology and the associated increase in the avail-
ability of information from a variety of sources, both expert
and otherwise, bullshit may be more pervasive than ever be-
fore. Despite these seemingly commonplace observations,
we know of no psychological research on bullshit. Are peo-
ple able to detect blatant bullshit? Who is most likely to fall
prey to bullshit and why?
Funding for this study was provided by the Natural Sciences and En-
gineering Research Council of Canada.
Copyright: © 2015. The authors license this article under the terms of
the Creative Commons Attribution 3.0 License.
Department o f Psychology, University of Waterloo, 200 Univer-
sity Avenue West, Waterloo ON, Canada, N2L 3G1. Email: gpen-
nyco@uwaterloo.ca.
Department of Psychology, University of Waterloo.
The School of Humanities and Creativity, Sheridan College.
2 Pseudo-profound bullshit
The Oxford English Dictionary defines bullshit as, simply,
“rubbish” and “nonsense”, which unfortunately does not get
to the core of bullshit. Consider the following statement:
“Hidden meaning transforms unparalleled ab-
stract beauty.
Although this statement may seem to convey some sort of
potentially profound meaning, it is merely a collection of
buzzwords put together randomly i n a sentence that retains
syntactic structure. The bullshit statement is not merely non-
sense, as would also be true of the following, which is not
bullshit:
“Unparalleled transforms meaning beauty hidden
abstract”.
The syntactic structure of a), unlike b), implies that it was
constructed to communicate something. Thus, bullshit, in
contrast to mere nonsense, is something that implies but
does not contain adequate meaning or truth. This sort of
phenomenon is similar to what Buekens and Boudry (2015)
referred to as obscurantism (p. 1): “[when] the speaker...
[sets] up a game of verbal smoke and mirrors to suggest
depth and insight where none exists. Our focus, however, is
somewhat different from what is found in the philosophy of
bullshit and related phenomena (e.g., Black, 1983; Buekens
& Boudry, 2015; Frankfurt; 2005). Whereas philosophers
549
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
550
have been primarily concerned with the goals and intentions
of the bullshitter, we are interested in the factors that pre-
dispose one to become or to resist becoming a bullshittee.
Moreover, this sort of bullshit which we refer to here as
pseudo-profound bullshit may be one of many different
types. We focus on pseudo-profound bullshit because it rep-
resents a rather extreme point on what could be considered
a spectrum of bullshit. We can say quite confidently that the
above example (a) is bullshit, but one might also label an
exaggerated story told over drinks to be bullshit. In future
studies on bullshit, it will be important to define the type of
bullshit under investigation (see Discussion for further com-
ment on this issue).
Importantly, pseudo-profound bullshit is not trivial. For a
real-world example of pseudo-profound bullshit and an ap-
plication of our logic, consider the following:
Attention and intention are the mechanics of
manifestation.
This statement bears a striking resemblance to (a), but is
(presumably) not a random collection of words. Rather, it
is an actual “tweet” sent by Deepak Chopra, M.D., who has
authored numerous books with titles such as Quantum Heal-
ing (Chopra, 1989) and The Soul of Leadership (Chopra,
2008) and who has been accused of furthering “woo-woo
nonsense” (i.e., pseudo-profound bullshit; e.g., Shermer,
2010). The connection between (a) and (c) is not inci-
dental, as (a) was derived using the very buzzwords from
Chopra’s “Twitter” feed.
1
The vagueness of (c) indicates
that it may have been constructed to impress upon the reader
some sense of profundity at the expense of a clear exposition
of meaning or truth.
Despite the lack of direct concern for truth noted by
Frankfurt (2005), pseudo-profound bullshit betrays a con-
cern for verisimilitude or truthiness. We argue that an im-
portant adjutant of pseudo-profound bullshit is vagueness
which, combined with a generally charitable attitude toward
ambiguity, may be exacerbated by the nature of recent me-
dia. As a prime example, the necessary succinctness and
rapidity of “Twitter” (140 characters per “Tweet”) may be
particularly conducive to the promulgation of bullshit. Im-
portantly, vagueness and meaning are, by definition, at cross
purposes, as the inclusion of vagueness obscures the mean-
ing of the statement and therefore must undermine or mask
“deep meaning” (i. e., profundity) that the statement purports
to convey. The concern for “profundity” reveals an impor-
tant defining characteristic of bullshit (in general): that it
attempts to impress rather than to inform; to be engaging
rather than instructive.
1
This example came from http://wisdomofchopra.com. See Method
section of Study 1 for further details.
3 Bullshit receptivity
What might cause someone to erroneously rate pseudo-
profound bullshit as profound? In our view, there are two
candidate mechanisms that might explain a general “recep-
tivity” to bullshit. The first mechanism relates to the pos-
sibility that some people may have a stronger bias toward
accepting things as true or meaningful from the outset. Ac-
cording to Gilbert (1991, following Spinoza), humans must
first believe something to comprehend it. In keeping with
this hypothesis, Gilbert, Tafarodi and Malone (1993) found
that depleting cognitive resources caused participants to er-
roneously believe information that was tagged as false. This
indicates that people have a response bias toward accepting
something as true. This asymmetry between belief and un-
belief may partially explain the prevalence of bullshit; we
are biased toward accepting bullshit as true and it there-
fore requires additional processing to overcome this bias.
Nonetheless, it should be noted that previous work on belief
and doubt focused on meaningful propositions such as “The
heart produces all mental activity. The startling possibility
with respect to pseudo-profound bullshit is that people will
first accept the bullshit as true (or meaningful) and, depend-
ing on downstream cognitive mechanisms such as conflict
detection (discussed below), either retain a default sense of
meaningfulness or i nvoke deliberative reasoning to assess
the truth (or meaningfulness) of the proposition. In terms
of individual differences, then, it is possible that some indi-
viduals approach pseudo-profound bullshit with a stronger
initial expectation for meaningfulness. However, since this
aspect of bullshit receptivity relates to one’s mindset when
approaching (or being approached with) bullshit, it is there-
fore not specific to bullshit. Nonetheless, it may be an im-
portant component of bullshit receptivity. Put differently,
some individuals may have an excessively “open” mind that
biases them to make inflated judgments of profundity, re-
gardless of the content.
The second mechanism relates to a potential inability to
detect bullshit, which may cause one to confuse vagueness
for profundity. In the words of Sperber (2010): All too
often, what readers do is judge profound what they have
failed to grasp” (p. 583). Here, t he bullshittee is simply un-
aware that the relevant stimulus requires special considera-
tion. This mechanism is linked to what has been labelled as
“conflict monitoring” failures (e.g., De Neys, 2014; Penny-
cook, Fugelsang & Koehler, 2015). In the context of reason-
ing research, for example, conflict monitoring is necessary
when two sources of information in a problem cue conflict-
ing responses (e.g., logical validity and conclusion believ-
ability in a syllogism). Recent research indicates that peo-
ple are capable of detecting these sorts of conflicts (see De
Neys, 2012 for a review), but that conflict monitoring fail-
ures are nonetheless an important source of bias in reason-
ing and decision making (Pennycook, Fugelsang & Koehler,
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
551
2015). Moreover, conflict detection is viewed as an im-
portant low-level cognitive factor that causes at least some
people to engage deliberative, analytic reasoning processes
(Pennycook, Fugelsang & Koehler, 2015). With respect to
bullshit, there are likely many factors that may lead an in-
dividual to successfully detect the need for skepticism that
will depend on the type of bullshit encountered and the bull-
shit context. For example, the source (perhaps a known
bullshitter) may be particularly untrustworthy. Or, perhaps,
the bullshit may conflict with common knowledge or spe-
cific knowledge or expertise of the recipient. For the present
investigation, we focus on pseudo-profound bullshit that is
missing any obvious external cue that skepticism is required.
The goal is to investigate whether there are consistent and
meaningful individual differences in the ability to sponta-
neously discern or detect pseudo-profound bullshit. Unlike
response bias, this mechanism involves distinguishing bull-
shit from non-bullshit.
4 The current investigation
Here we report four studies in which we ask participants
to rate pseudo-profound bullshit and other statements on a
profundity scale. Our primary goal is to establish this as
a legitimate measure of bullshit receptivity. For this, bull-
shit profundity ratings are correlated with a collection of in-
dividual difference factors that are conceptually related to
pseudo-profound bullshit in a variety of ways.
4.1 Analytic thinking
Dual-process theories of reasoning and decision making dis-
tinguish between intuitive (“Type 1”) processes that are au-
tonomously cued and reflective (“Type 2”) processes that are
effortful, typically deliberative, and require working mem-
ory (Evans & Stanovich, 2013). A crucial finding that has
emerged from the dual-process literature is that the ability
to reason involves a discretionary aspect (Stanovich, 2011;
Stanovich & West, 2000); a distinction that has long histori-
cal precedent (Baron, 1985). Namely, to be a good reasoner,
one must have both the capacity to do whatever computa-
tion is necessary (i.e., cognitive ability, intelligence) and the
willingness to engage deliberative reasoning processes (i.e.,
analytic cognitive style; thinking disposition). Moreover,
individual differences in analytic cognitive style are posi-
tively correlated wit h conflict detection effects in reason-
ing research (Pennycook, Cheyne, Barr, Koehler & Fugel-
sang, 2014; Pennycook, et al., 2015), indicating that more
analytic individuals are either better able to detect conflict
during reasoning or are more responsive to such conflict.
