Differential virtue discounting: Public generosity is seen as more selfish than public impartiality

Gordon T. Kraft-Todd*a, Max Kleiman-Weinerb, Liane Younga aDepartment of Psychology, McGuinn 300, 140 Commonwealth Ave, Boston College, Chestnut Hill, MA 02467 ; bDepartment of Psychology, Harvard University, Cambridge, MA 02138

*Corresponding author: [email protected]

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, virtue Introduction

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: observers can 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 have completed 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 Analyzed Data used size Pre- Experiment Design features variables Conditions in analysis (all ~100 registered? (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) 7 612 beahviors, [motivations:] x 3 (observability: 1,2 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] She is especially 3 when she is with [generous/impartial] others, she is when others are - Making sure everyone at a especially watching her act since social gathering receives the [generous/impartial] she knows that her same amount of food (e.g. when 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 like Doctors without Borders with her values. 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 - Donating blood during a blood Though she is 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 when others are against particular genders or [generous/impartial] watching her act. ethnicities don't enter into the 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 the primary 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 an effect 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, p<.001), and a Wald test reveals that the interaction effect of virtue and observability does not differ between the dependent measures (F(1,3581)=2.73, p=.098). Importantly, we note that although the results we report here are in aggregate, because the findings do not significantly differ by experiment, they represent nine independent replications.

Results As predicted (H1), we observe a significant effect of observability on trait ratings (F(1,3581)=728.03, p<.001, d=.90), such that participants rate public displays (m=69.65, 95% CI [68.65, 70.65]) as demonstrating virtue significantly less than private displays (m=86.54, 95% CI [85.80, 87.28], see Figure 1). There is no significant effect of virtue on trait ratings (F(1,3581)=.03, p=.855, d<.01). Also as predicted (H2), there is a significant interaction between virtue and observability on trait ratings (F(1,3581)=47.68, p<.001, d=.23). Computing pairwise comparisons of estimated marginal cell means corrected for multiple comparisons (using Scheffe’s adjustment; Winer, Brown, & Michels, 1991; though results are equivalent using Bonferroni correction), we observe two interesting patterns. First, for both virtues, public displays are rated as demonstrating the virtue significantly less than private displays (generosity public: m=67.41, 95% CI [65.98, 68.84]; generosity private: m=88.63, 95% CI [87.78, 89.48], Scheffe’s t=-24.00, p<.001, d=1.13; impartiality public: m=71.89, 95% CI [70.50, 73.27]; impartiality private: m=84.44, 95% CI [83.24, 85.64], Scheffe’s t=-12.58, p<.001, d=.67). Second, private displays of generosity are rated as demonstrating the virtue significantly more than private displays of impartiality (Scheffe’s t=4.21, p<.001, d=.20), while public displays of generosity are rated as demonstrating the virtue significantly less than public displays of impartiality (Scheffe’s t=-4.44, p<.001, d=.21). Central to H2, using seemingly unrelated regressions (Zellner, 1962), we observe that the standardized coefficient on observability is significantly larger for generosity (b=-.52, 95% CI [-.56, -.48]) than impartiality (b=-.31, 95% CI [-.35, -.26], χ2(1)=48.76, p<.001).

Fig 1. Actors who publicly display virtuous behavior are perceived as less virtuous than actors who privately display virtuous behavior, and this effect is greater for generosity than impartiality. Shown are means (with 95% CIs) of trait ratings (0-100 unmarked slider), as a function of whether the actor is said to engage in behaviors that are generous (green) or impartial (blue) and whether these behaviors are said to be displayed in public (solid) or private (lines).

In Analysis 1, we provide evidence in support of the first two hypotheses. Consistent with the virtue discounting hypothesis (H1), actors who publicly display virtuous behavior are perceived as less virtuous than actors who privately display virtuous behavior. Consistent with the differential discounting hypothesis (H2), we find that this effect is greater for generosity than impartiality. When we replicate this analysis restricting to the preregistered data, we observe virtue discounting for generosity only and not for impartiality, strong evidence of differential virtue discounting (see SI Section 4).

Analysis 2: Perceived selfish motivations explain (differential) virtue discounting

The purpose of Analysis 2 is to investigate the mechanism we propose for (differential) virtue discounting: perceptions of selfish motivations. We conduct two multiple mediation models to test: the multiple mediation hypothesis (H3), that virtue discounting (collapsed across generosity and impartiality) is explained by perceived selfish motivations; and the multiple moderated mediation hypothesis (H4), that the greater difference in virtue discounting for generosity compared with impartiality is explained by greater perceived selfish motivations for public (vs. private) displays of generosity compared with public (vs. private) displays of impartiality.

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 p<.05 except norm-signaling and 1st-party benefit, Bonferroni corrected for 15 simultaneous comparisons).

Table 3. Shown are Pearson’s correlation coefficients (significant values in bold) among secondary dependent measures used in Analysis 2. “Self-oriented” motivations are displayed in purple and “moral” motivations are displayed in orange. Reputation 1st-party benefit Moral Norm-signaling Authentic 3rd-party benefit Reputation X Key 1st-party benefit 0.59 X r<0.2 Moral -0.36 -0.31 X 0.20.6 3rd-party benefit -0.23 -0.17 0.54 0.28 0.52 X

To better understand the correlation structure among our secondary dependent measures, we conduct a preregistered exploratory factor analysis with varimax (orthogonal) rotation and iterated principal factors. The analysis yielded two factors explaining 95.1% of the variance. Factor 1 (explaining 65.4% of the variance) we labeled moral motivations due to the high loadings (>.4) by the following items: 3rd-party benefit, and moral, norm-signaling, and authentic motivations. Factor 2 (explaining 29.7% of the variance) we labeled self-oriented motivations due to high loadings (>.4) by the following items: 1st-party benefit and reputational motivation. To test both mediation hypotheses, we construct preregistered structural equation models using standardized variables, and indirect effects are calculated using the multivariate delta method (Sobel, 1982). To investigate our multiple mediation hypothesis (H3), we test for the following associations, collapsing across virtue: observability (dummy coded so that 1=public and 0=private) with trait ratings and each of our six secondary dependent measures as well as each of our six secondary dependent measures with trait ratings. To investigate our multiple moderated mediation hypothesis (H4; following models 59 and 74 in Hayes, 2013; see Figure 3), we test for associations of each of our six secondary dependent measures by the interaction of observability (dummy coded so that 1=public and 0=private) and virtue, and we also test for associations of trait ratings by the interaction of observability and virtue as well as by the interaction of each of our six secondary dependent measures with virtue.

Fig 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] p <.001 p =.001 p =.136 b =.50 b =-.07 b =-.04 1st-party 95% CI [.41, .60] 95% CI [-.11, -.04] 95% CI [-.08, .01] benefit p <.001 p< .001 p =.138 b =-.65 b =.26 b =-.17 Moral 95% CI [-.74, -.56] 95% CI [.21, .30] 95% CI [-.23, -.11] p <.001 p <.001 p <.001 b =-.002 b =.05 b =-8.6e-5 Norm- 95% CI [-.10, .10] 95% CI [.02, .09] 95% CI [9.49e-4, 1.77e-3] signaling p =.975 p= .002 p =.928 b =-.55 b =.32 b =-.18 Authentic 95% CI [-.65, -.46] 95% CI [.27, .36] 95% CI [-.23, -.12] p <.001 p <.001 p <.001 b =-.46 b =.12 b =-.06 3rd-party 95% CI [-.55, -.36] 95% CI [.09, .16] 95% CI [-.10, -.01] benefit p <.001 p <.001 p= .013

The total effect of public display on trait ratings of virtue is significant (b=-.34, 95% CI [- .46, -.22], p<.001), but the direct effect is not (b’=-.04, 95% CI [-.11, .03], p=.264), implying full mediation (92.9% of the total effect). The motivational attributions responsible for this mediation (indirect effects as percent of total effect mediated; see Column 3) in descending order of magnitude are: authentic (33.1%), moral (31.7%), reputational (10.8%), 3rd-party benefit (10.5%), 1st-party benefit (6.8%), and norm-signaling (1.6e-4%). A second structural equation model tests the multiple moderated mediation hypothesis (H4): the greater difference in virtue discounting for generosity compared with impartiality will be explained by greater perceived self-oriented motivations for generosity compared with impartiality (see Figure 4; for ease of interpretation, we visualize the model split by virtue). We will again begin by describing the correlations in each model, and then we will investigate indirect, total, and direct effects of each mediation.

Fig 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], p<.001), but the direct effect is not (b’=- .03, 95% CI [-13, .07], p=.526), implying full mediation (95.6% of the total effect). The motivational attributions responsible for this mediation (indirect effects as percent of total effect mediated; see Column 5) are: authentic (32.1%), moral (29.0%), reputational (14.3%), 3rd-party benefit (14.2%), 1st-party benefit (4.6%), and norm-signaling (1.5%).

