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 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 matterof 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.
Keywords: bullshit, bullshit detection, dual-process theories, analytic thinking, supernatural beliefs, religiosity, conspiratorial
ideation, complementary and alternative medicine.

1 Introduction

2 Pseudo-profound bullshit“It is impossible for someone to lie unless he thinks heknows the truth. Producing bullshit requires no such conviction.” – Harry Frankfurt
In On Bullshit, the philosopher Frankfurt (2005) defines
bullshit as something that is designed to impress but thatwas constructed absent direct concern for the truth. Thisdistinguishes bullshit from lying, which entails a deliberate
manipulation and subversion of truth (as understood by theliar). There is little question that bullshit is a real and consequential phenomenon. Indeed, given the rise of communication technology and the associated increase in the availability of information from a variety of sources, both expert
and otherwise, bullshit may be more pervasive than ever before. Despite these seemingly commonplace observations,
we know of no psychological research on bullshit. Are people able to detect blatant bullshit? Who is most likely to fallprey to bullshit and why?

The Oxford English Dictionary defines bullshit as, simply,“rubbish” and “nonsense”, which unfortunately does not getto the core of bullshit. Consider the following statement:

Funding for this study was provided by the Natural Sciences and Engineering Research Council of Canada.
Copyright: © 2015. The authors license this article under the terms of
the Creative Commons Attribution 3.0 License.
∗ Department of Psychology, University of Waterloo, 200 University Avenue West, Waterloo ON, Canada, N2L 3G1. Email: gpennyco@uwaterloo.ca.
† Department of Psychology, University of Waterloo.
‡ The School of Humanities and Creativity, Sheridan College.

“Hidden meaning transforms unparalleled abstract beauty.”
Although this statement may seem to convey some sort ofpotentially profound meaning, it is merely a collection of
buzzwords put together randomly in a sentence that retains
syntactic structure. The bullshit statement is not merely nonsense, as would also be true of the following, which is notbullshit:“Unparalleled transforms meaning beauty hidden
abstract”.
The syntactic structure of a), unlike b), implies that it wasconstructed to communicate something. Thus, bullshit, incontrast to mere nonsense, is something that implies but
does not contain adequate meaning or truth. This sort ofphenomenon 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, issomewhat different from what is found in the philosophy ofbullshit and related phenomena (e.g., Black, 1983; Buekens& Boudry, 2015; Frankfurt; 2005). Whereas philosophers549

Judgment and Decision Making, Vol. 10, No. 6, November 2015

have been primarily concerned with the goals and intentionsof the bullshitter, we are interested in the factors that predispose 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 represents a rather extreme point on what could be considereda spectrum of bullshit. We can say quite confidently that theabove example (a) is bullshit, but one might also label anexaggerated story told over drinks to be bullshit. In futurestudies on bullshit, it will be important to define the type ofbullshit under investigation (see Discussion for further comment on this issue).
Importantly, pseudo-profound bullshit is not trivial. For areal-world example of pseudo-profound bullshit and an application of our logic, consider the following:“Attention and intention are the mechanics ofmanifestation.”
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 Healing (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 incidental, as (a) was derived using the very buzzwords from
Chopra’s “Twitter” feed.1 The vagueness of (c) indicatesthat it may have been constructed to impress upon the readersome sense of profundity at the expense of a clear expositionof meaning or truth.
Despite the lack of direct concern for truth noted byFrankfurt (2005), pseudo-profound bullshit betrays a concern for verisimilitude or truthiness. We argue that an important adjutant of pseudo-profound bullshit is vagueness
which, combined with a generally charitable attitude toward
ambiguity, may be exacerbated by the nature of recent media. As a prime example, the necessary succinctness andrapidity of “Twitter” (140 characters per “Tweet”) may beparticularly conducive to the promulgation of bullshit. Importantly, vagueness and meaning are, by definition, at crosspurposes, as the inclusion of vagueness obscures the meaning 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 important 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.