Consistent with Sagan’s (1996) argument that critical think-
ing facilitates “baloney detection”, we posit that reflective
thinking should be linked to bullshit receptivity, such that
people who are better at solving reasoning problems should
be more likely to consider the specific meaning of the pre-
sented statements (or lack thereof) and judge failure to dis-
cern meaning as a possible defect of the statement rather
than of themselves. In other words, more analytic individ-
uals should be more likely to detect the need for additional
scrutiny when exposed to pseudo-profound bullshit. More
intuitive individuals, in contrast, should respond based on
a sort of first impression, which will be inflated due to the
vagueness of the pseudo-profound bullshit. Analytic think-
ing is thus the primary focus of our investigation, as it is
most directly related to the proposed ability to detect blatant
bullshit.
4.2 Ontological confusions
Both children and adults tend to confuse aspects of real-
ity (i.e., “core knowledge”) in systematic ways (Lindeman,
Svedholm-Hakkinen & Lipsanen, 2015). Any category mis-
take involving property differences between animate and
inanimate or mental and physical, as examples, constitutes
an ontological confusion. Consider the belief that prayers
have the capacity to heal (i.e., spiritual healing). Such
beliefs are taken to result from conflation of mental phe-
nomenon, which are subjective and immaterial, and physical
phenomenon, which are objective and material (Lindeman,
Svedholm-Hakkinen & Lipsanen, 2015). On a dual-process
view, ontological confusions constitute a failure to reflect
on and inhibit such intuitive ontological confusions (Sved-
holm & Lindeman, 2013). Ontological confusions may also
be supported by a bias toward believing the literal truth of
statements. Thus, ontological confusions are conceptually
related to both detection and response bias as mechanisms
that may underlie bullshit receptivity. As such, the propen-
sity to endorse ontological confusions should be linked to
higher levels of bullshit receptivity.
4.3 Epistemically suspect beliefs
Beliefs that conflict with common naturalistic conceptions
of the world have been labelled epistemically suspect (e.g.,
Lobato et al., 2014; Pennycook, Fugelsang & Koehler, in
press). For example, the belief in angels (and the corre-
sponding belief that they can move through walls) conflicts
with the common folk-mechanical belief that things cannot
pass through solid objects (Pennycook et al., 2014). Epis-
temically suspect beliefs, once formed, are often accompa-
nied by an unwillingness to critically reflect on such be-
liefs. Indeed, reflective thinkers are less likely to be re-
ligious and paranormal believers (e.g., Gervais & Noren-
zayan, 2012; Pennycook et al., 2012; Shenhav, Rand &
Greene, 2012), and are l ess likely to engage in conspira-
torial ideation (Swami et al., 2014) or believe in the effi-
cacy of alternative medicine (Browne et al., 2015; Linde-
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
552
man, 2011). Ontological confusions are also more com-
mon among believers in the supernatural (e.g., Lindeman,
Svedholm-Hakkinen & Lipsanen, 2015; Svedholm & Lin-
deman, 2013). Although epistemically suspect claims may
or may not themselves qualify as bullshit, the lack of skepti-
cism that underlies the acceptance of epistemically suspect
claims should also promote positive bullshit receptivity.
5 Study 1
We presented participants with ten statements that have syn-
tactic structure but that consist of a series of randomly se-
lected vague buzzwords. Participants were asked to indicate
the r elative profundity of each statement on a scale from
1 (not at all profound) to 5 (very profound). We argue
that high ratings indicate receptivity toward bullshit. Par-
ticipants also completed a series of relevant cognitive and
demographic questions.
6 Method
In all studies, we report how we determined our sample size,
all data exclusions, and all measures.
6.1 Participants
University of Waterloo undergraduates (N = 280, 58 male,
222 female, M
age
= 20.9, SD
age
= 4.8) volunteered to take
part in the study in return for course credit. Only partici-
pants who reported that English is their first language (on
a separate pre-screen questionnaire) were allowed to partic-
ipate. The sample size was the maximum amount allowed
for online studies in the University of Waterloo participant
pool. This study was run over two semesters.
One of the participants was removed due to a large num-
ber of skipped questions. Participants were also given an
attention check. For this, participants were shown a list of
activities (e.g., biking, reading) directly below the following
instructions: “Below is a list of leisure activities. If you are
reading this, please choose the “other” box below and type
in ‘I read the instructions’”. This attention check proved
rather difficult with 35.4% of the sample failing (N = 99).
However, the results were similar if these participants were
excluded. We therefore retained the full data set.
6.2 Materials
Ten novel meaningless statements were derived from two
websites and used to create a Bullshit Receptivity (BSR)
scale. The first, http://wisdomofchopra.com, constructs
meaningless statements with appropriate syntactic st ruc-
ture by randomly mashing together a list of words used in
Deepak Chopra’s tweets (e.g., “Imagination is inside expo-
nential space time events”). The second, “The New Age
Bullshit Generator” (http://sebpearce.com/bullshit/), works
on the same principle but uses a list of profound-sounding
words compiled by its author, Seb Pearce (e.g., “We are in
the midst of a self-aware blossoming of being that will align
us with the nexus itself”). A full list of items for t he BSR
scale can be found in Table S1 in the supplement. The fol-
lowing instructions were used for t he scale:
We are interested in how people experience the
profound. Below are a series of statements taken
from relevant websites. Please read each state-
ment and take a moment to think about what it
might mean. Then please rate how “profound”
you think it is. Profound means “of deep mean-
ing; of great and broadly inclusive significance.
Participants rated profoundness on the following 5-point
scale: 1= Not at all profound, 2 = somewhat profound, 3 =
fairly profound, 4 = definitely profound, 5 = very profound.
A bullshit receptivity score was the mean of the profound-
ness ratings for all bullshit items.
At t he beginning of the study (following demographic
questions), participants completed five cognitive tasks in-
tended to assess individual differences in analytic cognitive
style and components of cognitive ability. The Cognitive
Reflection Test (CRT; Frederick, 2005) consists of 3 math-
ematical word problems that cue an incorrect intuitive re-
sponse. The CRT has been shown to reflect the tendency to
avoid miserly cognitive processing (Campitelli & Gerrans,
2013; Toplak, West & Stanovich, 2011), presumably be-
cause those with an analytic cognitive style are more likely
to question or avoid the intuitive response. We also in-
cluded a recent 4-item addition to the CRT (Toplak, West
& Stanovich, 2014). The 7-item CRT measure had accept-
able internal consistency (Cronbach’s α = .74).
As an additional measure of reflective thinking, we in-
cluded a “heuristics and biases” battery (Toplak et al., 2011).
The heuristics and biases battery involves a series of ques-
tions derived from Kahneman and Tversky, such as the gam-
bler’s fallacy and the conjunction fallacy (Kahneman, 2011).
Much like the CRT, each item cues an incorrect intuitive re-
sponse based on a common heuristic or bias. However, the
heuristics and biases task was not as reliable (α = .59). This
likely reflects the fact that the heuristics and biases items are
more diverse than are the CRT problems.
We also included two cognitive ability measures. We as-
sessed verbal intelligence using a 12-item version of the
Wordsum test. For t his, participants were presented with
words and asked to select from a list the word that most
closely matches its meaning (e.g., CLOISTERED was pre-
sented with miniature, bunched, arched, malady, secluded).
The Wordsum has been used in many studies (see Malhotra,
Krosnick & Haertel, 2007 for a review), including t he Gen-
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
553
Table 1: Pearson product-moment correlations (Study 1; N = 279). BSR = Bullshit Receptivity scale; CRT = Cognitive
Reflection Test. Cronbach’s alphas are reported in brackets.
∗∗∗
p < .001, ** p < .01,
p < .05.
1 2 3 4 5 6 7
1. BSR (.82)
2. CRT .33
∗∗∗
(.74)
3. Heuristics/biases .28
∗∗∗
.50
∗∗∗
(.59)
4. Verbal intelligence .37
∗∗∗
.41
∗∗∗
.31
∗∗∗
(.65)
5. Numeracy .13
.38
∗∗∗
.27
∗∗∗
.30
∗∗∗
(.47)
6. Ontological confusions .31
∗∗∗
.33
∗∗∗
.38
∗∗∗
.26
∗∗∗
.16
∗∗
(.74)
7. Religious belief .27
∗∗∗
.21
∗∗∗
.20
∗∗
.15
.17
∗∗
.29
∗∗∗
(.94)
eral Social Survey (starting in 1974). The Wordsum mea-
sure had acceptable reliability (α = .65). We also assessed
numeracy using a 3-item measure (Schwartz, Woloshin,
Black & Welch, 1997). The frequently used 3-item nu-
meracy scale is strongly related to an expanded and more
difficult 7-item numeracy scale, suggesting that both scales
loaded on a single construct (labelled “global numeracy”
by Lipkus, Samsa, and Rimer, 2001). However, we em-
ployed the shorter 3-item version for expediency, but it did
not achieve acceptable reliability (α = .47).
