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The face of another: anonymity and facial symmetry influence cooperation in social dilemmas
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The face of another: anonymity and facial symmetry influence cooperation in social dilemmas Claudia Rodríguez-Ruiza, Santiago Sanchez-Pagesb, Enrique Turieganoa, a b
⁎
Biology Department, Universidad Autónoma de Madrid, C/Darwin 2, 28029 Madrid, Spain School of Economics, Universitat de Barcelona, C/John M. Keynes 1-11, 08034 Barcelona, Spain
A R T I C LE I N FO
A B S T R A C T
Keywords: Cooperation Prisoner's dilemma Anonymous interactions Fluctuating asymmetry Facial masculinity 2D:4D
In the present paper, we study how the morphological features related to developmental physiology of other participants influence the decision to cooperate in a social dilemma. To that end, we let a large sample of men play a prisoner's dilemma game, both anonymously and against a series of counterparts whose photographs were shown. We focus on three characteristics already linked to cooperative behavior and with described effects on the adult facial shape: facial fluctuating asymmetry, a frequently employed but debated proxy for developmental instability; the degree of facial dimorphism, related to levels of testosterone during puberty; and the second to fourth digit ratio, related to relative prenatal testosterone exposure. We find significantly higher cooperation rates in anonymous interactions than in the non-anonymous round. We also find that individuals are more likely to cooperate with more asymmetric counterparts, and that more asymmetric participants were less likely to believe that their counterpart would cooperate. Variables related to exposure to testosterone during development do not display any effect. We conclude by discussing how out-of-the-game rewards can explain our results.
1. Introduction Cooperation is a behavior which explanation remains elusive from a social and evolutionary perspective (Fehr & Gachter, 2002; West, El Mouden, & Gardner, 2011). Individual cooperation is influenced by many factors: the sociological context (Stirrat & Perrett, 2012), the individual's psychology (e.g. DeAngelo & McCannon, 2017) and her/his physiological features (e.g. Burnham, 2007; Dreher et al., 2016; MuñozReyes, Pita, Arjona, Sanchez-Pages, & Turiegano, 2014; Schipper, 2015). Studies on the behavioral effects of physiology have produced valuable insights by means of games which reproduce in the lab the key features of some social situation. In these games, participants interact with another individual and the result of their interaction depends on their decisions; they are aware of the impact that their counterpart's choices have on the outcome and adjust their own behavior in consequence. A strand of this literature has studied cooperative behavior in nonanonymous social dilemmas where individuals were given the opportunity to evaluate their counterparts' cooperative intent (Brosig, 2002; Frank, Gilovich, & Regan, 1993; Sparks, Burleigh, & Barclay, 2016). However, the effect of the counterpart's features on the decision to cooperate remains poorly studied; a few studies have explored this question but using computer-generated faces (Giang, Bell, & Buchner, ⁎
2012; Krupp, Debruine, & Barclay, 2008). In the present paper, we tackle this question by employing the prisoner's dilemma game (PD), a widely accepted tool to model real-life interactions (Axelrod, 1984) which has been applied to the analysis of the association between individual features and cooperation (Muñoz-Reyes et al., 2014; SanchezPages & Turiegano, 2010; Shinada & Yamagishi, 2014; Sylwester, Lyons, Buchanan, Nettle, & Roberts, 2012; Takahashi, Yamagishi, Tanida, Kiyonari, & Kanazawa, 2006; Yamagishi, Tanida, Mashima, Shimoma, & Kanazawa, 2003). We let a large sample of men play this game and studied the effect of the counterpart's visible morphological features on their cooperativeness. Naturally, the counterpart's traits most likely to influence cooperative behavior are those perceptible features associated with cooperation (Reimers & Diekhof, 2015; Sanchez-Pages & Turiegano, 2010; Shinada & Yamagishi, 2014; Stirrat & Perrett, 2012; Takahashi et al., 2006). These include some features related to the physiological state during fetal and pubertal development (Millet & Dewitte, 2006; MunozReyes et al., 2014; Sanchez-Pages & Turiegano, 2010; Stirrat & Perrett, 2012) which are known to influence visible morphology. These physiology-related characteristics are likely to be relevant in face-to-face interactions because individuals might use them as cues to adjust their behavior. One of these variables is facial fluctuating asymmetry (FA), which is usually considered as an indicator of developmental instability
Corresponding author at: C/Darwin 2, 28049 Madrid, Spain. E-mail addresses: [email protected] (C. Rodríguez-Ruiz), [email protected] (S. Sanchez-Pages), [email protected] (E. Turiegano).
https://doi.org/10.1016/j.evolhumbehav.2018.09.002 Received 26 April 2018; Received in revised form 21 August 2018; Accepted 3 September 2018 1090-5138/ © 2018 Elsevier Inc. All rights reserved.
Please cite this article as: Rodríguez-Ruiz, C., Evolution and Human Behavior, https://doi.org/10.1016/j.evolhumbehav.2018.09.002
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2. Materials and methods
(Møller, 1997; Van Dongen & Gangestad, 2011). Researchers have observed that men and women with a higher facial FA tend to be more prosocial and cooperative (Munoz-Reyes et al., 2014; Sanchez-Pages & Turiegano, 2010; Takahashi et al., 2006). FA has also been related to attractiveness (Perrett et al., 1999), which suggests that this feature influences observers' evaluations. Other variables linked to cooperative behavior relate to levels of sexual hormones during development, particularly in men. These levels can be estimated by measuring adult dimorphic physical traits which correlate with exposure to sexual hormones during fetal and pubertal development. Two of these traits are the degree of facial dimorphism and the second to fourth digit ratio (2D:4D). Facial masculinity in men, understood as a more extreme facial dimorphism, has been related to higher levels of testosterone during puberty (Welker, Bird, & Arnocky, 2016). Men with higher facial masculinity tend to behave less prosocially (Carre & McCormick, 2008; Carre, McCormick, & Mondloch, 2009; Haselhuhn & Wong, 2012; Stirrat & Perrett, 2010), except in ingroup male-male competitions (Stirrat & Perrett, 2012). On the other hand, 2D:4D is inversely related to prenatal testosterone experimentally modified in some non-human mammals (Talarovičová, Kršková, & Blažeková, 2009; Zheng & Cohn, 2011). Men with higher 2D:4D are less prosocial and cooperative (Brañas-Garza, Kovářík, & Neyse, 2013; Galizzi & Nieboer, 2015; Millet & Dewitte, 2006, 2009; Sanchez-Pages & Turiegano, 2010; Van den Bergh & Dewitte, 2006). Testosterone exposure during fetal development, assessed via 2D:4D (Burriss, Little, & Nelson, 2007; Fink et al., 2005; Meindl, Windhager, Wallner, & Schaefer, 2012; Weinberg, Parsons, Raffensperger, & Marazita, 2015), and directly measured perinatal testosterone (Whitehouse et al., 2015) have been shown to influence the adult face shape. Based on the aforementioned evidence, we postulated a number of exploratory hypotheses. We expected the counterpart's FA to have a positive relationship with the player's tendency to cooperate given that people with higher FA tend to be more cooperative (Muñoz-Reyes et al., 2014; Takahashi et al., 2006), and given that individuals are more likely to cooperate when they expect their counterpart to cooperate as well (Sanchez-Pages & Turiegano, 2010). We expected male players matched with counterparts exposed to lower relative levels of prenatal testosterone to cooperate less frequently, given that men with higher 2D:4D are less prone to behave prosocially (Brañas-Garza et al., 2013; Galizzi & Nieboer, 2015; Millet & Dewitte, 2006, 2009; Sanchez-Pages & Turiegano, 2010; van Honk, Montoya, Bos, van Vugt, & Terburg, 2012). Finally, men with higher facial masculinity tend to be less prosocial (e.g. Carre et al., 2009; Carre & McCormick, 2008; Haselhuhn & Wong, 2012; Stirrat & Perrett, 2010); thus, we expected men to be more cooperative with counterparts who displayed lower levels of facial masculinity. In addition to these direct effects, there might be an indirect influence of the counterpart's features on cooperative behavior when considered in conjunction with the player's own features. The effects of FA and masculinity on behavior are typically explained based on their relationship with individual status via a higher phenotypic quality (see Scott, Clark, Boothroyd, & Penton-Voak, 2013, for a review on masculinity and Rhodes et al., 2001, for FA). Prosociality can be viewed as a mechanism of competition among men (Farrelly, 2011; Millet, 2011; Van Vugt & Iredale, 2013). Perceived differences in status might, therefore, encourage this kind of competition (Archer, 2006; Puts, 2016). Thus, we postulated that participants with low FA, high facial masculinity or low 2D:4D cooperate more frequently when their counterparts show features related to high status. To that end, we included the morphological features of both players in all our analyses. Finally, according to the aforementioned evidence and independently of the counterpart's features, we expected low symmetry, low 2D:4D, and low facial masculinity participants to cooperate more frequently.
