Differential virtue discounting: Public generosity is seen as more selfish than public impartiality
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Differential virtue discounting:
Public generosity is seen as more selfish than public impartiality
Gordon T. Kraft-Todd*a, Max Kleiman-Weinerb, Liane Younga
a
Department of Psychology, McGuinn 300, 140 Commonwealth Ave, Boston College, Chestnut Hill, MA 02467 ;
b
Department of Psychology, Harvard University, Cambridge, MA 02138
*Corresponding author: gordon.kraft-todd@bc.edu
Abstract
There is a paradox in our desire to be seen as virtuous. If we do not overtly display our virtues,
others will not be able to see them; yet, if we do overtly display our virtues, others may think that
we do so only for social credit. Here, we investigate how virtue signaling works across two
distinct virtues—generosity and impartiality—in eleven online experiments (total N=4,586). We
demonstrate the novel phenomenon of differential virtue discounting, revealing that participants
perceive actors who demonstrate virtue in public to be less virtuous than actors who demonstrate
virtue in private, and, critically, that this effect is greater for generosity than impartiality. Further,
we provide evidence for the mechanism underlying these judgments, showing that they are
mediated by perceived selfish motivations. We discuss how these findings and our novel
terminology can shed light on open questions in the social perception of reputation and
motivation.
Keywords: virtue signaling, virtue discounting, reputation, generosity, impartiality, virtueIntroduction
Virtue signaling—i.e. conspicuous, public displays of admirable moral behavior—has
only recently entered the cultural lexicon (Bartholomew, 2015). The term was coined—and is
often used—to pejoratively describe a class of behaviors (e.g. "outrage": Crockett, 2017; Spring,
Cameron, & Cikara, 2018) enabled by social media where actors invest minimal effort to widely
broadcast their support for a cause. Though some defend such behavior by claiming that it can
raise awareness of a cause, many remain skeptical because it enables actors to reap reputational
rewards without meaningfully contributing to change. Such skeptics engage in what we call
virtue discounting, i.e. the devaluing of virtuous behavior to the extent that ulterior, selfish (e.g.
reputational) motivations can be inferred for actors’ behavior.
The phenomena of virtue signaling and virtue discounting predate social media. Various
spiritual and philosophical traditions have debated the merits of public displays of virtue (as
discussed in De Freitas, DeScioli, Thomas, & Pinker, 2019). Previous research demonstrating
these phenomena generally treat virtue as a single dimension: generosity (e.g. Barclay & Willer,
2007). Yet, in treatments of virtue both ancient (e.g. Aristotle’s virtue ethics) and modern
(Graham et al., 2011), virtue is not considered a unitary construct, but a collection of
conceptually distinct morally admirable traits. We depart from previous work by asking: are
some virtues more subject to skepticism than others? Here, we present the first evidence of
differential virtue discounting: different virtues are discounted to a different degree. Specifically,
we show that participants engage in greater discounting of generosity than of impartiality.
Why do people virtue signal? Individuals demonstrate concern for their reputations, i.e.
how they are perceived by others (Emler, 1990). A virtuous reputation, specifically, can grant
individuals higher social status (Bai, 2017), which can in turn lead to greater wealth and well-
being (Henrich & Gil-White, 2001). We define virtue as a stable trait demonstrating other-
regarding preferences through prosocial (i.e. other-benefiting) behavior. There is ample evidence
that when individuals’ behavior is observable to others, e.g. done in public, individuals are more
likely to behave prosocially (in the lab, e.g. Milinski, Semmann, & Krambeck, 2002; and in the
field, e.g. Yoeli, Hoffman, Rand, & Nowak, 2013). People do not merely react to being
observed, but also actively engage in managing others’ impressions of them (Jones & Pittman,
1982). It is therefore unsurprising that people attempt to signal their virtue (e.g. Barclay &
Willer, 2007; Jordan, Hoffman, Bloom, & Rand, 2016). It is worth noting, however, that most
previous demonstrations of virtue signaling have focused on a single virtue—e.g. generosity
(Barclay & Willer, 2007), trustworthiness (Jordan et al., 2016), or impartiality (Kleiman-Weiner,
Shaw, & Tenenbaum, 2017)—while little research exists comparing virtue signaling across
virtues.
Why (and how) do observers sometimes discount actors’ virtuous behavior? Given the
benefits of a virtuous reputation, people may be motivated to exaggerate or falsely signal their
virtue. Our distaste for such behavior may explain our condemnation of moral hypocrites, who
espouse moral virtues in public but fail to act on them in private (Jordan, Sommers, Bloom, &
Rand, 2017). Virtue discounting relies on the human capacity for theory of mind, i.e. the ability
to reason about others’ mental states (Saxe, Carey, & Kanwisher, 2004). Of particular relevance
here, this enables us to consider actors’ motivations, which in turn affects our moral judgments
(Young, Cushman, Hauser, & Saxe, 2007). When observers infer selfish ulterior motives for
prosocial behavior, they perceive actors less favorably (e.g. Newman & Cain, 2014). One cue to
such inference is when observers know that actors know that they are being observed: observerscan then infer that actors are motivated by the selfish desire to achieve a good reputation, rather
than by their virtue (Barclay & Willer, 2007). Here, we propose to replicate these findings,
showing that observers will discount public displays of virtue (H1, see Methods). Expanding on
this prior work, we explore perceptions of selfish motivations by decomposing the concept into
“negative” self-oriented motivations (e.g. for reputational benefit) and “positive” moral motives
(e.g. to signal a desired social norm). We expect these to be negatively correlated (see Methods
and Table 3).