Table 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] p <.001 p <.001 p =.002 p =.231 p =.109 p =.605 b =.68 b =.32 b =-.05 b =-.09 b =-.03 b =-.03 1st-party 95% CI [.55, .82] 95% CI [.18, .45] 95% CI [-.11, .01] 95% CI [-.13, -.04] 95% CI [-.12, .06] 95% CI [-.07, .02] benefit p <.001 p <.001 p =.108 p <.001 p =.476 p =.211 b =-.89 b =-.41 b =.24 b =.29 b =-.21 b =-.12 Moral 95% CI [-1.02, -.76] 95% CI [-.54, -.28] 95% CI [.17, .30] 95% CI [.23, .36] 95% CI [-.33, -.09] 95% CI [-.18, -.06] p <.001 p <.001 p <.001 p <.001 p <.001 p <.001 b =-.12 b =.12 b =.09 b =.02 b =-.01 b =.003 Norm- 95% CI [-.25, .02] 95% CI [-.02, .25] 95% CI [.04, .14] 95% CI [-.02, .07] 95% CI [-.03, .01] 95% CI [-.01, .02] signaling p =.093 p =.100 p <.001 p =.321 p =.212 p =.723 b =-.84 b =-.27 b =.28 b =.34 b =-.23 b =-.09 Authentic 95% CI [-.97, -.71] 95% CI [-.40, -.13] 95% CI [.21, .35] 95% CI [.29, .40] 95% CI [-.35, -.12] 95% CI [-.13, -.05] p <.001 p <.001 p <.001 p <.001 p <.001 p <.001 b =-.71 b =-.21 b =.15 b =.10 b =-.10 b =-.02 3rd-party 95% CI [-.84, -.57] 95% CI [-.34, -.08] 95% CI [.08, .21] 95% CI [.05, .14] 95% CI [-.20, -.01] 95% CI [-.05, .01] benefit p <.001 p =.002 p <.001 p <.001 p= .031 p =.154

Next, we detail results explaining trait ratings of impartiality (see Figure 5b). Beginning with estimates of model fit; the model accounts for 54.6% of the variance in trait ratings of impartiality. Investigating the association of trait ratings of impartiality with the proposed mediators (see Table 5), we observe that trait ratings are significantly associated with all secondary dependent measures except reputational and norm-signaling motivations (see Column 2). We then turn to associations with the observability manipulation: observability is significantly associated with all secondary dependent measures except norm-signaling (see Column 4). Consistent with H3, and again replicating the result from the first structural equation model, motivations are affected by observability, 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 2) and negatively associated with trait ratings (see Rows 1-2, Column 4), while moral motivations are negatively associated with public display (see Rows 3-6, Column 2) and positively associated with trait ratings (see Rows 3-6, Column 4). The total effect of observability on trait ratings of impartiality is significant (b=-.34, 95% CI [-.46, -.22], p<.001), but the direct effect is not (b’=-.06, 95% CI [-.15, .03], p=.226), implying full mediation (83.5% of the total effect). The motivational attributions responsible for this mediation (indirect effects as percent of total effect mediated; see Column 6) are: moral (36.0%), authentic (27.4%), 1st-party benefit (8.2%), reputational (6.5%), 3rd-party benefit (6.2%), and norm-signaling (- 0.9%). In Analysis 2, we provide evidence in support of our hypotheses that perceived selfish motivation is the mechanism of virtue discounting (H3) and differential virtue discounting (H4). Consistent with H3, we find that the virtue discounting effect (collapsed across generosity and impartiality) is explained by inferred selfish motivations (i.e. higher self-oriented motivations and lower moral motivations). Consistent with H4, we find that differential virtue discounting is also explained by inferred selfish motivations, with participants inferring greater selfish motivations for public (compared to private) displays of generosity than public (compared to private) displays of impartiality. Comparing confidence intervals on the observed correlations, we also observe that this pattern is significant (i.e. CIs are non-overlapping) for the following relationships: a) participants perceive less authentic and moral motivations, less desire for 3rd- party benefit, and more desire for 1st-party benefit for public displays of generosity compared to public displays of impartiality (see Table 5, Columns 1-2); and that b) authentic motivation and desire 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).

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Supplementary 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...... 49

1. 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 randomly 2. 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, p<.001). This is consistent with an analysis across all 100 participant-generated behaviors, that acts of generosity were perceived as more costly to the actor than acts of impartiality (coeff=6.27, z=2.20, p=.028). This result is unsurprising, however, because greater costliness of generous compared with impartial behaviors for actors is definitionally true: whereas impartiality can often be costless (as in cases where the actor merely divides resources among others), generosity necessarily requires that the actor give their own resources to someone else.

Fig S1. Our participant-generated stimulus sets of generous and impartial behaviors did not differ across important dimensions—particularly moral goodness—except that generosity stimuli were perceived as more costly to the actor than impartiality stimuli. Shown are means (with 95% CIs) of ratings of moral goodness, descriptive normativity, injunctive normativity, benefit to the recipient, and cost to the actor (0-100 unmarked slider) across the generosity stimulus set (green) and impartiality stimulus set (blue).

In Supplemental Study 2, an independent sample of participants from those who generated acts of generosity and impartiality in Supplemental Study 1 rated an edited selection (k=100) of these acts. We selected three behaviors each of generosity and impartiality to serve as stimulus sets which did not differ significantly across important dimensions—particularly moral goodness—but also descriptive normativity, injunctive normativity, and benefit to the recipient. Consistent with these virtues’ definitions, however, generosity stimuli were perceived as more costly to the actor than impartiality stimuli. We employ each set of three acts as stimuli in Experiments 7-9.

Table S3. Average ratings of participant-generated acts (stimuli are highlighted).

generosity impartiality no. de inj ben cost moral avg range de inj ben cost moral avg range 1 37.6 53.7 86.1 84.7 86.8 69.8 49.2 64.5 79.9 83.6 43.9 88.4 72.1 44.5 2 61.5 66.9 79.4 68.4 81.4 71.5 19.9 60.3 73.9 71.5 43.4 87.3 67.3 43.9 3 47.6 58.5 74.6 54.8 76.8 62.5 29.3 42.7 51.3 46.7 50.1 65.0 51.2 22.2 4 46.9 49.4 70.1 76.2 55.7 59.7 29.2 63.0 77.8 62.7 25.5 84.6 62.7 59.1 5 46.6 62.4 71.5 40.1 81.8 60.5 41.6 76.9 83.5 78.7 44.0 87.0 74.0 43.0 6 43.3 44.8 49.2 56.5 46.9 48.1 13.2 79.3 81.5 81.7 54.6 88.6 77.1 33.9 7 34.3 38.7 65.3 77.0 65.4 56.1 42.6 69.4 79.0 77.5 48.3 89.3 72.7 41.0 8 51.3 60.1 70.5 44.8 75.3 60.4 30.5 17.1 52.5 31.6 64.2 77.4 48.6 60.3 9 44.3 51.0 73.6 63.3 74.7 61.4 30.4 52.6 68.5 67.2 55.1 74.8 63.6 22.2 10 46.5 58.2 76.9 54.4 85.7 64.4 39.2 77.1 78.6 71.2 38.9 80.1 69.2 41.2 11 68.8 81.5 79.8 68.5 90.7 77.8 22.2 54.9 66.1 72.7 68.8 67.3 65.9 17.8 12 63.5 65.0 65.0 48.6 71.4 62.7 22.8 69.7 83.0 69.1 38.0 83.6 68.7 45.6 13 28.2 45.7 81.6 82.2 85.3 64.6 57.2 68.5 78.9 77.0 49.2 86.9 72.1 37.7 14 54.0 70.2 78.2 40.5 84.1 65.4 43.6 62.7 76.5 61.5 42.2 80.0 64.6 37.8 15 64.2 71.0 76.6 31.4 87.7 66.2 56.3 55.7 62.1 63.7 55.0 70.2 61.3 15.2 16 57.9 69.8 72.5 43.9 86.7 66.1 42.8 62.7 74.7 67.3 49.3 82.1 67.2 32.9 17 65.0 72.2 65.8 55.9 70.0 65.8 16.3 69.9 78.7 72.9 29.9 90.0 68.3 60.0 18 62.6 73.8 72.4 60.4 85.1 70.9 24.7 65.6 75.1 47.9 34.9 80.8 60.9 45.9 19 61.7 69.5 72.5 39.4 82.1 65.0 42.7 24.9 27.9 42.4 36.2 59.2 38.1 34.3 20 36.6 46.3 68.8 52.8 62.3 53.4 32.1 64.5 66.4 61.1 25.0 66.7 56.7 41.8 21 28.7 42.8 73.5 65.8 78.4 57.8 49.7 38.1 34.0 44.1 52.6 50.7 43.9 18.7 22 77.5 81.1 73.4 54.9 77.3 72.9 26.2 48.0 52.7 60.5 43.4 65.4 54.0 22.0 23 67.5 70.0 59.7 16.2 76.7 58.0 60.5 49.4 57.1 63.4 51.2 68.8 58.0 19.3 24 60.9 64.8 68.4 42.8 72.8 61.9 30.0 49.4 54.3 48.8 31.1 64.7 49.6 33.5 25 36.1 56.7 88.6 75.6 85.1 68.4 52.5 63.9 67.0 66.6 34.1 75.4 61.4 41.3 26 51.9 58.4 75.9 56.0 73.0 63.0 24.0 40.1 51.1 57.2 63.2 71.0 56.5 30.9 27 67.0 73.9 63.0 18.9 76.2 59.8 57.3 45.3 50.2 52.3 30.9 56.4 47.0 25.5 28 62.1 70.0 62.5 15.1 76.2 57.2 61.1 55.1 59.0 66.0 42.0 66.9 57.8 24.9 29 57.3 64.0 56.4 26.3 80.3 56.8 54.0 64.1 67.8 72.0 48.9 75.2 65.6 26.4 30 52.7 65.2 54.0 24.1 79.2 55.0 55.1 74.7 86.1 83.2 46.6 90.7 76.2 44.0 31 57.4 74.8 66.0 20.5 87.2 61.2 66.7 60.8 68.7 65.1 54.2 72.6 64.3 18.4 32 72.8 80.5 75.7 50.0 88.5 73.5 38.5 69.6 79.9 75.7 33.2 87.3 69.1 54.1 33 55.0 64.4 69.9 45.6 83.6 63.7 38.0 67.8 81.9 80.5 49.4 89.5 73.8 40.0 34 59.7 68.5 79.4 54.5 78.5 68.1 25.0 54.6 60.0 59.1 48.6 74.0 59.2 25.4 35 72.7 81.3 54.3 17.7 81.2 61.4 63.5 59.9 66.2 68.2 41.3 74.1 61.9 32.8 36 49.1 52.6 76.5 64.6 64.9 61.5 27.4 53.9 56.2 65.7 51.0 61.7 57.7 14.7 37 70.4 72.8 68.3 32.3 76.1 64.0 43.9 58.3 66.1 65.4 38.2 81.4 61.9 43.2 38 45.6 49.4 51.4 26.5 66.0 47.8 39.5 60.5 72.1 68.7 47.9 85.8 67.0 37.9 39 37.8 46.6 68.7 50.5 80.2 56.8 42.3 49.1 49.8 45.1 31.4 51.2 45.3 19.8 40 76.7 78.2 61.6 24.7 71.3 62.5 53.6 62.1 78.8 77.5 62.2 91.4 74.4 29.4 41 33.6 39.3 65.9 50.2 72.3 52.3 38.7 59.2 78.1 83.3 50.5 87.0 71.6 36.5 42 19.5 19.5 65.3 46.0 46.8 39.4 45.8 62.7 71.3 74.8 42.4 85.9 67.4 43.4 43 44.6 61.7 63.0 25.3 84.7 55.9 59.4 77.4 82.4 70.9 28.6 83.8 68.6 55.2 44 68.4 76.9 60.0 26.6 81.7 62.7 55.1 39.9 48.7 50.1 38.3 56.2 46.6 17.9 45 68.3 69.1 64.8 44.8 72.9 64.0 28.1 60.3 64.3 60.0 28.7 69.3 56.5 40.7 46 51.8 58.7 67.4 53.8 74.1 61.2 22.3 65.2 74.7 71.3 30.3 89.9 66.3 59.6 47 37.4 62.4 70.9 48.4 86.7 61.2 49.3 68.3 74.2 74.3 27.5 87.2 66.3 59.7 48 37.5 51.2 67.9 49.2 82.8 57.7 45.2 69.2 80.1 70.9 40.5 87.9 69.7 47.4 49 36.5 54.7 79.6 65.6 87.5 64.8 51.1 42.8 42.2 44.1 31.0 50.6 42.1 19.7 50 44.4 54.7 63.2 35.8 74.0 54.4 38.3 33.8 26.2 44.5 36.3 30.4 34.2 18.3 3. Analysis 1 of both primary dependent measures by experiment