2.1. Participants The experiment was carried out at Universidad Autónoma de Madrid (UAM). A total of 176 males aged between 18 and 28 participated in the experiment (mean ± SD: 21.90 ± 2.38 yr). Experiments were carried out exclusively with men for two reasons. First, because the effects on behavior of sexual hormones during development seem to be mainly relevant in males (Muñoz-Reyes et al., 2014). Second, because cooperation has been described as a competitive mechanism only among men (Farrelly, Lazarus, & Roberts, 2007; Van Vugt & Iredale, 2013). All participants classified themselves as Caucasian except nine individuals, whose data were discarded because ethnic homogeneity is required for the facial masculinity measure to be reliable. Written informed consent was obtained from all participants. The experimental procedure was approved by the UAM ethics committee (reference number: 73–1319). 2.2. Experimental design The experiments were performed employing the z-Tree 3.2.10 software for Economic Experiments (Fischbacher, 2007). Nine different PD stages were programmed. The first stage was an anonymous PD game. In this game, mutual cooperation ensures the best social outcome but both players have an individual incentive to behave opportunistically, leading to a socially inferior result. Participants had to decide whether to cooperate or not with a participant in a previous session. If the participant and his anonymous counterpart chose to cooperate, they both got 90 points; if only one of them cooperated, the cooperator obtained 10 points whereas the other received 160 points; if none of them cooperated, they both got 30 points. In addition to this choice, participants were asked what strategy they expected their counterpart to choose. In the eight remaining rounds, the PD game had the same payoff structure, but the photograph of a different male was shown in each round (see Supplementary figure). These men had played this PD in a previous experiment at least five years earlier, which reducing the possibility that they were considered ingroup by the participants. We obtained the consent from these eight males to use their photographs in further studies. In these eight non-anonymous rounds, participants were told they were playing with the person whose photograph they were seeing, and that the choice made by these individuals in an identical anonymous PD game in conjunction with their own choice now was going to determine their payment in that round. As in the anonymous round, we asked participants which choice they believed each of these eight individuals made when they played the PD. The order of the eight non-anonymous stages was randomized across sessions. The first stage was always anonymous. This was intended to avoid any priming from a previous non-anonymous round. We did not expect drastic changes in behavior between the first PD stage and the non-anonymous ones as there was no feedback between stages, thus leaving little room for learning or readjustment. 2.3. Experimental sessions No > 25 subjects participated in each session. Before the experiment started, subjects were instructed about the procedures. They filled in a questionnaire assessing their age, ethnicity and degree of study. Subjects were paid according to the points they had earned after the nine rounds, in addition to the show-up fee (5€). Each point was worth 1 euro cent. We took a hand-scan and frontal facial photographs of all participants. We employed a HP psc 2110 scanner, with a resolution of 600 × 1200 ppi, for the hand images. Photographs were taken with an Olympus E-500 digital camera with resolution 4288 × 2848 px in JPEG 2
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2.6. Statistical methods
format under standardized light conditions. The camera was always at 3 m from the subject, and the field was completely opened to avoid distortion. Participants were asked to remove facial adornments and were carefully instructed to pose looking directly into the camera with a neutral expression.
Our main variables of interest were binary: the participant's decision to cooperate and the expectation of the counterpart's cooperation. Our independent variables were the morphological measures described above, personal characteristics (age, self-classified ethnicity) and session fixed effects. Regression analysis is the most suitable technique to simultaneously study all these variables. We opted for a linear probability model (LPM) rather than for a Probit model as our main specification. Coefficients are much easier to understand in the former model; a one standard deviation increase in one variable is associated with a percentage points (pp) change in the dependent variable. It has been shown that the estimation bias of the LPM increases with the number of predicted probabilities outside the 0 and 1 interval. Only 0.01% of our predicted probabilities presented this problem, suggesting that our LPM estimates were unbiased. Nonetheless, we also ran the corresponding Probit regressions and reported them in the tables to demonstrate the robustness of our results.
2.4. 2D:4D The second and fourth digits of the right hand were measured on the scanned images, from the flexion crease proximal to the palm to the top of the digit, as in the previous literature (Apicella et al., 2011; Millet & Dewitte, 2006; Pearson & Schipper, 2012). Two researchers placed the landmarks (LMs) independently with the TPS software version 2.16 (by F.J. Rohlf; obtained from http://life.bio.sunysb.edu/ee/rohlf/software. html). The two measurements of 2D:4D were highly correlated (r176 = 0.872, p < .001). The average of both measurements was used. Analyses on PD behavior include the squared 2D:4D (Tables 2 and 3) in order to test a previously observed non-monotonic relationship between 2D:4D and prosociality (Brañas-Garza et al., 2013; Galizzi & Nieboer, 2015; Millet & Dewitte, 2006; Sanchez-Pages & Turiegano, 2010).