We further expand on previous research by exploring virtue signaling and virtue
discounting across two virtues that have been conceptually distinguished (Shaw, 2013):
generosity, which we define as trait willingness to confer benefits to others at cost to oneself; and
impartiality which we define as trait desire to treat others equally and without bias. These virtues
have also been empirically distinguished (e.g. Shaw, Choshen-Hillel, & Caruso, 2018). As
discussed above, there is ample evidence that people signal generosity (Barclay & Willer, 2007),
but there is also emerging evidence that people signal impartiality (Kleiman-Weiner et al., 2017),
and that this emerges early in development (Shaw & Olson, 2012).
We believe that generosity and impartiality might be further distinguished by the extent
to which they are discounted. Our tentative directional hypothesis is motivated by the intuition
that there might be greater selfish motivations for being perceived as generous compared to
impartial. Despite the growing body of work demonstrating the reputational benefits for being
seen as impartial (for a review, see Shaw, 2016), there is a large literature demonstrating the
reputational benefits for being seen as generous (for a review, see Barclay, 2013). It could be the
case that the latter outweigh the former: consider, for example, an observer’s desire to interact
with an actor who is seen as an exemplar of each virtue: while the observer could at most expect
fair treatment from an extremely impartial actor, they might expect special treatment from an
extremely generous actor. Thus, if an actor is perceived as generous (even if they are not), this
might make them more attractive than if they are perceived as impartial.
In sum: people stand to benefit from having virtuous reputations, and are therefore
motivated to signal (and perhaps exaggerate) their virtue. Because virtue is not monolithic, but is
comprised of conceptually distinct virtues, there may be heterogeneity in the benefit of having a
reputation for different virtues. Due to the potential for false signaling, observers are likely to be
skeptical of virtue signals to the extent that they infer ulterior selfish motivations for actors’
behavior. Finally, the extent that observers discount different virtues may depend on how selfish
they think actors’ motivations are for publicly signaling these virtues.
General Methods
All online experiments were conducted using Qualtrics survey software, a convenience
sample of participants were recruited using the crowdsourcing tool Amazon Mechanical Turk
(Arechar, Kraft-Todd, & Rand, 2017). Data analysis for all studies was completed using STATA
13, and informed consent was obtained from all participants. We excluded duplicate Amazon
worker IDs and IP addresses to prevent analyzing multiple observations per participant. The pre-
study procedure was to ask participants to provide their mTurk IDs and transcribe a sentence of
difficult-to-read handwritten text (the latter to prevent bot participation and discourage low-effort
workers, a commonly used method on this platform; e.g. Kraft-Todd & Rand, 2019). In total, we
requested N=4,000 participants (N=100/condition), but because some participants may havecompleted the survey but failed to enter their completion code to mTurk (thus allowing others to
complete the survey), the final sample was N=4,012 participants (47.0% female, average
age=35.8 years) across all nine experiments presented in the primary analyses. Participants
completed the study in m=3.8 minutes and were paid $1 for their participation. Experiments 8
and 9 were respectively preregistered at http://aspredicted.org/blind.php?x=zw4ee5 and
http://aspredicted.org/blind.php?x=s6v2bx. All data and code are publicly available at: (non-
blinded link to be added after review).
Though elements of the survey design varied across experiments (see Table 1), all
experiments involved hypothetical vignettes in which participants were randomly assigned to
one of four between-subjects conditions in a 2 (virtue: generosity vs impartiality) x 2
(observability: public vs private) design (except for Experiments 7 and 8, which included an
additional “baseline” observability condition not analyzed here; for an overview of the design of
all studies, see Table 1; for complete experimental instructions, see SI Section 7). On the first
screen of the experiment, which contained the stimuli, we asked participants to imagine that they
know someone whom we briefly described. We provided a name for the friend (henceforth: “the
actor”), which varied by condition, and was selected from a list of common female names in the
US (because we were not interested in the effect of actor gender on the dependent variables, we
used all female names). In all experiments, we provided a dictionary definition of the virtue
(which varied by condition) adapted from Merriam-Webster.com (e.g. “Generosity usually
means giving an abundance of one's money or time”; “Impartiality usually means treating
everyone equally and fairly, without bias”).
Table 1. Overview of experiments
Sample Data used
Analyzed Pre-
Experiment Design features size Conditions in analysis
variables registered?
(all ~100
(all randomized)
/condition)
no.