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3 Bullshit receptivity
What might cause someone to erroneously rate pseudoprofound bullshit as profound? In our view, there are twocandidate mechanisms that might explain a general “receptivity” to bullshit. The first mechanism relates to the possibility that some people may have a stronger bias toward
accepting things as true or meaningful from the outset. According to Gilbert (1991, following Spinoza), humans mustfirst believe something to comprehend it. In keeping withthis hypothesis, Gilbert, Tafarodi and Malone (1993) foundthat depleting cognitive resources caused participants to erroneously 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 unbelief may partially explain the prevalence of bullshit; weare biased toward accepting bullshit as true and it therefore 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 “Theheart 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, depending on downstream cognitive mechanisms such as conflict
detection (discussed below), either retain a default sense of
meaningfulness or invoke deliberative reasoning to assess
the truth (or meaningfulness) of the proposition. In termsof individual differences, then, it is possible that some individuals approach pseudo-profound bullshit with a stronger
initial expectation for meaningfulness. However, since this
aspect of bullshit receptivity relates to one’s mindset whenapproaching (or being approached with) bullshit, it is therefore not specific to bullshit. Nonetheless, it may be an important component of bullshit receptivity. Put differently,
some individuals may have an excessively “open” mind thatbiases them to make inflated judgments of profundity, regardless of the content.
The second mechanism relates to a potential inability todetect bullshit, which may cause one to confuse vaguenessfor profundity. In the words of Sperber (2010): “All too
often, what readers do is judge profound what they havefailed to grasp” (p. 583). Here, the bullshittee is simply unaware that the relevant stimulus requires special consideration. This mechanism is linked to what has been labelled as“conflict monitoring” failures (e.g., De Neys, 2014; Pennycook, Fugelsang & Koehler, 2015). In the context of reasoning research, for example, conflict monitoring is necessary
when two sources of information in a problem cue conflicting responses (e.g., logical validity and conclusion believability in a syllogism). Recent research indicates that people are capable of detecting these sorts of conflicts (see De
Neys, 2012 for a review), but that conflict monitoring failures are nonetheless an important source of bias in reasoning and decision making (Pennycook, Fugelsang & Koehler,

Judgment and Decision Making, Vol. 10, No. 6, November 20152015). Moreover, conflict detection is viewed as an important low-level cognitive factor that causes at least somepeople to engage deliberative, analytic reasoning processes(Pennycook, Fugelsang & Koehler, 2015). With respect tobullshit, there are likely many factors that may lead an individual to successfully detect the need for skepticism thatwill depend on the type of bullshit encountered and the bullshit context. For example, the source (perhaps a known
bullshitter) may be particularly untrustworthy. Or, perhaps,
the bullshit may conflict with common knowledge or specific 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 andmeaningful individual differences in the ability to spontaneously discern or detect pseudo-profound bullshit. Unlike
response bias, this mechanism involves distinguishing bullshit 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 asa legitimate measure of bullshit receptivity. For this, bullshit profundity ratings are correlated with a collection of individual difference factors that are conceptually related topseudo-profound bullshit in a variety of ways.

4.1

Analytic thinking

Dual-process theories of reasoning and decision making distinguish between intuitive (“Type 1”) processes that are autonomously cued and reflective (“Type 2”) processes that are
effortful, typically deliberative, and require working memory (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 historical precedent (Baron, 1985). Namely, to be a good reasoner,
one must have both the capacity to do whatever computation is necessary (i.e., cognitive ability, intelligence) and thewillingness to engage deliberative reasoning processes (i.e.,analytic cognitive style; thinking disposition). Moreover,individual differences in analytic cognitive style are positively correlated with conflict detection effects in reasoning research (Pennycook, Cheyne, Barr, Koehler & Fugelsang, 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 thinking facilitates “baloney detection”, we posit that reflective
thinking should be linked to bullshit receptivity, such that

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551

people who are better at solving reasoning problems should
be more likely to consider the specific meaning of the presented statements (or lack thereof) and judge failure to discern meaning as a possible defect of the statement rather
than of themselves. In other words, more analytic individuals should be more likely to detect the need for additional
scrutiny when exposed to pseudo-profound bullshit. Moreintuitive individuals, in contrast, should respond based ona sort of first impression, which will be inflated due to thevagueness of the pseudo-profound bullshit. Analytic thinking is thus the primary focus of our investigation, as it ismost directly related to the proposed ability to detect blatantbullshit.

4.2

Ontological confusions

Both children and adults tend to confuse aspects of reality (i.e., “core knowledge”) in systematic ways (Lindeman,
Svedholm-Hakkinen & Lipsanen, 2015). Any category mistake involving property differences between animate andinanimate or mental and physical, as examples, constitutes
an ontological confusion. Consider the belief that prayers
have the capacity to heal (i.e., spiritual healing). Suchbeliefs are taken to result from conflation of mental phenomenon, which are subjective and immaterial, and physicalphenomenon, 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 (Svedholm & Lindeman, 2013). Ontological confusions may also
be supported by a bias toward believing the literal truth ofstatements. Thus, ontological confusions are conceptuallyrelated to both detection and response bias as mechanismsthat may underlie bullshit receptivity. As such, the propensity to endorse ontological confusions should be linked tohigher levels of bullshit receptivity.

4.3

Epistemically suspect beliefs

Beliefs that conflict with common naturalistic conceptionsof the world have been labelled epistemically suspect (e.g.,
Lobato et al., 2014; Pennycook, Fugelsang & Koehler, inpress). For example, the belief in angels (and the corresponding 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). Epistemically suspect beliefs, once formed, are often accompanied by an unwillingness to critically reflect on such beliefs. Indeed, reflective thinkers are less likely to be religious and paranormal believers (e.g., Gervais & Norenzayan, 2012; Pennycook et al., 2012; Shenhav, Rand &Greene, 2012), and are less likely to engage in conspiratorial ideation (Swami et al., 2014) or believe in the efficacy of alternative medicine (Browne et al., 2015; Linde-Judgment and Decision Making, Vol. 10, No. 6, November 2015

man, 2011). Ontological confusions are also more common among believers in the supernatural (e.g., Lindeman,
Svedholm-Hakkinen & Lipsanen, 2015; Svedholm & Lindeman, 2013). Although epistemically suspect claims may
or may not themselves qualify as bullshit, the lack of skepticism that underlies the acceptance of epistemically suspectclaims should also promote positive bullshit receptivity.