We used a 14-item ontological confusions scale (Linde-
man & Aarnio, 2007; Lindeman, et al., 2008; Svedholm
& Lindeman, 2013), translated into English from Finnish.
Participants were given the following instructions: “Do you
think the following statements can be literally true, the way
a sentence such as ‘Wayne Gretzky was a hockey player’
is true? Or are they true only in a metaphorical sense, like
the expression ‘Friends are the salt of life’?”. They were
then presented items such as A rock lives for a long time”
and asked to rate how metaphorical/literal the statement is
on the following scale: 1= fully metaphorical, 2 = more
metaphorical than literal, 3 = in between, 4 = more literal
than metaphorical, 5 = fully literal. Those who rate the
statements as more literal are considered more ontologically
confused. Participants were also given 3 metaphors (e.g.,
An anxious person is a prisoner to their anxiety”) and 3 lit-
eral s tatements (e.g., “Flowing water is a liquid”) as filler
items that did not factor into the mean ontological confu-
sion score. The ontological confusions scale had acceptable
internal consistency (α = .74).
Finally, participants completed an 8-i tem religious belief
questionnaire (Pennycook et al., 2014). Participants were
asked to rate their level of agreement/disagreement (1
strongly disagree to 5 strongly agree) with 8 commonly
held religious beliefs (afterlife, heaven, hell, miracles, an-
gels, demons, soul, Satan). The scale had excellent internal
consistency (α = .94).
6.3 Procedure
Following a short demographic questionnaire, participants
completed the tasks in the following order: heuristics and
biases battery, Wordsum, numeracy, CRT2, CRT1, ontolog-
ical confusion scale, bullshit receptivity, and religious belief
questionnaire.
7 Results
The Bullshit Receptivity (BSR) scale had good internal con-
sistency (α = .82). A summary of descriptive statistics for
each item and the full BSR scale is reported in Table S1.
The mean profoundness rating was 2.6, which is in-between
“somewhat profound” and “fairly profound” on the 5-point
scale. Indeed, the mean profoundness rating for each item
was significantly greater than 2 (“somewhat profound”), all
ts > 5.7, all ps < .001, indicating that our items successfully
elicited a sense of profoundness on the aggregate. Moreover,
only 18.3% (N = 51) of the sample had a mean rating less
than 2. A slight majority of the sample’s mean ratings fell
on or in-between 2 and 3 (54.5%, N = 152) and over a quar-
ter of the sample (27.2%, N = 76) gave mean ratings higher
than 3 (“fairly profound”). These results indicate that our
participants largely failed to detect that the statements are
bullshit.
Next we investigate the possible association between re-
flective thinking and bullshit receptivity. Pearson product-
moment correlations can be found in Table 1. BSR was
strongly negatively correlated with each cognitive measure
except for numeracy (which was nonetheless significant).
Furthermore, both ontological confusions and religious be-
lief were positively correlated with bullshit receptivity.
8 Study 2
In Study 1, at least some participants appeared to find mean-
ing in a seri es of statements that contained a random collec-
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
554
tion of vague buzzwords organized in a sentence with syn-
tactic structure. This t endency was significantly related to
cognitive variables of conceptual interest in expected ways.
In Study 2 we set out to replicate this pattern of results us-
ing real-world examples of bullshit. For this, we created
an additional scale using particularly vague “tweets” from
Deepak Chopra’s “Twitter” account (see Table S2). We also
expanded our measures of analytic cognitive style by includ-
ing self-report measures of analytic and intuitive thinking
disposition. Finally, we expanded our cognitive ability mea-
sures by increasing the number of items on the numeracy
test and including a common measure of fluid intelligence.
9 Method
9.1 Participants
A total of 198 participants (98 male, 100 f emale, M
age
=
36, SD
age
= 11.4) were recruited from Amazon’s Mechan-
ical Turk in r eturn for pay. Only American residents were
permitted to sign up for the study. All participants reported
speaking fluent English. Given the novelty of the phe-
nomenon, we chose 200 participants as an arbitr ary target
sample size, as we determined this would provide adequate
power and stability of the correlations. These data were not
analyzed until the full sample was completed.
Eleven participants were removed because they re-
sponded affirmatively when asked if they responded ran-
domly at any time during the study. In addition, 23 partic-
ipants failed at least one of three attention check questions.
The instruction check questions included the one used in
Study 1 as well as the following question inserted into ques-
tionnaires at the middle and end of the survey: “I have been
to every country in the world” (all participants who selected
any option but “strongly disagree” were removed). How-
ever, as in Study 1, the results were similar when these par-
ticipants were excluded and we therefore retained the full
sample.
9.2 Materials
In addition to the 10 meaningless statements used in Study
1, we obtained 10 novel items from http://wisdomofchopra.
com and http://sebpearce.com/bullshit/. As noted, we also
obtained 10 items from Deepak Chopra’s Twitter feed
(http://twitter.com/deepakchopra; e.g. “Nature is a self-
regulating ecosystem of awareness”). These items can be
found in Table S2. We excluded hash tags and expanded
any shortened words and abbreviations, but the tweets were
not otherwise altered. We emphasize that we deliberately
selected tweets that seemed vague and, therefore, the se-
lected statements should not be taken as representative of
Chopra’s tweet history or body of work. Also, to reiter-
ate, we focus on Chopra here merely because others have
claimed that some of the things that he has written seem like
“woo-woo nonsense” (e.g., Shermer, 2010) and because of
the connection between these claims and the bullshit gen-
erator websites that we used. None of this is intended to
imply that every statement in Chopra’s tweet history is bull-
shit. Participants were given the same instructions as Study
1 and, therefore, we did not indicate the author of the s tate-
ments.
Participants completed one cognitive task and one self-
report questionnaire intended to assess individual differ-
ences in analytic cognitive style. Participants were given the
heuristics and biases battery (as in Study 1; α = .75) along
with Pacini and Epstein’s (1999) Rational-Experiential In-
ventory. The latter includes the 20-item Need for Cognition
(NFC) scale and the 20-item Faith in Intuition scale (FI).
Both scales had excellent reliability: α = .93 (NFC) and .94
(FI). Participants were given questions such as “reasoning
things out carefully is not one of my strong points” (NFC,
reverse scored) and “I like to rely on my intuitive impres-
sions” (FI). They were asked to respond based on a 5 point
scale from 1-Definitely not true of myself to 5-Definitely
true of myself.
To assess cognitive ability, we retained the Wordsum (α
= .63), and the numeracy test from Study 1. However, given
the low reliability for the 3-item numeracy test in Study 1,
we used an additional 6 items (Lipkus et al., 2001), which
lead to better reliability for the full 9-item scale (α = .63).
We also added a short form of Raven’s Advanced Progres-
sive Matrices (APM) that consists of 12 problems. The
APM are a widely used measure of fluid intelligence and the
short form has been validated in multiple studies (Arthur &
Day, 1994; Chiesi, Ciancaleoni, Galli, Morsanyi & Primi,
2012). It had acceptable internal consistency in our sample
(α = .69).
We used the same ontological confusion (α = .75) and re-
ligious belief measure (α = .96) as in Study 1. Finally, we
administered the Paranormal Belief Scale ( Tobacyk, 2004;
Pennycook et al., 2012) with the religious belief items ex-
cluded. The scale consisted of 22 items sampled from 6 cat-
egories of supernatural belief (example items in parenthe-
ses): Psi (“Mind reading is possible”), Witchcraft (“Witches
do exist”), Omens of luck (“Black cats can bring bad luck”),
Spiritualism (“It is possible to communicate with the dead”),
Extraordinary life forms (“The Loch Ness monster of Scot-
land exists”) and Precognition (“Astrology is a way to ac-
curately predict the future”). The full scale had excellent
internal consistency (α = .96).
Participants also completed wealth distribution and polit-
ical ideology measures. These measures were included as
part of separate investigations and will not be analyzed or
discussed further.
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
555
Table 2: Pearson product-moment correlations (Study 2). BSR = Bullshit Receptivity scale; H&B = Heuristics and Biases;
NFC = Need for Cognition; FI = Faith in Intuition; Num. = Numeracy; VI = Verbal Intelligence; APM = Advanced
Progressive Matrices; OC = Ontological Confusions; RB = Religious Belief; PB = Paranormal Belief. Bottom diagonal =
full sample (N = 187). Top diagonal = Participants with knowledge of Deepak Chopra excluded (N = 102). Cronbach’s
alphas for the full sample are reported in brackets.