3.1 Methods In this section, we repeat the method used in Analysis 1 on both dependent measures (moral goodness as well as trait ratings) disaggregated by experiment. We use multivariate regression in the following analyses to simultaneously test for the interaction of our experimental manipulations (virtue and observability) on both of our primary dependent measures (moral goodness and trait ratings), controlling for experiment, and use contrasts on predicted marginal means to obtain estimates of effect size. As noted in the manuscript, it is worth emphasizing that the results reported here represent nine independent replications.

3.2 Results As predicted (H1), and replicating Analysis 1, we observe a significant effect of observability on trait ratings (see Table S4a, Columns 7-10), such that participants rate public displays (see Table S5, Columns 6) as demonstrating the virtue significantly less than private displays (see Table S5, Columns 5) in each experiment. We also observe a significant effect of observability on moral goodness ratings (see Table S4b, Columns 7-10), such that participants rate public displays (see Table S5, Columns 10) as significantly less morally good than private displays (see Table S5, Columns 9) in each experiment. Again replicating Analysis 1, there is no significant effect of virtue on trait ratings (see Table S4a, Columns 3-6 and Table S5, Columns 3-4) in any experiment (except 6 and 8). We also fail to observe a significant effect of virtue on moral goodness ratings (see Table S4b, Columns 3-6 and Table S5, Columns 7-8) in any experiment (except 9). As predicted (H3), and replicating Analysis 1, there is a significant interaction between virtue and observability on trait ratings (see Table S4a, Columns 11-14) in each experiment (except 5). Finally, we also observe a significant interaction between virtue and observability on moral goodness ratings (see Table S4b, Columns 11-14) in each experiment (except 6, 8, and 9).

Table S4. Replication of Analysis 1 using disaggregated data. Shown are effects obtained by replicating Analysis 1 by experiment. Bolded are p-values that are qualitatively different than those reported in the aggregate analysis (i.e. those that are either significant disaggregated but not significant aggregated or not significant disaggregated but significant aggregated). Dependent measure: Trait ratings a Effect tested: Virtue Observability Interaction Statisitic: df F p d df F p d df F p d 1 (1,388) .01 .920 <.01 (1,388) 120.02 <.001 1.10 (1,388) 2.61 .107 .13 2 (1,394) 2.60 .108 .13 (1,394) 91.99 <.001 .96 (1,394) 6.96 .009 .25 3 (1,395) <.01 .972 <.01 (1,395) 113.47 <.001 1.06 (1,395) 11.01 .001 .32 4 (1,393) .88 .347 <.01 (1,393) 137.29 <.001 1.17 (1,393) 6.73 .001 .24 Experiment: 5 (1,396) .42 .518 <.01 (1,396) 190.61 <.001 1.38 (1,396) 2.60 .108 .13 6 (1,399) 4.01 .046 .17 (1,399) 247.00 <.001 1.57 (1,399) 5.11 .024 .20 7 (1,401) 2.47 .117 .12 (1,401) 6.54 .011 .23 (1,401) 8.69 .003 .28 8 (1,393) 6.16 .014 .23 (1,393) 10.12 .002 .30 (1,393) 5.16 .024 .20 9 (1,398) 1.33 .250 .06 (1,398) 14.00 <.001 .36 (1,398) 4.22 .041 .18

Dependent measure: Moral goodness ratings Effect tested: Virtue Observability Interaction b Statisitic: df F p d df F p d df F p d 1 (1,388) .70 .403 <.01 (1,388) 137.06 <.001 1.18 (1,388) 11.92 .001 .33 2 (1,394) 1.88 .171 .09 (1,394) 122.33 <.001 1.11 (1,394) 22.37 <.001 .46 3 (1,395) .07 .797 <.01 (1,395) 85.23 <.001 .92 (1,395) 24.86 <.001 .49 4 (1,393) 1.45 .229 .07 (1,393) 123.28 <.001 1.11 (1,393) 15.00 <.001 .37 Experiment: 5 (1,396) <.01 .944 <.01 (1,396) 155.68 <.001 1.25 (1,396) 16.63 <.001 .40 6 (1,399) .31 .581 <.01 (1,399) 214.10 <.001 1.45 (1,399) 3.52 .062 .16 7 (1,401) 2.30 .130 .11 (1,401) 10.08 .002 .30 (1,401) 5.91 .016 .22 8 (1,393) 2.21 .138 .11 (1,393) 12.83 <.001 .35 (1,393) 1.47 .226 .07 9 (1,398) 6.08 .014 .22 (1,398) 14.31 <.001 .36 (1,398) 2.20 .139 .11

Table S5. Disaggregated summary of primary dependent measures across conditions. Shown are means and 95% confidence intervals by condition by experiment (Columns 3-10) as well as correlations between primary dependent measures within experiment across conditions (Columns 11-12). Dependent measure: Trait ratings Moral goodness ratings Correlation between Virtue: Generosity Impartiality Generosity Impartiality DVs across conditions Condition: Observability: Private Public Private Public Private Public Private Public r p 89.68 64.96 86.70 68.84 86.72 61.05 79.45 65.48 1 .68 <.001 [87.07, 92.29] [60.21, 69.71] [83.60, 89.81] [64.30, 73.38] [84.10, 89.34] [57.08, 65.03] [76.52, 82.39] [61.75, 69.21] 88.58 62.45 86.39 71.53 85.56 59.57 80.03 69.61 2 .67 <.001 [85.50, 91.66] [57.51, 67.39] [82.67, 90.11] [66.63, 76.43] [83.06, 88.06] [55.39, 63.75] [77.08, 82.98] [66.43, 72.79] 90.96 65.30 84.80 71.33 84.36 59.92 75.35 68.05 3 .67 <.001 [88.59, 93.33] [61.07, 69.53] [81.19, 88.41] [67.28, 75.38] [81.52, 87.21] [55.97, 63.87] [71.78, 78.92] [64.88, 71.22] 88.99 62.67 85.95 69.17 87.51 62.59 79.06 67.03 4 .75 <.001 [86.48, 91.50] [58.55, 66.79] [82.29, 89.61] [65.15, 73.19] [84.73, 90.28] [59.14, 66.04] [75.68, 82.44] [63.52, 70.54] 87.60 59.75 85.86 63.83 86.46 59.58 79.97 66.32 Experiment: 5 .75 <.001 [85.08, 90.12] [55.74, 63.77] [82.00, 89.72] [60.10, 67.57] [84.04, 88.92] [55.88, 63.29] [76.64, 83.29] [63.04, 69.60] 88.68 56.19 88.21 63.89 84.82 56.89 82.14 61.00 6 .78 <.001 [86.11, 91.24] [51.67, 60.71] [85.22, 91.20] [51.67, 60.71] [82.09, 87.56] [52.98, 60.80] [78.65, 85.63] [57.72, 64.28] 87.72 78.54 80.19 80.84 81.79 72.46 75.22 73.75 7 .61 <.001 [85.04, 90.41] [75.34, 81.74] [76.31, 84.07] [77.48, 84.20] [78.52, 85.07] [69.35, 75.56] [71.87, 78.56] [70.27, 77.23] 87.67 78.24 79.45 77.88 83.29 75.80 79.07 75.37 8 .52 <.001 [84.97, 90.38] [75.29, 81.19] [75.58, 83.32] [75.29, 81.19] [80.33, 86.24] [72.73, 78.87] [76.12, 82.02] [71.98, 78.77] 87.82 78.35 82.58 79.82 83.27 74.73 76.87 73.14 9 [85.62, 90.03] [75.08, 81.61] [79.00, 86.16] [76.11, 83.53] [80.26, 86.27] [71.55, 77.92] [73.67, 80.07] [69.69, 76.59] .58 <.001