1 No example 399
2 behaviors, 398
3 motive stipulated 399
Experiment- Moral goodnes
4 generated behaviors, 397 1
and trait ratings 2 (virtue: impartiality v
motive stipulated
generosity)
Experiment-
x 2 (observability:
5 generated behaviors, 400
public v private)
motive not stipulated
No
6 406
Moral goodnes,
trait ratings,
1st-party benefit, 2 (virtue: impartiality v
Participant-generated 3rd-party benefit, generosity)
7 beahviors, [motivations:] 612 1,2
x 3 (observability:
motive not stipulated reputation, public v private v
authentic, baseline)
8 norm-signaling, 599
moral 2 (virtue: impartiality v
generosity) Yes
9 402
x 2 (observability:
public v private)Important differences in survey design across experiments were the operationalization of
observability (public vs private; see Table 2, Columns 1-2) and the example behaviors for each
virtue (see Table 2, Columns 3-4). Regarding the former, in Experiments 1-4, we explicitly
stipulated the actors’ motivation for their behavior. We believe this is a stronger manipulation of
observability than not doing so because it explains away other motivations that the actor might
have had to display this virtue in public vs. in private and does not require participants to infer
the actors’ (ambiguous) motivation for themselves. In Experiments 4-9, we provided examples of
generous and impartial virtuous behaviors to further clarify the concepts (see Table 2, Columns
3-4). In Experiments 4-6, these examples were experimenter-generated, whereas in Experiments
7-9, these examples were participant-generated (see Supplemental Study 1, SI Section 1) and
pre-tested by an independent sample (see Supplemental Study 2, SI Section 2).
Table 2. Elements of the stimuli which varied across experiments.
Virtue
Observability
(example behaviors)
Experiment Private Public Generosity Impartiality
1
Though she is
2 (none) (none)
[generous/impartial]
3 She is especially
when she is with
[generous/impartial]
others, she is - Making sure everyone at a
when others are
especially social gathering receives the
watching her act since
[generous/impartial] same amount of food (e.g. when
she knows that her
when no one is four people share a large pizza
4 reputation for being - Volunteering at a homeless
watching since she with eight slices, ensuring
[generous/impartial] shelter
knows that acting in everyone gets two)
will improve. - Donating money to charities
this way is consistent - Dividing work evenly among all
with her values. like Doctors without Borders
participants in a group project
(one of their functions is to
(i.e. not giving your friend less
provide relief to victims of natural
work because you like them)
disasters)
- Making auditions or job
Though she is - Donating blood during a blood
applications blind (i.e. evaluators
[generous/impartial] drive (e.g. to the American Red
She is especially can't see applicants' faces) so
5 when she is with Cross)
[generous/impartial] that subtle, unconscious biases
others, she is even against particular genders or
when others are
[generous/impartial] ethnicities don't enter into the
watching her act.
when no one is decision-making process
watching.
6
- gave her children equal
- bought a friend an expensive
7 She did these things allowances
She did these things gift
in private; therefore, - conducted a blind audition
in public; therefore, - gave a waiter a large tip
8 other people did not - drew names from a hat for a
other people knew that - stayed late to help a coworker
know that she did project at work
she did them.
9 them.
Following the stimuli, in all experiments, we presented participants with the two primary
dependent measures (in randomized order): moral goodness (“How morally good is [your
friend]?” measured with a 100-point unmarked slider scale with anchors at 0 “extremely morally
bad”; 50 “neither morally bad nor morally good”; and 100 “extremely morally good”), and trait
ratings (“How [generous/impartial] is [your friend]?” measured with a 100-point unmarked
slider scale with anchors at 0 “not at all” and 100 “very much”). Secondary dependent measures
varied by experiment (see SI Section 7 for more details), and we presented these, as well as theprimary dependent measures in randomized order. This was true in all experiments except
Experiments 2 and 3, where we presented the primary dependent measures in randomized order
first, and then we presented the secondary measures in randomized order. All six secondary
dependent measures we analyze here appeared in Experiments 6-9, and these measured
participants’ perceptions of the actor’s motivation. Two assessed the benefit participants
perceived to various parties relative to the actor: 1st-party benefit (“How much do you think Jen
will personally benefit from behaving this way?”); and 3rd-pary benefit (“How much do you
think another person would benefit from interacting with Jen?”). Four assessed participants’
perceived motivations for the actor’s behaviors (“How much do you think Jen is motivated to act
[generously/impartially]…”): reputational (“…because she is trying to make others think she is
[generous/impartial]?”); authentic (“…because she wants to be [generous/impartial]?”); norm-
signaling (“…because she wants others to be [generous/impartial], and she is trying to lead by
example?”); and moral (“…because she thinks it is the right thing to do?”). All six secondary
dependent measures were answered on 100-point unmarked slider scales with anchors at 0 “not
at all” and 100 “very much.” Following secondary dependent measures, we presented (in
randomized order) participants with basic demographic questions (gender, age, race, income,
education, and political affiliation; see SI Section 7 for more details).
We present two sets of analyses across these experiments in the following sections
grouped by the hypotheses they test. In Analysis 1, we test for evidence of:
H1 (Virtue discounting hypothesis): Participants will discount ratings of an actor’s
virtue when the actor behaves virtuously in public compared to in private.
This logic motivates our novel differential discounting hypothesis:
H2 (Differential discounting hypothesis): Participants will engage in greater virtue
discounting of an actor when their behavior demonstrates generosity compared to
impartiality.
In Analysis 2, we test for the proposed mechanisms for these effects, respectively,
H3 (Multiple mediation hypothesis): Participants’ virtue discounting will be explained
by their attributing selfish motivations to actors.