3. Results 3.1. Cooperation
2.5. FA and masculinity measurements
Table 2 contains the results of the analysis on the decision to cooperate. In column 1, we simply compared behavior in the first PD round, where participants played against an anonymous subject, with the other eight non-anonymous rounds. As conjectured, we found a very strong effect of expected cooperation. Participants who expected their counterpart to cooperate were 36 pp. more likely to cooperate themselves. We found that anonymity had a strong effect as well: Controlling just for age, session and ethnicity, participants were 13.5 pp. more likely to cooperate in the anonymous PD. This is consistent with aggregate figures: subjects cooperated in the 55.11% of anonymous decisions but only in 40.13% of the non-anonymous ones. The coefficient maintained its magnitude in column 2, where we controlled for the morphological features of the subject. None of them were statistically significant. Columns 3 and 4 include the facial features of the counterpart. Estimates show that participants were more likely to cooperate with a counterpart with a more asymmetric face. A one standard deviation increment in the counterpart's FA increased the likelihood of
Two independent observers placed 39 predefined landmarks, which we had already used in previous works (Muñoz-Reyes et al., 2014; Sanchez-Pages, Rodriguez-Ruiz, & Turiegano, 2014; Sanchez-Pages & Turiegano, 2010), in two frontal facial photographs of each subject. FA and masculinity scores were calculated using the MorphoJ software, version 1.04a (by C.P. Klingenberg; obtained from http://www. flywings.org.uk/morphoj_page.html). FA scores were obtained from these landmarks by means of a Procrustes ANOVA run using the aforementioned software as in Sanchez-Pages and Turiegano (2010). This procedure compares each image with its mirrored image and decomposes asymmetry into two factors: directional and fluctuating asymmetry. Error in LM positioning was not significant (Procrustes ANOVA, error SS = 6.318 × 10−2, df = 13,024, F = 0.469, p = .999). The score for fluctuating asymmetry employed was the Mahalanobis distance, as it avoids the effect of the landmarks spatial distribution on asymmetry. Masculinity scores were computed performing a discriminant function on the facial shape information obtained by employing Geometric Morphometrics, a fitted method to measure the effect of masculinity on behavior (Sanchez-Pages et al., 2014). To this end, we used a sample of 460 women of the same age and ethnicity to those of the men in our sample (mean ± SD: 21.55 ± 2.57 yr). The function calculates the best possible discrimination between the male and female sample. The resulting discriminant function correctly classifies the sex of 95.82% of the faces (T2 test: T2 = 2528.2938; p < .001). Discriminant function scores for each individual were used as an index of masculinity, with high scores indicating a more masculine face shape. Table 1 presents descriptive statistics for the sample of participants and the counterparts.
Table 2 The effect of morphological features on cooperation. Independent variables
Anonymous Belief
Cooperation LPM [1]
LPM [2]
0.135*** (0.036) 0.366*** (0.022)
0.135*** (0.036) 0.362*** (0.022) −1.552 (17.774) 0.480 (9.200) −0.004 (0.002) 0.003 (0.018)
2D:4D ratio 2D:4D2 Facial masculinity
Table 1 Descriptive statistics for the variables considered in our participants sample and in the counterparts in the non-anonymous group. Data are the mean ± SD.
Facial FA Facial masculinity 2D:4D ratio Age
Participants (N = 176)
Counterpart in non-anonymous stage (N = 8)
3.997 ± 0.644 5.763 ± 3.865 0.960 ± 0.031 21.903 ± 2.383
3.678 ± 0.697 9.244 ± 5.889 0.954 ± 0.037 20.625 ± 1.408
Facial FA Counterpart's Masculinity Counterpart's Facial FA R-Squared N
0.180 1737
0.182 1737
LPM [3]
Probit [4]
0.332*** (0.024) −23.564 (19.163) 11.833 (9.916) −0.003 (0.003) 0.011 (0.020) −0.000 (0.002) 0.045** (0.022) 0.146 1408
0.936*** (0.074) −96.956 (52.586) 34.225 (29.095) −0.011 (0.009) 0.029 (0.060) −0.000 (0.007) 0.130** (0.064) 0.115 1408
Notes: Robust standard errors in parentheses *** (**) (*) indicate significance at the 1%, 5% and 10% level. 3
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Table 3 The effect of morphological features on expected cooperation by the counterpart. Independent variables
Anonymous
Independent variables
Belief on counterpart's cooperation LPM [1]
LPM [2]
0.038 (0.038)
0.038 (0.038) −13.570 (19.070) 6.519 (9.875)
2D:4D ratio 2D:4D2
−0.003 (0.003) −0.048*** (0.020)
Facial masculinity Facial FA Counterpart's Masculinity Counterpart's Facial FA R-Squared N
Table 4 The effect of morphological features on changes in cooperation.
0.035 1737
0.043 1737
LPM [3]
Probit [4]
−18.274 (20.859) 8.964 (10.797) −0.002 (0.003) −0.054** (0.022) −0.001 (0.002) 0.012 (0.023)
−47.407 (54.239) 23.238 (28.076) −0.005 (0.009) −0.140** (0.058) −0.003 (0.007) 0.003 (0.062)
0.029 1408
0.021 1408
Cooperated against anonymous 2D:4D ratio Facial masculinity Facial FA Counterpart's Masculinity Counterpart's Facial FA R-Squared N
Changed decision against at least one counterpart
Switched anonymous decision
LPM [1]
Probit [2]
LPM [3]
Probit [4]
0.217*** (0.069) −0.065 (1.059) −0.003 (0.008) 0.098** (0.048)
0.745*** (0.226) −0.673 (3.738) −0.009 (0.029) 0.400** (0.200)
0.225*** (0.025) 0.379 (0.425) −0.005 (0.003) 0.086*** (0.020) −0.000 (0.002) −0.018 (0.022)
0.118 176
0.110 174
0.648*** (0.076) 0.999 (1.228) −0.015 (0.009) 0.242*** (0.059) −0.001 (0.007) −0.050 (0.065) 0.079 1408
Notes: Robust standard errors in parentheses *** (**) (*) indicate significance at the 1%, 5% and 10% level, respectively. All regressions include subjects' age, ethnic group and session dummies.
Notes: Robust standard errors in parentheses *** (**) (*) indicate significance at the 1%, 5% and 10% level, respectively. All regressions include subjects' age, ethnic group and session dummies.
Columns 3 and 4 of Table 3 show the effect of counterpart's facial features on the likelihood of a switch from the first stage decision. We considered each face as a new treatment, so the coefficient estimates represent the average effect of the counterpart's feature on an individual's decision to change his decision. We found no statistically significant effect.
cooperation by 2.9 pp. 3.2. Beliefs Subjects expected their counterpart to cooperate in 54.41% of the occasions. Table 3 reports the results of the regression analyses on the expectation of cooperation. As before, column 1 leaves out all morphological features. We found no differences in beliefs across anonymous and non-anonymous rounds. Column 2 looks at the influence of an individual's morphological features on beliefs. We found that Facial FA had a negative impact on the expected cooperativeness of the counterpart. A standard deviation increment in this variable reduced the likelihood of a participant expecting his counterpart to cooperate by 3.7 pp. In other words, more asymmetric participants were less likely to believe that their counterpart would cooperate. Column 3 looks at the effect of the facial features of the counterpart. There was no significant effect on expected cooperation.
