Tuesday, May 18, 2021

New normal for body size perception: Participants consistently mis-categorized overweight male bodies as normal weight, while accurately categorizing normal weight

Misalignment between perceptual boundaries and weight categories reflects a new normal for body size perception. Annie W. Y. Chan, Danielle L. Noles, Nathan Utkov, Oguz Akbilgic & Webb Smith. Scientific Reports volume 11, Article number: 10442. May 17 2021. https://www.nature.com/articles/s41598-021-89533-5

Abstract: Combatting the current global epidemic of obesity requires that people have a realistic understanding of what a healthy body size looks like. This is a particular issue in different population sub-groups, where there may be increased susceptibility to obesity-related diseases. Prior research has been unable to systematically assess body size judgement due to a lack of attention to gender and race; our study aimed to identify the contribution of these factors. Using a data-driven multi-variate decision tree approach, we varied the gender and race of image stimuli used, and included the same diversity among participants. We adopted a condition-rich categorization visual task and presented participants with 120 unique body images. We show that gender and weight categories of the stimuli affect accuracy of body size perception. The decision pattern reveals biases for male bodies, in which participants showed an increasing number of errors from leaner to bigger bodies, particularly under-estimation errors. Participants consistently mis-categorized overweight male bodies as normal weight, while accurately categorizing normal weight. Overweight male bodies are now perceived as part of an expanded normal: the perceptual boundary of normal weight has become wider than the recognized BMI category. For female bodies, another intriguing pattern emerged, in which participants consistently mis-categorized underweight bodies as normal, whilst still accurately categorizing normal female bodies. Underweight female bodies are now in an expanded normal, in opposite direction to that of males. Furthermore, an impact of race type and gender of participants was also observed. Our results demonstrate that perceptual weight categorization is multi-dimensional, such that categorization decisions can be driven by ultiple factors.

Discussion

By providing corroborating evidence from univariate and multi-variate analyses to investigate body size perception, we are able to identify the complex relationship between gender and race types of the stimuli and of the participants, and the impact of these factors on body size categorization. In particular, we have revealed that performance (percent accuracy) for body stimuli is not uniform, whereby participants performed best for Normal weight and worst for Obese stimuli. We also revealed evidence of an interaction between weight category and gender of the stimuli; participants were more accurate for Underweight and Normal male stimuli (leaner size) relative to the same weight category of female bodies, but they were more accurate for overweight and obese female stimuli compared to male bodies of the same size.

Multi-variate decision tree analysis provided not only consistent results but has pinpointed the direction of estimation errors. Specifically, it revealed that while our participants were reliably making more under-estimation errors for Overweight and Obese male stimuli, they were quite accurate when categorizing Overweight and Obese female stimuli. The overall decision tree pattern (Fig. 2 and Supplemental Figure 2) suggests a strong bias for male stimuli where participants showed an increasing number of errors from leaner to bigger bodies, particularly under-estimation errors. Importantly, there was an expansion of Normal weight category, such that for male stimuli, while a high percent accuracy was found for Normal weight (Fig. 2B), there were also substantial under-estimating errors for identification of Overweight male bodies (Fig. 2C), where participants consistently mis-identified Overweight as Normal weight. Thus, it ndicated that the perceptual BMI for Normal male bodies is now higher than the recognized BMI. For female stimuli however, an expanded boundary for Normal size was found in the opposite direction. Participants have categorized Underweight as Normal (Fig. 2A) as well as accurately categorized Normal bodies (Fig. 2B), suggesting that the averaged perceptual BMI for ormal female bodies is now lower than the recognized BMI. The fact that both male and female participants shared many of the same biases also suggests that visual learning plays a critical role in developing these specific biases. Part of these results was consistent with previous findings; for example, it has been reported5,6 that participants (predominately Caucasian women) make more under-estimation errors when judging Caucasian Overweight or Obese male bodies. It is also worth highlighting that due to the diverse range of our stimuli and equal sampling across both gender and race of participants in the current study, we are able to capture opposite response patterns when judging male vs female bodies, thus, a more complex pattern than previously reported.

As mentioned earlier, prior work has primarily reported perceptual biases for own body weight that might associate with race or gender types, while others have reported biases when judging others’ bodies, but theyhave primarily focused on a particular gender, race, and/or weight category of the stimuli or participants. Our current study focused on assessing others’ body weight as observers, accounting for race and gender of both stimuli and participants. We found that perceptual errors could be associated with characteristics of the participants and the stimuli. For example, all participants, regardless of their race and gender, showed more under-estimating errors by mis-categorizing AA female overweight bodies as normal (Fig. 3). Intriguingly, (Fig. 2A) when judging female underweight bodies (all race types), AA participants (both genders), showed a stronger over-estimating bias for female underweight bodies, mis-categorizing those images as normal weight. CA participants, however, did not exhibit such bias.