H4 (Multiple moderated mediation hypothesis): Participants’ greater virtue
discounting of an actor demonstrating behavior that is generous, compared to impartial,
will be explained by their attribution of more selfish motivations.
For conciseness, in the main text we report effects only for the trait ratings primary dependent
measure, though qualitatively similar results are obtained for effects for the moral goodness
primary dependent measure (see SI Section 3 for more details).
For our preregistered experiments (8 and 9), we conduct posthoc power analyses using
G*Power3 software (Faul, Erdfelder, Lang, & Buchner, 2007). First, using only the experiments
with the same manipulations (experiments 6 and 7), testing for a 2x2 interaction with an effect
size of d=.21 (the interaction effect size we find across these two experiments), and an alpha of
.05, results showed that a total sample size of 252 participants with 4 equally sized groups would
be powered at .80. Next, using all previous experiments, testing for a 2x2 interaction with aneffect size of d=.31 (the interaction effect size we find across all previous experiments), and an
alpha of .05, results showed that a total sample size of 118 participants with 4 equally sized
groups would be powered at .80. Thus, the sample size of all experiments (400) provided
adequate power to detect our effect of interest.
Analysis 1. Generosity and impartiality exhibit differential virtue discounting
The purpose of Analysis 1 is to conceptually replicate previous observations of virtue
discounting and investigate the novel phenomenon of differential virtue discounting. We conduct
a multivariate regression analysis to test the virtue discounting hypothesis (H1): i.e. whether
public displays of virtue (collapsed across generosity and impartiality) are perceived as
displaying the virtue less than private displays of virtue, as well as the differential discounting
hypothesis (H2): i.e. whether the difference between perceptions of public and private displays
of virtue is greater for generosity than impartiality.
Methods
We use data from all 9 online experiments (not including baseline observability
conditions; total N=3,597; 46.6% female, average age=35.9 years). We first use a three-way
MANOVA to test for an interaction of our experimental manipulations (virtue and observability)
and study on our primary dependent measures (moral goodness and trait ratings). We do not
observe a significant three-way interaction (Wilks’ lamda=.99, F(16,7112)=1.50, p=.090), so we
use the combined data in further analyses and include experiment as a covariate, using contrasts
on predicted marginal means to obtain estimates of effect size. We observe that moral goodness
and trait ratings are strongly correlated (r=.68, pgenerosity are rated as demonstrating the virtue significantly less than public displays of impartiality (Scheffe’s t=-4.44, p
Methods
For Analysis 2, we combine all data from experiments in which we administered the
complete battery of secondary dependent measures (Experiments 6-9). Analysis 2 therefore
included 1,606 participants (47.4% female, average age=35.7 years). We first investigate the
pairwise correlations among the secondary dependent measures (see Table 3). We observe that
they are moderately correlated (average r=.35, each correlation pFig 2. Conceptual diagram of structural equation models used to test the multiple moderated
mediation hypothesis (H4). Note that the conceptual diagram of the structural equation model used to
test the multiple mediation hypothesis (H3) would look identical but without the “virtue” box and connected
arrows (because this analysis is collapsed across virtue).
Results
The first structural equation model tests the multiple mediation hypothesis (H3): virtue
discounting will be explained by perceived selfish motivations (see Figure 3). We first describe
correlations in this model, and then we investigate indirect, total, and direct effects in the
mediation. Beginning with estimates of model fit, we observe that the model accounts for 57.2%
of the variance in trait ratings.
Fig 3. Virtue discounting is explained by perceived selfish motivations (with more variance
explained by lower perceived moral motivations than higher perceived self-oriented motivations).
The first set of arrows left-to-right represents strength of association of each of the six secondary
dependent measures with observability, and the second set of arrows left-to-right represents strength of
association of trait ratings with each of the six secondary dependent measures. “Self-oriented”
motivations are displayed in purple, and “moral” motivations are displayed in orange. Line thickness
shows correlation strength among variables in the model collapsed across virtues (see Table 4 for more
information). Significant correlations are represented by solid lines, and non-significant correlations are
represented by dashed lines. Direction of correlation indicated by “+” for positive and “-” for negative.Investigating associations of the observability manipulation with the secondary
dependent measures (see Table 4), we observe that public displays of virtue are significantly
associated with all secondary dependent measures (reputational, moral, and authentic motivation,
1st- and 3rd-party benefit), except norm-signaling (see Column 1). Turning to the association of
trait ratings with the proposed mediators, we observe that trait ratings are significantly associated
with all secondary dependent measures (see Column 2). Consistent with H3, we observe that
perceived motivations are affected by public display, and trait ratings are affected by motivations
in the hypothesized directions: self-oriented motivations are positively associated with public
display (see Rows 1-2, Column 1) and negatively associated with trait ratings (see Rows 1-2,
Column 2), while moral motivations are negatively associated with public display (see Rows 3-6,
Column 1) and positively associated with trait ratings (see Rows 3-6, Column 2). Indirect effects
of public display on trait ratings through each secondary dependent measure (see Column 3)
represent the product of the two associations displayed in Columns 1 and 2.