∗∗∗
p < .001,
∗∗
p < .01,
p < .05.
1 2 3 4 5 6 7 8 9 10
1. BSR (.96) .36
∗∗∗
.08 .32
∗∗
.12 .30
∗∗
.26
∗∗
.46
∗∗∗
.25 .31
∗∗
2. H&B .34
∗∗∗
(.75) .08 .28
∗∗
.42
∗∗∗
.43
∗∗∗
.40
∗∗∗
.41
∗∗∗
.31
∗∗
.46
∗∗∗
3. NFC .13 .20
∗∗
(.93) .32
∗∗
.17 .24 .19 .18 .15 .10
4. FI .30
∗∗∗
.37
∗∗∗
.28
∗∗∗
(.94) .17 .34
∗∗∗
.05 .24 .34
∗∗∗
.37
∗∗∗
5. Num. .25
∗∗
.46
∗∗∗
.22
∗∗
.27
∗∗∗
(.63) .34
∗∗∗
.45
∗∗∗
.20 .07 .21
6. VI .30
∗∗∗
.40
∗∗∗
.27
∗∗∗
.31
∗∗∗
.31
∗∗∗
(.63) .27
∗∗
.38
∗∗∗
.16 .30
∗∗
7. APM .27
∗∗∗
.45
∗∗∗
.24
∗∗
.14 .46
∗∗∗
.36
∗∗∗
(.69) .33
∗∗
.07 .12
8. OC .45
∗∗∗
.41
∗∗∗
.29
∗∗∗
.34
∗∗∗
.26
∗∗
.33
∗∗∗
.34
∗∗∗
(.75) .12 .34
∗∗
9. RB .27
∗∗∗
.34
∗∗∗
.20
∗∗
.35
∗∗∗
.17 .24
∗∗
.14 .22
∗∗
(.96) .34
∗∗
10. PB .35
∗∗∗
.45
∗∗∗
.10 .44
∗∗∗
.33
∗∗∗
.26
∗∗
.18 .38
∗∗∗
.44
∗∗∗
(.96)
9.3 Procedure
In contrast to Study 1, participants evaluated the meaning-
less st atements before completing the cognitive tasks. More-
over, the Chopra-Twitter items followed directly after the
meaningless statements. We asked participants if they knew
who Deepak Chopra is (yes / maybe / no) and, if so, whether
they follow him on “Twitter” or have read any of his books.
The cognitive tasks were then completed in the following
order: heuristics and biases battery, Wordsum, numeracy,
and APM. Participants then completed the ontological con-
fusions scale, followed by the religious and paranormal be-
lief scales (in that order). The NFC and FI questionnaires
came at the very end of the study.
10 Results
Of the 187 participants, 85 (45.5%) indicated that they know
who Deepak Chopra is (“uncertain”: N = 26, 13.9%; “no”:
N = 76, 40.6%). This knowledge was associated with lower
profoundness ratings for the pseudo-profound bullshit items
(“no/maybe” M = 2.6; “yes” M = 2.3), t(185) = 2.84, SE =
.11, p = .005, and Chopra-Twitter items (“no/maybe” M =
2.9; “yes” M = 2.6), t(185) = 2.32, SE = .12, p = .022. Below
we report key analyses with the full and restricted (i.e., those
with knowledge of Chopra being excluded) samples.
Focusing on the full sample, the 20-item BSR scale had
excellent internal consistency (α = .93) and the 10-item
Chopra-Twitter scale was also reliable (α = .89). A sum-
mary of descriptive statistics for each item is reported in
Table S2. Participants rated the Chopra-Twitter items (M
= 2.77, SD = .84) as more profound than the bullshit state-
ments (M = 2.46, SD = .76), participant-level: t(187) = 10.6,
SE = .03, p < .001, item-level: t(28) = 3.98, SE = .08, p <
.001. However, mean ratings for the two scales were very
strongly correlated ( r = .88). Moreover, the pattern of corre-
lations for the scales was identical (see supplementary mate-
rials, Table S3). We therefore combined all of the items for
both scales into a single Bullshit Receptivity (BSR) scale,
which had excellent internal consistency (α = .96).
The BSR scale significantly correlated with each variable
apart from Need for Cognition (Table 2, bottom diagonal),
which (curiously) was only modestly correlated with heuris-
tics and biases performance. Specifically, BSR was nega-
tively correlated with performance on the heuristics and bi-
ases battery and positively correlated with Faith in Intuition.
The cognitive ability measures, including numeracy, were
also negatively correlated with BSR. Finally, BSR was pos-
itively correlated with ontological confusions, and both reli-
gious and paranormal belief. The pattern of results was very
similar when the correlations are restricted only to partici-
pants who did not report having any knowledge of Deepak
Chopra (Table 2, top diagonal).
11 Study 3
In Studies 1 and 2, we established a statistically reliable
measure of bullshit receptivity that correlated with a variety
of conceptually related variables. It remains unclear, how-
ever, whether these associations are driven by a bias toward
accepting pseudo-profound bullshit as meaningful or a fail-
ure to detect the need for skepticism (or both) when skep-
ticism is warranted (i.e., sensitivity, as distinct fr om bias,
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
556
in the sense of signal-detection theory). It may be that in-
creased profundity ratings are associated with lower reflec-
tive thinking (for example), regardless of the presented con-
tent.
The goal of Study 3 was to test the possibility that some
people may be particularly insensitive to pseudo-profound
bullshit, presumably because they are less capable of de-
tecting conflict during reasoning. For this, we created a
scale using ten motivational quotations that are convention-
ally considered to be profound (e.g., A river cuts through
a rock, not because of its power but its persistence”) in that
they are written in plain language and do not contain the
vague buzzwords that are characteristic of the statements
used in Studies 1 and 2. The difference between profun-
dity ratings between legitimately meaningful quotations and
pseudo-profound bullshit will serve as our measures of bull-
shit sensitivity. Secondarily, we also included mundane
statements that contained clear meaning but that would not
be considered conventionally profound (e.g., “Most people
enjoy some sort of music”). If the association between ana-
lytic thinking and profundity ratings for pseudo-profound
bullshit is due to bullshit detection in particular, analytic
thinking should not be associated with profundity ratings for
mundane statements.
12 Method
12.1 Participants
A total of 125 participants (52 male, 73 female, M
age
= 36.4,
SD
age
= 13.3) were recruited from Amazon’s Mechanical
Turk in return for pay. Only American residents were per-
mitted to sign up for the study. All participants reported
speaking fluent English. Given the strength (and accumu-
lating cost) of the previous findings, 125 participants was
deemed a sufficient sample. These data were not analyzed
until the full sample was completed.
Eleven participants were removed because they re-
sponded affirmatively when asked if they responded ran-
domly at any time during the study. Fourteen participants
failed an attention check question but were retained, as in
Studies 1 and 2.
12.2 Materials
We created four 10-item scales. For the BSR, we used the
original 10 items from Study 1 and the 10 Chopra-Twitter
items from Study 2. We created a scale with 10 statements
that convey meaning, but that are mundane (e.g., “Newborn
babies require constant attention”; see Table S4 for full list).
Finally, ten motivational quotations were found through an
internet s earch and used to f orm a second scale (e.g., A wet
person does not fear the rain”; see Table S5 for full list). Par-
ticipants completed the heuristics and biases measure from
Studies 1 and 2 (α = .61).
12.3 Procedure
The four types of statements were intermixed in a unique
random order for each participant. The statements were pre-
sented at the beginning of the study. Participants then com-
pleted the heuristics and biases battery.
13 Results
Of the 114 participants, 47 (41.2%) indicated that they know
who Deepak Chopra is (“uncertain”: N = 7, 6.1%; “no”: N =
60, 52.6%). This knowledge was not associated with lower
profoundness ratings for bullshit or Chopra-Twitter items,
ts < 1.4, ps > .17. Nonetheless, we report our correlational
analyses with the full and restricted sample.
Focusing on the full sample, profoundness ratings for the
BSR items (α = .91) and for Deepak Chopra’s actual tweets
(α = .93) were very highly correlated (r = .89). We com-
bined the two sets of items into a single BSR scale, which
had excellent internal consistency (α = .96). The motiva-
tional quotation scale had acceptable internal consistency
(α= .82) and the mundane statement scale was also reliable
(α= .93). However, the distribution of profoundness ratings
for each of the mundane statements was highly skewed (see
Table S4). Further inspection revealed that the vast major-
ity of ratings (80.1%) for mundane statements were 1 (not
at all profound) and many participants (N = 52, 46%) re-
sponded with 1 for every statement. Three standard devia-
tions above the mean f or the mundane statement scale was
not larger than 5, indicating that there were outliers. There
were no outliers for the other scales. A recursive outlier
analysis revealed 22 participants who had profoundness rat-
ings for mundane statements that were statistical outliers.