It has been well-established in the face perception literature that people are more accurate in recognizing and identifying faces of their own race compared to other race groups. This discrepancy in performance is known as the “other-race effect32,33,34,35,36,37,38,39,40. In the context of body weight perception, our current results did not show any other-race effect; no interaction between stimulus and participants’ race types was found in the univariate analysis or multi-variate analysis. However, we identified various participant-specific race effects from the multi-variate results. For example, we found that AA participants were slightly better at categorizing Obese male bodies relative to CA participants. AA participants also over-estimated Underweight female bodies, as they had consistently mis-categorized Underweight female bodies as Normal size (and this effect was not present in CA participants). For normal male bodies, AA performed better than CA, but AA made more over-estimation errors than CA. Interestingly, some stimuli-specific race effects were also identified. Overall, categorization performance was slightly (but significantly) better for Avatar stimuli in terms of percent accuracy. Multi-variate analysis further revealed that during categorization of female overweight stimuli, participants showed higher accuracy for Avatar and CA bodies than for AA (Fig. 3). A recent study20 had used visual adaptation to study the after-effect following repeated exposure of Asian or Caucasian female bodies, and their results seemed to be consistent to our findings. They also reported a lack of “other-race effect” at the stimuli level, but they reported that Asian participants seemed to show a weaker adaptation effect relative to Caucasians; however, the effect was not specific to Asian or Caucasian stimuli.

“Own-gender biases” have also been reported in face perception literature41. People are better at recalling or recognizing faces of their own gender relative to faces of the opposite gender41,42. Limited work has been conducted regarding gender-biases in body perception. Our recent study43 investigated gaze-pattern during perception of upright vs inverted bodies, but observed no differences in eye-movement patterns between male and female participants during a same/different categorization task of male body images. Multi-variate analysis in the current study has identified significant differences in performance between viewing female and male body images. There is a stimuli- and participant-specific gender effect that is particularly prominent for Obese bodies. Specifically, a marked difference was found between male and female participants, where male participants showed significantly higher accuracy for female Obese bodies. For male Overweight bodies, male participants performed better than female, while female participants showed more under-estimation errors. This suggests that under-estimation bias for Overweight male bodies was primarily driven by female participants. A stimuli-specific gender effect was also observed whereby, consistent with the univariate analysis, participants performed more accurately for Underweight male bodies than female Underweight bodies. Overall performance for Normal weight images was also better for male than female bodies. For Obese bodies, performance was better for female bodies, and there were also more under-estimation errors for male Obese bodies. These findings demonstrated that, by increasing the diversity in the stimuli and participants tested and by adopting a multi-variate approach, a more complex categorization pattern can be revealed. Furthermore, our observations of behavioural biases for higher BMI male stimuli and for lower BMI female stimuli seem to be consistent with the idea that partial overlapping or multiple gender-specific neural mechanisms may be at play during body size perception24,25.

Two major theories have been adopted to elucidate perceptual weight biases: the Weber’s law and contraction bias12,13,44. Specifically, the Weber’s law would predict that since detection of change of one’s body size is in constant proportion with one’s own weight, it is more diffcult to notice the change when one is overweight/obese. Alternatively, contradiction bias predicts that one’s perceived own BMI is inversely correlated with their own actual BMI. It has been reported that such correlation was only found during size estimation of participants’ own avatar, but did not generalize to estimating others’ body size12. While these theories may be helpful for explaining error in estimating one’s own weight, it is rather difficult to apply them to explain errors/biases during identification of others’ weight, especially when there are a lot more variables (race, gender, body weight, etc.) when dealing with “other bodies”. As we have shown here, estimation accuracies and errors interact with the type of stimuli presented in the experiment, thus illustrating that with increasing diversity in the stimuli, it might not be possible to show an “one-to-one mapping” using the above theories, as estimation decisions might be more complex than previously thought. While it is important to recognize that people have different body sizes, shapes, and other physical characteristics19, and that even BMI cut-off points may not capture variations in physiological measurements across cultures45, our current approach aims demonstrated that it is possible to capture and quantify some of the multi-dimensional visual characteristics, and it is critical that future work should also harness similar approaches.

Our findings here certainly do not attempt to capture categorization patterns for all types of bodies, and despite the constraints in our well-controlled paradigm (in real life, people with the same BMI may have different body shapes, and we see bodies from many different viewpoints other than straight-on), we have taken an important first step to quantify complex patterns in body weight perception. Finally, we believe that providing a careful characterization of perceptual biases in body weight here may lead to better diagnostic decision-making and development of personalized intervention programmes in both clinical and non-clinical settings.

Quantifying collective intelligence in human groups

Quantifying collective intelligence in human groups. Christoph Riedl et al. Proceedings of the National Academy of Sciences, May 25, 2021 118 (21) e2005737118; https://doi.org/10.1073/pnas.2005737118

Significance: Collective intelligence (CI) is critical to solving many scientific, business, and other problems. We find strong support for a general factor of CI using meta-analytic methods in a dataset comprising 22 studies, including 5,279 individuals in 1,356 groups. CI can predict performance in a range of out-of-sample criterion tasks. CI, in turn, is most strongly predicted by group collaboration process, followed by individual skill and group composition. The proportion of women in a group is a significant predictor of group performance, mediated by social perceptiveness.