Table 4. Shown are correlations (Columns 1 and 2) in structural equation model testing H3 as well as
indirect effects (Column 3; significant beta values in bold). “Self-oriented” motivations are displayed in
purple, and “moral” motivations are displayed in orange.
Observability -> Motivation Motivation -> Trait ratings Indirect effect
b =.85 b =-.07 b =-.06
Reputation 95% CI [.76, .93] 95% CI [-.11, -.03] 95% CI [-.13, .02]
pFig 4. Virtue discounting of both generosity and impartiality is explained by perceived selfish
motivations (with more variance explained for each by lower perceived moral motivations than
higher perceived self-oriented motivations). Stronger motivational inferences are made for
generosity compared to impartiality. For generosity (a) and impartiality (b), the first set of arrows left-
to-right represents strength of association of each of the six secondary dependent measures with the
interaction of observability and virtue, and the second set of arrows left-to-right represents strength of
association of trait ratings with the interaction of virtue and each of the six secondary dependent
measures. “Self-oriented” motivations are displayed in purple, and “moral” motivations are displayed in
orange. Line thickness shows correlation strength among variables in the model collapsed across virtues
(see Table 4 for more information). Significant correlations are represented by solid lines, and non-
significant correlations are represented by dashed lines. Direction of correlation indicated by “+” for
positive and “-” for negative.
First, we detail results explaining trait ratings of generosity (see Figure 5a). Beginning
with estimates of model fit, we observe that the model accounts for 61.1% of the variance in trait
ratings of generosity. Next, we investigate associations of secondary dependent measures with
the observability manipulation (see Table 5): public generosity is significantly associated with all
secondary dependent measures (reputational, moral, and authentic motivation, 1st- and 3rd-party
benefit), except norm-signaling (see Column 1). We then turn to the association of trait ratings of
generosity with the proposed mediators: trait ratings are significantly associated with all
secondary dependent measures except 1st-party benefit (see Column 3). Consistent with H3, and
replicating the result from the first structural equation model, motivations are affected by public
display, and trait ratings are affected by motivations in the hypothesized directions: self-oriented
motivations are positively associated with public display (see Rows 1-2, Column 1) and
negatively associated with trait ratings (see Rows 1-2, Column 1), while moral motivations are
negatively associated with public display (see Rows 3-6, Column 1) and positively associated
with trait ratings (see Rows 3-6, Column 1). The total effect of observability on trait ratings of
generosity is significant (b=-.74, 95% CI [-.87, -.62], pTable 5. Correlations in structural equation model testing H4 (significant beta values in bold).
Virtue x Observability -> Motivation Virtue x Motivation -> Trait ratings Indirect effect
Generosity Impartiality Generosity Impartiality Generosity Impartiality
b =1.03 b =.66 b =-.10 b =-.03 b =-.10 b =-.02
Reputation 95% CI [.90, 1.15] 95% CI [.54, .79] 95% CI [-.17, -.04] 95% CI [-.09, .02] 95% CI [-.23, .02] 95% CI [-.10, .06]
pdesire for 3rd-party benefit explain virtue discounting for generosity to a greater extent than
impartiality (see Table 5, Columns 5-6). Finally, while neither effect was itself significant, we
note that participants perceive less motivation for norm-signaling for public compared to private
displays of generosity (consistent with other moral motivations), while they perceive greater
motivation for norm-signaling when reading about public compared to private displays of
impartiality, and these effects are significantly different from each other.
Discussion
Here we provide evidence for the novel phenomenon of differential virtue discounting:
participants devalued the virtue of actors who engaged in public (versus private) acts of
generosity to a greater extent than they devalued the virtue of actors who engaged in public
(versus private) acts of impartiality. These results build on previous findings that observers
discount signals of virtue—in particular, generosity—when observers: 1) know that actors know
that they’re being observed (Barclay & Willer, 2007); and 2) infer ulterior, selfish motives for
actors’ behavior (e.g. Newman & Cain, 2014). These results also build on previous findings
distinguishing the virtues of generosity and impartiality (e.g. Shaw et al., 2018). We provide
evidence that discounting both virtues can be explained by observers’ inferring more selfish
motivations for actors who engage in public (versus private) acts of virtue. These findings have
implications for disparate research programs unified by the concept of virtue signaling and
suggests fruitful avenues for future research on ultimate mechanisms of reputation as well as the
relationship between person perception and moral judgment.
First, we introduce precise terminology that may help to conceptually link findings on the
general phenomenon of conspicuous, public displays of virtue. Virtue signaling is a term coined
recently in the popular press (Bartholomew, 2015); yet, there are few examples of its use in
academic literature (e.g. Grubbs, Warmke, Tosi, James, & Campbell, 2019). Virtue signaling
encompasses an array of findings, including outrage expressed online (Crockett, 2017; Spring et
al., 2018) as well as the application of costly signaling theory to prosocial behavior and
cooperation (e.g. Barclay & Willer, 2007; Jordan et al., 2016). We also introduce a new term,
virtue discounting, to describe people’s tendency to devalue signals of virtue when actors’ selfish
motives can be inferred, uniting previously cited work (e.g. Newman & Cain, 2014) with
research on self-signaling: e.g. exploring the phenomena of bragging (Berman, Levine, Barasch,
& Small, 2014) and humblebragging (Sezer, Gino, & Norton, 2018). Critically, we also provide
evidence for and introduce the novel concept of differential virtue discounting, showing
heterogeneity in virtue discounting across two fundamental virtues, pointing to interesting future
work on virtue discounting across other conceptually distinct virtues (e.g. loyalty, authority, and
purity; Graham et al., 2011).