5 Study 1
We presented participants with ten statements that have syntactic structure but that consist of a series of randomly selected vague buzzwords. Participants were asked to indicate
the relative profundity of each statement on a scale from1 (not at all profound) to 5 (very profound). We argue
that high ratings indicate receptivity toward bullshit. Participants also completed a series of relevant cognitive anddemographic 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, SDage = 4.8) volunteered to takepart in the study in return for course credit. Only participants who reported that English is their first language (ona separate pre-screen questionnaire) were allowed to participate. 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 number of skipped questions. Participants were also given an
attention check. For this, participants were shown a list ofactivities (e.g., biking, reading) directly below the following
instructions: “Below is a list of leisure activities. If you arereading this, please choose the “other” box below and typein ‘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 structure by randomly mashing together a list of words used in

Bullshit receptivity

552

Deepak Chopra’s tweets (e.g., “Imagination is inside exponential 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-soundingwords compiled by its author, Seb Pearce (e.g., “We are in
the midst of a self-aware blossoming of being that will alignus with the nexus itself”). A full list of items for the BSR
scale can be found in Table S1 in the supplement. The following instructions were used for the scale:
We are interested in how people experience theprofound. Below are a series of statements takenfrom relevant websites. Please read each statement and take a moment to think about what it
might mean. Then please rate how “profound”
you think it is. Profound means “of deep meaning; 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 profoundness ratings for all bullshit items.
At the beginning of the study (following demographic
questions), participants completed five cognitive tasks intended to assess individual differences in analytic cognitive
style and components of cognitive ability. The Cognitive
Reflection Test (CRT; Frederick, 2005) consists of 3 mathematical word problems that cue an incorrect intuitive response. The CRT has been shown to reflect the tendency to
avoid miserly cognitive processing (Campitelli & Gerrans,
2013; Toplak, West & Stanovich, 2011), presumably because those with an analytic cognitive style are more likely
to question or avoid the intuitive response. We also included a recent 4-item addition to the CRT (Toplak, West
& Stanovich, 2014). The 7-item CRT measure had acceptable internal consistency (Cronbach’s α = .74).
As an additional measure of reflective thinking, we included a “heuristics and biases” battery (Toplak et al., 2011).
The heuristics and biases battery involves a series of questions derived from Kahneman and Tversky, such as the gambler’s fallacy and the conjunction fallacy (Kahneman, 2011).
Much like the CRT, each item cues an incorrect intuitive response based on a common heuristic or bias. However, theheuristics 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 assessed verbal intelligence using a 12-item version of theWordsum test. For this, participants were presented withwords and asked to select from a list the word that mostclosely matches its meaning (e.g., CLOISTERED was presented with miniature, bunched, arched, malady, secluded).
The Wordsum has been used in many studies (see Malhotra,
Krosnick & Haertel, 2007 for a review), including the Gen-

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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
1. BSR
2. CRT
3. Heuristics/biases
4. Verbal intelligence
5. Numeracy
6. Ontological confusions
7. Religious belief

2

3

4

5

(.82)
−.33∗∗∗ (.74)−.28∗∗∗ .50∗∗∗ (.59)−.37∗∗∗ .41∗∗∗ .31∗∗∗ (.65)−.13∗.38∗∗∗ .27∗∗∗ .30∗∗∗ (.47)∗∗∗.31−.33∗∗∗ −.38∗∗∗ −.26∗∗∗ −.16∗∗.27∗∗∗ −.21∗∗∗ −.20∗∗ −.15∗ −.17∗∗

6

7

(.74)
.29∗∗∗ (.94)

eral Social Survey (starting in 1974). The Wordsum measure had acceptable reliability (α = .65). We also assessed
numeracy using a 3-item measure (Schwartz, Woloshin,
Black & Welch, 1997). The frequently used 3-item numeracy scale is strongly related to an expanded and moredifficult 7-item numeracy scale, suggesting that both scales
loaded on a single construct (labelled “global numeracy”
by Lipkus, Samsa, and Rimer, 2001). However, we employed the shorter 3-item version for expediency, but it did
not achieve acceptable reliability (α = .47).

6.3

We used a 14-item ontological confusions scale (Lindeman & 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, likethe expression ‘Friends are the salt of life’?”. They werethen presented items such as “A rock lives for a long time”
and asked to rate how metaphorical/literal the statement ison the following scale: 1= fully metaphorical, 2 = more
metaphorical than literal, 3 = in between, 4 = more literalthan metaphorical, 5 = fully literal. Those who rate thestatements as more literal are considered more ontologicallyconfused. Participants were also given 3 metaphors (e.g.,“An anxious person is a prisoner to their anxiety”) and 3 literal statements (e.g., “Flowing water is a liquid”) as filler
items that did not factor into the mean ontological confusion score. The ontological confusions scale had acceptableinternal consistency (α = .74).