4. Discussion In this work, we studied how the morphological features related to the developmental physiology of the counterpart affect cooperation in social dilemmas. We ran an experiment in which subjects participated in a series of anonymous and non-anonymous PD games. By comparing their behavior across these rounds, we observed an unexpected result: cooperation rates were higher in the anonymous round than in the non-anonymous ones. We had not postulated any specific hypothesis in this regard, but we would have expected higher cooperation rates in nonanonymous interactions, as individuals tend to show more positive perceptions and behaviors towards their counterparts in face-to-face interactions (Bos, Olson, Gergle, Olson, & Wright, 2002; Burnham, 2003; Hill, Bartol, Tesluk, & Langa, 2009; Tanis & Postmes, 2007). In addition, the aggregate results in Fig. 1 show that participants who expected their counterpart to cooperate defected more often in the nonanonymous rounds than in the anonymous round. This result became even more surprising after noticing that anonymity had no effect on the expected behavior of the counterpart, so it could not be explained by participants expecting their partners to be less cooperative in the nonanonymous rounds. This suggests that the observed change in behavior was due to the out-of-the-game benefits from defecting which our participants might have taken into consideration after seeing an image of their counterpart. A similar result was observed by Yamauchi (1982), who found that face-to-face interactions made subjects more willing to outscore their counterpart in the PD. These underlying rewards (West et al., 2011) are partially captured by what the economics literature calls social preferences (Fehr & Schmidt, 1999; Rabin, 1993). Among these, spiteful or competitive preferences are consistent with this change in behavior, as they have been shown to explain why individuals pay to earn more than others (Levine, Bluni, & Hochman, 1998), a behavior in line with intrasexual competition motivations (Puts, 2016). The relevance of out-of-the-game rewards on cooperation could be
3.3. External cues We next studied the tendency of participants to change their decision when presented with photographs. Columns 1 and 2 of Table 4 show results for the characteristics of subjects who changed their anonymous decision in later rounds. Only 24.43% of subjects maintained their first stage decision across the eight non-anonymous stages. Subjects who cooperated in the first stage were more likely to change their behavior in later stages; specifically, these subjects were 21 pp. more likely to switch their anonymous stage decision than subjects who defected in the first round. This was to be expected since cooperation rates were lower in non-anonymous rounds. On the other hand, subjects with higher FA were more likely to change their decision. This effect could have been driven by two previous results: Since cooperation was less frequent in non-anonymous rounds and subjects with higher FA expected less cooperation from their counterparts, these participants might have been more likely to change their first stage decision because they switched from cooperation to defection. But separate regressions (see Supplementary Table 1) based on whether subjects cooperated or not in the first stage, showed that higher FA participants were more likely to switch in both directions. This suggests that these individuals were more sensitive to external cues. 4
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Fig. 1. Aggregated data for cooperators and non-cooperators in the anonymous and non-anonymous rounds.
(Wilson & Eckel, 2006; Zaatari & Trivers, 2007) whereas others found the opposite (Sanchez-Pages & Turiegano, 2010; Takahashi et al., 2006). Our participants played several rounds of the PD with different nonanonymous counterparts. When playing with these counterparts, participants could adjust their decision from round to round. We observed (Table 3) that more symmetrical individuals were less likely to change their decision in the first stage during the non-anonymous rounds. In other words, symmetric individuals seemed to be less affected by external cues, whereas less symmetrical individuals seemed to adjust their behavior to the circumstances. This is consistent with the idea that high-fitness individuals are more capable of obtaining resources on their own and can thus behave more independently (Munoz-Reyes et al., 2014; Sanchez-Pages & Turiegano, 2010; Zaatari & Trivers, 2007; Zaatari, Palestis, & Trivers, 2009). It is also feasible that, as subjects were paid for all PD rounds, they might have hedged their odds by diversifying their choices. A switch in decisions might then reflect risk preferences rather than sensitivity to cues. These hypotheses, which are outside the scope of the present paper, could be tested by eliciting second order beliefs from participants (e.g. what behavior do you think your counterpart expects from you?) whilst controlling for their risk aversion. Finally, we found no association between participants' cooperative behavior and the counterpart's testosterone-related developmental features, as measured by facial masculinity and 2D:4D. This contrasts with the previous literature employing the facial width-to-height ratio as a measure of facial masculinity, a variable which correlates only weakly with the measure of masculinity we employed (Sanchez-Pages et al., 2014). However, there is no longer a consensus on the dimorphism of the facial width-to-height ratio (Kramer, 2017), and it might not be a valid proxy to pubertal testosterone levels (HodgesSimeon, Sobraske, Samore, Gurven, & Gaulin, 2016, although see Welker et al., 2016). On the other hand, the lack of correlation between the counterpart's 2D:4D and cooperative behavior might have been due to the relatively weak impact that 2D:4D has on the adult facial shape (Burriss et al., 2007; Fink et al., 2005; Meindl et al., 2012; Weinberg et al., 2015), given that further exposure to sexual hormones has also an effect on face shape (Welker et al., 2016; Whitehouse et al., 2015). In addition, it has recently been shown that effects of biological variables on behavior, especially current testosterone levels, may be mediated by 2D:4D (Millet, 2011; Ryckmans et al., 2015; van Honk et al., 2012). Some of the effects of 2D:4D on behavior are likely to depend on these other biological variables, some of which cannot be perceived in a facial photograph. This might also contribute to explain why the counterpart's 2D:4D displayed no behavioral effect in our study.
observed again in the analysis of the effect on behavior of the counterpart's morphological features. Participants were more likely to cooperate with counterparts with higher FA, even when they were not more likely to believe that these individuals were going to cooperate. Expected counterpart behavior and chosen behavior did not match. This suggests that the effect of perceived FA on behavior operated through preferences. In other words, this result is consistent with participants expecting higher out-of-the game advantages from cooperation with less symmetric individuals, and the contrary from cooperating with more symmetric ones. This tendency to cooperate with low FA individuals against stated beliefs could be built on past cooperative interactions, as low symmetric individuals tend to be more cooperative (Muñoz-Reyes et al., 2014; Sanchez-Pages & Turiegano, 2010). The mismatch between not cooperating with more symmetric counterparts and expecting a cooperative behavior from them is consistent with the “what is beautiful is good” stereotype, the tendency to expect prosocial behavior from more attractive people (Andreoni & Petrie, 2008; Farrelly et al., 2007; Putz, Palotai, Cserto, & Bereczkei, 2016; Solnick & Schweitzer, 1999; Wilson & Eckel, 2006). We did not find any effect of the counterpart's features on their expected behavior. Features of other participants, such as masculinity (Stirrat & Perrett, 2010; Tognetti, Berticat, Raymond, & Faurie, 2013) and attractiveness (Ma, Hu, Jiang, & Meng, 2015), have been shown to influence their perceived cooperativeness and trustworthiness. However, the perception of prosocial features in another individual may not be strongly related to the formation of beliefs about her/his actual behavior in strategic interactions, as suggested by studies showing that defectors often pass undetected (Sylwester et al., 2012, but see Tognetti et al., 2013). In line with Sanchez-Pages and Turiegano (2010), we found that participants' own FA influenced their expectation about the cooperativeness of their counterparts. Hence, FA influenced cooperation through the expected behavior of the counterpart as the latter is a strong determinant of individual cooperation (Muñoz-Reyes et al., 2014; Sanchez-Pages et al., 2014; Sanchez-Pages & Turiegano, 2010). A likely explanation for this effect is the experience of these subjects in previous strategic interactions. Some works (Andreoni & Petrie, 2008; Farrelly et al., 2007; Putz et al., 2016; Wilson & Eckel, 2006) has showed that people are more likely to behave prosocially with high fitness individuals. Less symmetric participants might have experienced low cooperation rates in the past and might have adjusted their expectations accordingly in the lab. However, the literature offers mixed results on the association between expected behavior in strategic anonymous interactions and features related to higher fitness; some observed a higher expected prosociality from high fitness individuals 5
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In sum, our results offer new insights on the complexity of human cooperation, adding new data on how the biological characteristics of all participants influence cooperation. Although variables related to former testosterone levels seemed not to have any effect, facial fluctuating asymmetry did influence behavior. Future research should study whether this influence is related to individuals' expectations and the feedback they gather in their everyday life interactions. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.evolhumbehav.2018.09.002.