Evidently, these participants found the ostensibly mundane
statements at least somewhat profound. This may reflect a
response bias toward excess profundity among some partic-
ipants. Indeed, relative to the remainder of the sample, the
22 outlying participants had higher profundity ratings for the
pseudo-profound bullshit, t(112) = 2.50, SE = .21, p = .014,
and (marginally) the motivational quotations, t(112) = 1.83,
SE = .16, p = .071. Moreover, the outlying participants also
scored lower on the heuristics and biases task, t(112) = 3.23,
SE = .13, p = .002. Key analyses below are reported with
outliers both retained and removed for t he mundane state-
ment scale. The mundane statement scale had low reliabil-
ity (α= .35) when the outlying participants were removed,
as would be expected given the low variability in ratings.
The mean profoundness rating was lower for the BSR
items (M = 2.72, SD = .90) than for the motivational quota-
tions (M = 3.05, SD = .69), participant-level: t(113) = 3.90,
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
557
Table 3: Pearson product-moment correlations (Study 3). BSR = Bullshit Receptivity scale; a = full scale, b = outliers (N
= 22) removed. Bottom diagonal = full sample (N = 114). Top diagonal = Participants with knowledge of Deepak Chopra
excluded (N = 67). Cronbach’s alphas for the full sample are reported in brackets. *** p < .001,
∗∗
p < .01,
p < .05.
1 2 3 4 5 6
1. BSR (.96) .40
∗∗
.26
.21 .38
∗∗
.71
∗∗∗
2. Motivational quotations .38
∗∗∗
(.82) .15 .14 .10 .36
∗∗
3. Mundane statements a .26
∗∗
.17 (.93) . .28
.15
4. Mundane statements b .19 .14 . (.35) .13 .10
5. Heuristics/biases .33
∗∗∗
.12 .24
∗∗
.08 (.61) .31
6. BS sensitivity (Var2–Var1) .71
∗∗∗
.38
∗∗∗
.13 .08 .23
.
SE = .08, p < .001, item-level: t(28) = 3.44, SE = .10, p =
.002. Moreover, the mundane statements (outliers retained,
M = 1.44, SD = .78) were judged to be less profound than
the BSR items, participant-level: t(113) = 13.24, SE = .10, p
< .001, item-level: t (28) = 14.60, SE = .09, p < .001, and the
motivational quotations, participant-level: t(113) = 18.13,
SE = .09, p < .001, item-level: t(18) = 19.56, SE = .08, p <
.001.
Focusing on the full sample (Table 3, bottom diagonal),
BSR was negatively associated with heuristics and biases
performance. This replicates Studies 1 and 2. However,
there was no such association between profoundness ratings
for motivational quotations and heuristics and biases perfor-
mance (p = .192). To further explore the specific association
between heuristics and biases performance and profundity
ratings for pseudo-profound bullshit, we created a “bullshit
sensitivity” score by subtracting the BSR from motivational
quotation means (Table 3). Heuristics and biases was posi-
tively correlated with this measure (r = .23, p = .013), indi-
cating an association between analytic thinking and the abil-
ity to spontaneously detect pseudo-profound bullshit. These
results were similar when the sample was restricted to those
with no knowledge of Deepak Chopra (Table 3, top diag-
onal). Indeed, the association between bullshit sensitivity
and heuristics and biases performance was nominally larger
in the restricted sample (r = .31, p = .012).
The BSR was correlated with profoundness ratings for
motivational quotations and mundane statements (Table 3,
bottom diagonal; although only marginally when outliers
are removed in the latter case, p = .072). Profoundness
ratings for motivational quotations and mundane statements
were also marginally correlated (p = .067; p = .170 when
outliers are removed), indicating a potential disposition to-
ward higher profoundness ratings among some participants
(i.e., response bias). There was also an association between
heuristics and biases performance and profoundness ratings
for mundane statements (p = .009), but it did not remain
significant once the outliers were removed (p = .476). This
pattern of results is identical in the restricted sample. These
results indicate that, at least for some participants, response
bias plays a role in bullshit receptivity and explains some of
its association with analytic thinking.
14 Study 4
The results of Study 3 indicate that the association between
profoundness ratings and reflective thinking is largely spe-
cific to bullshit items. The lack of correlation between
heuristics and biases performance and profoundness rat-
ings for motivational quotations, in particular, indicates that
more reflective participants are not merely more skeptical
toward all manner of profound-sounding statements. How-
ever, there was an unequal number of bullshit (N = 20) and
motivational (N = 10) items in Study 3. Moreover, it is
unclear whether the inclusion of mundane statements inter-
acted in s ome way with participants’ evaluation of the bull-
shit and motivational statements. Thus, in Study 4, we asked
participants to rate the relative profoundness of 20 randomly
intermixed statements (10 bullshit and 10 motivational).
In Study 3, we did not include any measures of epistem-
ically suspect beliefs. Thus, in Study 4, participants com-
pleted the heuristics and biases battery, along with measures
of paranormal belief, conspiracist ideation, and endorse-
ment of complementary and alternative medicine.
15 Method
15.1 Participants
We recruited 242 participants (146 male, 107 female, M
age
= 33.9, SD
age
= 10.6) from Amazon’s Mechanical Turk in
return for pay. Only American residents were permitted to
sign up for the study. All participants reported speaking flu-
ent English. We chose a larger target of 250 participants
given some of the marginal results in Study 3. These data
were not analyzed until the full sample was completed.
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
558
Twenty-three participants were removed because they re-
sponded affirmatively when asked if they responded ran-
domly at any time during the study. Twelve participants
failed an attention check question but were retained as re-
moving them had no effect on the pattern of results.
15.2 Materials
We used the BSR (10 items) from Study 1. We used the
same motivational quotation scale from Study 3 (see Table
S6 for full list). Participants also completed the heuristics
and biases battery (α = .67) from Studies 1-3 and the para-
normal belief scale (including religious belief items; α =
.96) from Study 2. We measured conspiracy ideation us-
ing a 15-item general conspiracy beliefs scale (Brotherton,
French & Pickering, 2013). The scale included items such
as A small, secret group of people is responsible for making
all major world decisions, such as going to war” (α = .95).
Responses were made on t he following 5-point scale: 1)
Definitely not true, 2) Probably not true, 3) Not sure/cannot
decide, 4) Probably true, 5) Definitely true. For the com-
plementary and alternative medicine scale, we asked partic-
ipants to rate the degree to which they believe in the effi-
cacy of 10 common types of alternative medicines (CAM;
Complementary and Alternative Medicine, e.g., homeopa-
thy) on the following 5-point scale (Lindeman, 2011): 0)
Don’t know/cannot say [removed from analysis], 1) Do not
believe at all, 2) Slightly believe, 3) Moderately believe, 4)
Believe fully. An overall CAM score was created by sum-
ming the responses (α = .94).
Participants also completed a ten item personality scale
(Gosling, Rentfrow & Swann, 2003) that indexes individ-
ual differences in the Big Five personality traits ( extraver-
sion, agreeableness, conscientiousness, emotional stability,
and openness). These data will not be considered further.
15.3 Procedure
The bullshit and motivational statements were presented
first in a unique random order for each participant. Par-
ticipants then completed the remainder of the tasks in the
following order: Heuristics and biases battery, personality
scale, paranormal belief scale, conspiracy ideation scale,
and CAM scale.
16 Results
Of the 217 participants, 98 (42.2%) indicated that they know
who Deepak Chopra is (“uncertain”: N = 33, 14.2%; “no”:
N = 101, 43.5%). This knowledge was not associated wit h
lower profundity ratings for bullshit statements (“yes” M =
2.2; “no/maybe” M = 2.35), t(230) = 1.34, SE = .10, p =
.182. Nonetheless, in keeping with Studies 2 and 3, we re-
port our correlational analyses with the full and restricted
sample.
Focusing on the full sample, the 10-item BSR scale had
good internal consistency (α = .89) and the 10-item motiva-
tional quotation scale was also reliable (α = .80). The mean
profoundness rating was higher for the motivational quota-
tions (M = 3.13, SD = .67) than the BSR items (M = 2.29,
SD = .82), participant-level: t(231) = 15.93, SE = .05, p <
.001, item-level: t(18) = 9.45, SE = .09, p < .001, although
the motivational quotations were far from ceiling.
BSR was negatively correlated with heuristics and biases
performance and positively correlated with paranormal be-
lief, conspiracist ideation, and belief in the efficacy of com-
plementary and alternative medicine. However, the mean
profoundness r atings for the BSR and motivational quota-
tions was strongly correlated (r = .43) and, in contrast to
Study 3, the motivational quotation scale was correlated
with heuristics and biases performance (p = .035). The
mean profoundness rating for motivational quotations was
also positively correlated with conspiracist ideation, com-
plementary and alternative medicine, and (marginally) para-
normal belief (p = .088). Thus, as in Study 3, we computed
a “bullshit sensitivity” variable by subtracting the mean pro-
fundity ratings for the motivational quotations from the bull-
shit items. Unlike in Study 3, however, heuristics and biases
performance was not significantly correlated with bullshit
sensitivity in the full sample (r = .10, p = .121). There was
also no correlation between bullshit sensitivity and conspir-
acist ideation (r = –.03, p = .652) or complementary and
alternative medicine (r = –.08, p = .218). In contrast, para-
normal belief remained negatively correlated with bullshit
sensitivity (r = –.21, p = .002).