The Bullshit Receptivity (BSR) scale had good internal consistency (α = .82). A summary of descriptive statistics foreach 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”), allt’s > 5.7, all p’s < .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 lessthan 2. A slight majority of the sample’s mean ratings fellon or in-between 2 and 3 (54.5%, N = 152) and over a quarter of the sample (27.2%, N = 76) gave mean ratings higher
than 3 (“fairly profound”). These results indicate that ourparticipants largely failed to detect that the statements arebullshit.
Next we investigate the possible association between reflective thinking and bullshit receptivity. Pearson productmoment correlations can be found in Table 1. BSR wasstrongly negatively correlated with each cognitive measure
except for numeracy (which was nonetheless significant).
Furthermore, both ontological confusions and religious belief were positively correlated with bullshit receptivity.

Finally, participants completed an 8-item religious belief
questionnaire (Pennycook et al., 2014). Participants wereasked to rate their level of agreement/disagreement (1 –strongly disagree to 5 – strongly agree) with 8 commonly
held religious beliefs (afterlife, heaven, hell, miracles, angels, demons, soul, Satan). The scale had excellent internalconsistency (α = .94).

Procedure

Following a short demographic questionnaire, participants
completed the tasks in the following order: heuristics andbiases battery, Wordsum, numeracy, CRT2, CRT1, ontological confusion scale, bullshit receptivity, and religious belief
questionnaire.

7 Results

8 Study 2
In Study 1, at least some participants appeared to find meaning in a series of statements that contained a random collec-

Judgment and Decision Making, Vol. 10, No. 6, November 2015tion of vague buzzwords organized in a sentence with syntactic structure. This tendency was significantly related tocognitive variables of conceptual interest in expected ways.
In Study 2 we set out to replicate this pattern of results using real-world examples of bullshit. For this, we createdan 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 including self-report measures of analytic and intuitive thinking
disposition. Finally, we expanded our cognitive ability measures 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 female, M age =36, SDage = 11.4) were recruited from Amazon’s Mechanical Turk in return for pay. Only American residents werepermitted to sign up for the study. All participants reported
speaking fluent English. Given the novelty of the phenomenon, we chose 200 participants as an arbitrary target
sample size, as we determined this would provide adequate
power and stability of the correlations. These data were notanalyzed until the full sample was completed.
Eleven participants were removed because they responded affirmatively when asked if they responded randomly at any time during the study. In addition, 23 participants failed at least one of three attention check questions.
The instruction check questions included the one used inStudy 1 as well as the following question inserted into questionnaires at the middle and end of the survey: “I have been
to every country in the world” (all participants who selectedany option but “strongly disagree” were removed). However, as in Study 1, the results were similar when these participants were excluded and we therefore retained the fullsample.

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 selfregulating ecosystem of awareness”). These items can befound 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 selected statements should not be taken as representative ofChopra’s tweet history or body of work. Also, to reiter-

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ate, we focus on Chopra here merely because others haveclaimed 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 generator websites that we used. None of this is intended to
imply that every statement in Chopra’s tweet history is bullshit. Participants were given the same instructions as Study
1 and, therefore, we did not indicate the author of the statements.
Participants completed one cognitive task and one selfreport questionnaire intended to assess individual differences in analytic cognitive style. Participants were given theheuristics and biases battery (as in Study 1; α = .75) alongwith Pacini and Epstein’s (1999) Rational-Experiential Inventory. 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 impressions” (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), whichlead to better reliability for the full 9-item scale (α = .63).
We also added a short form of Raven’s Advanced Progressive Matrices (APM) that consists of 12 problems. The
APM are a widely used measure of fluid intelligence and theshort 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 religious 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 excluded. The scale consisted of 22 items sampled from 6 categories of supernatural belief (example items in parentheses): 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 Scotland exists”) and Precognition (“Astrology is a way to accurately predict the future”). The full scale had excellent
internal consistency (α = .96).
Participants also completed wealth distribution and political ideology measures. These measures were included aspart of separate investigations and will not be analyzed or
discussed further.