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Evolution and Human Behavior journal homepage: www.elsevier.com/locate/ens
The face of another: anonymity and facial symmetry influence cooperation in social dilemmas Claudia Rodríguez-Ruiza, Santiago Sanchez-Pagesb, Enrique Turieganoa, a b
⁎
Biology Department, Universidad Autónoma de Madrid, C/Darwin 2, 28029 Madrid, Spain School of Economics, Universitat de Barcelona, C/John M. Keynes 1-11, 08034 Barcelona, Spain
A R T I C LE I N FO
A B S T R A C T
Keywords: Cooperation Prisoner's dilemma Anonymous interactions Fluctuating asymmetry Facial masculinity 2D:4D
In the present paper, we study how the morphological features related to developmental physiology of other participants influence the decision to cooperate in a social dilemma. To that end, we let a large sample of men play a prisoner's dilemma game, both anonymously and against a series of counterparts whose photographs were shown. We focus on three characteristics already linked to cooperative behavior and with described effects on the adult facial shape: facial fluctuating asymmetry, a frequently employed but debated proxy for developmental instability; the degree of facial dimorphism, related to levels of testosterone during puberty; and the second to fourth digit ratio, related to relative prenatal testosterone exposure. We find significantly higher cooperation rates in anonymous interactions than in the non-anonymous round. We also find that individuals are more likely to cooperate with more asymmetric counterparts, and that more asymmetric participants were less likely to believe that their counterpart would cooperate. Variables related to exposure to testosterone during development do not display any effect. We conclude by discussing how out-of-the-game rewards can explain our results.
1. Introduction Cooperation is a behavior which explanation remains elusive from a social and evolutionary perspective (Fehr & Gachter, 2002; West, El Mouden, & Gardner, 2011). Individual cooperation is influenced by many factors: the sociological context (Stirrat & Perrett, 2012), the individual's psychology (e.g. DeAngelo & McCannon, 2017) and her/his physiological features (e.g. Burnham, 2007; Dreher et al., 2016; MuñozReyes, Pita, Arjona, Sanchez-Pages, & Turiegano, 2014; Schipper, 2015). Studies on the behavioral effects of physiology have produced valuable insights by means of games which reproduce in the lab the key features of some social situation. In these games, participants interact with another individual and the result of their interaction depends on their decisions; they are aware of the impact that their counterpart's choices have on the outcome and adjust their own behavior in consequence. A strand of this literature has studied cooperative behavior in nonanonymous social dilemmas where individuals were given the opportunity to evaluate their counterparts' cooperative intent (Brosig, 2002; Frank, Gilovich, & Regan, 1993; Sparks, Burleigh, & Barclay, 2016). However, the effect of the counterpart's features on the decision to cooperate remains poorly studied; a few studies have explored this question but using computer-generated faces (Giang, Bell, & Buchner, ⁎
2012; Krupp, Debruine, & Barclay, 2008). In the present paper, we tackle this question by employing the prisoner's dilemma game (PD), a widely accepted tool to model real-life interactions (Axelrod, 1984) which has been applied to the analysis of the association between individual features and cooperation (Muñoz-Reyes et al., 2014; SanchezPages & Turiegano, 2010; Shinada & Yamagishi, 2014; Sylwester, Lyons, Buchanan, Nettle, & Roberts, 2012; Takahashi, Yamagishi, Tanida, Kiyonari, & Kanazawa, 2006; Yamagishi, Tanida, Mashima, Shimoma, & Kanazawa, 2003). We let a large sample of men play this game and studied the effect of the counterpart's visible morphological features on their cooperativeness. Naturally, the counterpart's traits most likely to influence cooperative behavior are those perceptible features associated with cooperation (Reimers & Diekhof, 2015; Sanchez-Pages & Turiegano, 2010; Shinada & Yamagishi, 2014; Stirrat & Perrett, 2012; Takahashi et al., 2006). These include some features related to the physiological state during fetal and pubertal development (Millet & Dewitte, 2006; MunozReyes et al., 2014; Sanchez-Pages & Turiegano, 2010; Stirrat & Perrett, 2012) which are known to influence visible morphology. These physiology-related characteristics are likely to be relevant in face-to-face interactions because individuals might use them as cues to adjust their behavior. One of these variables is facial fluctuating asymmetry (FA), which is usually considered as an indicator of developmental instability
Corresponding author at: C/Darwin 2, 28049 Madrid, Spain. E-mail addresses: [email protected] (C. Rodríguez-Ruiz), [email protected] (S. Sanchez-Pages), [email protected] (E. Turiegano).
https://doi.org/10.1016/j.evolhumbehav.2018.09.002 Received 26 April 2018; Received in revised form 21 August 2018; Accepted 3 September 2018 1090-5138/ © 2018 Elsevier Inc. All rights reserved.
Please cite this article as: Rodríguez-Ruiz, C., Evolution and Human Behavior, https://doi.org/10.1016/j.evolhumbehav.2018.09.002
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(Møller, 1997; Van Dongen & Gangestad, 2011). Researchers have observed that men and women with a higher facial FA tend to be more prosocial and cooperative (Munoz-Reyes et al., 2014; Sanchez-Pages & Turiegano, 2010; Takahashi et al., 2006). FA has also been related to attractiveness (Perrett et al., 1999), which suggests that this feature influences observers' evaluations. Other variables linked to cooperative behavior relate to levels of sexual hormones during development, particularly in men. These levels can be estimated by measuring adult dimorphic physical traits which correlate with exposure to sexual hormones during fetal and pubertal development. Two of these traits are the degree of facial dimorphism and the second to fourth digit ratio (2D:4D). Facial masculinity in men, understood as a more extreme facial dimorphism, has been related to higher levels of testosterone during puberty (Welker, Bird, & Arnocky, 2016). Men with higher facial masculinity tend to behave less prosocially (Carre & McCormick, 2008; Carre, McCormick, & Mondloch, 2009; Haselhuhn & Wong, 2012; Stirrat & Perrett, 2010), except in ingroup male-male competitions (Stirrat & Perrett, 2012). On the other hand, 2D:4D is inversely related to prenatal testosterone experimentally modified in some non-human mammals (Talarovičová, Kršková, & Blažeková, 2009; Zheng & Cohn, 2011). Men with higher 2D:4D are less prosocial and cooperative (Brañas-Garza, Kovářík, & Neyse, 2013; Galizzi & Nieboer, 2015; Millet & Dewitte, 2006, 2009; Sanchez-Pages & Turiegano, 2010; Van den Bergh & Dewitte, 2006). Testosterone exposure during fetal development, assessed via 2D:4D (Burriss, Little, & Nelson, 2007; Fink et al., 2005; Meindl, Windhager, Wallner, & Schaefer, 2012; Weinberg, Parsons, Raffensperger, & Marazita, 2015), and directly measured perinatal testosterone (Whitehouse et al., 2015) have been shown to influence the adult face shape. Based on the aforementioned evidence, we postulated a number of exploratory hypotheses. We expected the counterpart's FA to have a positive relationship with the player's tendency to cooperate given that people with higher FA tend to be more cooperative (Muñoz-Reyes et al., 2014; Takahashi et al., 2006), and given that individuals are more likely to cooperate when they expect their counterpart to cooperate as well (Sanchez-Pages & Turiegano, 2010). We expected male players matched with counterparts exposed to lower relative levels of prenatal testosterone to cooperate less frequently, given that men with higher 2D:4D are less prone to behave prosocially (Brañas-Garza et al., 2013; Galizzi & Nieboer, 2015; Millet & Dewitte, 2006, 2009; Sanchez-Pages & Turiegano, 2010; van Honk, Montoya, Bos, van Vugt, & Terburg, 2012). Finally, men with higher facial masculinity tend to be less prosocial (e.g. Carre et al., 2009; Carre & McCormick, 2008; Haselhuhn & Wong, 2012; Stirrat & Perrett, 2010); thus, we expected men to be more cooperative with counterparts who displayed lower levels of facial masculinity. In addition to these direct effects, there might be an indirect influence of the counterpart's features on cooperative behavior when considered in conjunction with the player's own features. The effects of FA and masculinity on behavior are typically explained based on their relationship with individual status via a higher phenotypic quality (see Scott, Clark, Boothroyd, & Penton-Voak, 2013, for a review on masculinity and Rhodes et al., 2001, for FA). Prosociality can be viewed as a mechanism of competition among men (Farrelly, 2011; Millet, 2011; Van Vugt & Iredale, 2013). Perceived differences in status might, therefore, encourage this kind of competition (Archer, 2006; Puts, 2016). Thus, we postulated that participants with low FA, high facial masculinity or low 2D:4D cooperate more frequently when their counterparts show features related to high status. To that end, we included the morphological features of both players in all our analyses. Finally, according to the aforementioned evidence and independently of the counterpart's features, we expected low symmetry, low 2D:4D, and low facial masculinity participants to cooperate more frequently.