Table S6. Disaggregated summary of primary dependent measures by condition. Shown are means and 95% confidence intervals of trait ratings (Columns 3-6) and moral goodness ratings (Columns 7-10) by condition (columns) by experiment (rows) as well as correlations between primary dependent measures within experiment across conditions (Columns 11-12). Trait ratings Moral goodness ratings Virtue Observability Virtue Observability Condition: Generous Impartial Private Public Generous Impartial Private Public 77.32 77.68 88.21 66.90 73.95 72.43 83.12 63.27 1 [74.12, 80.52] [74.67, 80.69] [86.19, 90.23] [63.63, 70.17] [70.98, 76.92] [69.88, 74.98] [81.11, 85.14] [60.55, 65.98] 75.52 78.88 87.49 66.99 72.57 74.77 82.82 64.59 2 [72.10, 78.93] [76.65, 82.11] [85.10, 89.89] [63.48, 70.50] [69.54, 75.59] [72.49, 77.04] [80.87, 84.78] [61.89, 67.29] 78.07 78.07 87.86 68.32 72.08 71.70 79.83 63.99 3 [75.06, 81.07] [75.21, 80.92] [85.68, 90.05] [65.38, 71.25] [69.12, 75.04] [69.28, 74.12] [77.48, 82.19] [61.41, 66.56] 75.63 77.56 87.45 65.92 74.86 73.05 83.22 64.81 4 [72.59, 78.67] [74.62, 80.50] [85.22, 89.67] [63.03, 68.81] [72.04, 77.67] [70.49, 75.60] [80.96, 85.47] [62.35, 67.27] 75.35 75.35 89.68 64.96 75.35 75.35 89.68 64.96 Experiment: 5 [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] 75.35 75.35 89.68 64.96 75.35 75.35 89.68 64.96 6 [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] 75.35 75.35 89.68 64.96 75.35 75.35 89.68 64.96 7 [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] 75.35 75.35 89.68 64.96 75.35 75.35 89.68 64.96 8 [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] 75.35 75.35 89.68 64.96 75.35 75.35 89.68 64.96 9 [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71] [71.78, 78.92] [71.78, 78.92] [87.07, 92.29] [60.21, 69.71]

4. Preregistered analyses only

As a robustness check, we here re-run our analyses among only our two preregistered experiments (8 and 9; not including baseline observability conditions; total N=799; 46.3% female, average age=35.1 years). All results reported here replicate results reported in the manuscript unless otherwise noted. 4.1 Analysis 1 As reported in the main text, 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.

4.1.1 Methods In Analysis 1, 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=1.00, F(1,791)=.12, p=.891), so we use the combined data in these analyses, entering experiment as a covariate. We observe that moral goodness and trait ratings are strongly correlated (r=.55, p<.001) and a Wald test reveals that the interaction effect of virtue and observability does not differ between our dependent measures (F(1,794)=1.78, p=.183). For the sake of concision, we therefore report effects on trait ratings here. We use multivariate regression in the following analyses to simultaneously test for the interaction of our experimental manipulations (virtue and observability) on both of our primary dependent measures (moral goodness and trait ratings), controlling for experiment, and use contrasts on predicted marginal means to obtain estimates of effect size.

4.1.2 Results As predicted (H1), we observe a significant effect of observability on trait ratings (F(1,794)=23.83, p<.001, d=.34; see Figure S2), such that participants rate public displays (m=78.58, 95% CI [76.85, 80.31]) as demonstrating the virtue significantly less than private displays (m=84.38, 95% CI [82.79, 85.98]). Unlike our primary analysis, there is also a significant effect of virtue on trait ratings (F(1,794)=6.73, p=.010, d=.17) such that participants rate displays of generosity (m=83.00, 95% CI [81.53, 84.46]) as demonstrating the virtue significantly more displays of impartiality (m=79.92, 95% CI [78.04, 81.81]). Also as predicted (H3), there is a significant interaction between virtue and observability on trait ratings (F(1,794)=9.43, p<.001, d=.21). Computing pairwise comparisons of estimated marginal cell means corrected for multiple comparisons (using Scheffe’s adjustment; Winer, Brown, & Michels, 1991), we observe four interesting patterns. First, for generosity, public displays are rated as demonstrating the virtue significantly less than private displays (Scheffe’s t=-5.63, p<.001, d=.15). Second, unlike or primary analysis, for impartiality, participants do not rate public displays and private displays as demonstrating the virtue significantly differently (Scheffe’s t=-1.28, p=.651, d=.04). Third, private displays of generosity are rated as demonstrating the virtue significantly more than private displays of impartiality (Scheffe’s t=3.99, p<.001, d=.12). Finally, unlike or primary analysis, participants do not rate public displays of generosity and impartiality significantly differently (Scheffe’s t=-.34, p=.990, d<.01). Central to our hypothesis (H3), using seemingly unrelated regressions, we observe that the standardized coefficient on observability is significantly larger for generosity (b=-.45, 95% CI [- .59, -.32]) than impartiality (b=-.10, 95% CI [-.28, .08], χ2(1)=9.47, p=.002).

Fig S2. Public displays of virtue are perceived as demonstrating that virtue to a lesser extent than private displays of virtue for generosity but not impartiality. Shown are means (with 95% CIs) trait ratings (0-100 unmarked slider), as a function of whether the actor is said to engage in behaviors that are generous (green) or impartial (blue) and whether these behaviors are displayed in public (solid) or private (lines).

In Analysis 1, we provide evidence in support of two of our hypotheses. Consistent with H1, we find that public displays of virtue are perceived as demonstrating the virtue less than private displays. Consistent with H2, we find that these effects are greater for generosity than impartiality. It is interesting to note that here, there is no effect of observability in the impartiality conditions. This may be due to the fact that our preregistered stimuli lacked explicit stipulation of actors’ motivation (as in Experiments 1-5)

4.2 Analysis 2 As reported in the main text, the purpose of Analysis 2 is to investigate the mechanism we propose for (differential) virtue discounting: perceptions of selfish motivations. We again conduct the mediation model from the main text to test the multiple mediation hypothesis (H3), that virtue discounting (collapsed across generosity and impartiality) is explained by perceived selfish motivations. Because here we do not find evidence of an effect of observability in our impartiality conditions, however, we next conduct the mediation model in the main text for the generosity conditions only (because there is no effect to be explain in the impartiality conditions).

4.2.1 Methods We first investigate the pairwise correlations among our secondary dependent measures, and observe that they are moderately correlated (average r=.25, each correlation p<.05, Bonferroni corrected for 15 simultaneous comparisons). Here, the only non-significant correlation was 3rd-party benefit and 1st-party benefit, while in the main text, the only non- significant correlation was norm-signaling and 1st-party benefit. To better understand the correlation structure among our secondary dependent measures, we conduct a pre-registered exploratory factor analysis with varimax (orthogonal) rotation and iterated principal factors. The analysis yielded two factors explaining 88.2% of the variance. Factor 1 (explaining 51.8% of the variance); we maintain the label moral motivations due to the high loadings (>.4) by the following items: 3rd-party benefit, and moral and authentic motivations. Factor 2 (explaining 36.5% of the variance); we maintain the label self-oriented motivations due to high loadings (>.4) by the following items: 1st-party benefit and reputational motivation. Interestingly, here, norm-signaling loads more heavily on the self-oriented factor (.41) than on the moral factor (.26), which is the reverse pattern we observe in the main text. To test our multiple mediation hypothesis (H3), we construct a preregistered structural equation model in which we test for the following associations, collapsing across virtue: observability (dummy coded so that 1=public and 0=private) with trait ratings and each of our six secondary dependent measures as well as each of our six secondary dependent measures with trait ratings. All structural equation models are conducted using standardized variables, and indirect effects are calculated using the multivariate delta method (Sobel, 1982, 1986). To test our multiple moderated mediation hypothesis (H4), we construct a preregistered structural equation model (following models 59 and 74 in Hayes, 2013) in which we test for associations of each of our six secondary dependent measures by the interaction of observability (dummy coded so that 1=public and 0=private) and virtue (here, only for generosity), and also test for associations of trait ratings by the interaction of observability and virtue as well as by the interaction of each of our six secondary dependent measures with virtue.

4.2.2 Results Our first structural equation model tests our multiple mediation hypothesis (H3), that virtue discounting will be explained by perceived selfish motivations. We investigate associations of secondary dependent measures with our observability manipulation and observe that public display of virtue are associated with all secondary dependent measures qualitatively similarly (i.e. same significance and direction, with minor variations in magnitude) as reported in the main text. The only exception is for norm-signaling, where the association is here significant, and opposite in direction (as may be inferred by its loading on the self-oriented rather than the moral factor). We note that this change in the direction of the association of our variables with the norm-signaling measure holds in subsequent results. We then turn to the association of trait ratings of virtue with our proposed mediators, and again replicate results reported in the main text, except that associations with reputational and norm-signaling motivations are not significant. Consistent with H3, we again observe that motivations are affected by observability and trait ratings are affected by motivations in the hypothesized directions: self-oriented motivations are positively associated with public display and negatively associated with trait ratings while moral motivations are negatively associated with public display and positively associated with trait ratings. The total effect of public observability on trait ratings of virtue is significant (b=-.28, 95% CI [-.39, -.17], p<.001), but the direct effect is not (b’=-.04, 95% CI [-.14, .05], p=.357), implying full mediation (84.3% of the total effect). The motivational attributions responsible for this mediation (indirect effects as percent of total effect mediated) in descending order of magnitude are: moral (35.1%), authentic (24.9%), reputational (12.8%), 1st-party benefit (8.4%), 3rd-party benefit (6.5%), and norm-signaling (-2.6%). Unsurprisingly, when we conduct this analysis in the generosity conditions, we obtain qualitatively similar results as those reported here (because the only variation to explain in trait ratings was in the generosity conditions). In Analysis 2, we replicate results reported in the main text, supporting our hypotheses that perceived selfish motivation is the mechanism of virtue discounting (H3), though because we fail to find virtue discounting in impartiality here, we cannot test for the mechanism of differential virtue discounting (H4). Consistent with H3, we find that the virtue discounting effect (collapsed across generosity and impartiality) is explained by inferred selfish motivations (i.e. higher self-oriented motivations and lower moral motivations).

5. Complete experimental instructions

NOTE: Long solid grey lines represent breaks between pages as experienced by subjects. Long dashed grey lines represent breaks between questions on the same page. Headers for each section (not part of the experiment) displayed in italics.