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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
1. BSR
2. H&B
3. NFC
4. FI
5. Num.
6. VI
7. APM
8. OC
9. RB
10. PB

9.3

2

3

4

6

7

8

9

10

(.96) −.36∗∗∗ −.08.32∗∗ −.12−.30∗∗ −.26∗∗.46∗∗∗ .25∗
.31∗∗−.34∗∗∗ (.75).08−.28∗∗.42∗∗∗ .43∗∗∗ .40∗∗∗ −.41∗∗∗ −.31∗∗ −.46∗∗∗−.13.20∗∗ (.93) −.32∗∗
.17
.24∗
.19
−.18
−.15
−.10
∗∗∗
∗∗∗
∗∗∗
∗∗∗
∗∗∗
.30
−.37
−.28
(.94) −.17
−.34
−.05
.24∗
.34
.37∗∗∗−.25∗∗.46∗∗∗ .22∗∗ −.27∗∗∗ (.63).34∗∗∗ .45∗∗∗ −.20∗ −.07
−.21∗
∗∗∗
∗∗∗
∗∗∗
∗∗∗
∗∗∗
∗∗
∗∗∗
−.30
.40
.27
−.31
.31
(.63)
.27
−.38
−.16
−.30∗∗−.27∗∗∗ .45∗∗∗ .24∗∗ −.14.46∗∗∗ .36∗∗∗ (.69) −.33∗∗ −.07
−.12
∗∗∗
∗∗∗
∗∗∗
∗∗∗
.45
−.41
−.29
.34
−.26∗∗ −.33∗∗∗ −.34∗∗∗ (.75)
.12
.34∗∗
.27∗∗∗ −.34∗∗∗ −.20∗∗.35∗∗∗ −.17∗ −.24∗∗ −.14.22∗∗ (.96).34∗∗.35∗∗∗ −.45∗∗∗ −.10.44∗∗∗ −.33∗∗∗ −.26∗∗ −.18∗.38∗∗∗ .44∗∗∗ (.96)

Procedure

In contrast to Study 1, participants evaluated the meaningless statements before completing the cognitive tasks. Moreover, the Chopra-Twitter items followed directly after themeaningless 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 confusions scale, followed by the religious and paranormal belief scales (in that order). The NFC and FI questionnaires
came at the very end of the study.

10

5

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., thosewith 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 summary of descriptive statistics for each item is reported inTable 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 verystrongly correlated (r = .88). Moreover, the pattern of correlations for the scales was identical (see supplementary materials, Table S3). We therefore combined all of the items forboth 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 heuristics and biases performance. Specifically, BSR was negatively correlated with performance on the heuristics and biases battery and positively correlated with Faith in Intuition.
The cognitive ability measures, including numeracy, werealso negatively correlated with BSR. Finally, BSR was positively correlated with ontological confusions, and both religious and paranormal belief. The pattern of results was very
similar when the correlations are restricted only to participants 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 reliablemeasure of bullshit receptivity that correlated with a varietyof conceptually related variables. It remains unclear, however, whether these associations are driven by a bias toward
accepting pseudo-profound bullshit as meaningful or a failure to detect the need for skepticism (or both) when skepticism is warranted (i.e., sensitivity, as distinct from bias,

Judgment and Decision Making, Vol. 10, No. 6, November 2015

in the sense of signal-detection theory). It may be that increased profundity ratings are associated with lower reflective thinking (for example), regardless of the presented content.
The goal of Study 3 was to test the possibility that somepeople may be particularly insensitive to pseudo-profoundbullshit, presumably because they are less capable of detecting conflict during reasoning. For this, we created ascale using ten motivational quotations that are conventionally considered to be profound (e.g., “A river cuts througha rock, not because of its power but its persistence”) in thatthey are written in plain language and do not contain thevague buzzwords that are characteristic of the statements
used in Studies 1 and 2. The difference between profundity ratings between legitimately meaningful quotations andpseudo-profound bullshit will serve as our measures of bullshit sensitivity. Secondarily, we also included mundanestatements 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 analytic thinking and profundity ratings for pseudo-profoundbullshit is due to bullshit detection in particular, analytic
thinking should not be associated with profundity ratings formundane statements.

12

Method12.1

Participants

A total of 125 participants (52 male, 73 female, M age = 36.4,
SDage = 13.3) were recruited from Amazon’s Mechanical
Turk in return for pay. Only American residents were permitted to sign up for the study. All participants reported
speaking fluent English. Given the strength (and accumulating cost) of the previous findings, 125 participants wasdeemed a sufficient sample. These data were not analyzed
until the full sample was completed.
Eleven participants were removed because they responded affirmatively when asked if they responded randomly at any time during the study. Fourteen participants
failed an attention check question but were retained, as inStudies 1 and 2.

12.2

Materials

We created four 10-item scales. For the BSR, we used theoriginal 10 items from Study 1 and the 10 Chopra-Twitter
items from Study 2. We created a scale with 10 statementsthat 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 aninternet search and used to form a second scale (e.g., “A wet
person does not fear the rain”; see Table S5 for full list). Par-