2.1. Participants The experiment was carried out at Universidad Autónoma de Madrid (UAM). A total of 176 males aged between 18 and 28 participated in the experiment (mean ± SD: 21.90 ± 2.38 yr). Experiments were carried out exclusively with men for two reasons. First, because the effects on behavior of sexual hormones during development seem to be mainly relevant in males (Muñoz-Reyes et al., 2014). Second, because cooperation has been described as a competitive mechanism only among men (Farrelly, Lazarus, & Roberts, 2007; Van Vugt & Iredale, 2013). All participants classified themselves as Caucasian except nine individuals, whose data were discarded because ethnic homogeneity is required for the facial masculinity measure to be reliable. Written informed consent was obtained from all participants. The experimental procedure was approved by the UAM ethics committee (reference number: 73–1319). 2.2. Experimental design The experiments were performed employing the z-Tree 3.2.10 software for Economic Experiments (Fischbacher, 2007). Nine different PD stages were programmed. The first stage was an anonymous PD game. In this game, mutual cooperation ensures the best social outcome but both players have an individual incentive to behave opportunistically, leading to a socially inferior result. Participants had to decide whether to cooperate or not with a participant in a previous session. If the participant and his anonymous counterpart chose to cooperate, they both got 90 points; if only one of them cooperated, the cooperator obtained 10 points whereas the other received 160 points; if none of them cooperated, they both got 30 points. In addition to this choice, participants were asked what strategy they expected their counterpart to choose. In the eight remaining rounds, the PD game had the same payoff structure, but the photograph of a different male was shown in each round (see Supplementary figure). These men had played this PD in a previous experiment at least five years earlier, which reducing the possibility that they were considered ingroup by the participants. We obtained the consent from these eight males to use their photographs in further studies. In these eight non-anonymous rounds, participants were told they were playing with the person whose photograph they were seeing, and that the choice made by these individuals in an identical anonymous PD game in conjunction with their own choice now was going to determine their payment in that round. As in the anonymous round, we asked participants which choice they believed each of these eight individuals made when they played the PD. The order of the eight non-anonymous stages was randomized across sessions. The first stage was always anonymous. This was intended to avoid any priming from a previous non-anonymous round. We did not expect drastic changes in behavior between the first PD stage and the non-anonymous ones as there was no feedback between stages, thus leaving little room for learning or readjustment. 2.3. Experimental sessions No > 25 subjects participated in each session. Before the experiment started, subjects were instructed about the procedures. They filled in a questionnaire assessing their age, ethnicity and degree of study. Subjects were paid according to the points they had earned after the nine rounds, in addition to the show-up fee (5€). Each point was worth 1 euro cent. We took a hand-scan and frontal facial photographs of all participants. We employed a HP psc 2110 scanner, with a resolution of 600 × 1200 ppi, for the hand images. Photographs were taken with an Olympus E-500 digital camera with resolution 4288 × 2848 px in JPEG 2
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format under standardized light conditions. The camera was always at 3 m from the subject, and the field was completely opened to avoid distortion. Participants were asked to remove facial adornments and were carefully instructed to pose looking directly into the camera with a neutral expression.
Our main variables of interest were binary: the participant's decision to cooperate and the expectation of the counterpart's cooperation. Our independent variables were the morphological measures described above, personal characteristics (age, self-classified ethnicity) and session fixed effects. Regression analysis is the most suitable technique to simultaneously study all these variables. We opted for a linear probability model (LPM) rather than for a Probit model as our main specification. Coefficients are much easier to understand in the former model; a one standard deviation increase in one variable is associated with a percentage points (pp) change in the dependent variable. It has been shown that the estimation bias of the LPM increases with the number of predicted probabilities outside the 0 and 1 interval. Only 0.01% of our predicted probabilities presented this problem, suggesting that our LPM estimates were unbiased. Nonetheless, we also ran the corresponding Probit regressions and reported them in the tables to demonstrate the robustness of our results.
2.4. 2D:4D The second and fourth digits of the right hand were measured on the scanned images, from the flexion crease proximal to the palm to the top of the digit, as in the previous literature (Apicella et al., 2011; Millet & Dewitte, 2006; Pearson & Schipper, 2012). Two researchers placed the landmarks (LMs) independently with the TPS software version 2.16 (by F.J. Rohlf; obtained from http://life.bio.sunysb.edu/ee/rohlf/software. html). The two measurements of 2D:4D were highly correlated (r176 = 0.872, p < .001). The average of both measurements was used. Analyses on PD behavior include the squared 2D:4D (Tables 2 and 3) in order to test a previously observed non-monotonic relationship between 2D:4D and prosociality (Brañas-Garza et al., 2013; Galizzi & Nieboer, 2015; Millet & Dewitte, 2006; Sanchez-Pages & Turiegano, 2010).