Second, the evidence we provide for differential virtue discounting (H2) provides a clear
avenue for future research employing evolutionary theoretical approaches to reputation to
illuminate the nature of the selfish benefit observers infer. The predominant account of human
reputation is provided by the theory of indirect reciprocity (Nowak & Sigmund, 1998): we gain a
good reputation by following social norms and cooperating with others who do the same
(Ohtsuki & Iwasa, 2006). If observers infer greater selfish motivations for actors’ behavior when
it signals compliance with social norms, then a stronger social norm for being generous versus
impartial may account for our results. Alternatively, on the theory of partner choice (Barclay,2013; Noë & Hammerstein, 1994), individuals compete to display desirable traits so they are
chosen as interaction partners for potentially mutually beneficial cooperative interactions. If
observers infer greater selfish motivations for actors’ behavior when it signals more attractive
traits, then generosity’s being more attractive than impartiality to potential interaction partners
may account for our results. It would not be surprising if the strength of social norms and the
attractiveness of interaction partner traits were correlated, though there might also be interesting
moderators of this association, such as relational obligations (McManus, Kleiman-Weiner, &
Young, 2020). There might be interesting cases where These explanations are neither mutually
exclusive nor exhaustive, and future work may dissociate their contributions to differential virtue
discounting across generosity and impartiality, and other virtues (Graham et al., 2011).
Finally, our mediation results have interesting implications for research at the intersection
of moral judgment and person perception (e.g. Kim, Park, & Young, 2020; Tamir & Thornton,
2018). We provide evidence for the mechanism of (differential) virtue discounting: observers
devalue signals of virtue when they infer actors’ selfish motives. Yet, examining the
motivational attributions responsible for this mediation (considering our first model supporting
H3, though similar results hold for H4), we note the perhaps surprising result that this effect is
explained mostly by a decrease in perceived moral motivations (totaling indirect effects by
factor score, 76.8%) rather than an increase in perceived self-oriented motivations (totaling
indirect effects by factor score, 18.9%). In other words, virtue discounting is the effect of a
perceived lack of relevant moral motivation rather than an abundance of self-orientation, per se.
Our selection of items in our motivational scale was not exhaustive (Braver et al., 2014), so
future work accommodating other motivational inferences may yield additional insight into the
cognitive process underlying (differential) virtue discounting.
We all want to be seen as virtuous. The paradox of this desire is that the best way to be
seen as virtuous is to be virtuous in public; yet, if we are virtuous in public—as we have shown
here—observers may believe our behavior to be selfishly motivated. Or, as Oscar Wilde put it:
“The nicest feeling in the world is to do a good deed anonymously—and have somebody find
out.”Author Contributions
All authors developed the study concept and contributed to the study design. Data collection and
analysis were performed by G. T. Kraft-Todd. G. T. Kraft-Todd performed the interpretation
under the supervision of L. Young. G. T. Kraft-Todd drafted the manuscript, and M. Kleiman-
Weiner and L. Young provided critical revisions. All authors approved the final version of the
manuscript for submission.
Acknowledgments
This research was made possible by funding by the John Templeton Foundation and The Virtue
Project at Boston College. We would like to thank the Morality Lab at Boston College for their
feedback.
Declaration of Conflicting Interests
The authors declare that there were no conflicts of interest with regard to the authorship or the
publication of this article.
Open Practices Statement
All data and analysis code for all experiments have been made publicly available via the
Open Science Framework and can be accessed at (non-blinded link to be added after review). All
stimuli can be found in SI Section 7. The design and analysis plans for Experiments 8 and 9 were
respectively preregistered at http://aspredicted.org/blind.php?x=zw4ee5 and
http://aspredicted.org/blind.php?x=s6v2bx (Experiments 1-7 were not preregistered).References
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doi:10.1080/01621459.1962.10480664Supplementary Information
for
Differential virtue discounting:
Public generosity is seen as more selfish than public impartiality
Gordon T. Kraft-Todd, Max Kleiman-Weiner, Liane Young
Contents
1. Supplemental Study 1: Subject-generated acts of virtue .........................................................................20
2. Supplemental Study 2: Pretesting participant-generated acts of virtue ...................................................23
2.1 Methods ..............................................................................................................................................23
2.2 Results ................................................................................................................................................23
3. Analysis 1 of both primary dependent measures by experiment .............................................................27
3.1 Methods ..............................................................................................................................................27
3.2 Results ................................................................................................................................................27
4. Preregistered analyses only ......................................................................................................................30
4.1 Analysis 1...........................................................................................................................................30
4.1.1 Methods .......................................................................................................................................30
4.1.2 Results .........................................................................................................................................30
4.2 Analysis 2...........................................................................................................................................31
4.2.1 Methods .......................................................................................................................................32
4.2.2 Results .........................................................................................................................................32
5. Complete experimental instructions ........................................................................................................34
6. Unedited participant-generated acts from Supplemental Study 1............................................................491. Supplemental Study 1: Subject-generated acts of virtue
Our aim in this study was to create a set of participant-generated behaviors that we would
pretest (see Supplemental Study 2, SI Section 2) and use as stimuli in Experiments 7-9.