Bullshit receptivity

556

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 uniquerandom order for each participant. The statements were presented at the beginning of the study. Participants then completed 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,
t’s < 1.4, p’s > .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 combined the two sets of items into a single BSR scale, which
had excellent internal consistency (α = .96). The motivational quotation scale had acceptable internal consistency(α= .82) and the mundane statement scale was also reliable(α= .93). However, the distribution of profoundness ratingsfor each of the mundane statements was highly skewed (seeTable S4). Further inspection revealed that the vast majority of ratings (80.1%) for mundane statements were 1 (notat all profound) and many participants (N = 52, 46%) responded with 1 for every statement. Three standard deviations above the mean for 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 ratings for mundane statements that were statistical outliers.
Evidently, these participants found the ostensibly mundanestatements at least somewhat profound. This may reflect a
response bias toward excess profundity among some participants. Indeed, relative to the remainder of the sample, the22 outlying participants had higher profundity ratings for thepseudo-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 alsoscored lower on the heuristics and biases task, t(112) = 3.23,
SE = .13, p = .002. Key analyses below are reported withoutliers both retained and removed for the mundane statement scale. The mundane statement scale had low reliability (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 quotations (M = 3.05, SD = .69), participant-level: t(113) = 3.90,

Judgment and Decision Making, Vol. 10, No. 6, November 2015

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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

1. BSR
(.96)
.40∗∗
.26∗
.21
∗∗∗
2. Motivational quotations
.38
(.82)
.15
.14
3. Mundane statements a
.26∗∗
.17
(.93)
.
4. Mundane statements b
.19
.14
.
(.35)
∗∗∗
∗∗
5. Heuristics/biases
−.33
−.12
−.24
−.08
6. BS sensitivity (Var2–Var1) −.71∗∗∗ .38∗∗∗ −.13−.08

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 thanthe 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 performance (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 positively correlated with this measure (r = .23, p = .013), indicating an association between analytic thinking and the ability to spontaneously detect pseudo-profound bullshit. These
results were similar when the sample was restricted to thosewith no knowledge of Deepak Chopra (Table 3, top diagonal). 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 whenoutliers are removed), indicating a potential disposition toward 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). Thispattern of results is identical in the restricted sample. These5

6−.38∗∗ −.71∗∗∗
−.10
.36∗∗
−.28∗ −.15
−.13
−.10
(.61)
.31∗
∗
.23
.

results indicate that, at least for some participants, responsebias 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 specific to bullshit items. The lack of correlation between
heuristics and biases performance and profoundness ratings for motivational quotations, in particular, indicates that
more reflective participants are not merely more skeptical
toward all manner of profound-sounding statements. However, there was an unequal number of bullshit (N = 20) andmotivational (N = 10) items in Study 3. Moreover, it isunclear whether the inclusion of mundane statements interacted in some way with participants’ evaluation of the bullshit and motivational statements. Thus, in Study 4, we asked
participants to rate the relative profoundness of 20 randomlyintermixed statements (10 bullshit and 10 motivational).
In Study 3, we did not include any measures of epistemically suspect beliefs. Thus, in Study 4, participants completed the heuristics and biases battery, along with measuresof paranormal belief, conspiracist ideation, and endorsement of complementary and alternative medicine.

15

Method15.1

Participants

We recruited 242 participants (146 male, 107 female, M age= 33.9, SD age = 10.6) from Amazon’s Mechanical Turk inreturn for pay. Only American residents were permitted tosign up for the study. All participants reported speaking fluent 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

Twenty-three participants were removed because they responded affirmatively when asked if they responded randomly at any time during the study. Twelve participants
failed an attention check question but were retained as removing them had no effect on the pattern of results.

15.2

Materials

We used the BSR (10 items) from Study 1. We used thesame 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 paranormal belief scale (including religious belief items; α =.96) from Study 2. We measured conspiracy ideation using a 15-item general conspiracy beliefs scale (Brotherton,
French & Pickering, 2013). The scale included items suchas “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 the 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 complementary and alternative medicine scale, we asked participants to rate the degree to which they believe in the efficacy of 10 common types of alternative medicines (CAM;
Complementary and Alternative Medicine, e.g., homeopathy) on the following 5-point scale (Lindeman, 2011): 0)
Don’t know/cannot say [removed from analysis], 1) Do notbelieve at all, 2) Slightly believe, 3) Moderately believe, 4)Believe fully. An overall CAM score was created by summing the responses (α = .94).
Participants also completed a ten item personality scale(Gosling, Rentfrow & Swann, 2003) that indexes individual differences in the Big Five personality traits (extraversion, 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. Participants then completed the remainder of the tasks in thefollowing 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 withlower 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-Bullshit receptivity

