REPORT
Virtue Discounting: Observability Reduces
Moral Actors’ Perceived Virtue
Gordon T. Kraft-Todd1
, Max Kleiman-Weiner2
, and Liane Young1
1Department of Psychology and Neuroscience, 140 Commonwealth Ave, Boston College, Chestnut Hill, MA 02467, USA
2School of Engineering and Applied Sciences, Harvard Universität, 33 Kirkland St., Cambridge, MA 02138, USA
Keine offenen Zugänge
Tagebuch
Schlüsselwörter: virtue, observability, motivation, generosity, fairness
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ABSTRAKT
Performing prosociality in public presents a paradox: only by doing so can people demonstrate
their virtue and also influence others through their example, yet observers may derogate actors’
behavior as mere “virtue signaling.” Here we investigate the role of observability of actors’
behavior as one reason that people engage in such “virtue discounting.” Further, we investigate
observers’ motivational inferences as a mechanism of this effect, using the comparison of
generosity and fairness as a case study among virtues. Across 14 Studien (7 preregistered, total
N = 9,360), we show that public actors are perceived as less virtuous than private actors, Und
that this effect is stronger for generosity compared to fairness (d.h., differential virtue discounting).
Exploratory factor analysis suggests that three types of motives—principled, reputation-signaling,
and norm-signaling—affect virtue discounting. Using structural equation modeling, we show
that observability’s effect on actors’ trait virtue ratings is largely explained by inferences that
actors have less principled motivations. Weiter, we leverage experimental evidence to provide
stronger causal evidence of these effects. We discuss theoretical and practical implications of
our findings, as well as future directions for research on the social perception of virtue.
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EINFÜHRUNG
A [person] of the highest virtue does not keep to virtue and that is why [they have] virtue.
A [person] of the lowest virtue never strays from virtue and that is why [they are] without
virtue.
—Lao Tzu, Tao Te Ching (Kapitel 38, L.1-4; Tzu & Lau, 1963)
Public prosociality presents a paradox: For an actor’s virtue to be known—and for their exam-
ple to be followed—their morally good behavior must be observed by others; yet when an
actor’s morally good behavior is observable, others may doubt the actor’s virtue. Resolving
this paradox is particularly perplexing for early adopting advocates of uncommon prosocial
behaviors (z.B., installing residential solar panels, buying electric vehicles, adopting vegan
diets): can such an individual effectively demonstrate the moral worth of their behavior while
avoiding observers’ skepticism of their moral character?
To illustrate this paradox, imagine browsing a printed list of people who donated the same
amount to a charitable cause. The first two names listed are one of your friend’s and
Zitat: Kraft-Todd, G. T., Kleiman-
Wiener Würstchen, M., & Jung, L. (2023). Virtue
Discounting: Observability Reduces
Moral Actors’ Perceived Virtue. Open
Geist: Discoveries in Cognitive Science,
7, 460–482. https://doi.org/10.1162
/opmi_a_00085
DOI:
https://doi.org/10.1162/opmi_a_00085
Supplemental Materials:
https://doi.org/10.1162/opmi_a_00085
Erhalten: 29 August 2022
Akzeptiert: 16 Mai 2023
Konkurrierende Interessen: The authors
declare no conflict of interests.
Korrespondierender Autor:
Gordon T. Kraft-Todd
gordon.kraft-todd@bc.edu
Urheberrechte ©: © 2023
Massachusetts Institute of Technology
Veröffentlicht unter Creative Commons
Namensnennung 4.0 International
(CC BY 4.0) Lizenz
Die MIT-Presse
Virtue Discounting
Kraft-Todd et al.
“Anonymous”; whose behavior is more indicative of their virtue? If you think your friend
appears less virtuous by comparison, your intuitions are aligned with ancient philosophical
arguments (Maimonides, 1170) borne out in recent empirical work (De Freitas et al., 2019).
Trotzdem, your (less virtuous) friend is likely to have more prosocial influence on you than the (mehr
virtuous) anonymous giver (Smith et al., 2015). From a consequentialist standpoint, your friend
actually caused more overall good; Warum, Dann, do we think they’re less virtuous?
This paradox has long been puzzled over in the context of charitable giving (z.B., Lin-Healy
& Small, 2012; Newman & Cain, 2014)—a prime example of behavior expressing the virtue of
generosity—but are the dynamics the same when considering behaviors expressing other vir-
tues (z.B., fairness)? This question is of theoretical interest for understanding social perception
of prosociality, but it is also of practical interest for its downstream consequences: we can be
more effective advocates if we can understand which types of behaviors face the paradox of
public prosociality (and why).
“Virtue Discounting” and Observability
We define a virtue as: a quality of individuals valued by their culture and expressed through a
stable pattern of properly motivated behavior (Kraft-Todd et al., 2022). In the present work, Wir
are particularly focused on how attribution of actors’ motivations is linked to perceptions of
their virtue. Following most work in the Western philosophical and empirical traditions, viele
fundamental aspects of our concept of virtue can be traced to Aristotle’s Ethics (Aristotle,
1999). Namely, that virtue is trait-like, d.h., a stable, dispositional characteristic of individuals;
that it is expressed through behaviors; and that it requires “proper” motivation (Cokelet &
Fowers, 2019). Proper motivation evokes Aristotle’s concept of eudaimonia (often translated
as “human flourishing”) which he meant as an end in itself (rather than a means to some other
end; Aristotle, 1999), interpreted in recent work as, “one’s understanding of the virtue is itself
motivating” (Cokelet & Fowers, 2019).
Moral judgments can range from assessments of specific behaviors to broad characteriza-
tion of individuals, and people use the former as input to the latter (Hartman et al., 2022).
Zusätzlich, people often make judgments at the level of mental states and traits (Tamir &
Thornton, 2018) as well as other “mental occurrents” (z.B., beliefs; Critcher et al., 2020)—
when evaluating others’ moral characters from their behavior. Relevant to the present inves-
tigation, perceptions of actors’ motivations (Carlson et al., 2022) are a commonly documented
type of mental state inference affecting such “person-centered” characterological moral judg-
gen (Pizarro & Tannenbaum, 2012). To be clear, we differentiate judgments of moral char-
acter as domain-general assessments of individuals’ morality (z.B., on a spectrum from “good”
to “bad”) from judgments of virtue as domain-specific assessments of individuals’ positive
(moral) qualities.
In the attribution literature, there is a long history of work examining “discounting” (Kelley,
1972) of observers’ perceptions of the causes of actors’ behavior. This work has typically inves-
tigated different types of explanations (z.B., as attributable to the person vs. the situation) für
actors’ behavior (McClure & Hilton, 1997). In the present investigation, we are focused on
observers’ attributions of motivations, speziell, as explanations for actors’ behavior (Fein,
1996). In keeping with this work, we describe the phenomena in which observers’ motiva-
tional attributions lead them to believe that actors’ behavior is less attributable to actors’ virtue
as “virtue discounting.”
Here we focus on the role of observability, d.h., the degree to which actors’ behavior is vis-
ible to uninvolved third parties (as opposed to recipients, interaction-partners, usw.), as a cause
OPEN MIND: Discoveries in Cognitive Science
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Virtue Discounting
Kraft-Todd et al.
of virtue discounting. Observability is a central component of the theory of indirect reciprocity
(Nowak & Sigmund, 1998), which explains how cooperation can evolve among unrelated
individuals when there are rules (z.B., social norms) governing individuals’ behavior (Ohtsuki
& Iwasa, 2006) and information regarding individuals’ (non-)adherence to these rules can be
stored and transmitted (d.h., through their “reputations”). Implications of this theory are borne
out in field experiments (für eine Rezension, sehen: Kraft-Todd et al., 2015) showing that making peo-
ple’s behavior observable activates people’s reputational concerns, causing them to follow
social norms supporting prosocial behavior. Despite the efficacy of observability for motivating
such behavior (z.B., Yoeli et al., 2013), observers may be less likely to infer that the behavior it
inspires is a signal of actors’ virtue because actors are not properly motivated. Daher, observers
may infer (correctly) that actors are motivated by reputational benefit, rather than, z.B., genu-
ine outrage at injustice, desire for environmental conservation, concern for others’ welfare,
usw. Mit anderen Worten, observability introduces an ulterior motive (reputational concerns) Das
taint observers’ inferences of actors’ virtue because actors’ behavior is not (properly) motivated
by pursuit of the virtue as an end in itself. Entsprechend, we formulate our first preregistered
hypothesis “virtue discounting”: people will discount actors’ virtue when actors’ behavior is
observable.