Methods
Our methods for this study follow the same procedure as that described in the General
Methods section. We requested N=100 participants, though because some participants may have
completed the survey but failed to enter their completion code to mTurk (thus allowing others to
complete the survey), our final sample was N=114 participants (we did not collect demographics
for this study). In randomized order, we provided participants with a dictionary definition of each
virtue (from Meriam-Webster.com; generosity: “giving or sharing in abundance”; impartiality:
“lack of favoritism toward one side or another”), and participants responded to the prompt:
“Please name at least 3 and up to 10 real-life acts of [generosity/impartiality]” using free-
response text boxes.
Results
Participants generated on average m=7.48 responses (generosity m=4.18; impartiality
m=3.30), indicating that they followed instructions to provide at least 6 total. These were edited
for responses which were nonsensical (e.g. “23”; “ruban”), spelling, punctuation, and grammar
(see Tables S8 and S9 for complete list of unedited responses). Responses were further edited for
simplicity (e.g. generalizing pronouns such as “woman” and “man” to “person”), part of speech
(all responses were edited to be in the present participle; i.e. using ending in “-ing”), and
semantic commonality (“give a homeless person some food” and “buying a homeless person
food”; for complete unedited responses, see SI Section 8). This process yielded a list of 50
unique responses for both generosity (see Table S1) and impartiality (see Table S2). This study
therefore provided us with the list of participant-generated generous and impartial act (total
k=853).Table S1. Edited participant-generated acts of generosity (stimuli are highlighted).
no. generous acts
1 adopting a child 26 giving a waiter a large tip
2 adopting a pet 27 giving praise
3 babysitting for friend (for free) 28 giving someone a compliment
4 buying a friend an expensive gift 29 giving someone a hand carrying groceries
5 buying a homeless person food 30 giving up your seat on a bus
6 buying a round of drinks 31 helping an elderly person cross the street
7 buying everyone lunch 32 helping out a friend in need
8 buying someone a meal 33 helping someone fix a flat tire
9 buying someone groceries 34 helping someone move
10 buying supplies for an animal shelter 35 holding the door for someone
11 caring for a sick person 36 lending money to a friend
letting a friend stay at your house for the
12 cooking for someone 37
night
13 donating a kidney 38 letting someone ahead of you in line
14 donating blood 39 mowing your neighbor's lawn (for free)
offering advice to someone who
15 donating clothes to homeless shelter 40
wants/needs it
paying for person behind you in line (for
16 donating food to a food pantry 41
example: toll or coffee)
17 donating money at church 42 picking up a hitchhiker
18 donating money to charity 43 picking up trash in a park
19 donating to a toy drive 44 recycling
20 donating to artists or content creators 45 sharing food with friends
21 donating your car to charity 46 staying late to help a coworker
22 giving a gift 47 volunteering at a homeless shelter
23 giving a hug 48 volunteering at an animal shelter
24 giving a ride to someone 49 volunteering to build homes for others
25 giving a scholarship to a student in need 50 walking a neighbor's dog (for free)Table S2. Edited participant-generated acts of impartiality (stimuli are highlighted).
no. impartial acts
a boss giving a promotion purely based on donating the same amount to all countries
1 26
merit in need
drawing names from a hat for a project at
2 a boss treating all employees the same 27
work
a disinterested bystander mediating an giving an award to an equal number of
3 28
argument between two people white and black people
a judge giving the same sentence to
4 29 giving children equal allowance
people of different races
a parent dividing assets equally among giving equal attention to each of your
5 30
their children in their will children
a parent giving children equally valuable giving equal attention to each of your
6 31
Christmas gifts friends
a parent hearing both sides of her giving equal attention to each of your
7 32
children's dispute without playing favorites parents
giving the same level of customer service
8 a police officer giving themselves a ticket 33
to all customers
a politician voting for a policy that affects helping to moderate when your friends are
9 34
the poor and the rich equally having a disagreement
a restaurant giving tables on a first-come hiring people without regard to whether
10 35
first-serve basis they're your friend or family
implementing affirmative action in a hiring
11 a scientist performing an experiment 36
or admissions decision
learning to pronounce others' names
12 a teacher calling on all students equally 37
regardless of their country of origin
a teacher giving all students the same
13 38 listening to both parties in a conflict equally
opportunities to make up work
a teacher who disciplines all students the
14 39 making a decision by flipping a coin
same
planning an event to be accessible to
15 acting as referee in sporting event 40
disabled people
16 adhering to the law every moment 41 providing equal pay for males and females
being friendly to people no matter what
17 42 sharing things equally between two people
race they are
calling the police regardless of who splitting a candy bar evenly between two
18 43
commits the crime kids
cheering for both sports teams in a staying neutral when politics are being
19 44
competition discussed
20 choosing a winner's name out of a hat 45 staying out of an argument
choosing brands at random when treating people the same regardless of
21 46
shopping their religion
treating people the same regardless of
22 conducting a blind audition 47
their sexual orientation
23 conducting a blind study 48 treating siblings equally
using a random number generator to make
24 conducting a blind vote 49
a decision
dividing food by cutting and letting other voting for a candidate in an election
25 50
person pick which piece they want randomly2. Supplemental Study 2: Pretesting participant-generated acts of virtue
Our aim in this study was to have an independent sample of participants rate our edited
list of participant-generated behaviors from Supplemental Study 1 along dimensions of common
interest in social psychology (Kraft-Todd & Rand, 2019) in order to create more tightly-
controlled stimuli for Experiments 7-9 than the (non-pretested) experimenter-generated stimuli
used in Experiments 4-6.