Common elements across all experiments

Consent

You are being asked to participate in a research study titled “Social Judgment and Decision- Making”. You were selected to participate in this project because you are an adult over age 18. This study is sponsored by Boston College and the National Science Foundation.

The purpose of this study is social decision-making, and specifically how people judge the decisions and values of others.

This study will be conducted through this online survey. The survey should take you approximately 10 minutes to complete.

There are no direct benefits to you, but you may feel gratified knowing that you helped further the scholarly work in this research area. You will be compensated $1.00 for participating in this study. There are no costs to you associated with your participation.

This Principal Investigator will exert all reasonable efforts to keep your responses and your identity confidential. We may have access to, and may maintain in our data collection, your worker ID or user ID for the internet survey platform that you use. However, aside from your worker ID or user ID, we will not maintain within our research data any information that uniquely identifies you, such as your name, location, or Internet Protocol (IP) address. In any report we publish, we will not include any information that will make it possible to identify a participant.

Data collected from the experiment will be coded to remove your name or any other personal identifiers. All records will be secured in a locked cabinet in our lab. Access to the records will be limited to the researchers; however, please note that regulatory agencies and the Institutional Review Board and internal Boston College auditors may review the research records. Please note that regulatory agencies, the Boston College Institutional Review Board, and Boston College internal auditors may review research records. Please also note the organization that operates your Internet survey platform may retain your responses and, additionally, may maintain a link identifying you as the source of those responses. Your user agreement with the survey platform organization may address this topic.

Your participation is voluntary. If you choose not to participate it will not affect your relations with Boston College. Some questions on the survey, such as comprehension questions, may be required in order to complete the survey and receive compensation. However, you may still choose to end your participation in the study at any time.

If you have questions or concerns concerning this research you may contact the Principal Investigator at 617-552- 0240 or [email protected]. If you have questions about your rights as a research participant, you may contact the Office for Research Protections, Boston College, at 617-552-4778 or [email protected].

The Boston College IRB has approved this protocol from July 23, 2019 – July 22, 2020.

If you agree to the statements above and agree to participate in this study, please press the “Consent Given” button below. o Consent given o Consent not given

ID screener and transcription task

To begin, please enter your Amazon Mechanical Turk Worker ID here:

(Please see below for where you can find your Worker ID.)

Your Worker ID starts with the letter A and has 12-14 letters or numbers. It is NOT your email address. If we do not have your correct Worker ID we will not be able to pay you. ______

Note that your Worker ID can be found on your dashboard page:

To begin, please type the following paragraph into the box below.

______

On the following pages, we will describe an individual and ask you some questions about them.

Demographics

NOTE: These questions were included in all experiments except Supplemental Study 1.

Gender: o Male o Female

Age: ______

Please specify your race. (Choose one or more categories)

▢ White/Caucasian (Anglo/Euro) American ▢ Black or African American ▢ Asian or Asian American ▢ American Indian or Alaska Native ▢ Native Hawaiian or other Pacific Islander ▢ Hispanic/Latino ▢ Multicultural

Highest level of education completed: o Less than a high school degree o High School Diploma o Vocational Training o Attended College o Bachelor’s Degree o Graduate Degree o Unknown

Please choose the category that describes the total amount of income you earned in 2018. Consider all forms of income, including salaries, tips, interest and dividend payments, scholarship support, student loans, parental support, social security, alimony, and child support, and others. o Under $5,000 o $5,000-$10,000 o $10,001-$15,000 o $15,001-$25,000 o $25,001-$35,000 o $35,001-$50,000 o $50,001-$65,000 o $65,001-$80,000 o $80,001-$100,000 o Over $100,000

Which US political party do you identify with more strongly? o 1-Strongly Republican o 2 o 3 o 4-Neutral o 5 o 6 o 7-Strongly Democrat

What do you think this study is about? ______

Manipulations

Experiment 1

(Condition: Generous, Public)

Imagine you have a friend named Jen. Jen is always thinking about how her actions will be perceived by others, more than most people do. In particular, she really wants her friends to think that she is a generous person. Jen thinks being generous means giving more of her money or time than is strictly necessary or expected. She is especially generous when others are watching her act since she knows that her reputation for being generous will improve.

(Condition: Generous, Private)

Imagine you have a friend named Liz. Liz tries to act in ways that align with her values, regardless of how her actions will be perceived by others. In particular, she thinks it is important to be generous. Liz thinks being generous means giving more of her money or time than is strictly necessary or expected. Though she is generous when she is with others, she is especially generous when no one is watching since she knows that acting in this way is consistent with her values.

(Condition: Impartial, Public)

Imagine you have a friend named Jess. Jess is always thinking about how her actions will be perceived by others, more than most people do. In particular, she really wants her friends to think that she is an impartial person. Jess thinks being impartial means treating everyone equally and fairly, without bias. She is especially impartial when others are watching her act since she knows that her reputation for being impartial will improve.

(Condition: Impartial, Private)

Imagine you have a friend named Emily. Emily tries to act in ways that align with her values, regardless of how her actions will be perceived by others. In particular, she thinks it is important to be impartial. Emily thinks being impartial means treating everyone equally and fairly, without bias. Though she is impartial when she is with others, she is especially impartial when no one is watching since she knows that acting in this way is consistent with her values.

Experiments 2 and 3

(Condition: Generous, Public)

Imagine you have a friend named Jen. She really wants her friends to think that she is a generous person. Jen thinks being generous means giving more of her money or time than is strictly necessary or expected. She is especially generous when others are watching her act since she knows that her reputation for being generous will improve.

(Condition: Generous, Private)

Imagine you have a friend named Liz. Liz tries to act in ways that align with her values, regardless of how her actions will be perceived by others. In particular, she thinks it is important to be generous. Liz thinks being generous means giving more of her money or time than is strictly necessary or expected. Though she is generous when she is with others, she is even generous when no one is watching since she knows that acting in this way is consistent with her values.

(Condition: Impartial, Public)

Imagine you have a friend named Jess. She really wants her friends to think that she is an impartial person. Jess thinks being impartial means treating everyone equally and fairly, without bias. She is especially impartial when others are watching her act since she knows that her reputation for being impartial will improve.

(Condition: Impartial, Private)

Imagine you have a friend named Emily. Emily tries to act in ways that align with her values, regardless of how her actions will be perceived by others. In particular, she thinks it is important to be impartial. Emily thinks being impartial means treating everyone equally and fairly, without bias. Though she is impartial when she is with others, she is even impartial when no one is watching since she knows that acting in this way is consistent with her values.

On the next few pages, we will ask you to evaluate Emily's stable personality traits. We'd like to know how you think Emily tends to be *in general*. You should make this judgment however you think is best, but you might consider something like whether or not you could say "She's a very ______person." The key to these particular judgments is the 'in general.'

Experiments 4, 5, and 6

NOTE: Bracketed sections were displayed in Experiment 4 but not in Experiments 5 and 6.

(Condition: Generous, Public)

Some people think that generosity is a virtue. Generosity usually means giving more of one's money or time than is strictly necessary or expected. Some examples of generosity include: • Volunteering at a homeless shelter • Donating money to charities like Doctors without Borders (one of their functions is to provide relief to victims of natural disasters) • Donating blood during a blood drive (e.g. to the American Red Cross) Imagine you have a friend named Jen. She really wants her friends to think that she is a generous person. She is especially generous when others are watching her act [since she knows that her reputation for being generous will improve].

(Condition: Generous, Private)

Some people think that generosity is a virtue. Generosity usually means giving more of one's money or time than is strictly necessary or expected. Some examples of generosity include: • Volunteering at a homeless shelter • Donating money to charities like the Red Cross (one of their functions is to provide relief to victims of natural disasters) • A teacher staying after school (unpaid) to mentor students Imagine you have a friend named Liz. Liz tries to act in ways that align with her values, regardless of how her actions will be perceived by others. In particular, she thinks it is important to be generous. Though she is generous when she is with others, she is even generous when no one is watching [since she knows that acting in this way is consistent with her values].

(Condition: Impartial, Public)

Some people think that impartiality is a virtue. Impartiality usually means treating everyone equally and fairly, without bias. Some examples of impartiality include: • Making sure everyone at a social gathering receives the same amount of food (e.g. when four people share a large pizza with eight slices, ensuring everyone gets two) • Dividing work evenly among all participants in a group project (i.e. not giving your friend less work because you like them) • Making auditions or job applications blind (i.e. evaluators can't see applicants' faces) so that subtle, unconscious biases against particular genders or ethnicities don't enter into the decision-making process Imagine you have a friend named Jess. She really wants her friends to think that she is an impartial person. She is especially impartial when others are watching her act [since she knows that her reputation for being impartial will improve].

(Condition: Impartial, Private)

Some people think that impartiality is a virtue. Impartiality usually means treating everyone equally and fairly, without bias. Some examples of impartiality include: • Making sure everyone at a social gathering receives the same amount of food (e.g. when four people share a large pizza with eight slices, ensuring everyone gets two) • Dividing work evenly among all participants in a group project (i.e. not giving your friend less work because you like them) • Making auditions or job applications blind (i.e. evaluators can't see applicants' faces) so that subtle, unconscious biases against particular genders or ethnicities don't enter into the decision-making process Imagine you have a friend named Emily. Emily tries to act in ways that align with her values, regardless of how her actions will be perceived by others. In particular, she thinks it is important to be impartial. Though she is impartial when she is with others, she is even impartial when no one is watching [since she knows that acting in this way is consistent with her values].

On the next few pages, we will ask you to evaluate Emily's stable personality traits. We'd like to know how you think Emily tends to be *in general*. You should make this judgment however you think is best, but you might consider something like whether or not you could say "She's a very ______person." The key to these particular judgments is the 'in general.'

Experiments 7 and 8

(Condition: Generous, Baseline)

Some people think that generosity is a virtue. Generosity usually means giving an abundance of one's money or time.

Imagine you know someone named Lisa who buys a friend an expensive gift, gives a waiter a large tip, and stays late to help a coworker.