Generosity vs. Fairness as A Case Study in Virtue Discounting
Much existing empirical work demonstrates virtue discounting in the context of the virtue gener-
osity (z.B., Newman & Cain, 2014). Previous work has argued that fairness is well-suited as a
comparison virtue to generosity; Zum Beispiel, there is evidence that generosity and fairness differ
across many psychological dimensions, as well as in the natural language people use to describe
example behaviors of each virtue (Kraft-Todd et al., 2022). We build on much prior work distin-
guishing these virtues: in virtue ethics (z.B., as “natural” vs. “artificial” virtues; Hume, 1902); In
recent theoretical arguments distinguishing these virtues’ functions (d.h., generosity enables indi-
viduals to make cooperative partnerships, whereas fairness enables individuals to avoid punish-
ment from their cooperative partners; Shaw, 2016); and in empirical work demonstrating how
these virtues can be operationally distinguished and shown to come into conflict (z.B.,
Kleiman-Weiner, Shaw, et al., 2017; Shaw & Olson, 2012). Taken together, fairness may serve
as a valuable comparison to generosity for investigating virtue discounting across virtues.
As in previous work, we employ a “narrow” definition of both virtues. We define generosity as
“giving an abundance of one’s money or time”, capturing most uses of the term, but not, z.B., gen-
erosity of attitudes (Gulliford & Roberts, 2018). We define fairness as “treating others equally and
fairly, without bias”, capturing recent work on impartiality (Shaw, 2013), but not, z.B., work on fair-
ness that focuses on the need of recipients (d.h., charity; Niemi & Jung, 2017). Daher, our case study
might be more precisely described as: “a case study of generosity vs. fairness (as impartiality).” To
avoid confusion: we will henceforth use the terms generosity and impartiality when discussing
our experiments—because these are the terms we use in our stimuli—but to refer to the respec-
tive virtues in keeping with the virtue literature, we will use the terms generosity and fairness.
Pertinent to the present investigation, there is also reason to believe that generosity and
fairness might be discounted to different degrees. Fairness (as a component of justice) has long
been considered enforceable through law whereas generosity has not (Schneewind, 1990).
Folglich, there may be greater plausible deniability in attributing actors’ fairness (vs. gen-
erosity) to a desire to conform to formal regulations (and social expectations) rather than a
desire to improve one’s reputation. It might be argued that behaving in accordance with social
expectations is itself a means of improving one’s reputation (Ohtsuki & Iwasa, 2006). We posit,
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Jedoch, that such behavior will be seen as less self-serving than “morally motivated devi-
ance” (Cramwinckel et al., 2015), z.B., when people engage in antisocial punishment, penal-
izing individuals who self-sacrifice to benefit the group because it goes against perceived
norms (Herrmann et al., 2008). Consistent with this account, previous work distinguishing gen-
erosity and fairness provides evidence of the inverse; Zum Beispiel, in a resource distribution
paradigm, Erwachsene (Shaw & Knobe, 2013) as well as children (Shaw & Olson, 2012) würde
rather throw away a windfall resource (the ungenerous but fair choice) in order to avoid
appearing biased (d.h., rather than make the generous but unfair choice). Such decisions
may be motivated by individuals’ perceptions that it would be worse to be seen violating a
social expectation (to be unfair) rather than to merely be seen as ungenerous.
Further complicating the prosocial interpretation of generous behaviors, although generosity
can be a signal of cooperative intent (d.h., willingness to provide benefits to others), it can
also be a signal of wealth (Barclay, 2016), and thus individuals may show generosity so that
others think they are rich. Auch, the ideal of fairness (as impartiality) has a specific numerical
connotation—i.e., to treat others with zero bias—whereas the ideal of generosity is effectively
without ceiling (d.h., to be maximally generous, one can always give more). Infolge, es ist
easier to coordinate around a (categorical) norm of fairness than a (continuous) norm of gener-
osity. There is a wealth of evidence from mathematical models and empirical studies ( Yoeli &
Hoffman, 2022) suggesting that plausible deniability and categorical norms are two important
mechanisms motivating human behavior and how it is perceived. In the present context, inter-
preting fairness compared to generous behaviors seems simpler, both because of the categorical
nature of applicable norms, and also because of greater plausible deniability in the attribution
of selfish motivations. Daher, we arrive at our second preregistered hypothesis, “differential
virtue discounting”: people will discount fairness (as impartiality) less than generosity.
Motivational Inference in Perceptions of Virtue
To this point, we have discussed “motivation” in a limited sense; d.h., as either the proper moti-
vation requisite for virtue or as the motivation to benefit one’s reputation. Noch, prior work has
explored many distinct motivations for prosocial behavior (Carlson et al., 2022; Kodipady
et al., 2021; Narvaez & Snow, 2019; Reiss & Havercamp, 1998). To better understand the
motives observers attribute to prosocial actors and how these contribute to virtue discounting,
we focus on six motivations suggested by this literature: self-presentation, norm-signaling, self-
benefit, other-benefit, moral rules, and virtue identification.
We opened with a paradox of public prosociality that highlights the tension between two
Motivationen. Pulling in one direction (and to put a finer point on “reputational concerns”), Wir
call the motivation to affect others’ impression of oneself self-presentation, following work
documenting how people manage others’ impression of them through “self-presentation
strategies” ( Jones & Pittman, 1982). Pulling in the other direction, we call the motivation to
lead by example norm-signaling, deriving from work on the role individuals have to influence
social norms in a “grassroots” manner (Tankard & Paluck, 2016). Although the idea of “leading
by example” is a topic of increasing theoretical (Henrich, 2009) and empirical (Kraft-Todd
et al., 2018) interest, we are unaware of previous work investigating “leading by example”
as a motivation (though see: Kodipady et al., 2021).
We briefly alluded to another pair of conflicting motivations in our discussion of observable
generosity. A number of recent reviews have emphasized how fundamental the motivation of
other-benefit, d.h., the desire to improve the welfare of others, is for motivating prosocial behavior
(z.B., Keltner et al., 2014). The emphasis of these reviews stands in contrast to a historical bias,
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informed by the economic and evolutionary literatures (z.B., Friedman, 1953), to a reductive
focus on the motivation of self-benefit, d.h., the desire to improve one’s own welfare.
Endlich, we explore two identity-relevant motivations. Research on social norms has distin-
guished types of social rules guiding behavior, among which is the class of moral rules that indi-
viduals believe should guide behavior regardless of others’ expectations (d.h., as opposed to
“socially-dependent” social rules that rely on others’ expectations, moral rules are “socially-
independent”; Bicchieri, 2006; Levine et al., 2020). This motivation interestingly differs from
the previously discussed motivations because it is not outcome-oriented; stattdessen, it derives from
an individual’s socially-independent moral values. Another socially-independent motivation for
virtuous behavior derives from actors’ sense of identity, as explored in research on, z.B., “moral
identity” (Aquino & Reed, 2002), “moral consistency” (Kleiman-Weiner, Sachsen, et al., 2017;
Mullen & Monin, 2016), and “self-concept maintenance” (Mazar et al., 2008). In the context
of the present work, we study whether individuals’ identification with the specific virtue under
investigation might be a motivation for virtuous behavior, and call this virtue identification.1 This
motivation most closely approximates “proper” motivation in our definition of virtue.