558

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 motivational quotation scale was also reliable (α = .80). The mean
profoundness rating was higher for the motivational quotations (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 belief, conspiracist ideation, and belief in the efficacy of complementary and alternative medicine. However, the mean
profoundness ratings for the BSR and motivational quotations was strongly correlated (r = .43) and, in contrast to
Study 3, the motivational quotation scale was correlatedwith heuristics and biases performance (p = .035). The
mean profoundness rating for motivational quotations was
also positively correlated with conspiracist ideation, complementary and alternative medicine, and (marginally) paranormal belief (p = .088). Thus, as in Study 3, we computed
a “bullshit sensitivity” variable by subtracting the mean profundity ratings for the motivational quotations from the bullshit 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 wasalso no correlation between bullshit sensitivity and conspiracist ideation (r = –.03, p = .652) or complementary andalternative medicine (r = –.08, p = .218). In contrast, paranormal belief remained negatively correlated with bullshit
sensitivity (r = –.21, p = .002).
Unlike in Studies 2 and 3, the pattern of results was different when the analysis was restricted to those with no knowledge of Deepak Chopra. Namely, when the analysis was restricted, bullshit sensitivity was significantly positively correlated with heuristics and biases performance (r = .19, p= .032). Moreover, conspiracist ideation was marginallynegatively associated with bullshit sensitivity (r = –.16, p= .070). Paranormal belief remained negatively correlated(r = –.23, p = .009) and complementary and alternative remained uncorrelated (r = –.06, p = .497) with bullshit sensitivity. These results support the idea that the difference
between profundity ratings for genuine motivational quotations and pseudo-profound bullshit can be used as a measureof bullshit sensitivity. However, they also indicate that caution is required – at least when the 10-item scales are used
– as familiarity with Deepak Chopra may limit the usefulness of the scale. Chopra has a distinct style and it is possible that prior knowledge may have confounded our bullshit measure. For example, it may have helped some people
detect the bullshit. Conversely, among those who have a favorable 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 andalternative 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 theindividual differences in receptivity to pseudo-profoundbullshit. We gave people syntactically coherent sentencesthat consisted of random vague buzzwords and, across fourstudies, these statements were judged to be at least somewhat profound. This tendency was also evident when we
presented participants with similar real-world examples ofpseudo-profound bullshit. Most importantly, we have provided evidence that individuals vary in conceptually interpretable ways in their propensity to ascribe profundity tobullshit statements; a tendency we refer to as “bullshit receptivity”. Those more receptive to bullshit are less reflective, lower in cognitive ability (i.e., verbal and fluid intelligence, numeracy), are more prone to ontological confusions and conspiratorial ideation, are more likely to hold religious and paranormal beliefs, and are more likely to endorse complementary and alternative medicine. Finally, we
introduced a measure of pseudo-profound bullshit sensitivity by computing a difference score between profundity ratings for pseudo-profound bullshit and legitimately meaningful motivational quotations. This measure was related toanalytic cognitive style and paranormal skepticism. However, there was no association between bullshit sensitivity
and either conspiratorial ideation or acceptance of complementary and alternative medicine (CAM). Nonetheless, ourfindings are consistent with the idea that the tendency to ratevague, meaningless statements as profound (i.e., pseudoprofound bullshit receptivity) is a legitimate psychologicalphenomenon that is consistently related to at least some variables 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 thismechanism is not specific to bullshit, it may at least partly
explain why our pseudo-profound bullshit measure was so
consistently positively correlated with epistemically suspect
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 enjoy at least some sort of music”) as at least somewhat profound. Our results suggest that this tendency – which resembles a general gullibility factor – is a component of pseudoprofound bullshit receptivity. There is, of course, a great
deal of research on this sort of mechanism. As a prominent 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 that consisted of 13 statements and asked them to rate
both the accuracy of the statements and the overall efficacyof the DIB. Unbeknownst to the students, Forer had actually
given every student the same personality sketch that consisted entirely of vague, generalized statements taken froma newsstand astrology book (e.g., “You have a great need forother people to like and admire you.”). Although some people 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 goodor perfect instrument for personality measurement” (Forer,
1949, p. 121). Meehl (1956) first referred to this as theBarnum effect, after the notorious hoaxer (bullshitter) P. T.
Barnum.2
2 In an amusing irony, P. T. Barnum is often erroneously attributed thephrase “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

As a secondary point, it is worthwhile to distinguish
uncritical or reflexive open-mindedness from thoughtfulor reflective open-mindedness. Whereas reflexive openmindedness results from an intuitive mindset that is very
accepting of information without very much processing, reflective 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 criticalanalysis and reflection. Thus, the former should cause one
to be more receptive of bullshit whereas the latter, much likeanalytic cognitive style, should guard against it.
The foregoing highlights what appears to be a strong general susceptibility to bullshit, but what cognitive mechanisms inoculate against bullshit? Drawing on recent dualprocess 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 bullshit. Our results modestly support this claim. Namely, we
created a bullshit “sensitivity” measure by subtracting profundity ratings for pseudo-profound bullshit from ratings for
legitimate motivational quotations. Increased bullshit sensitivity was associated with better performance on measuresof analytic thinking. This is consistent with Sagan’s (1996)
famous claim that critical thinking facilitates “baloney detection”.
Further, bullshit sensitivity was associated with lower
paranormal belief, but not conspiratorial ideation or acceptance 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 supernatural beliefs are a unique subclass because they entail
a conflict between some immaterial claim and (presumably universal) intuitive folk concepts (Atran & Norenzayan, 2004). For example, the belief in ghosts conflicts withfolk-mechanics – that is intuitive belief that objects cannot pass through solid objects (Boyer, 1994). Pennycook
et al. (2014) found that degree of belief in supernatural religious claims (e.g., angels, demons) is negatively correlatedwith conflict detection effects in a reasoning paradigm. This
result suggests that the particularly robust association between pseudo-profound bullshit receptivity and supernatural beliefs may be because both response bias and conflict
detection (sensitivity) support both factors. Further researchis needed to test this claim.