(Condition: Impartial, Baseline)

Some people think that impartiality is a virtue. Impartiality usually means treating everyone equally and fairly, without bias.

Imagine you know someone named Laura who gave her children equal allowances, conducted a blind audition, and drew names from a hat for a project at work.

Experiments 7, 8, and 9

(Condition: Generous, Public)

Some people think that generosity is a virtue. Generosity usually means giving an abundance of one's money or time.

Imagine you know someone named Jen who bought a friend an expensive gift, gave a waiter a large tip, and stayed late to help a coworker. She did these things in public; therefore, other people knew that she did them.

(Condition: Generous, Private)

Some people think that generosity is a virtue. Generosity usually means giving an abundance of one's money or time.

Imagine you know someone named Liz who bought a friend an expensive gift, gave a waiter a large tip, and stayed late to help a coworker. She did these things in private; therefore, other people did not know that she did them.

(Condition: Impartial, Public)

Some people think that impartiality is a virtue. Impartiality usually means treating everyone equally and fairly, without bias.

Imagine you know someone named Jess who gave her children equal allowances, conducted a blind audition, and drew names from a hat for a project at work. She did these things in public; therefore, other people knew that she did them.

(Condition: Impartial, Private)

Some people think that impartiality is a virtue. Impartiality usually means treating everyone equally and fairly, without bias.

Imagine you know someone named Emily who gave her children equal allowances, conducted a blind audition, and drew names from a hat for a project at work. She did these things in private; therefore, other people did not know that she did them.

Dependent measures

NOTE: All sliders recorded values from 0-100 but did not display these values to participants.

All Experiments

Trait rating

How [generous/impartial] is [name]? Extremely selfish Neither generous Extremely nor selfish generous

Moral goodness rating

How morally good is [name]? Extremely morally Neither morally Extremely morally bad good nor morally good bad

1st-party benefit

Experiments 2 and 3:

How much do you think [name] will personally benefit from being perceived as generous by others? Not at all Very much

Experiments 6, 7, 8, and 9:

How much do you think [name] is motivated to act [generously/impartially] because she thinks she will personally benefit from acting this way? Not at all Very much

3rd-party benefit

Experiments 4 and 5:

How much do you think another person would benefit from interacting with [name]? Not at all Very much

Experiments 6, 7, 8, and 9:

How much do you think [name] is motivated to act [generously/impartially] because she wants to benefit others? Not at all Very much

Reputational motivation

Experiments 4 and 5:

Think about [name]’s motivation for acting the way she does. How much do you think [name] is acting this way because... 1: Not at 7: Very 2 3 4 5 6 all much ...she is thinking about what others would think of her o o o o o o o ...it's important to her that others positively evaluate her o o o o o o o ...it's important to her that others accept her o o o o o o o

Experiments 6, 7, 8, and 9:

How much do you think [name] is motivated to act [generously/impartially] because she is trying to make others think she is [generous/impartial]? Not at all Very much

Authentic motivation

Experiments 4 and 5:

Think about [name]’s motivation for acting the way she does. How much do you think [name] is acting this way because... 1: Not at 7: Very 2 3 4 5 6 all much ...she thinks it is important to act in this way o o o o o o o ...she likes acting this way o o o o o o o

...she values doing so o o o o o o o

Experiments 6, 7, 8, and 9:

How much do you think [name] is motivated to act [generously/impartially] because she wants to be [generous/impartial]? Not at all Very much

Norm-signaling motivation

Experiments 4 and 5:

Think about [name]’s motivation for acting the way she does. How much do you think [name] is acting this way because... 1: Not at 7: Very 2 3 4 5 6 all much

...she is modelling the behavior she wants others to engage in o o o o o o o ...she wants others to follow her example o o o o o o o ...it's important to her to show others how she thinks everyone should behave o o o o o o o

Experiments 6, 7, 8, and 9:

How much do you think [name] is motivated to act [generously/impartially] because she wants others to be [generous/impartial], and she is trying to lead by example? Not at all Very much

Moral motivation

Experiments 6, 7, 8, and 9:

How much do you think [name] is motivated to act [generously/impartially] because she thinks it is the right thing to do? Not at all Very much

2nd-party benefit

Experiments 2, and 3:

How much do you think you would benefit from interacting with [name]? Not at all The same as with Very much anyone else

Supplemental Study 1

(Condition: Generosity)

Merriam-Webster's dictionary defines generosity as: • "giving or sharing in abundance" Please name at least 3 and up to 10 real-life acts of generosity: o Generous act 1: ______o Generous act 2: ______o Generous act 3: ______o Generous act 4: ______o Generous act 5: ______o Generous act 6: ______o Generous act 7: ______o Generous act 8: ______o Generous act 9: ______o Generous act 10: ______

(Condition: Impartiality)

Merriam-Webster's dictionary defines impartiality as: • "lack of favoritism toward one side or another" Please name at least 3 and up to 10 real-life acts of impartiality: o Impartial act 1: ______o Impartial act 2: ______o Impartial act 3: ______o Impartial act 4: ______o Impartial act 5: ______o Impartial act 6: ______o Impartial act 7: ______o Impartial act 8: ______o Impartial act 9: ______o Impartial act 10: ______

Supplemental Study 2

The following questions will refer to the following behavior: • [behavior]

Moral goodness

In your opinion, how morally good is it to do this behavior? Very morally bad Neither morally Very morally good good nor morally bad

0 10 20 30 40 50 60 70 80 90 100

Descriptive normativity

In your opinion, how many people in your community do this behavior when they are in the relevant situation? Very few Very many

0 10 20 30 40 50 60 70 80 90 100

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? Very little Very much

0 10 20 30 40 50 60 70 80 90 100

Benefit to the recipient

In your opinion, how much benefit (in terms of money, time, effort, etc.) does the recipient of this behavior receive? Very little Very much

0 10 20 30 40 50 60 70 80 90 100

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? Very little Very much

0 10 20 30 40 50 60 70 80 90 100

6. Unedited participant-generated acts from Supplemental Study 1.

Table S8. Unedited participant-generated acts of generosity from Supplemental Study 1.

doing a favor and not asking for 1 buying a stranger’s wedding dress 31 being patient with time 61 anything in return 2 buying someone a meal 32 boy 62 donate old clothes 3 buying someone else’s groceries 33 buying a friend an expensive gift 63 donated to a charity 4 donating a massive cash prize 34 buying a homeless person food 64 donating 5 ending a tough commute 35 buying a meal for someone 65 donating 6 giving away valuable jewelry 36 buying a stranger a coffee 66 donating 7 giving blood for decades 37 buying everyone lunch 67 donating 8 helping a homeless 38 buying food for the less privileges 68 donating helping a homeless good 9 39 buying food for the poor 69 donating samaritan 10 leaving a huge restaurant tip 40 buying homeless people food 70 donating 11 leaving a huge restaurant tip 41 buying people things they need 71 donating a kidney 12 lifting spirits with pizza 42 buying someone a meal 72 donating a massive cash prize a best people can describe their 13 43 buying someone coffee 73 donating blood truth of law a man who helps his neighbor 14 44 buying someone dinner 74 donating blood carry out her trash a millionaire giving their with to donating clothing, etc. to a 15 45 buying someone else’s groceries 75 charity battered women's shelter a volunteer donating their buying supplies for an animal 16 weekend to a environmental 46 76 donating food to a food pantry shelter cleanup donating food to a homeless 17 abundance 47 caring for a sick person 77 shelter 18 adopt a homeless pet 48 charity 78 donating money 19 adopting a child or pet 49 charity 79 donating money adopting a dog/cat from an animal 20 50 charity 80 donating money shelter 21 adopting a rescue pet 51 charity 81 donating money 22 advising 52 child 82 donating money 23 aiding the less privileged 53 churchs giving to the poor 83 donating money 24 amplitude 54 complimenting others 84 donating money at church 25 arun 55 cooking for friends 85 donating money to a charity 26 assisting the elderly 56 cooking for someone 86 donating money to a local church 27 babysitting 57 copiousness 87 donating money to a non-profit babysitting your younger family devoting any necessary time to 28 58 88 donating money to chairty members help someone in need 29 being kind 59 dhileep 89 donating money to charity do some baking and drop it to the 30 being patient with others 60 90 donating money to charity neighbours house.

donating money to organizations driving someone to work while 91 121 151 give someone a compliment like kiva their car is broken down each and every second we can 92 donating money to the poor 122 152 give someone flowers change our mind set each of these actions changed give something to someone what 93 donating money 123 lives, and in some cases saved 153 makes happy lives 94 donating time 124 establishing an annual scholarship 154 give support even the smallest actions can 95 donating time or money to charity 125 155 giving a big tip have an impact 96 donating to a charity 126 feeding a homeless man 156 giving a dollar to homeless 97 donating to a charity 127 feeding a homeless person 157 giving a donation to charity water 98 donating to an organization 128 feeding the hungry 158 giving a homeless person money 99 donating to chairty 129 feeding the poor 159 giving a homeless person money giving a homeless person some 100 donating to charity 130 filling your kid's car with gas 160 food giving a ride to a senior citizen to a 101 donating to charity 131 fostering a child 161 doctor's appointment 102 donating to charity 132 fostering adoptive pets 162 giving a ride to someone

giving a very poor person a $100 103 donating to charity 133 fostering or adopting a child 163 bill

104 donating to charity 134 fostering or adopting a dog 164 giving a waiter a large tip 105 donating to charity 135 fostering pets 165 giving alms 106 donating to charity 136 free 166 giving away belongings 107 donating to charity 137 freehanded 167 giving blood 108 donating to charity 138 fulsome 168 giving blood at a bloodbank generosity is sometimes used to 109 donating to charity 139 169 giving food to homeless denote charity generous from the merriam- webster thesaurus, plus 48 related 110 donating to food drive 140 170 giving food to hungry people words, definitions, ... 1 giving or sharing in abundance 111 donating to goodwill 141 gifting 171 giving food to someone 112 donating to the homeless 142 gifting a car to a friend 172 giving food to the homeless donating to your favorite content 113 143 gifting a meal to the homeless 173 giving free clothing creator donating toys to kids that do not 114 144 give a gift 174 giving free food have any 115 donating your car to charity 145 give a hug 175 giving gifts donating your time to a charity or give food to the one who does not 116 146 176 giving gifts cause have 117 donation 147 give homeless guy a buck 177 giving gifts 118 donation 148 give homeless woman a taco 178 giving homeless people shelter 119 donations 149 give praise 179 giving material things 120 drawing 150 give shirt off ones back 180 giving money