In keeping with previous work, our third preregistered hypothesis is: (differential) virtue dis-
counting will be explained by observers’ inferences that public actors have more selfish moti-
vations than private actors. In the present work, Jedoch, we extend this previous work which
typically invokes “selfish” motivations (generally) and reputational concerns (speziell) als
drivers of virtue discounting (z.B., Raihani & Power, 2021). We do not intend our investigation
to be an exhaustive account of all possible motivational inferences, but our preregistered
exploratory factor analyses and structural equation models shed new light on the social per-
ceptions underlying virtue discounting.
GENERAL METHODS
We describe the general procedure in common across experiments here, and summarize more
fine-grained detail in Table 1 (as well as Supplement Section 1). In the Supplement, we provide
justifications for changes in experiment design across experiments (Abschnitt 2), and also pro-
vide complete experimental instructions (Abschnitt 8). All measures, Manipulationen, and exclu-
sions in all experiments are disclosed across the main text and Supplement. All experiments
were conducted online using Qualtrics survey software. A convenience sample of participants
were recruited using the crowdsourcing tool Cloud Research and Amazon Mechanical Turk
(“mTurk”; Arechar et al., 2017; Berinsky et al., 2012). We excluded duplicate Amazon worker
IDs and IP addresses to prevent analyzing multiple observations per participant (sowie
participants who dropped out prior to assignment to condition), yielding a final sample of
N = 9,360 Teilnehmer (51.2% weiblich, average age = 37.7 Jahre). Informed consent was
obtained from all participants, who completed experiments in mean = 5 minutes and were paid
mean = $0.89 for their participation. For conciseness, we abbreviate references to specific
experiments as “E#” (z.B., E3 = Experiment 3).
After providing consent and entering their mTurk ID, we randomly assigned participants to
one between-subjects condition. We crossed our primary manipulations in all experiments in a
2 (virtue: generosity vs. impartiality) × 2 (observability: public vs. private) factorial design. Erste,
participants read text delivering our virtue manipulation, adapted from Merriam-Webster.com
(siehe Tabelle 1). We asked participants to imagine that they know someone (fortan: “the
1 We note that although we treat moral rule and virtue identification motivations as “socially-independent”,
this may only apply to the actors’ proximate psychology, as both motivations are likely shaped through cultural
norm internalization (Henrich, 2016).
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Tisch 1.
experimental instructions, see Supplement Section 8).
Key elements of stimuli. Shown are characteristics and language of key elements of stimuli bearing on hypotheses in all experiments (for complete
Virtue (example behaviors)
Observability
Stimuli language
Impartiality
Private
Ö
P
E
N
M
N
D
ICH
:
ich
D
S
C
Ö
v
e
R
ich
e
S
ich
N
C
Ö
G
N
ich
T
ich
v
e
S
C
e
N
C
e
ich
Exp.
num.
1
2
3
4
N
389
394
394
388
Stimuli information
Motive
stipulated?
Ja
Example
behaviors
(none)
Experimenter-
generated
Generosity
[Virtue definition]:
“Generosity usually
means giving an
abundance of one’s
money or time”
– volunteered at a
homeless shelter
– donated money to
charities like Doctors
without Borders
[Virtue definition]: Impartiality
usually means treating
everyone equally and fairly,
without bias
– made sure everyone at a social
gathering receives the same
amount of food
– divided work evenly among all
participants in a group project
5
393
– donated blood during a
– made auditions or job
blood drive
applications blind so that
subtle, unconscious biases
against particular genders or
ethnicities don’t enter into the
decision-making process
Participant-
generated
– bought a friend an
expensive gift
– gave her children equal
allowances
– gave a waiter a large tip
– stayed late to help a
– conducted a blind audition
– drew names from a hat for a
coworker
project at work
– gave someone a hand
carrying groceries
– shared food with friends
– gave someone praise
– bought someone a meal
– donated blood
– volunteered at an animal
shelter
– stayed out of an argument
– divided food by cutting and
letting the other person pick
which piece they want
– helped to moderate when your
friends had a disagreement
– divided food by cutting it and
letting the other person pick
which piece they wanted
– learned to pronounce others’
names regardless of their
country of origin
– listened to both parties in a
conflict equally
6
7
8
9
10
11
12
13
14
393
582
577
386
663
394
377
NEIN
Yes*
NEIN
1,770
2,260
Yes*
4
6
5
Though she is [G/I]
when she is with
Andere, she is
especially [G/I]
when no one is
watching since she
knows that acting
in this way is
consistent with her
Werte.
Though she is [G/I]
when she is with
Andere, she is even
[G/I] when no one
is watching.
She did these things in
private; daher,
other people did not
know that she did
ihnen.
Public
She is especially
[G/I] Wann
others are
watching her
act since she
knows that her
reputation for
Sein [G/I] Wille
improve.
She is especially
[G/I] Wann
others are
watching her
Akt.
She did these
things in
öffentlich;
daher, andere
people knew
that she did
ihnen.
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G
K
R
A
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actor”) whom we named using 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).
We then told participants that the actor engaged in a set of three behaviors demonstrating
[generosity/impartiality]. Dann, participants read text delivering our observability manipulation
(siehe Tabelle 1, Columns 7 Und 8).
The behaviors used as stimuli were generated in a rigorous “bottom-up” manner (Kraft-Todd
et al., 2022). Erste, participants were randomly assigned to virtue condition (generosity vs.
impartiality) and asked them to provide behaviors that demonstrated the virtue using free-
response text. Zweite, an independent sample (also randomly assigned to virtue condition)
was recruited to rate a subset of these participant-generated behaviors on nine underlying
dimensions impacting moral judgment. Endlich, to avoid idiosyncrasies of any specific behav-
ior, a set of three behaviors were selected that described hypothetical actors engaging in to
create a general impression of the actors as demonstrating each virtue in participants’ minds.
Previous work found no significant differences in participants’ ratings between the sets of
behaviors we used as stimuli in the generosity and impartiality conditions of each experiment
across three dimensions: moral goodness, descriptive normativity, and the extent to which
behavior is indicative of the actor’s consistency across situations (Kraft-Todd et al., 2022). Das
evidence speaks against alternative explanations of our effects, z.B., based on the diagnosticity
of the behavior (Mende-Siedlecki et al., 2013) for actors’ virtue.
Following the stimuli, we presented participants with the two primary dependent measures
and six secondary dependent measures (siehe Tabelle 2) in randomized order. All dependent mea-
sures were answered on 100-point unmarked slider scales with extreme anchors labeled (Und
midpoints labeled for primary dependent measures). At the end of each experiment, we pre-
sented participants with basic demographic questions in randomized order (see Supplement
Tisch 2 for summary of participant demographics by experiment).
We conducted analyses using STATA (16.1) and R software (4.1.2). We obtained effect sizes
(Cohen’s D) through use of an online calculator (Lenhard & Lenhard, 2016). For regression
Analysen, we compute pairwise comparisons of estimated marginal cell means corrected for
multiple comparisons using Scheffe’s adjustment ( Winer et al., 1991; though results are equiv-
alent using Bonferroni correction). Structural equation models were constructed using stan-
dardized variables (Hayes, 2013), and indirect effects are calculated using the multivariate
delta method (Sobel, 1982) with bootstrapped standard errors (UCLA: Statistical Consulting
Group, 2021). Prior to conducting E8, we conducted a power analysis using the Superpower
package in R (Lakens & Caldwell, 2021), using data from E7. With a desired effect size of
d = .30 (for the virtue * observability interaction; see Supplement Section 3 for effects by exper-
iment), our sample size of N = 100 per cell was powered at 83.25% with an alpha level of .05.
For E1–7, we used the heuristic of recruiting N = 100 per cell. Sample size for each experiment
was determined before any data analysis. Sensitivity analyses were conducted using G*Power
(3.1.9.7) Software (Faul et al., 2007).