2.1 Methods
Our methods for this study follow the same procedure as that described in the General
Methods section. We requested N=500 participants from mTurk who did not participate in
Supplemental Study 1 for this study, though after screening for repeat IP addresses and mTurk
IDs (including only the first entry of either) and filtering participants who accepted the HIT on
mTurk but neglected to complete the survey, our final sample was N=460 participants (54.1%
female, average age=37.6 years). We randomly assigned participants to one of two between-
subjects conditions, in which they were asked to rate either generous or impartial behaviors. We
presented participants with a randomly selected subset of 20 behaviors (presented in randomized
order) from the 50 generated for the respective virtue in Supplemental Study 1. Thus, each
behavior was rated by an average of m=92 participants. Participants rated each behavior on five
dimensions (presented in randomized order): moral goodness (“In your opinion, how morally
good is it to do this behavior?”); as well as four which replicated the method of previous work
(Kraft-Todd & Rand, 2019): descriptive normativity (“In your opinion, how many people in your
community do this behavior when they are in the relevant situation?”); injunctive normativity
(“In your opinion, how much do people in your community think doing this behavior is what you
are supposed to do when you are in the relevant situation?”); benefit to the recipient (“In your
opinion, how much benefit (in terms of money, time, effort, etc.) does the recipient of this
behavior receive?”); and cost to the actor (“In your opinion, how much cost (in terms of money,
time, effort, etc.) does the person who does this behavior incur?”). All ratings were completed
using anchored sliding scales ranging from 0 to 100 (see SI Section 7 for more details).
2.2 Results
Using the complete pretesting ratings (see Table S3 for complete ratings of all behaviors),
we selected six participant-generated acts; three each for generosity and impartiality to be
included as stimuli in Experiments 7-9. A number of considerations went into this selection
procedure, both semantic (considerations 1-4 below) and numeric (considerations 5-7 below).
First, we limited our selection to behaviors that were not role-specific (thus we excluded
impartiality behaviors 1-14 which involve specific roles, e.g. “a judge”, “a boss”, etc.). Second,
we limited our selection to behaviors that were one-shot interactions, rather than repeated,
chronic, or with lasting impacts (and so we excluded behaviors which included e.g. “adopting a
child”, “treating people the same regardless of their sexual orientation”, etc.). Third, we sought a
diversity of targets of the behaviors (e.g. 10 behaviors across generosity and impartiality
mentioned “friend(s)” as the recipient, and we did not want to include more than one “friend”
behavior for each virtue). Fourth, we sought a diversity of verbs describing the behaviors (e.g.generosity behaviors 13-21 use the word “donating”, and we did not want to include more than
one “donating” behavior). Fifth, we limited our selection to behaviors that did not have extreme
ratings across dimensions; neither high (e.g. generosity: “caring for a sick person”; impartiality:
“a parent giving children equally valuable Christmas gifts”) nor low (e.g. generosity: “picking up
a hitchhiker”; impartiality: “voting for a candidate in an election randomly”). Sixth, we limited
our selection to behaviors that did not have extreme variation in ratings across dimensions (e.g.
generosity: “helping an elderly person cross the street”; impartiality: “a parent hearing both sides
of her children's dispute without playing favorites”). With these considerations, we selected three
behaviors each for generosity (“buying a friend an expensive gift”, “giving a waiter a large tip”,
“staying late to help a coworker”) and impartiality (“conducting a blind audition”, “drawing
names from a hat for a project at work”, “giving children equal allowance”) as a potential
stimulus set for our final, statistical consideration.
Finally, we aimed to select a subset of behaviors that would be as similar as possible in
each of the dimensions measured—particularly in ratings of moral goodness—so that these
dimensions would not bias subsequent results. We therefore use multilevel mixed-effects linear
regression to compare each rating as the dependent measure across virtue stimulus set
(generosity vs impartiality as a binary predictor), entering act (of which there are 6) as a random
factor. First, and, most importantly, our generosity stimulus set was not perceived as more
morally good than our impartiality stimulus set (coeff=1.16, z=.16, p=.869; see Figure S1).
Further, our generosity stimulus set was not perceived as different from our impartiality stimulus
set across other dimensions: descriptive normativity (coeff=-5.77, z=-1.02, p=.310), injunctive
normativity (coeff=-3.74, z=-.61, p=.541), and benefit to the recipient (coeff=8.59, z=1.88,
p=.060). Our generosity stimulus set, however, was perceived as more costly to the actor than
our impartiality stimulus set (coeff=22.22, z=3.52, pYou can also read