181 giving money 211 giving scholarships 241 giving to homeless giving money or supplies to the 182 212 giving someone a gift 242 giving to others homeless 183 giving money to a charity 213 giving someone a gift 243 giving to the poor 184 giving money to a charity 214 giving someone a gift 244 giving to the poor giving money to a homeless giving someone a hand carrying 185 215 245 giving to the poor person groceries 186 giving money to beggars 216 giving someone a present 246 giving to the poor 187 giving money to charity 217 giving someone a ride 247 giving up a bus seat giving someone a ride who doesn't 188 giving money to charity 218 248 giving up your seat on a bus have one giving your neighbor a few of the 189 giving money to charity 219 giving someone clothes 249 tomatos you grew in your garden giving someone the last piece of 190 giving money to friends or family 220 250 giving your old stuff to a thrift store pizza giving something valuable away giving your time to volunteer at a 191 giving money to homeless 221 251 instead of selling it charity giving something who doesn't 192 giving money to homeless 222 252 good have anything giving strangers who ask for it 193 giving money to homeless people 223 253 good money 194 giving money to the homeless 224 giving time 254 good giving money to the homeless guy 195 225 giving time to someone 255 good at the on-ramp giving money to the homeless or a 196 226 giving tip to waiters 256 good stanger 197 giving money to the poor 227 giving to a go fund me 257 good giving one of your items to 198 someone who wants or deserves it 228 giving to charities 258 good more 199 giving or sharing in abundance 229 giving to charity 259 good 200 giving or sharing in abundance 230 giving to charity 260 good 201 giving or sharing in abundance 231 giving to charity 261 good 202 giving or sharing in abundance 232 giving to charity 262 good bonues groups of people helping in a 203 giving or sharing in abundance 233 giving to charity 263 diastor zone 204 giving or sharing in abundance 234 giving to charity 264 gving back to the less fortunate 205 giving or sharing in abundance 235 giving to charity 265 habitat for humanity handing out full sized candy bars 206 giving or sharing in abundance 236 giving to charity 266 on halloween 207 giving or sharing in abundance 237 giving to charity 267 healthcare providers 208 giving or sharing in abundance 238 giving to charity 268 heart

giving or sharing in abundance see: ... i still maintain that any 209 neoconservative after reading the 239 giving to church 269 help dictionary's definition of the noun would 210 giving people food 240 giving to homeless 270 help the needy

271 help to poor 301 hold door open for someone 331 love 272 helping 302 hold the door for someone 332 make offerings hold the door open for 273 helping a friend 303 333 making a donation someone holding someones hair while making dinner for a sick 274 helping a friend 304 334 they barf friend helping a sibling with wise money 275 305 holding the door 335 mentoring management 276 helping a stranger 306 holding the door for someone 336 mow someones lawn keeping the environment mowing someone's lawn for 277 helping a stranger 307 337 clean free 278 helping an elderly neighbor 308 largeness 338 mowing your neighbors lawn 279 helping an elderly person cross the street 309 lavishness 339 munificent leaving a huge tip at a 280 helping friends 310 340 naveen restaurant nearly each one inspired others to act a little kinder or lending gas money to 281 helping it charity work 311 341 give more of themselves. strangers stuck on road good deeds are funny like that 282 helping others 312 lending money 342 nursing a bird back to health offering advice to someone 283 helping out a friend in need 313 lending money 343 who wants/needs it lending money and saying 284 helping out a friend 314 dont worry about paying it 344 offering food to someone back 285 helping pay someone's utility bill 315 lending money to a friend 345 offering someone a ride offering something to make 286 helping people cross the street 316 lending out a favor 346 people comfortable offering to babysit a friends lending your time to the red 287 helping someone 317 347 kids so that they can get a cross break letting multiple cars merge in offering to cook dinner for 288 helping someone fix a flat tire 318 348 front of you during rush hour your significant other letting someone ahead of you 289 helping someone living on the street 319 349 offering to help with groceries in line letting someone cut you in 290 helping someone move 320 350 open line letting someone go ahead of 291 helping someone move 321 351 openhanded you in line at the store letting someone have the last opening the door for 292 helping someone on the street 322 352 of an item during a great sale someone helping someone stranded on the side of the letting someone have your opening the door for 293 323 353 road seat on a crowded bus someone letting someone out who is opening the door for 294 helping someone who needs a hand 324 354 stuck in traffic someone letting someone sleep in your 295 helping the elderly 325 355 parents house parents who sacrifice their 296 helping the elderly cross the street 326 liberal 356 time and most of their earnings for their children patiently listening to your 297 helping the homeless 327 liberality 357 elderly grandparent tell the same story for the 3ooth time liz jensen found the perfect 298 helping the homeless 328 wedding dress last month at 358 pay for a stranger's parking. a utah dress shop pay for someone elses 299 helping those in need 329 loaning money to a friend 359 morning coffee 300 helping your neighbor 330 love 360 pay toll for person behind you

sending extra school supplies for stopping for a bicyclist in a paying for a relative's college 361 391 the teacher to use for students 421 hailstorm, throwing his bike in the education who couldnt afford them truck bed, and giving him a ride 362 paying for someone else's coffee 392 share a activity 422 superabundance 363 paying for someone else's meal 393 share a meal 423 supporting causes 364 paying for someone’s groceries 394 share a moment 424 taking a meal to an elderly person taking care of a child for a friend 365 paying for someone's dinner 395 share a movie 425 for free paying for someones food in the 366 396 share a smile 426 taking one for the team store taking time out of your day to help 367 paying it forward 397 share time 427 a neighbor taking your kid's friend on vacation 368 paying it forward 398 sharing 428 with your family, knowing that his family can't afford vacations 369 paying it forward 399 sharing food 429 teachers that's why it's so striking when peole's should learn about whats 370 400 sharing food 430 strangers do something their truth unexpected people generally aren't used to the act may be as simple as kindness from strangers. most of holding the door open for 371 us are too wrapped up in our lives 401 sharing food 431 someone else, or letting a person to pay much attention to anyone go first in line else the other woman had been at the 372 people who open up them homes 402 sharing food with friends 432 shop trying on dresses at the same time people who work in social services 373 and make very little for a highly 403 sharing food with someone hungry 433 tipping better than average demanding job tipping more than expected at a 374 pick up a hitchhiker 404 sharing food with the hungry 434 restaurant picking up trash from the outside 375 405 sharing food 435 to charity of a park to her fetus when a cesarean section is recommended to save the life of or to prevent ...... the 376 plentifulness 406 sharing money with family 436 beginning of pregnancy up to the point where maternal-fetal conflict occurs potential links with neurochemicals 377 407 sharing somthing we have more 437 to strangers such as oxytocin sharing the last of yours favorite 378 presents 408 438 to the poor 'snack' with a loved one 379 profuseness 409 sharing with neighbors 439 treating the sick providing a homeless person with 380 410 sharing with others 440 unselfish a warm meal 381 providing free food to a food bank 411 sharing your food 441 unsparling 382 rahul 412 sharing your food with everyone. 442 unstinting sharing your food with someone valunteering your time to help an 383 recycling 413 443 that does not have it organization relief efforts are frequently 384 414 sharing your ideas without reward 444 volunteer provided 385 richness 415 sharing your lunch with someone 445 volunteer at an animal shelter 386 ruban 416 sharing your time with others 446 volunteer workers sacrifies their studys for sippings 387 417 sparing change 447 volunteering sties 388 self confidence 418 spending time with the elderly 448 volunteering sponsoring a starving child in a 389 self esteem 419 449 volunteering third world country 390 selflessness 420 staying late to help a coworker 450 volunteering

451 volunteering 452 volunteering at a homeless shelter 453 volunteering at an animal shelter 454 volunteering at charities volunteering at habitat for 455 humanity 456 volunteering at homeless shelter 457 volunteering for a good cause volunteering for an organization 458 like mercy ships 459 volunteering for charity 460 volunteering for charity 461 volunteering in a soup kitchen 462 volunteering time volunteering time at a charity or for 463 a cause 464 volunteering time volunteering to build homes for 465 others 466 walk a neighbors dog we shold know about a hoping 467 mind of life 468 welcoming people in home 469 well paying hits when she went to pay for it, she learned that another woman had 470 already taken care of the $495 cost when someone regularly makes 471 large contributions to charity 472 wish the girl even she cheat them with some people, though, the well 473 of generosity runs deep working as a volunteer for a non- 474 profit 475 working at a soup kitchen 476 working in soup kitchen working overtime to complete a 477 sick colleague's project

Table S9. Unedited participant-generated acts of impartiality from Supplemental Study 1.