Below we present these preregistered analyses using data aggregated across all of our
experiments (though we also provide precise preregistered analyses in the Supplement
(see Supplementary Tables 4–7). Although our preregistered hypotheses include both of our
primary dependent measures (d.h., moral goodness ratings and trait ratings), these measures
were highly correlated (across all experiments: r = .74, P < .001), so we present trait rating
results here for conciseness. Results do not qualitatively differ if moral goodness ratings are
used instead (see Supplementary Tables 5 and 7). E10, E11, E13, and E14 included preregis-
tered exclusions for participants who failed attention checks (average failure rate across
OPEN MIND: Discoveries in Cognitive Science
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Table 2. Dependent measures. Shown are labels (Column 2) and item wording (Column 3) for dependent measures used in all experiments.
Primary dependent measures
Secondary dependent measures
(motivational inferences)
Item
Moral goodness
Trait ratings
Moral rule
Virtue identification
Other-benefit
Self-presentation
Self-benefit
Norm-signaling
“How morally good is [the actor]?”
Wording
“How [generous/impartial] is [the actor]?”
“...because she thinks it is the right thing to do?”*
“...because she wants to be [generous/impartial]?”*
“...because she wants to benefit others?”*
“...because she is trying to make others think she
is [generous/impartial]?”*
“...because she thinks she will personally benefit
from acting this way?”*
“...because she wants others to be [generous/impartial],
and she is trying to lead by example?”*
*Preceded by: “How much do you think [name] is motivated to act [generously/impartially]…”
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studies = 12.2%). To maintain consistency in our results across experiments and to be maximally
inclusive of data we collected, the results presented below include participants who failed
attention checks (N = 720, 7.7% of total N ). Results are robust to excluding these participants
(Supplementary Table 8).
Preregistrations were conducted for: E8 (https://aspredicted.org/FLG_VRD), E9 (https://
aspredicted.org/NUP_ESB), E10 (https://aspredicted.org/FCO_HXM), E11 (https://aspredicted
.org/2Y2_YKT), E12 (https://aspredicted.org/AES_HGO), E13 (https://aspredicted.org/G6S
_S35), and E14 (https://aspredicted.org/SHW_9PN). All data and code are publicly available
at: https://osf.io/sud3m/?view_only=380a169770b9474f93d2b5b73adc7410.
ANALYSIS 1. VIRTUE DISCOUNTING AFFECTS GENEROSITY MORE
THAN IMPARTIALITY
The purpose of Analysis 1 is to test for evidence of our first two hypotheses (preregistered in
E8–14): 1) virtue discounting: people will discount actors’ virtue when actors’ behavior is
observable; and 2) differential virtue discounting: people will discount fairness (as impartiality)
less than generosity. To do so, we examine participants’ ratings of actors’ trait virtue in our hypo-
thetical vignettes across conditions, using multivariate regression (collapsing across experi-
ments) as well as meta-analysis (using the “metan” package in R; Olivoto & Lúcio, 2020).
We also provide an exploratory test of the directionality implied by our virtue discounting
terminology, i.e., that participants discount public virtue rather than reward private virtue. In
two experiments (E7 and E8, see Supplement Section 4) we added an additional “baseline”
observability condition that provided no information about observability (i.e., we simply omit-
ted the line, “She did these things in [public/private]; therefore, other people [knew/did not
know] that she did them” from our experimental instructions; see Supplement Section 8). Cru-
cially, we note that the example behaviors used as stimuli in these experiments were not rated
differently on the dimension of “potential for anonymity” in our previous data (Kraft-Todd
et al., 2022), supporting our interpretation that participants did not perceive differences across
virtues in the extent to which these behaviors were known to uninvolved third-parties. By
comparing participants’ trait ratings in the public and private observability conditions to the
baseline observability condition, we provide a test of whether public virtue is discounted, or
instead, whether private virtue is rewarded.
Methods
We use data from all conditions in all experiments in which we manipulated observability (N =
8,969; 51.2% female, average age = 37.8 years). First, we conduct a multivariate regression
analysis predicting moral goodness and trait ratings by our virtue manipulation (generosity vs.
impartiality), observability manipulation (public vs. private), and their interaction, with Exper-
iment as a covariate. Second, we conduct a random-effects meta-analysis on the effect sizes
from the virtue * observability interaction.2
Results
As predicted in our first preregistered hypothesis (virtue discounting), we find a significant
effect of our observability manipulation, collapsed across virtue condition, on trait ratings
(F(1, 8954) = 545.86, p < .001, d = .49) such that public actors (m = 72.06, 95% CI
[71.41, 72.71]) are perceived as significantly less virtuous than private actors (m = 82.30,
2 Note that we only tested generosity in E10 so this experiment is not included in this analysis.
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95% CI [81.71, 82.88]). Sensitivity analysis revealed that (at p = .05 and power = 80%) the
minimum detectable effect size for this test is d = .06.
As predicted in our second preregistered hypothesis (differential virtue discounting), we also
find a significant interaction between virtue and observability on trait ratings (F(1, 8952) =
42.18, p < .001, d = .14; see Figure 1). Sensitivity analysis revealed that (at p = .05 and power =
80%) the minimum detectable effect size for this test is d = .06. Publicly generous actors are
perceived as significantly less virtuous (m = 71.26, 95% CI [70.35, 72.17]) than privately gen-
erous actors (m = 84.20, 95% CI [83.43, 84.96], Scheffe’s t = −21.62, p < .001, d = .61).
Publicly impartial actors (m = 72.99, 95% CI [72.07, 73.92]) are also perceived as significantly
less virtuous than privately impartial actors (m = 80.10, 95% CI [79.23, 80.98], Scheffe’s t =
−11.18, p < .001, d = .34). Providing the crucial test of our preregistered differential virtue
discounting hypothesis, a Wald test (χ2(1) = 42.70, p < .001) reveals that the effect of observ-
ability is greater for generosity (contrast = −12.91, 95% CI [−14.08, −11.75]) than impartiality
(contrast = −7.19, 95% CI [−8.45, −5.92]).
We also provide multiple demonstrations of the robustness of our effects and our interpre-
tation. A random-effects meta-analysis on the 13 virtue*observability interaction effect sizes
reveals that generosity is discounted to a greater extent than impartiality (rpartial = −.10, 95%
CI [−.13, −.07], Z = 7.50, p < .001; see Figure 1b). Further, we do not observe evidence of
heterogeneity in effect size across experiments ( χ2(12) = 14.93, p = .245), implying that this
result is robust to differences in experimental design. Note that across all experiments, the
virtue * observability interaction is either significant, such that generosity is discounted more
than impartiality, or it is not significant; it is never the case that impartiality is discounted more
than generosity. We further demonstrate the robustness of our effects by replicating these
results in nearly all meaningful subsets of our experiments; importantly, including among
our preregistered experiments (see Supplement Section 3).
Finally, we provide evidence in support of the directionality implied by our virtue discounting
terminology. Comparing participants’ trait ratings in the public and private observability condi-
tions to the baseline observability condition (see Supplement Section 4), we find that, compared
to generous actors described without observability information (i.e., the baseline condition),
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Figure 1. Virtue discounting (i.e., public actors are rated less virtuous than private actors) affects generosity more than impartiality. Shown
are a) means (with 95% CIs) of trait ratings (0–100 unmarked slider) collapsed across all 14 experiments, as a function of whether the actor is
said to have engaged in generous (green) or impartial (blue) behaviors and whether the actor is said to have engaged in behaviors publicly
(solid) or privately (lines). Significant contrasts denoted with (*). From left to right: private generosity N = 2,397, public generosity N = 2,430,
private impartiality N = 2,082, public impartiality N = 2,071. b) Random effects meta-analysis of the virtue*observability interaction on trait
ratings across 13 experiments (E10 only investigated generosity), N = 8,317. Effect sizes are shown as partial correlation coefficients; error bars
indicate 95% CIs. The relative sizes of the boxes indicate the weighting assigned to the experiments by the meta-analysis.