Unlike in Studies 2 and 3, the pattern of results was differ-
ent when the analysis was restricted to those with no knowl-
edge of Deepak Chopra. Namely, when the analysis was re-
stricted, bullshit sensitivity was significantly positively cor-
related with heuristics and biases performance (r = .19, p
= .032). Moreover, conspiracist ideation was marginally
negatively associated with bullshit sensitivity (r = –.16, p
= .070). Paranormal belief remained negatively correlated
(r = –.23, p = .009) and complementary and alternative re-
mained uncorrelated (r = –.06, p = .497) with bullshit sen-
sitivity. These results support the idea that the difference
between profundity ratings for genuine motivational quota-
tions and pseudo-profound bullshit can be used as a measure
of bullshit sensitivity. However, they also indicate that cau-
tion is required at least when the 10-item scales are used
as familiarity with Deepak Chopra may limit the useful-
ness of the scale. Chopra has a distinct style and it is pos-
sible that prior knowledge may have confounded our bull-
shit measure. For example, it may have helped some people
detect the bullshit. Conversely, among those who have a fa-
vorable opinion of Chopra, this may have artificially inflated
profoundness ratings for the bullshit.
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
559
Table 4: Pearson product-moment correlations (Study 4). BSR = Bullshit Receptivity scale; CAM = Complementary and
alternative medicine. Bottom diagonal = full sample (N = 232). Top diagonal = Participants with knowledge of Deepak
Chopra excluded (N = 134). Cronbach’s alphas for the full sample are reported in brackets.
∗∗∗
p < .001,
∗∗
p < .01,
p <
.05.
1 2 3 4 5 6 7
1. BSR (.89) .38
∗∗∗
.68
∗∗∗
.30
∗∗∗
.23
∗∗
.15 .17
2. Motivational quotations .43
∗∗∗
(.80) .42
∗∗∗
.14 .01 .01 .13
3. BS Sensitivity (Var2–Var1) .66
∗∗∗
.40
∗∗∗
. .19
.23
∗∗
.16 .06
4. Heuristics/Biases .21
∗∗
.14 .10 (.67) .40
∗∗∗
.11 .37
∗∗∗
5. Paranormal Belief .30
∗∗∗
.11 .21
∗∗
.33
∗∗∗
(.96) .47
∗∗∗
.54
∗∗∗
6. Conspiracist Ideation .17
∗∗
.17
∗∗
.03 .10 .49
∗∗∗
(.95) .26
∗∗
7. CAM .24
∗∗∗
.19
∗∗
.08 .29
∗∗∗
.58
∗∗∗
.22
∗∗
(.94)
17 General discussion
The present study represents an initial investigation of the
individual differences in receptivity to pseudo-profound
bullshit. We gave people syntactically coherent sentences
that consisted of random vague buzzwords and, across four
studies, these statements were judged to be at least some-
what profound. This tendency was also evident when we
presented participants with similar real-world examples of
pseudo-profound bullshit. Most importantly, we have pro-
vided evidence that individuals vary in conceptually inter-
pretable ways in their propensity to ascribe profundity to
bullshit statements; a tendency we refer to as “bullshit re-
ceptivity”. Those more receptive to bullshit are less reflec-
tive, lower in cognitive ability (i.e., verbal and fluid intel-
ligence, numeracy), are more prone to ontological confu-
sions and conspiratorial ideation, are more likely to hold re-
ligious and paranormal beliefs, and are more likely to en-
dorse complementary and alternative medicine. Finally, we
introduced a measure of pseudo-profound bullshit sensitiv-
ity by computing a difference score between profundity rat-
ings for pseudo-profound bullshit and legitimately meaning-
ful motivational quotations. This measure was related to
analytic cognitive style and paranormal skepticism. How-
ever, there was no association between bullshit sensitivity
and either conspiratorial ideation or acceptance of comple-
mentary and alternative medicine (CAM). Nonetheless, our
findings are consistent with the idea that the tendency to rate
vague, meaningless statements as profound (i.e., pseudo-
profound bullshit receptivity) is a legitimate psychological
phenomenon that is consistently related to at least some vari-
ables of theoretical interest.
17.1 Response bias and sensitivity
We proposed two mechanisms that explain why people
might rate bullshit as profound. The first is a type of
response bias wherein some individuals are simply more
prone to relatively high profundity ratings. Although this
mechanism is not specific to bullshit, it may at least partly
explain why our pseudo-profound bullshit measure was so
consistently positively correlated with epistemically s uspect
beliefs. Some people may have an uncritically open mind.
As the idiom goes: “It pays to keep an open mind, but not
so open your brains fall out”. In Study 3, some people even
rated entirely mundane statements (e.g., “Most people en-
joy at least some sort of music”) as at least somewhat pro-
found. Our results suggest that this tendency which resem-
bles a general gullibility factor is a component of pseudo-
profound bullshit receptivity. There is, of course, a great
deal of research on this sort of mechanism. As a promi-
nent example, consider the “Barnum effect”. In his classic
demonstration of gullibility, Forer (1949) had introductory
psychology students complete a personality measure (the
“Diagnostic Interest Blank”, DIB). One week later, he gave
each of the students an ostensibly personalized personality
sketch t hat consisted of 13 statements and asked them to rate
both the accuracy of the statements and the overall efficacy
of the DIB. Unbeknownst to the students, Forer had actually
given every student the same personality sketch that con-
sisted entirely of vague, generalized statements taken from
a newsstand astrology book (e.g., “You have a great need for
other people to like and admire you.”). Although some peo-
ple were more skeptical than others, the lowest number of
specific statements accepted was 8 (out of 13). Moreover,
the students were quite convinced of the personality tests’
efficacy All of the students accepted the DIB as a good
or perfect instrument for personality measurement” (Forer,
1949, p. 121). Meehl (1956) first referred to this as the
Barnum effect, after the notorious hoaxer (bullshitter) P. T.
Barnum.
2
2
In an amusing irony, P. T. Barnum is often erroneously attributed the
phrase “There’s a sucker born every minute. This is true even in at least
one review of research on the Barnum effect (Furnham & Shofield, 1987).
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
560
As a secondary point, it is worthwhile to distinguish
uncritical or reflexive open-mindedness from thoughtful
or reflective open-mindedness. Whereas reflexive open-
mindedness results from an intuitive mindset that is very
accepting of information without very much processing, re-
flective open-mindedness (or active open-mindedness; e.g.,
Baron, Scott, Fincher & Metz, 2014) results from a mindset
that searches for information as a means to facilitate critical
analysis and reflection. Thus, t he former should cause one
to be more receptive of bullshit whereas the latter, much like
analytic cognitive style, should guard against it.
The foregoing highlights what appears to be a strong gen-
eral susceptibility to bullshit, but what cognitive mecha-
nisms inoculate against bullshit? Drawing on recent dual-
process theories that posit a key role for conflict detection
in reasoning (De Neys, 2012; Pennycook et al., 2015), we
proposed that people may vary in their ability to detect bull-
shit. Our results modestly support this claim. Namely, we
created a bullshit “sensitivity” measure by subtracting pro-
fundity ratings for pseudo-profound bullshit from ratings for
legitimate motivational quotations. Increased bullshit sensi-
tivity was associated with better performance on measures
of analytic thinking. This is consistent with Sagan’s (1996)
famous claim that critical thinking facilitates “baloney de-
tection”.
Further, bullshit sensitivity was associated with lower
paranormal belief, but not conspiratorial ideation or accep-
tance of complementary and alternative medicine. This was
not predicted as all three forms of belief are considered
“epistemically suspect” (e.g., Pennycook, et al., in press).
One possible explanation for this divergence is that super-
natural beliefs are a unique subclass because they entail
a conflict between some immaterial claim and (presum-
ably universal) intuitive folk concepts (Atran & Norenza-
yan, 2004). For example, the belief in ghosts conflicts with
folk-mechanics that is intuitive belief that objects can-
not pass through solid objects (Boyer, 1994). Pennycook
et al. (2014) found that degree of belief in supernatural reli-
gious claims (e.g., angels, demons) is negatively correlated
with conflict detection effects in a reasoning paradigm. This
result suggests that the particularly robust association be-
tween pseudo-profound bullshit r eceptivity and supernatu-
ral beliefs may be because both response bias and conflict
detection (sensitivity) support both factors. Further research
is needed to test this claim.