3. Results 3.1. Cooperation
2.5. FA and masculinity measurements
Table 2 contains the results of the analysis on the decision to cooperate. In column 1, we simply compared behavior in the first PD round, where participants played against an anonymous subject, with the other eight non-anonymous rounds. As conjectured, we found a very strong effect of expected cooperation. Participants who expected their counterpart to cooperate were 36 pp. more likely to cooperate themselves. We found that anonymity had a strong effect as well: Controlling just for age, session and ethnicity, participants were 13.5 pp. more likely to cooperate in the anonymous PD. This is consistent with aggregate figures: subjects cooperated in the 55.11% of anonymous decisions but only in 40.13% of the non-anonymous ones. The coefficient maintained its magnitude in column 2, where we controlled for the morphological features of the subject. None of them were statistically significant. Columns 3 and 4 include the facial features of the counterpart. Estimates show that participants were more likely to cooperate with a counterpart with a more asymmetric face. A one standard deviation increment in the counterpart's FA increased the likelihood of
Two independent observers placed 39 predefined landmarks, which we had already used in previous works (Muñoz-Reyes et al., 2014; Sanchez-Pages, Rodriguez-Ruiz, & Turiegano, 2014; Sanchez-Pages & Turiegano, 2010), in two frontal facial photographs of each subject. FA and masculinity scores were calculated using the MorphoJ software, version 1.04a (by C.P. Klingenberg; obtained from http://www. flywings.org.uk/morphoj_page.html). FA scores were obtained from these landmarks by means of a Procrustes ANOVA run using the aforementioned software as in Sanchez-Pages and Turiegano (2010). This procedure compares each image with its mirrored image and decomposes asymmetry into two factors: directional and fluctuating asymmetry. Error in LM positioning was not significant (Procrustes ANOVA, error SS = 6.318 × 10−2, df = 13,024, F = 0.469, p = .999). The score for fluctuating asymmetry employed was the Mahalanobis distance, as it avoids the effect of the landmarks spatial distribution on asymmetry. Masculinity scores were computed performing a discriminant function on the facial shape information obtained by employing Geometric Morphometrics, a fitted method to measure the effect of masculinity on behavior (Sanchez-Pages et al., 2014). To this end, we used a sample of 460 women of the same age and ethnicity to those of the men in our sample (mean ± SD: 21.55 ± 2.57 yr). The function calculates the best possible discrimination between the male and female sample. The resulting discriminant function correctly classifies the sex of 95.82% of the faces (T2 test: T2 = 2528.2938; p < .001). Discriminant function scores for each individual were used as an index of masculinity, with high scores indicating a more masculine face shape. Table 1 presents descriptive statistics for the sample of participants and the counterparts.
Table 2 The effect of morphological features on cooperation. Independent variables
Anonymous Belief
Cooperation LPM [1]
LPM [2]
0.135*** (0.036) 0.366*** (0.022)
0.135*** (0.036) 0.362*** (0.022) −1.552 (17.774) 0.480 (9.200) −0.004 (0.002) 0.003 (0.018)
2D:4D ratio 2D:4D2 Facial masculinity
Table 1 Descriptive statistics for the variables considered in our participants sample and in the counterparts in the non-anonymous group. Data are the mean ± SD.
Facial FA Facial masculinity 2D:4D ratio Age
Participants (N = 176)
Counterpart in non-anonymous stage (N = 8)
3.997 ± 0.644 5.763 ± 3.865 0.960 ± 0.031 21.903 ± 2.383
3.678 ± 0.697 9.244 ± 5.889 0.954 ± 0.037 20.625 ± 1.408
Facial FA Counterpart's Masculinity Counterpart's Facial FA R-Squared N
0.180 1737
0.182 1737
LPM [3]
Probit [4]
0.332*** (0.024) −23.564 (19.163) 11.833 (9.916) −0.003 (0.003) 0.011 (0.020) −0.000 (0.002) 0.045** (0.022) 0.146 1408
0.936*** (0.074) −96.956 (52.586) 34.225 (29.095) −0.011 (0.009) 0.029 (0.060) −0.000 (0.007) 0.130** (0.064) 0.115 1408
Notes: Robust standard errors in parentheses *** (**) (*) indicate significance at the 1%, 5% and 10% level. 3
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Table 3 The effect of morphological features on expected cooperation by the counterpart. Independent variables
Anonymous
Independent variables
Belief on counterpart's cooperation LPM [1]
LPM [2]
0.038 (0.038)
0.038 (0.038) −13.570 (19.070) 6.519 (9.875)
2D:4D ratio 2D:4D2
−0.003 (0.003) −0.048*** (0.020)
Facial masculinity Facial FA Counterpart's Masculinity Counterpart's Facial FA R-Squared N
Table 4 The effect of morphological features on changes in cooperation.
0.035 1737
0.043 1737
LPM [3]
Probit [4]
−18.274 (20.859) 8.964 (10.797) −0.002 (0.003) −0.054** (0.022) −0.001 (0.002) 0.012 (0.023)
−47.407 (54.239) 23.238 (28.076) −0.005 (0.009) −0.140** (0.058) −0.003 (0.007) 0.003 (0.062)
0.029 1408
0.021 1408
Cooperated against anonymous 2D:4D ratio Facial masculinity Facial FA Counterpart's Masculinity Counterpart's Facial FA R-Squared N
Changed decision against at least one counterpart
Switched anonymous decision
LPM [1]
Probit [2]
LPM [3]
Probit [4]
0.217*** (0.069) −0.065 (1.059) −0.003 (0.008) 0.098** (0.048)
0.745*** (0.226) −0.673 (3.738) −0.009 (0.029) 0.400** (0.200)
0.225*** (0.025) 0.379 (0.425) −0.005 (0.003) 0.086*** (0.020) −0.000 (0.002) −0.018 (0.022)
0.118 176
0.110 174
0.648*** (0.076) 0.999 (1.228) −0.015 (0.009) 0.242*** (0.059) −0.001 (0.007) −0.050 (0.065) 0.079 1408
Notes: Robust standard errors in parentheses *** (**) (*) indicate significance at the 1%, 5% and 10% level, respectively. All regressions include subjects' age, ethnic group and session dummies.
Notes: Robust standard errors in parentheses *** (**) (*) indicate significance at the 1%, 5% and 10% level, respectively. All regressions include subjects' age, ethnic group and session dummies.
Columns 3 and 4 of Table 3 show the effect of counterpart's facial features on the likelihood of a switch from the first stage decision. We considered each face as a new treatment, so the coefficient estimates represent the average effect of the counterpart's feature on an individual's decision to change his decision. We found no statistically significant effect.
cooperation by 2.9 pp. 3.2. Beliefs Subjects expected their counterpart to cooperate in 54.41% of the occasions. Table 3 reports the results of the regression analyses on the expectation of cooperation. As before, column 1 leaves out all morphological features. We found no differences in beliefs across anonymous and non-anonymous rounds. Column 2 looks at the influence of an individual's morphological features on beliefs. We found that Facial FA had a negative impact on the expected cooperativeness of the counterpart. A standard deviation increment in this variable reduced the likelihood of a participant expecting his counterpart to cooperate by 3.7 pp. In other words, more asymmetric participants were less likely to believe that their counterpart would cooperate. Column 3 looks at the effect of the facial features of the counterpart. There was no significant effect on expected cooperation.