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Kraft-Todd et al.
privately generous actors are perceived as equivalently virtuous (contrast = −3.17, 95% CI
[−8.65, 2.31], Scheffe’s t = −1.93, p = .571), whereas publicly generous actors are perceived
as significantly less virtuous (contrast = −6.23, 95% CI [−11.71, −.75], Scheffe’s t = −3.79, p =
.014). We interpret this result as showing that, consistent with our terminology, observers discount
public virtue. In these experiments, impartial actors’ virtue was not discounted (comparing public
to private observability conditions: contrast = −.43, 95% CI [−5.95, 5.09], Scheffe’s t = −.26, p =
1.000), so this comparison cannot be made for impartiality. Still, these results are consistent with
one motivation for our differential virtue discounting hypothesis: although both conformity with
social norms (Ohtsuki & Iwasa, 2006) and “morally motivated deviance” (Cramwinckel et al.,
2015) may be means by which to enhance one’s reputation, our baseline condition results are
consistent with the idea that perceived reputation management (through publicly observable vir-
tuous behavior) may negatively impact observers’ perceptions of actors’ virtue more strongly in
the case of the latter (here, generosity) compared to the former (here, impartiality).
Discussion
Here we provide robust evidence in support of both of our first two preregistered hypotheses.
First, our results demonstrate virtue discounting; participants rated public actors as less
virtuous than private actors. Second, our results demonstrate differential virtue discounting;
participants discounted public (compared to private) generosity to a greater extent than they
discounted public (compared to private) impartiality. It is worth noting that, in both analyses,
although observability reduces participants’ ratings of actors’ trait virtue, public actors are still
qualitatively perceived as virtuous (i.e., mean ratings are above the response scale midpoint).
These results are consistent with much previous work showing virtue discounting of generosity
(e.g., Lin-Healy & Small, 2012). Further, it is the first demonstration, to our knowledge, of
virtue discounting of impartiality. Finally, we provide evidence in support of the directionality
implied by our virtue discounting terminology. Namely, participants rate publicly generous
actors as less virtuous than privately generous actors and also generous actors described with-
out observability information (i.e., the baseline condition), but they do not rate the latter two
types of actors differently. This result implies that public virtue is discounted (although without
this evidence it might have been argued that private virtue is rewarded ). Next, we turn to our
analyses showing motivational inferences as a mechanism of observability in virtue
discounting.
ANALYSIS 2. VIRTUE DISCOUNTING DUE TO OBSERVABILITY CAN BE EXPLAINED
BY MOTIVATIONAL INFERENCES
The purpose of Analysis 2 is to explore the role of motivational inferences as a mechanism of
observability in virtue discounting, testing our third preregistered hypothesis (in E8, E9, and
E11–13) that virtue discounting will be explained by observers’ inferences that public actors
have more selfish motivations than private actors. It would follow from our previous results
to explore how motivational inferences mediate the virtue * observability interaction, i.e.,
accounting for the differential virtue discounting effect (this analysis presented in Supplement
Section 5). An important result of that analysis, however, is that there are not qualitative dif-
ferences in the motivational inferences driving virtue discounting of generosity compared to
impartiality (i.e., it is not the case that different types of motivations explain virtue discounting
for each virtue, only the degree to which observers infer these motivations). We acknowledge
that this may be due to the fact that our exploration of motivational inferences was not exhaus-
tive (and comment on this issue in greater detail in the General Discussion). That is, a similar
investigation employing a broader range of motivational inferences might find that there are
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distinct motivational inferences driving virtue discounting in generosity compared to impartial-
ity. Though we admit this possibility, here we present an analysis of how motivational infer-
ences explain virtue discounting, i.e., collapsing across generosity and impartiality.
Additionally, we believe that our investigation of the mechanism of observability in virtue
discounting could be of greater theoretical interest (i.e., than such an analysis of differential
virtue discounting) because it could suggest a generalizable mechanism explaining virtue dis-
counting via motivational inferences across an even broader range of virtues. Since we only
use two virtues as stimuli, further research will be needed before such conclusions could be
drawn. Still, we believe our analysis is an important first step towards such work.
Methods
We use data from all experiments in which we measured motivational inferences (E6–9 and
E11–13; N = 4,087; 49.9% female, average age = 37.9 years). We present correlations among
these items in Supplement Section 6. Here we present an exploratory factor analysis (EFA;
preregistered in E8, E9, and E11–13) of motivational inference items to better understand their
latent structure, and then fit a multiple mediation model using these factor scores. We
constructed generalized structural equation models to compute the mediation results (see
General Methods for more details), and present alternative model specifications in
Supplement Section 7.
Results
We begin with an EFA (preregistered in E8, E9, and E11–13) of our six motivational inference
items using iterated principal factors and oblique rotation. The analysis yielded two factors
explaining 95.5% of the variance. Factor 1 explained 61.0% of the variance, and items with
high loadings (> .6) war: moral rule, virtue identification, and other-benefit. Following our
previous work (Kraft-Todd et al., 2022), we labeled Factor 1 “principled” because these moti-
vations pertain either to actors’ moral beliefs/identity (d.h., moral rule and virtue identification)
or prosociality (other-benefit). Factor 2 explained 34.4% of the variance, and we labeled
it “reputation-signaling” due to high loadings (> .6) by the items: reputational benefit and
self-benefit.
We note, Jedoch, that our norm-signaling item loads almost equivalently on these factors
(principled = .39; reputation-signaling = .45). Because norm-signaling did not load uniquely
on either factor, and also because we are specifically interested in this novel construct, Wir
therefore conduct a second EFA omitting this item, with the intention to use the resulting factor
scores in addition to norm-signaling ratings as mediators in our subsequent analysis. Das
second EFA (also using iterated principal factors and oblique rotation) retains the same two
factors, on which all items load as described above. We observe that they also explain sim-
ilar proportions of the variance among motivational inference items ( principled = 69.2%;
reputation-signaling = 28.0%), and that these factors are moderately and negatively corre-
verspätet (r = −.46).
Nächste, we examine the mediation of observability on trait ratings by the two motivational
inference factor scores plus the norm-signaling item (collapsed across virtue, controlling for
Experiment and the covariance among mediators). Participants infer that, compared to private
actors, public actors have significantly lower principled motivation (b = −.56, 95% CI [−.62,
−.50], P < .001; see Figure 2), and significantly higher reputation-signaling motivation (b =
.67, 95% CI [.62, .73], p < .001) as well as norm-signaling motivations (b = .28, 95%
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Figure 2. The effect of observability on virtue discounting is explained by inferences that actors
have lower principled motivations. Shown is a generalized structural equation model (showing
multiple mediation) of the effect of observability on trait ratings by motivational inference factor
scores and norm-signaling item collapsed across virtue (N = 4,087). Bottom arrow (black) represents
the effect of the observability manipulation (public compared to private condition) on trait ratings
with (b) and without (b’) mediators as covariates. From left-to-right, the first set of arrows represents
the effect of the observability manipulation on mediators, and the second set of arrows represents the
correlation of mediators with trait ratings. Line thickness represents correlation strength; “+” and “−”
represent correlation direction; all variables standardized for this analysis.
CI [.22, .34], p < .001). Next, we find that participants’ trait ratings are significantly associated
with their motivational inferences, such that higher principled (b = .55, 95% CI [.53, .58], p <
.001) and norm-signaling (b = .05, 95% CI [.03, .07], p < .001) inferences are associated with
higher trait ratings, while higher reputation-signaling inferences are associated with lower trait
ratings (b = −.07, 95% CI [−.09, −.04], p < .001).
Finally, we turn to the mediation results. Restating the virtue discounting result we present
in Analysis 1, the total effect of observability on trait ratings is significant, such that participants
rate public actors as less virtuous than private actors (b = −.36, 95% CI [−.41, −.31], p < .001).
The direct effect of observability on trait ratings (i.e., accounting for indirect effects through
motivational inferences) is not significant (b’ = −.02, 95% CI [−.05, .02], p = .418), implying
full mediation (95.6% of the total effect). Calculating indirect effects as percent of total effect,
principled motivation accounts for 86.6% of this mediation, reputation-signaling motivation
accounts for 12.7%, and norm-signaling motivation accounts for −3.7%.