17.2 Future directions
The focus of this work was on investigating individual dif-
ferences in the tendency to accept bullshit statements, and
our initial evidence indicates that reflectiveness may be a
key individual difference variable. At a very basic level,
the willingness to stop and think analytically about the ac-
tual meanings of the presented words and t heir associations
would seem an a priori defense against accepting bullshit
at face value (i.e., to avoid an excessively open-minded re-
sponse bias). Moreover, increased detection of bullshit may
reinforce a critical attitude and potentially engender a more
restrained attitude to profundity judgments. The present
findings also provide evidence that an increased knowledge
of word meaning (via verbal intelligence) may assist in
critical analysis. An understanding of more precisely nu-
anced meanings of words may reveal inconsistencies, incon-
gruities, and conflicts among terms in bullshit statements.
Conflict detection is a key aspect of dual-process theories
(e.g., De Neys, 2012; Pennycook, et al., 2015), though in
this case it remains unclear precisely what features of bull-
shit statements might cue reflective thinking. What is it
about a statement like “good health imparts reality to subtle
creativity” that might cause someone to stop and consider
the meaning of the sentence more deeply?
Although a reflective thinking style appears to militate
against bullshit acceptance, other cognitive processes that
underlie the propensity to find meaning in meaningless
statements remain to be elucidated. It may be that people
naturally assume that statements presented in a psychology
study (vague or otherwise) are constructed with the goal
of conveying some meaning. Indeed, the vagueness of the
statements may imply t hat the i ntended meaning is so im-
portant or profound that it cannot be stated plainly (Sper-
ber, 2010). In the current work, we presented the partici-
pants with meaningless statements without cueing them to
the possibility that t hey are complete bullshit. Although
this is likely how bullshit is often encountered in everyday
life, it may be that some skepticism about the source of the
statement is the key force that may guard against bullshit
acceptance. For example, poems attributed to prestigious
sources are evaluated more positively (Bar-Hillel, Mahar-
shak, Moshinsky & Nofech, 2012). Interpretation is difficult
and humans surely rely on simple heuristics (e.g., “do I trust
the source?”) to help with the task.
In this vein, psychological research should aim to eluci-
date contextual factors that interact with individual differ-
ences in the reception and detection of bullshit. As noted by
philosophers studying the topic, the bullshitter oft has the
intention of implying greater meaning than is literally con-
tained in the message, though the nature of the intent can
vary. For example, the literary critic Empson (1947) de-
scribes the use of ambiguity in literature, including a type
of intentional ambiguity used by poets in which a passage
“says nothing, by tautology, by contradiction, or by irrele-
vant statements; so that the reader is forced to invent state-
ments of his own . . . (p. 176). The employment and re-
ception of such literary devices in the context of a broader
meaningful work seems related to but dissociable from iso-
lated statements such as those used here. By examining
pseudo-profound bullshit in an empirical fashion, we set
the stage for further refinement of this important conceptual
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
561
variable as it converges with and diverges from other related
uses of vagueness. We anticipate that there are many varia-
tions of vague, ambiguous, or otherwise unclear statements
that have unique psychological correlates in varied contexts
that are amenable to study.
18 Limitations and caveats
Bullshit comes in many forms and we have focused on only
one type. Frankfurt (2005) discusses the so-called bull ses-
sion wherein “people try out various thoughts and attitudes
in order to see how it feels to hear themselves saying such
things and in order to discover how others respond, with-
out it being assumed that they are committed to what they
say: It is understood by everyone in a bull session that the
statements people make do not necessarily reveal what they
really believe or how they really feel” ( p. 9). This quali-
fies as bullshit under Frankfurt’s broad definition because
the content is being communicated absent a concern for the
truth. Nonetheless, the character of conversational bullshit
is likely quite different from pseudo-profound bullshit, and
by extension the reception and detection of it may be de-
termined by different psychological factors. It is important
for researchers interested in the psychology of bullshit to be
clear about the type of bullshit that they are investigating.
Our bullshit receptivity scale was quite successful overall,
but future work is needed to r efine and improve it. In par-
ticular, the bullshit sensitivity measure would be improved
if there was a more direct mapping between the pseudo-
profound bullshit and the genuinely meaningful control
items. Naturally, more items would improve both scales.
Finally, knowledge of Deepak Chopra may subtly confound
experiments using our bullshit sensitivity scale (or, at least,
slightly restrict the effect size).
Finally, we have focused on an individual differences ap-
proach given that our primary goal was to demonstrate that
bullshit receptivity is a consequential thing that can be reli-
ably measured. This preliminary work is r equired f or exper-
iments to be meaningful. Future work should focus on the
dual goals of further refining our measure of bullshit recep-
tivity and experimentally modulating profundity ratings for
pseudo-profound bullshit.
19 Conclusion
Bullshit is a consequential aspect of the human condition.
Indeed, with the rise of communication technology, people
are likely encountering more bullshit in their everyday lives
than ever before. Profundity ratings for statements contain-
ing a random collection of buzzwords were very strongly
correlated with a selective collection of actual “Tweets”
from Deepak Chopra’s “Twitter” feed (rs = .88–89). At
the time of this writing, Chopra has over 2.5 million follow-
ers on “Twitter” and has written more than twenty New York
Times bestsellers. Bullshit is not only common; it is popu-
lar.
3
Chopra is, of course, just one example among many.
Using vagueness or ambiguity to mask a lack of meaning-
fulness is surely common in political rhetoric, marketing,
and even academia (Sokal, 2008). Indeed, as intimated by
Frankfurt (2005), bullshitting is something that we likely all
engage in to some degree (p. 1): “One of the most salient
features of our culture is that there is so much bullshit. Ev-
eryone knows this. Each of us contributes his share. One
benefit of gaining a better understanding of how we reject
other’s bullshit is that it may teach us to be more cognizant
of our own bullshit.
The construction of a reliable index of bullshit receptivity
is an important first step toward gaining a better understand-
ing of the underlying cognitive and social mechanisms that
determine if and when bullshit is detected. Our bullshit re-
ceptivity scale was associated with a relatively wide range
of important psychological factors. This is a valuable first
step toward gaining a better understanding of the psychol-
ogy of bullshit. The development of interventions and strate-
gies that help individuals guard against bullshit is an impor-
tant additional goal that requires considerable attention from
cognitive and social psychologists. That people vary in their
receptivity toward bullshit is perhaps less surprising than the
fact that psychological scientists have heretofore neglected
this issue. Accordingly, although this manuscript may not
be truly profound, it is indeed meaningful.
20 References
Arthur, W., & Day, D. (1994). Development of a short form
for the Raven Advanced Progressive Matrices test. Edu-
cational and Psychological Measurement, 54, 395–403.
Atran, S., & Norenzayan, A. (2004). Religion’s evolution-
ary landscape: Counterintuition, commitment, compas-
sion, communion. Behavioural and Brain Sciences, 27,
713–770.
Baron, J. (1985). Rationality and intelligence. New York:
Cambridge University Press.
Baron, J., Scott, S., Fincher, K. S., & Metz, E. (2014). Why
does the Cognitive Reflection Test (sometimes) predict
utilitarian moral judgment (and other things)? Journal of
Applied Research in Memory and Cognition, 4, 265–284.
Bar-Hillel, M., Maharshak, A., Moshinsky, A., & Nofech,
R. (2012). A rose by any other name: A social-cognitive
3
And profitable. Deepak Chopra is one of the wealthiest holistic-health
“gurus” (Perry, 1997). This is not to say that everything Deepak Chopra has
written is bullshit. Nonetheless, some of it seems to meet our definition of
pseudo-profound bullshit. Our goal here is to simply raise the possibility
that Chopra’s tend ency to bullshit ( as claimed by others, Shermer, 2010)
may have played an important role in his popularity.
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
562
perspective on poets and poetry. Judgment and Decision
Making, 7, 149–164.
Black, M. (1983). The prevalence of Humbug and other
essays. Ithaca/London: Cornell University Press.
Boyer, P. (1994). The naturalness of religious ideas: A cog-
nitive theory of religion. Berkeley, CA: University of Cal-
ifornia Press.
Brotherton, R., French, C. C., & Pickering, A. D. (2013).
Measuring belief in conspiracy theories: The generic
conspiracist beliefs scale. Frontiers in Personality Sci-
ence and Individual Differences, 4, 279. http://doi.org/
10.3389/fpsyg.2013.00279.
Browne, M., Thomson, P., Rockloff, M. J., & Pennycook,
G. (2015). Going against the herd: Psychological and
cultural factors underlying the “vaccination confidence
gap”. PLoS ONE 10(9), e0132562. http://doi.org/10.
1371/journal.pone.0132562.
Buekens, F. & Boudry, M. ( 2015). The dark side of the long:
Explaining the temptations of obscurantism. Theoria, 81,
126–142.