"four sublime states" are 1 31 abstaining from giving your opinion 61 bills benevolence, compassion 2 1 32 acting as referee in sporting event 62 blind studies adherence to the law every 3 1 33 63 blind votes moment 4 1 34 affirmative action 64 booing a away football team bosses that treat all employees the 5 2 35 alcohol 65 same allowing someone to talk without 6 2 36 66 breathing interruption of your own input calling someone a name for being 7 2 37 an umpire calling a baseball game 67 or looking differnet calling the police regardless of who 8 2 38 applet 68 commits the crime appreciation, and 9 23 39 69 candid impartiality/equanimity 23 synonyms of justice from the merriam-webster thesaurus, plus 10 40 assigning tasks at work 70 cartoon 28 related words, definitions, and antonyms 11 3 41 avoiding being a judge 71 cheating be friendly no matter what race 12 3 42 72 checking the weather they are 3 lack of favoritism toward one side 13 43 beginning a trial as a jury 73 cheering for both sports teams or another a boss giving a promotion purely choosing a winner's name out of a 14 44 being a democrat or republican 74 based on merit hat 15 a cop giving himself a ticket 45 being a judge at a court 75 choosing brands at random a cop, however, cannot consider these right to life and liberty issues choosing to make a decision by 16 because they themselves would be 46 being a judge. 76 flipping a coin violating the law if they do not arrest a disinterested bystander 17 mediating an argument between 47 being a manager in a store 77 classroom two people 18 a fair analysis of a job application 48 being a middle man in a deal 78 coin toss 19 a judge assigning a sentencing 49 being a moderate in politics 79 commerce connecting our stories to the way 20 a judge presiding over a trial 50 being a moderate politically 80 of love - episcopal diocese of northern michigan, marquette a judge properly dealing out 21 51 being a referee for a game 81 counting votes in an election judgments a judge truly deciding a case 22 52 being a referee for a sports game 82 daughter in law and daughter based on the evidence a judge who acts fairly to both day by day census changing their 23 53 being an independent voter 83 sides rate from a target point to another a mother hearing both sides of her 24 54 being in a court 84 death children's dispute with no bias a parent dividing his assets equally 25 55 being in a perfect class 85 death among his children in his will a parent giving children christmas 26 56 being mean to someone 86 deciding between 2 bland dishes gifts equally a scientist performing an 27 57 being neutral in certain situations 87 deomocratic acts experiment a song that you neither like or 28 58 being pan 88 depreesion dislike a teacher giving all students the developing seven factors are 29 same opportunities to make up 59 being racist 89 conducive to the attainment of work enlightenmen a teacher who disciplines all 30 students the same, even though 60 biased sports reporters 90 dinesh she favors some

disciplining your child when the do first come first serve at giving the same money to each 91 121 151 wrong restaurants person first preference to first child in giving the same opportunity to 92 disinterested 122 152 home people giving to charity that you don't 93 disputants 123 first preference to media 153 know about dividing cake by cutting and giving your children equal 94 124 flipping a coin 154 letting other person pick allowance do not watch football so not into giving your children the same 95 125 flipping a coin for a decision 155 the super bowl gifts on special occasions donating the same amount to all giving your two kids the same 96 126 flipping a coin to choose a winner 156 countries in need rewards drawing names from a hat for a flipping a coin to decide who gets going to the closest restaurant 97 127 157 project at work the ball first in football instead of your favorite 98 driving 128 flipping a coin to make a decision 158 going with whatever is free following the rules without 99 driving to work 129 159 good preference for one party 100 drug 130 fraud 160 good each and every time peolpes are 101 dying and one part are birthing as 131 friends 161 good new born each officer swears an oath to from a different country so don't 102 uphold the law and to defend an 132 162 good care about your issues individual's constitutional rights 103 elections 133 funny 163 good 104 equal 134 gender inequality 164 good equal amount of white and black 105 135 getting both your kids equal gifts 165 good people getting an award getting to know everyone in a equal opportunity for male and 106 136 group, especially those different 166 good female from you give first preference to popular 107 equal opportunity practices 137 167 good man giving a job to the most qualified 108 equal sharing in your kids 138 168 good candidate 109 equal treatment of all rivals 139 giving children equal allowance 169 google giving equal attention to each of grabbing a random drink at a 110 equality 140 170 your children restaurant giving equal attention to each of 111 equality 141 171 gravity your friends giving equal attention to each of 112 equitable 142 172 guessing your parents hate baseball so who cares about 113 evenhandedness 143 giving everyone a punishment 173 world series he was able to bring humor and giving someone the silent 114 facebook 144 174 energy to the lives of many, treatment especially those he was able to bring humor and giving the promotion to the top 115 facts 145 175 energy to the lives of many, performing employee especially those giving the same attention to every helping one parent as much as 116 fair 146 176 kid in the family you would the other giving the same clothing to each helping people of different 117 fairness 147 177 person backgrounds giving the same food to each 118 fairness in competition 148 178 helping people of same sex person fairness is defined as: “fair or giving the same job opportunity to 119 impartial treatment; lack of 149 179 hiring men and women equally both females and males favoritism toward one side giving the same level of customer 120 favoring a sports team 150 180 home court advantage service to all customers in my house i am impartial in any not caring which team wins a 181 211 making a blind choice 241 discussion game in my work i am impartial in any making people pick a number to not caring who wins a sports 182 212 242 discussion see who gets something desired match in objectivity, lorraine daston and peter galison chart the emergence 183 of ... this is a story of lofty 213 management 243 not choosing sides epistemic ideals fused with workaday practices in the ... Title independent voter and not a not discriminating against people 184 214 manager on work 244 democrat or republican with different religions most of the peoples are changing not engaging in discussion due to 185 indifferent 215 their mind set from one part to 245 lack of interest or care another not favoring one child over 186 innocent until proven guilty 216 n/a 246 another job is awarded to the most not giving a student better grades 187 217 n/a 247 qualified candidate because they're better behaved not having a child you call upon 188 job issuing 218 n/a 248 more often than the other job performance evaluations with 189 219 n/a 249 not having a favorite sports team all the same criteria not having a preference of sports 190 judge 220 n/a 250 team winning not having a preference on food 191 judge or jury in court 221 n/a 251 choice not having and opinion on 192 judges 222 n/a 252 abortion not hiring someone just because 193 judging a case fairly 223 n/a 253 they're your friend not hiring your kids over someone 194 judging without bias 224 n/a 254 more qualified 195 jury deliberation 225 n/a 255 not leaving out anyone not loving one child more than the 196 jury duty 226 nature 256 other 197 just 227 needing water and food 257 not making a decision

198 lack of a wage gap 228 neutralism 258 not picking a political party

199 laws 229 neutrality 259 not reacting to something letting every kid have a slice of 200 230 no judging 260 not sharing stuff pizza not siding with a friend over a 201 life and death 231 no leverage on another person 261 stranger in an argument not taking gifts from potential 202 like all colors and shapes 232 no prior rules to follow 262 clients 203 liking dogs and cats equally 233 no selection based on prejudice 263 not taking side when family fights

204 liking one kid more than the other 234 not being biased 264 not voting listening to both parties in a 205 235 not caring 265 not voting conflict equally 206 listening to both sides of the story 236 not caring 266 not voting listening to only one side of a 207 237 not caring about politics 267 not voting on election day argument living in one country and not caring about the attitudes of 208 238 268 objective comparing to another coworkers one of the ethical issues that an officer faces daily is the ability to 209 lots of friends 239 not caring what sex your child is 269 uphold these oaths when they are seemingly contradictory not caring whether or not 210 lottery 240 270 one political side over the other someone shows up at a party

the best chance at succeeding in parents that treat all children the life, they need to develop five dis- 271 301 school 331 same tinct skills; at least, in the opinion of one writer. see this perspective the dictionary.com link shows to the definition for "objective", and picking college applicants from seeing both sides of the story 272 302 332 the ... philosophy : existing high school before making a decision outside of the mind : existing in the real world the great pumpkin, charlie brown, select members of the scotus author ... it is said that charles 273 picking job applicants for a job 303 333 ruling with no bias schulz did not assign any religious meaning to the story serving customers on a first the love a mother has for her 274 police officer 304 334 come, first serve basis children police officers are held to an extremely high standard that 275 requires their personal lives to 305 serving food 335 the sun reflect the integrity of their position they must maintain a professional 276 political discourse 306 serving on a jury 336 image at all times because they are under constant public scrutiny political reporters asking favored settling an argument over who 277 307 337 thilak questions gets something with a coin toss this often puts them in direct conflict with society, especially 278 politics 308 sexism 338 those that have little respect for the law or the badge punishing everyone involved with 279 a crime, instead of exempting 309 sexism 339 time based competitions some based on finances putting away personal feelings in sharing things equally between treating all of your children the 280 310 340 favor of what is right two people same 281 racism 311 sharing with everyone 341 treating all of your kids equally shopping for a tv with no budget treating all subordinate workers 282 racism 312 342 in mind equally 283 racism 313 showing disinterest 343 treating all your students equally 284 ram 314 showing no emotion 344 treating both parents equally 285 ram 315 siblings 345 treating men and women equally 286 random lotteries 316 son and daughter 346 treating other races equally randomly selecting people for spending as much time with one 287 317 347 treating poor people nicely something through a lottery person as you do another splitting a candybar evenly 288 reality shows 318 348 treating sibblings equally between two kids treating two groups of people 289 referee 319 splitting evenly 349 fairly referee awards a penalty cause a trying everything/trying new 290 320 sports 350 foul is comitted things 291 referees judging a game or match 321 square 351 trying to treat children equally turning down the radio when a 292 religion 322 staying out of an argument 352 song you don't like comes on rely on the public's trust to 293 323 stopping racism 353 umpire maintain their power position removing demographic 294 information from college 324 stress 354 umpire calling a close play applications 295 republican acts 325 suicide 355 umpires in a sports match 296 republican and democratic 326 taking whatever is left 356 unbiased 297 right to good administration 327 taxes 357 union acts using a random number 298 right to good administration 328 teacher 358 generator to decide teacher award marks based on 299 same salary b/w man and woman 329 359 vickey performance only teachers that treat all students 300 saying that all women suck 330 360 volunteering to help others equally 361 voting 362 voting for a candidate randomly 363 walking away from a fight we should know about daily laws 364 are changing to new rules 365 welfare to the poor when a news channel is reporting 366 on a story and they only tell the facts instead of their opinion when politics are being discussed, 367 staying netural when someone is caught with a few illegal marijuana seeds, they 368 could face imprisonment, fines, job loss, loss of social reputation

when your friends are having a 369 disagreement, helping to moderate for them 370 while hiring people

while most jobs end when the individual clocks out, policeman 371 are faced with the ethical issues of maintaining their level of social respect

372 winner take all in gambling 373 winning a role for a good audtion with my friends i do not side with 374 anyone 375 work 376 working with coworkers

References

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