Discussion
Here we provide evidence consistent with an explanation of observability’s effect on virtue
discounting through motivational inferences. In short, participants’ motivational inferences
(i.e., reputation-signaling factor score, principled motivation factor score, and norm-signaling
item) mediate 95.6% of the effect of our observability manipulation (i.e., public vs. private
conditions) on trait ratings (collapsed across virtue condition). Although our reputation-signaling
and principled motivational inference factors intuitively seem like conceptual opposites, we
note that they are interestingly only moderately negatively correlated (r = −.46). Further, our
finding that the norm-signaling motivational inference item does not uniquely load on either of
our two other motivational inference factors suggests that this construct may have a unique
role in contributing to an explanation of virtue discounting (Kodipady et al., 2021).
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The results of this analysis only weakly support our third preregistered hypothesis (i.e., that
virtue discounting will be explained by observers’ inferences that public actors have more
selfish motivations than private actors). Despite the finding that an increase in (“selfish”)
reputation-signaling motivational inferences account for 12.7% of the virtue discounting effect,
86.6% of the effect was explained through a decrease in principled motivational inferences.
Our mediation result is robust to alternative model specifications, including one in which we
model the mediating effect of the reputation-signaling factor score through the principled
motivation factor score (see Supplement Section 7). That is, it might have been the case that
participants perceived publicly virtuous actors to have greater reputation-signaling motivation,
and therefore participants perceived them to have lower principled motivation, but our alter-
native model specification does not support such an account. This finding stands somewhat at
odds with previous work showing that selfish motivations account for virtue discounting (e.g.,
Newman & Cain, 2014), although it should be noted that previous work did not simulta-
neously test multiple motivations that might explain this effect.
ANALYSIS 3. OBSERVABILITY DOES NOT CAUSE VIRTUE DISCOUNTING WHEN
OBSERVERS KNOW ACTORS’ MOTIVATIONS
The purpose of Analysis 3 is to provide stronger causal evidence that motivational inferences
explain why observability causes virtue discounting. Our results from Analysis 2 suggest that
observability engenders ambiguity in observers’ motivational inferences; i.e., observers can
attribute different—and even conflicting—motivations to publicly virtuous actors. To reiterate,
participants inferred that, compared to private actors, public actors had lower principled moti-
vation and higher reputation-signaling motivation (both associated with participants rating
actors as less virtuous). Yet, participants also inferred that public actors had higher norm-
signaling motivation, which is associated with participants rating actors as more virtuous.
Rather than rely on correlational mediation (as in Analysis 2), here we leverage a design
feature of many of our experiments (E1-6, and some conditions in E10 and E14) in which we
explicitly manipulated actors’ motivation alongside observability. By comparing the effect of
our observability manipulation among conditions in which we stipulate actors’ motivation to
those in which we do not (as in E7-9, E11-13, and other conditions in E10 and E14), we can
test the “motivational ambiguity hypothesis” (preregistered in E10 and E14): the main effect of
observability (i.e., public vs. private) on ratings of trait virtue will be substantially reduced when
we stipulate actors’ motivation compared to when we do not. To put this hypothesis plainly:
observers may discount virtue because they are uncertain about actors’ motivations (as in our
“no motive” conditions, and presumably in real life). Explicitly providing people with informa-
tion about actors’ motivations, therefore, should drastically reduce the effect of observability
on perceptions of actors’ virtue.
Methods
We use data from all conditions in all experiments in which we manipulated observability
(same as Analysis 1; N = 8,969; 51.2% female, average age = 37.8 years), subgrouping by
manipulations of actors’ motivation in our hypothetical vignettes (principled, N = 2,151 vs.
reputation-signaling, N = 2,150 vs. no motivation stipulated, N = 4,671). Although details
varied by experiment (see Table 1), our manipulations of actor motive generally stipulated
that actors either simultaneously had principled but not reputation-signaling motivations or
reputation-signaling but not principled motivations. For conditions in which we did not
stipulate actor motivation, we simply omitted language regarding actors’ motivation.
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As in Analysis 2, here we are primarily interested to explore the observability*motive inter-
action collapsed across virtues; we therefore include the virtue manipulation as a covariate in
the results presented here (see Supplement Section 3 for results disaggregated by virtue as well
as a demonstration that these results are robust to simply omitting the virtue manipulation from
the model presented below). As a result, the regression analysis presented here predicts moral
goodness and trait ratings by the interaction of the observability manipulation (public vs. pri-
vate) and the actor motive manipulation (reputation-signaling vs. principled vs. none), with
Experiment and the virtue manipulation as covariates.
Results
Overall, we find a significant interaction between observability and motive on trait ratings (F(2,
8960) = 26.36, p < .001, d = .15). Sensitivity analysis revealed that (at p = .05 and power =
80%) the minimum detectable effect size for this test is d = .07. When we do not stipulate actor
motivation, we again observe virtue discounting; i.e., public actors are rated as less virtuous
than private actors (contrast = −5.60, 95% CI [−7.41, −3.78], t = −10.27, p < .001, see
Figure 3).
Consistent with our hypothesis (preregistered in E10 and E14), we observe that public and
private actors are not rated differently on trait virtue when we stipulate that actors have repu-
tation-signaling motivation (contrast = −2.59, 95% CI [−6.19, 1.01], t = −2.39, p = .334) or
principled motivation (contrast = 2.80, 95% CI [−.82, 6.43], t = 2.58, p = .249).
Discussion
In this analysis, we show that observability does not affect participants’ ratings of actors’ trait
virtue when we stipulate actors’ motivation. Specifically, when we describe actors as having
principled (but not reputation-signaling) motivations or reputation-signaling (but not
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Figure 3. Observability does not affect actors’ perceived virtue when their motivation is stipu-
lated. Shown are means (with 95% CIs) of trait ratings (0–100 unmarked slider), as a function of
whether the actor is said to have engaged in behaviors privately (lines) or publicly (solid) and
whether the actor’s motivation is stipulated as: none (yellow), reputation-signaling (purple), princi-
pled (orange). Significant contrasts denoted with (*). From left to right: private no motive N = 2,312;
public no motive N = 2,360; private reputation-signaling N = 486; public reputation-signaling
N = 1,669; private principled N = 1,681; public principled N = 472.
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principled ) motivations, participants’ trait ratings do not differ by observability condition (i.e.,
public vs. private). We note that, qualitatively, participants rate actors’ trait virtue slightly pos-
itively (i.e., close to, but above the response scale midpoint) when we stipulate that actors
have reputation-signaling motivations. Comparing these results to those of Analysis 1, it is also
interesting to note that the magnitude that participants discount actors’ trait virtue is roughly
twice as great when we explicitly stipulate actors’ reputation-signaling motivation (as we do
here) compared to when we merely describe actors’ behavior as publicly observable (as in
Analysis 1).
This analysis provides stronger causal evidence of the account we propose in Analysis 2:
information about actors’ motivations impacts observers’ ratings of actors’ trait virtue. When
this information is not explicit—as in the design of Experiments investigated in Analysis 2 and
presumably in real life—people use the observability of actors’ behavior as a proxy to infer
actors’ motivation. When people know actors’ motivation (as in the design of Experiments
investigated in this analysis), however, this information determines their trait judgment, regard-
less of the observability of actors’ behavior.
GENERAL DISCUSSION
Across three analyses martialing data from 14 experiments (seven preregistered, total N =
9,360), we provide robust evidence of virtue discounting. In brief, we show that when actors’
behavior is observable, people are less likely to attribute this behavior to actors’ virtue. In
Analysis 1—which includes a meta-analysis of all experiments we ran—we show that observ-
ability causes virtue discounting (supporting our first preregistered hypothesis), and that this
effect is larger in the context of generosity compared to fairness (as impartiality; supporting
our second preregistered hypothesis). In Analysis 2, we provide suggestive evidence that par-
ticipants’ motivational inferences mediate a large portion (72.6%) of the effect of observability
on their ratings of actors’ trait virtue (supporting our third preregistered hypothesis). In Analysis
3, we show that when we experimentally manipulate actors’ motivation, observability loses its
significant effect on participants’ judgments of actors’ trait virtue (providing stronger evidence
supporting our third preregistered hypothesis). We now consider the contributions of our find-
ings to the empirical literature as well as limitations of the present investigation. Finally, we
conclude with practical implications for effective prosocial advocacy.