17.2

Future directions

The focus of this work was on investigating individual differences in the tendency to accept bullshit statements, andour 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 actual meanings of the presented words and their associations

Bullshit receptivity

560

would seem an a priori defense against accepting bullshit
at face value (i.e., to avoid an excessively open-minded response 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 knowledgeof word meaning (via verbal intelligence) may assist in
critical analysis. An understanding of more precisely nuanced meanings of words may reveal inconsistencies, incongruities, 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 inthis case it remains unclear precisely what features of bullshit 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 meaninglessstatements 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 goalof conveying some meaning. Indeed, the vagueness of thestatements may imply that the intended meaning is so important or profound that it cannot be stated plainly (Sperber, 2010). In the current work, we presented the participants with meaningless statements without cueing them tothe possibility that they 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 thestatement is the key force that may guard against bullshit
acceptance. For example, poems attributed to prestigious
sources are evaluated more positively (Bar-Hillel, Maharshak, Moshinsky & Nofech, 2012). Interpretation is difficultand 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 elucidate contextual factors that interact with individual differences in the reception and detection of bullshit. As noted byphilosophers studying the topic, the bullshitter oft has theintention of implying greater meaning than is literally contained in the message, though the nature of the intent canvary. For example, the literary critic Empson (1947) describes the use of ambiguity in literature, including a typeof intentional ambiguity used by poets in which a passage“says nothing, by tautology, by contradiction, or by irrelevant statements; so that the reader is forced to invent statements of his own . . . ” (p. 176). The employment and reception of such literary devices in the context of a broader
meaningful work seems related to but dissociable from isolated 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

variable as it converges with and diverges from other related
uses of vagueness. We anticipate that there are many variations of vague, ambiguous, or otherwise unclear statementsthat 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 session wherein “people try out various thoughts and attitudes
in order to see how it feels to hear themselves saying suchthings and in order to discover how others respond, without it being assumed that they are committed to what theysay: It is understood by everyone in a bull session that thestatements people make do not necessarily reveal what they
really believe or how they really feel” (p. 9). This qualifies as bullshit under Frankfurt’s broad definition because
the content is being communicated absent a concern for thetruth. Nonetheless, the character of conversational bullshit
is likely quite different from pseudo-profound bullshit, andby extension the reception and detection of it may be determined by different psychological factors. It is important
for researchers interested in the psychology of bullshit to beclear about the type of bullshit that they are investigating.
Our bullshit receptivity scale was quite successful overall,but future work is needed to refine and improve it. In particular, the bullshit sensitivity measure would be improved
if there was a more direct mapping between the pseudoprofound bullshit and the genuinely meaningful control
items. Naturally, more items would improve both scales.
Finally, knowledge of Deepak Chopra may subtly confoundexperiments using our bullshit sensitivity scale (or, at least,slightly restrict the effect size).
Finally, we have focused on an individual differences approach given that our primary goal was to demonstrate thatbullshit receptivity is a consequential thing that can be reliably measured. This preliminary work is required for experiments to be meaningful. Future work should focus on the
dual goals of further refining our measure of bullshit receptivity and experimentally modulating profundity ratings forpseudo-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 containing a random collection of buzzwords were very strongly
correlated with a selective collection of actual “Tweets”
from Deepak Chopra’s “Twitter” feed (r’s = .88–89). At

Bullshit receptivity

561

the time of this writing, Chopra has over 2.5 million followers on “Twitter” and has written more than twenty New YorkTimes bestsellers. Bullshit is not only common; it is popular.3 Chopra is, of course, just one example among many.
Using vagueness or ambiguity to mask a lack of meaningfulness is surely common in political rhetoric, marketing,and even academia (Sokal, 2008). Indeed, as intimated byFrankfurt (2005), bullshitting is something that we likely all
engage in to some degree (p. 1): “One of the most salientfeatures of our culture is that there is so much bullshit. Everyone knows this. Each of us contributes his share.” One
benefit of gaining a better understanding of how we rejectother’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 understanding of the underlying cognitive and social mechanisms that
determine if and when bullshit is detected. Our bullshit receptivity scale was associated with a relatively wide rangeof important psychological factors. This is a valuable firststep toward gaining a better understanding of the psychology of bullshit. The development of interventions and strategies that help individuals guard against bullshit is an important additional goal that requires considerable attention from
cognitive and social psychologists. That people vary in their
receptivity toward bullshit is perhaps less surprising than thefact that psychological scientists have heretofore neglected
this issue. Accordingly, although this manuscript may not
be truly profound, it is indeed meaningful.

20

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