Campitelli, G. & Gerrans, P. (2014). Does the cognitive re-
flection test measure cognitive reflection? A mathemati-
cal modeling approach. Memory & Cognition, 42, 434–
447.
Chiesi, F., Ciancaleoni, M., Galli, S., Morsanyi, K., & Primi,
C. (2012). Item response theory analysis and differen-
tial item functioning across age, gender, and country of a
short form of the Advanced Progressive Matrices. Learn-
ing and Individual Differences, 22, 390–396.
Chopra, D. (1989). Quantum Healing. New York: Bantam
Books.
Chopra, D. (2008). The Soul of Leadership. New York:
Harmony Books.
De Neys, W. (2012). Bias and conflict: A case for logi-
cal intuitions. Perspectives on Psychological Science, 7,
28–38.
De Neys, W. (2014). Conflict detection, dual processes, and
logical intuitions: Some clarifications. Thinking & Rea-
soning, 20, 167–187.
Empson, W. (1947). Seven Types of Ambiguity. Chatto &
Windus, London
Evans, J. St. B. T., & Stanovich, K. E. (2013). Dual-process
theories of higher cognition: Advancing the debate. Per-
spectives in Psychological Science, 8, 223–241.
Forer, B. R., (1949). The fallacy of personal validation: A
classroom demonstration of gullibility. Journal of Abnor-
mal and Social Psychology, 44, 118–123.
Frederick, S. (2005). Cognitive reflection and decision mak-
ing. The Journal of Economic Perspectives, 19, 25–42.
Frankfurt, H. G. (2005) On Bullshit. Cambridge: Cam-
bridge University Press.
Furnham, A., & Schofield, S. (1987). Accepting personality
test feedback: A review of the Barnum effect. Current
Psychological Research and Reviews, 6, 162–178.
Gervais, W. M., & Norenzayan, A. (2012). Analytic think-
ing promotes religious disbelief. Science, 336, 493–496.
Gilbert, D. T. (1991). How mental systems believe. Ameri-
can Psychologist, 46, 107–119.
Gilbert, D. T., Tafarodi, R. W., & Malone, P. S. (1993). You
can’t not believe everything you read. Journal of Person-
ality and Social Psychology, 65, 221–233.
Gosling, S. D., Rentfrow, P. J., & Swann, W. B. (2003). A
very brief measure of the Big-Five personality domains.
Journal of Research in Personality, 37, 504–528.
Kahneman, D. (2011). Thinking, fast and slow. New York:
Farrar, Strauss, & Giroux.
Lindeman, M. (2011). Biases in intuitive reasoning and be-
lief in complementary and alternative medicine. Psychol-
ogy & Health, 26, 371–82.
Lindeman, M., & Aarnio, K. ( 2007). Superstitious, magical,
and paranormal beliefs: An integrative model. Journal of
Research in Personality, 41, 731–744.
Lindeman, M., Cederström, S., Simola, P., Simula, A., Ol-
likainen, S., & Riekki, T. (2008). Sentences with core
knowledge violations increase the size of n400 among
paranormal believers. Cortex, 44, 1307–1315.
Lindeman, M., Svedholm-Hakkinen, A. M., & Lipsanen, J.
(2015). Ontological confusions but not mentalizing abili-
ties predict religious belief, paranormal beliefs, and belief
in supernatural purpose. Cognition, 134, 63–76.
Lipkus, I. M., Samsa, G., & Rimer, B. K. (2001). General
performance on a numeracy scale among highly educated
samples. Medical Decision Making, 21, 37–44.
Lobato, E., Mendoza, J., Sims, V., & Chin, M. (2014).
Examining the relationship between conspiracy theories,
paranormal beliefs, and pseudoscience acceptance among
a university population. Applied Cognitive Psychology,
28, 617–625.
Malhorta, N., Krosnick, J. A., & Haertel, E. (2007). The
psychometric properties of the GSS Wordsum vocabulary
test, GSS Methodology Report No. 111. Chicago: NORC.
Meehl, P. E. (1956). Wanted—a good cookbook. American
Psychologist, 11, 262–272.
Pacini, R., & Epstein, S. (1999). The relation of rational and
experiential information processing styles to personality,
basic beliefs, and the ratio-bias phenomenon. Journal of
Personality and Social Psychology, 76, 972–987.
Pennycook, G., Cheyne, J. A., Barr, N., Koehler, D. J. &
Fugelsang, J. A. (2014). Cognitive style and religiosity:
The role of conflict detection. Memory & Cognition, 42,
1–10.
Pennycook, G., Cheyne, J. A., Seli, P., Koehler, D. J. &
Fugelsang, J. A. (2012). Analytic cognitive style predicts
religious and paranormal belief. Cognition, 123, 335–
346.
Pennycook, G., Fugelsang, J. A., & Koehler, D. J. (2015).
What makes us think? A three-stage dual-process model
Judgment and Decision Making, Vol. 10, No. 6, November 2015 Bullshit receptivity
563
of analytic engagement. Cognitive Psychology, 80, 34–
72.
Pennycook, G., Fugelsang, J. A., & Koehler, D. J. (in press).
Everyday consequences of analytic thinking. Current Di-
rections in Psychological Science.
Perry, T. (1997). “So Rich, So Restless”. Los Angeles
Times. 7 September.
Sagan, C. (1996). The fine art of baloney detection. The
Demon-Haunted World: Science as a Candle in the Dark.
New York: Random House, 201–218.
Schwartz, L. M., Woloshin, S., Black, W. C., & Welch, H.
G. (1997). The role of numeracy in understanding the
benefit of s creening mammography. Annals of Internal
Medicine, 127, 966–972.
Shenhav, A., Rand, D. G., & Greene, J. D. (2012). Divine
intuition: Cognitive style influences belief in god. Jour-
nal of Experimental Psychology: General, 141, 423–428.
Shermer, M. (2010). Deepakese: The Woo-Woo Master
Deepak Chopra Speaks. http://www.huffingtonpost.
com/michael-shermer/deepakese-the-woo-woo-mas_b_
405114.html.
Sokal, A. (2008). Beyond the Hoax: Science, Philosophy
and Culture. New York: Oxford.
Sperber, D. (2010). The guru effect. Review of Philosophi-
cal Psychology, 1, 583–592.
Stanovich, K. E. (2011). Rationality and the reflective mind.
New York, NY: Oxford University Press.
Stanovich, K. E., & West, R. F. (2000). Individual differ-
ences in reasoning: Implications for the rationality de-
bate? Behavioral and Brain Sciences, 23, 645–726.
Svedholm, A. M., & Lindeman, M. (2013). The separate
roles of the reflective mind and involuntary inhibitory
control in gatekeeping paranormal beliefs and the under-
lying intuitive confusions. British Journal of Psychology,
3, 303–319.
Swami, V., Voracek, M., Stieger, S., Tran, U. S., & Furnham,
A. (2014). Analytic thinking reduces belief in conspiracy
theories. Cognition, 133, 572–585.
Tobacyk, J. (2004). A revised paranormal belief scale. In-
ternational Journal of Transpersonal Studies, 23, 94–98.
Toplak, M. V., West, R. F., & Stanovich, K. E. (2011). The
Cognitive Reflection Test as a predictor of performance
on heuristics-and-biases tasks. Memory & Cognition, 39,
1275–1289.
Toplak, M. V., West, R. F., & Stanovich, K. E. (2014). As-
sessing miserly information processing: An expansion of
the Cognitive Reflection Test. Thinking & Reasoning, 20,
147–168.
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By far the most common strategy used in the attempt to modify negative attitudes toward vaccination is to appeal to evidence-based reasoning. We argue, however, that focusing on science comprehension is inconsistent with one of the key facts of cognitive psychology: Humans are biased information processors and often engage in motivated reasoning. On this basis, we hypothesised that negative attitudes can be explained primarily by factors unrelated to the empirical evidence for vaccination; including some shared attitudes that also attract people to complementary and alternative medicine (CAM). In particular, we tested psychosocial factors associated with CAM endorsement in past research; including aspects of spirituality, intuitive (vs analytic) thinking styles, and the personality trait of openness to experience. These relationships were tested in a cross-sectional, stratified CATI survey (N = 1256, 624 Females). Whilst educational level and thinking style did not predict vaccination rejection, psychosocial factors including: preferring CAM to conventional medicine (OR .49, 95% CI .36–.66), endorsement of spirituality as a source of knowledge (OR .83, 95% CI .71–.96), and openness (OR .86, 95% CI .74–.99), all predicted negative attitudes to vaccination. Furthermore, for 9 of the 12 CAMs surveyed, utilisation in the last 12 months was associated with lower levels of vaccination endorsement. From this we suggest that vaccination scepticism appears to be the outcome of a particular cultural and psychological orientation leading to unwillingness to engage with the scientific evidence. Vaccination compliance might be increased either by building general confidence and understanding of evidence-based medicine, or by appealing to features usually associated with CAM, e.g. 'strengthening your natural resistance to disease'.
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