Contributions to the Literature
Consistent with the majority of studies demonstrating virtue discounting (e.g., Newman &
Cain, 2014), we show robust evidence of this effect in the context of generosity (Analysis 1).
To this literature, the present investigation adds novel evidence that virtue discounting also
occurs in the context of fairness (as impartiality), though to a lesser extent. Our investigation
of motivational inferences as a mechanism of observability on ratings of trait virtue (Analysis 2)
yield insights into: 1) the structure of motivational inferences; 2) a relatively novel motivational
construct; and 3) mechanistic explanations of virtue discounting via motivational inferences.
First, following prior work (e.g., Lin-Healy & Small, 2012), we hypothesized that virtue dis-
counting will be explained by observers attributing selfish motivations to publicly virtuous
actors. Our exploratory factor analysis of motivational inference items yielded two factors that
we labeled principled and reputation-signaling, and although these factors intuitively seem like
conceptual opposites, they are only moderately negatively correlated (r = −.46). It may be
compelling to broadly conceptualize the construct of “motivation” as a bipolar scale with
the endpoints “selfish” and “selfless”, but here, we show that the conceptually “selfish”
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reputation-signaling motivation factor and the conceptually “selfless” principled motivation
factor are less strongly (though still negatively) correlated than one might expect. It is intui-
tively plausible that actors might be motivated both to help others and to have others think
well of them. Future work might therefore eschew a simplistic unidimensional conceptualiza-
tion of motivational inferences, instead taking a more pluralistic approach and extending the
present work to include other motivations for prosocial behavior suggested by the literature
(Narvaez & Snow, 2019; Reiss & Havercamp, 1998).
Second, we were surprised to find that our norm-signaling motivational inference item was
not uniquely captured by either of the two factors resulting from our exploratory factor anal-
ysis. One previous study has demonstrated the importance of norm-signaling motivational
inferences in explaining perceptions of individuals sharing their gender pronouns (Kodipady
et al., 2021), although we are unaware of other work exploring this construct. Although it
might be argued that the mediation demonstrated by this item (i.e., explaining the effect of
observability on trait ratings) was relatively minor (−7.3%), it is worth noting that this was
roughly equivalent in magnitude to the effect of our reputation-signaling motivation factor
(9.3%; technically, an “opposing mediation”; Kenny et al., 1998), which represents the most
frequently cited motivational explanation of virtue signaling in previous work.
Third, perhaps the most puzzlingly counterintuitive finding we present is that virtue dis-
counting is largely explained by observers’ inferences that public actors have lower principled
motivations (accounting for 72.3% of the effect), and that reputation-signaling inferences medi-
ate only 9.3% of this effect. Building on prior work, we expected that the effect of observability
on virtue discounting would be explained by inferred selfish motivations; instead, it appears
that it is actually a decrease in (conceptually “selfless”) principled motivational inferences,
rather than an increase in (conceptually “selfish”) reputation-signaling motivational inferences
that explains virtue discounting in our paradigm. We rule out a possible alternative explana-
tion, that reputation-signaling motivational inferences mediate the effect of principled motiva-
tional inferences on trait ratings (see Supplement Section 7). Still, we believe more research is
needed before placing great confidence in this conclusion. For example, previous demonstra-
tions of virtue discounting often employ within-subjects comparisons of public vs. private
actors (Lin-Healy & Small, 2012), but we compare public vs. private actors in between-
subjects designs. Consistent with the literature on “joint vs. separate evaluation” (Hsee
et al., 1999), it could be the case that reputation-signaling motivational inferences would
emerge as the primary mechanism in a within-subjects design (see, e.g., a paradigm eliciting
such reversals of moral judgment; McManus et al., 2020).
Although more research is needed to better understand which specific motivations contrib-
ute to virtue discounting, our results from Analysis 3 strengthen our interpretation that motiva-
tional inferences can explain the effect of observability in virtue discounting. Additional insight
about the role of motivational inferences in virtue discounting is provided by comparing our
results from Analysis 3 with our “baseline” (i.e., no observability information) conditions in
Analysis 1. Taken together, these results suggest that people assume that actors have principled
motivations, both when these actors’ behavior is conducted privately and also when informa-
tion about the observability of their behavior is absent. It is unclear whether this pattern of
results might be attributed to a simple “behavior-motivation congruency heuristic” (i.e., per-
haps people tend to think that the valence of actors’ motivation matches their behavior) or
reflects some sort of generalized trust (i.e., people assume others have good intentions).
Across our analyses, it is interesting to note that the relatively limited information we pro-
vide about actors’ behavior is sufficient to cause participants to rate actors as generally
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virtuous. Although observability reduces participants’ ratings of actors’ trait virtue—and explic-
itly stipulating actors’ reputation-signaling motivation roughly doubles that effect—participants
still qualitatively rate actors positively. These results provide some evidence of people’s gen-
eral willingness to charitably interpret others’ prosocial behavior. In light of this, it may provide
justification—via promoting accurate assessment of others’ moral character and counteracting
exploitation by manipulative actors—for some people to express skepticism in reaction to
others’ observable prosocial behavior, including posting their good deeds on social media
(i.e., speculating about others’ “virtue signaling”).
We conclude these considerations by contrasting our results with a puzzlingly divergent
set of results. In many situations, observers react to virtuous behavior with positive valence
emotions (see work on, e.g., elevation; Haidt, 2003), and further, that people often emulate
virtuous behavior when they observe it (Thomson & Siegel, 2017). Yet, beyond the virtue
discounting literature we discuss here, other work also suggests that such “do-gooders” are
frequently derogated for their morally-motivated behavior (e.g., Sparkman & Attari, 2020).
We propose a fascinating question for future research to explore: what individual- and/or
situational-factors moderate such celebration (Bai et al., 2019) versus derogation (Minson &
Monin, 2012) responses in social comparison (Mussweiler, 2003)?
Limitations
The present investigation is not without shortcomings. We believe some caution is warranted
regarding the mechanistic account of the effect of observability on trait virtue through motiva-
tional inferences given a comparison of our results across Analyses 2 and 3. In Analysis 3,
when we stipulate that virtuous actors have reputation-signaling (and not principled ) motiva-
tions, participants’ ratings of actors’ trait virtue are reduced to a greater extent than when we
merely describe public actors (with no motive stipulated). Our manipulation of actor motiva-
tion thus may have been an overdetermination of our proposed mechanism, which could
imply, for example, that potential mechanisms we failed to consider have a milder effect on
trait ratings, or that there are individual differences in our proposed motivational inference
mechanism. It could also be the case that observers infer that public actors have mixed
motives, e.g., both principled and reputation-signaling motivations (see Analysis 2, correlation
of these factors, r = −.46), which is obscured by our manipulations in Analysis 3 (e.g., we
describe actors having reputation-signaling but not principled motivations).
Although we provide evidence that observers’ motivational inferences are a mechanism of
virtue discounting, we do not claim that this is the only mechanism of virtue discounting. For
example, the “bottom-up” manner in which the behaviors we used as stimuli were generated
(Kraft-Todd et al., 2022) involved participants rating a set of behaviors expressing each virtue
on 9 dimensions (e.g., descriptive normativity). It could be the case that another mechanism of
virtue discounting are these underlying dimensions; i.e., if prototypical behaviors expressing
virtues are systematically perceived differently along these (as well as other) dimensions, such
variation could explain differential virtue discounting. Consider, for example, one dimension
used in this prior work: the potential for actors to engage in these behaviors anonymously. If
behaviors that prototypically express some virtues are lower on this dimension (i.e., they are
necessarily publicly observable) than those that prototypically express other virtues, we might
expect less discounting of the former compared to the latter. This is because actors’ discretion
about observability in the latter case provides observers an opportunity to infer the motivations
for actors’ choice (i.e., to do these behaviors publicly), which might include reputation-
signaling. Future work might therefore explore the contribution of such underlying dimensions
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of behaviors prototypically expressing virtues as another potential mechanism of virtue
discounting.