4. Discussion In this work, we studied how the morphological features related to the developmental physiology of the counterpart affect cooperation in social dilemmas. We ran an experiment in which subjects participated in a series of anonymous and non-anonymous PD games. By comparing their behavior across these rounds, we observed an unexpected result: cooperation rates were higher in the anonymous round than in the non-anonymous ones. We had not postulated any specific hypothesis in this regard, but we would have expected higher cooperation rates in nonanonymous interactions, as individuals tend to show more positive perceptions and behaviors towards their counterparts in face-to-face interactions (Bos, Olson, Gergle, Olson, & Wright, 2002; Burnham, 2003; Hill, Bartol, Tesluk, & Langa, 2009; Tanis & Postmes, 2007). In addition, the aggregate results in Fig. 1 show that participants who expected their counterpart to cooperate defected more often in the nonanonymous rounds than in the anonymous round. This result became even more surprising after noticing that anonymity had no effect on the expected behavior of the counterpart, so it could not be explained by participants expecting their partners to be less cooperative in the nonanonymous rounds. This suggests that the observed change in behavior was due to the out-of-the-game benefits from defecting which our participants might have taken into consideration after seeing an image of their counterpart. A similar result was observed by Yamauchi (1982), who found that face-to-face interactions made subjects more willing to outscore their counterpart in the PD. These underlying rewards (West et al., 2011) are partially captured by what the economics literature calls social preferences (Fehr & Schmidt, 1999; Rabin, 1993). Among these, spiteful or competitive preferences are consistent with this change in behavior, as they have been shown to explain why individuals pay to earn more than others (Levine, Bluni, & Hochman, 1998), a behavior in line with intrasexual competition motivations (Puts, 2016). The relevance of out-of-the-game rewards on cooperation could be
3.3. External cues We next studied the tendency of participants to change their decision when presented with photographs. Columns 1 and 2 of Table 4 show results for the characteristics of subjects who changed their anonymous decision in later rounds. Only 24.43% of subjects maintained their first stage decision across the eight non-anonymous stages. Subjects who cooperated in the first stage were more likely to change their behavior in later stages; specifically, these subjects were 21 pp. more likely to switch their anonymous stage decision than subjects who defected in the first round. This was to be expected since cooperation rates were lower in non-anonymous rounds. On the other hand, subjects with higher FA were more likely to change their decision. This effect could have been driven by two previous results: Since cooperation was less frequent in non-anonymous rounds and subjects with higher FA expected less cooperation from their counterparts, these participants might have been more likely to change their first stage decision because they switched from cooperation to defection. But separate regressions (see Supplementary Table 1) based on whether subjects cooperated or not in the first stage, showed that higher FA participants were more likely to switch in both directions. This suggests that these individuals were more sensitive to external cues. 4
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Fig. 1. Aggregated data for cooperators and non-cooperators in the anonymous and non-anonymous rounds.
(Wilson & Eckel, 2006; Zaatari & Trivers, 2007) whereas others found the opposite (Sanchez-Pages & Turiegano, 2010; Takahashi et al., 2006). Our participants played several rounds of the PD with different nonanonymous counterparts. When playing with these counterparts, participants could adjust their decision from round to round. We observed (Table 3) that more symmetrical individuals were less likely to change their decision in the first stage during the non-anonymous rounds. In other words, symmetric individuals seemed to be less affected by external cues, whereas less symmetrical individuals seemed to adjust their behavior to the circumstances. This is consistent with the idea that high-fitness individuals are more capable of obtaining resources on their own and can thus behave more independently (Munoz-Reyes et al., 2014; Sanchez-Pages & Turiegano, 2010; Zaatari & Trivers, 2007; Zaatari, Palestis, & Trivers, 2009). It is also feasible that, as subjects were paid for all PD rounds, they might have hedged their odds by diversifying their choices. A switch in decisions might then reflect risk preferences rather than sensitivity to cues. These hypotheses, which are outside the scope of the present paper, could be tested by eliciting second order beliefs from participants (e.g. what behavior do you think your counterpart expects from you?) whilst controlling for their risk aversion. Finally, we found no association between participants' cooperative behavior and the counterpart's testosterone-related developmental features, as measured by facial masculinity and 2D:4D. This contrasts with the previous literature employing the facial width-to-height ratio as a measure of facial masculinity, a variable which correlates only weakly with the measure of masculinity we employed (Sanchez-Pages et al., 2014). However, there is no longer a consensus on the dimorphism of the facial width-to-height ratio (Kramer, 2017), and it might not be a valid proxy to pubertal testosterone levels (HodgesSimeon, Sobraske, Samore, Gurven, & Gaulin, 2016, although see Welker et al., 2016). On the other hand, the lack of correlation between the counterpart's 2D:4D and cooperative behavior might have been due to the relatively weak impact that 2D:4D has on the adult facial shape (Burriss et al., 2007; Fink et al., 2005; Meindl et al., 2012; Weinberg et al., 2015), given that further exposure to sexual hormones has also an effect on face shape (Welker et al., 2016; Whitehouse et al., 2015). In addition, it has recently been shown that effects of biological variables on behavior, especially current testosterone levels, may be mediated by 2D:4D (Millet, 2011; Ryckmans et al., 2015; van Honk et al., 2012). Some of the effects of 2D:4D on behavior are likely to depend on these other biological variables, some of which cannot be perceived in a facial photograph. This might also contribute to explain why the counterpart's 2D:4D displayed no behavioral effect in our study.
observed again in the analysis of the effect on behavior of the counterpart's morphological features. Participants were more likely to cooperate with counterparts with higher FA, even when they were not more likely to believe that these individuals were going to cooperate. Expected counterpart behavior and chosen behavior did not match. This suggests that the effect of perceived FA on behavior operated through preferences. In other words, this result is consistent with participants expecting higher out-of-the game advantages from cooperation with less symmetric individuals, and the contrary from cooperating with more symmetric ones. This tendency to cooperate with low FA individuals against stated beliefs could be built on past cooperative interactions, as low symmetric individuals tend to be more cooperative (Muñoz-Reyes et al., 2014; Sanchez-Pages & Turiegano, 2010). The mismatch between not cooperating with more symmetric counterparts and expecting a cooperative behavior from them is consistent with the “what is beautiful is good” stereotype, the tendency to expect prosocial behavior from more attractive people (Andreoni & Petrie, 2008; Farrelly et al., 2007; Putz, Palotai, Cserto, & Bereczkei, 2016; Solnick & Schweitzer, 1999; Wilson & Eckel, 2006). We did not find any effect of the counterpart's features on their expected behavior. Features of other participants, such as masculinity (Stirrat & Perrett, 2010; Tognetti, Berticat, Raymond, & Faurie, 2013) and attractiveness (Ma, Hu, Jiang, & Meng, 2015), have been shown to influence their perceived cooperativeness and trustworthiness. However, the perception of prosocial features in another individual may not be strongly related to the formation of beliefs about her/his actual behavior in strategic interactions, as suggested by studies showing that defectors often pass undetected (Sylwester et al., 2012, but see Tognetti et al., 2013). In line with Sanchez-Pages and Turiegano (2010), we found that participants' own FA influenced their expectation about the cooperativeness of their counterparts. Hence, FA influenced cooperation through the expected behavior of the counterpart as the latter is a strong determinant of individual cooperation (Muñoz-Reyes et al., 2014; Sanchez-Pages et al., 2014; Sanchez-Pages & Turiegano, 2010). A likely explanation for this effect is the experience of these subjects in previous strategic interactions. Some works (Andreoni & Petrie, 2008; Farrelly et al., 2007; Putz et al., 2016; Wilson & Eckel, 2006) has showed that people are more likely to behave prosocially with high fitness individuals. Less symmetric participants might have experienced low cooperation rates in the past and might have adjusted their expectations accordingly in the lab. However, the literature offers mixed results on the association between expected behavior in strategic anonymous interactions and features related to higher fitness; some observed a higher expected prosociality from high fitness individuals 5
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In sum, our results offer new insights on the complexity of human cooperation, adding new data on how the biological characteristics of all participants influence cooperation. Although variables related to former testosterone levels seemed not to have any effect, facial fluctuating asymmetry did influence behavior. Future research should study whether this influence is related to individuals' expectations and the feedback they gather in their everyday life interactions. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.evolhumbehav.2018.09.002.
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