Additionally, we provide two empirical hypotheses among our motivations for our differ-
ential virtue discounting hypothesis that we do not test here. First, that perceived reputation
management (through publicly observable virtuous behavior) will negatively impact observers’
perceptions of actors’ virtue more strongly in cases of “morally motivated deviance”
(Cramwinckel et al., 2015) compared to conformity with social norms (Ohtsuki & Iwasa,
2006). Although we believe that the results of our “baseline condition” experiments (see
Analysis 1) are consistent with this account—with these reasons for virtue discounting instan-
tiated, respectively, in our generosity and fairness (as impartiality) conditions—directly testing
this hypothesis represents a promising direction for future work. Second, we posited that virtue
discounting is less likely to affect categorical norms (as with fairness/impartiality) than contin-
uous norms (as with generosity). Although we believe this is beyond the scope of the current
work, it represents another specific empirical hypothesis that we encourage future work to
explore.
The generalizability of our findings may be limited because we investigated only two vir-
tues, measured only six items of motivational inference, and our methods relied on exclusively
hypothetical vignette scenarios administered to convenience samples. There is a substantial
literature investigating other virtues (e.g., Peterson & Seligman, 2004)—and despite ambiguity
in virtue concepts and their operationalization (McGrath, 2014)—we leave it to future work to
examine whether the virtue discounting effect generalizes to other virtues (see, e.g., research
on trustworthiness; Jordan, Hoffman, Bloom, et al., 2016). Similarly, we also recognize that
motivation (like virtue) is a multidimensional construct (e.g., Reiss & Havercamp, 1998) and
that previous work has suggested that distinct virtues are driven by distinct motivations
(Narvaez & Snow, 2019). Future work might also measure a greater range of motivations for
each virtue (see, e.g., Kodipady et al., 2021). For example, motivational inferences relevant to
the present work that future research might explore are the degree to which observers believe
that actors were motivated to: 1) demonstrate their moral superiority; 2) impose their values on
others; and 3) manipulate others into behaving similarly (the latter two representing a negative
interpretation of our “norm-signaling” item). Due to the limitations of drawing generalizable
conclusions about moral judgment from hypothetical vignette studies (Feldman-Hall et al.,
2012) and online convenience samples (Simons et al., 2017), we encourage future work to
employ more diverse methods.
We also expect that different cultures may discount virtue differently. Fundamental to our
definition of virtue is that the value of a trait that constitutes virtue derives from the social
norms of the culture under investigation. Therefore, in addition to merely replicating our
results in non-WEIRD samples (Henrich et al., 2010), we propose that our results are likely
to vary in accordance with the value that different cultures place on different virtues. Beyond
considering “culture” at such a broad level of analysis (e.g., nationality), we further encourage
future work to consider narrower social identities (e.g., workplace) that might inform group
members’ perception of virtues. Because individuals’ perception of virtues may be informed
by social norms belonging to any of the social groups with which they identify—and compre-
hensively documenting these may be beyond the scope of any particular investigation—we
finally suggest that future studies exploring perceptions of virtue incorporate measures of indi-
vidual differences in participants’ motivational inferences. One source of variation might be
people’s valuation of the virtues they are asked to make judgments about in others; e.g., in the
present context, such data might show that individuals who more highly value particular
virtues (e.g., generosity) are more likely to discount publicly observable behavior expressing
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those virtues. Another source of variation might be broader measures of sociability; e.g., peo-
ple who are generally less trusting of others may be generally more skeptical of the motivations
for others’ prosocial behavior.
In addition to these specific limitations, we also believe that our studies provide directions
for future research that are beyond the scope of the current work. For example, we exclusively
explored virtue discounting in the context of virtuous (i.e., morally good) behavior, although
future work might consider exploring this phenomenon in the context of unvirtuous (i.e.,
morally bad) behavior.
Practical Implications and Conclusion
Finally, our findings yield insights about effective advocacy of real-world virtuous behaviors.
We started with a paradox of public prosociality: while others can only infer your virtue and
learn from your prosocial example by observing your behavior, they simultaneously may be
less likely to attribute your behavior to your virtue when your behavior is observable. Our
results are consistent with this paradox of public prosociality, particularly when we consider
the “opposing mediation” (Kenny et al., 1998; i.e., the negative mediation effect) of our norm-
signaling item on trait ratings. To reiterate: the effect of observability on motivation inference is
in the same direction for norm-signaling and reputation-signaling motivations, whereas the
effect of motivation inference on trait virtue is in the same direction for norm-signaling and
principled motivations. In other words, observable actors can be perceived positively if
observers infer that actors have norm-signaling motivations; yet, observably virtuous actors
also can be perceived negatively if observers infer that actors have low principled motivations
(and also high reputation-signaling motivations). This pattern of results suggests that, to be per-
ceived positively and potentially influence observer behavior, actors should consider how to
convincingly convey norm-signaling motivations without engendering perceptions of low
principled motivations (and also high reputation-signaling motivations).
Developing effective strategies for such communication is crucial for real-world advocates,
and one hint of how this might be accomplished is provided by recent work on sharing gender
pronouns in the workplace (Kodipady et al., 2021). One finding from this work is that a trans-
gender (compared to a cisgender) advocate is more likely to be perceived as norm-signaling
and less likely to be perceived as reputation-signaling. These results suggest that recruiting
advocates whose identity is congruent with the target issue may mitigate reputation-signaling
attributions. This work leaves open the question of how non-identity-congruent (in the context
of that work, cisgender) advocates can be effective communicators, highlighting another direc-
tion for future research related to “effective ally-ship” (Radke et al., 2020).
Further, following our preceding discussion regarding a costly signaling account of virtue
discounting, it could be the case that for virtues where “selfish” and “selfless” motivations are
perceived more dichotomously, actors need to more clearly demonstrate their “selfless” moti-
vations to avoid observers discounting their virtue. This concern echoes our second preregis-
tered hypothesis (“differential virtue discounting”), which suggests that practitioners (as well as
researchers) should carefully examine which virtues they are displaying in their advocacy, and
consider whether these are particularly susceptible to virtue discounting and diluting their
overall message.
If prosocial advocates can credibly demonstrate that they are motivated by principles and
norm-signaling, and not by reputation-signaling—particularly in the context of some virtues
(e.g., generosity)—they may be able to resolve the paradox of public prosociality. One might
wonder, “how can prosocial advocates credibly demonstrate their motivation?” In addition to
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a direction for future research, we leave this question to prosocial advocates as a prompt for
reflection. The answer will undoubtedly be contingent on the individual, audience, and set-
ting, but finding it may be a key to catalyzing the contagion of prosociality.
ACKNOWLEDGMENTS
We would like to thank the members of the Morality Lab and the reviewers for their generous
feedback.
FUNDING INFORMATION
This research was made possible by funding by the John Templeton Foundation, The Virtue
Project at Boston College, and NSF award #1627157.
OPEN PRACTICES
Preregistrations were conducted for: E8 (https://aspredicted.org/ FLG_VRD), E9 (https://
aspredicted.org/NUP_ESB), E10 (https://aspredicted.org/FCO_HXM), E11 (https://aspredicted
.org/2Y2_YKT), E12 (https://aspredicted.org/AES_HGO), E13 (https://aspredicted.org/G6S
_S35), and E14 (https://aspredicted.org/SHW_9PN). All data and code are publicly available
at: https://osf.io/sud3m/?view_only=380a169770b9474f93d2b5b73adc7410.
SUPPORTING INFORMATION
Details on our supplementary materials are as follows:
(cid:129) Supplementary Materials: We provide supplementary materials—including supplemen-
tary analyses and complete experimental instructions—in a Word file available for
download from the journal’s website as a separate file named “Virtue Discounting
Supplemental Materials.docx”.
(cid:129) Code and Data Repository: The code and data used for our statistical analyses are avail-
able at: https://osf.io/sud3m/?view_only=380a169770b9474f93d2b5b73adc7410.
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