Abstract: Collective intelligence (CI) is critical to solving many scientific, business, and other problems, but groups often fail to achieve it. Here, we analyze data on group performance from 22 studies, including 5,279 individuals in 1,356 groups. Our results support the conclusion that a robust CI factor characterizes a group’s ability to work together across a diverse set of tasks. We further show that CI is predicted by the proportion of women in the group, mediated by average social perceptiveness of group members, and that it predicts performance on various out-of-sample criterion tasks. We also find that, overall, group collaboration process is more important in predicting CI than the skill of individual members.

Keywords: collective intelligencehuman groupsteam performance


Honoring Confucius’ Golden Mean philosophy, both Chinese males & females are supposed to avoid being either extremely emotional or extremely restrained, resulting in a diminished sex difference in empathy

Culture, Sex, and Group-Bias in Trait and State Empathy. Qing Zhao et al. Front. Psychol., April 28 2021. https://doi.org/10.3389/fpsyg.2021.561930

Abstract: Empathy is sharing and understanding others’ emotions. Recently, researchers identified a culture–sex interaction effect in empathy. This phenomenon has been largely ignored by previous researchers. In this study, the culture–sex interaction effect was explored with a cohort of 129 participants (61 Australian Caucasians and 68 Chinese Hans) using both self-report questionnaires (i.e., Empathy Quotient and Interpersonal Reactivity Index) and computer-based empathy tasks. In line with the previous findings, the culture–sex interaction effect was observed for both trait empathy (i.e., the generalized characteristics of empathy, as examined by the self-report questionnaires) and state empathy (i.e., the on-spot reaction of empathy for a specific stimulus, as evaluated by the computer-based tasks). Moreover, in terms of state empathy, the culture–sex interaction effect further interacted with stimulus traits (i.e., stimulus ethnicity, stimulus sex, or stimulus emotion) and resulted in three- and four-way interactions. Follow-up analyses of these higher-order interactions suggested that the phenomena of ethnic group bias and sex group favor in empathy varied among the four culture–sex participant groups (i.e., Australian female, Australian male, Chinese female, and Chinese male). The current findings highlighted the dynamic nature of empathy (i.e., its sensitivity toward both participant traits and stimulus features). Furthermore, the newly identified interaction effects in empathy deserve more investigation and need to be verified with other Western and Asian populations.

Discussion

In this study, the culture–sex interaction effect in empathy was studied with Australian and Chinese participants. Moreover, this interaction effect was identified on both trait and state empathy. For trait empathy, the current observation was consistent with previous findings (Melchers et al., 2015Zhao et al., 2019). For state empathy, the culture–sex interaction effect further interacted with stimulus traits (e.g., stimulus ethnicity, stimulus sex, and stimulus emotion), resulting in three- or four-way interactions (see Table 5). Follow-up analyses of the higher-order interactions revealed that the impacts of stimulus traits varied among the culture–sex participant groups (i.e., Australian female, Australian male, Chinese female, and Chinese male). To conclude, the current results support the theory of culture–sex interaction effect in empathy (Zhao et al., 2019). Furthermore, the current results highlight that beyond the fundamental culture–sex interaction effect in empathy, there could be more intriguing interactions across participant traits and stimulus features.

Trait Empathy

The culture–sex interaction effect emerged as a clear trend in terms of trait empathy (see Table 4). This finding is in line with that of Zhao et al. (2019), who evaluated trait empathy with Australian Caucasian (n = 196) and Chinese Han (n = 211) university students. Specifically, in both the current and the previous study (Zhao et al., 2019), the cultural differences in trait empathy were significant in female participants (i.e., Australian female > Chinese female participant) but not in male participants. Furthermore, sex differences in trait empathy were only significant with Australian participants (i.e., Australian female > Australian male participant) but not with Chinese participants. Zhao et al. (2019) proposed that the culture–sex interaction in trait empathy might be germane to social expectations for emotional expressions. Generally, Western cultures encourage females to externalize their emotions more than males (i.e., the so-called emotional female and rational male; Merten, 2005). In contrast, honoring Confucius’ Golden Mean philosophy, both Chinese males and Chinese females are supposed to avoid being either extremely emotional or extremely restrained (Huang, 2006Zhao et al., 2019), resulting in a diminished sex difference in empathy (also see Zhao et al., 2020). Nevertheless, it should be noted that the above relationship between empathy and social expectations is only a theoretical proposal by Zhao et al. (2019), and future empirical studies are necessary to verify this proposal.

State Empathy

The current state empathy results were more complex, spanning significant two-, three-, and four-way interactions (see Table 5). For example, there were four-way interactions on overall and cognitive empathy for NimStim stimuli (i.e., participant culture × participant sex × stimulus ethnicity × stimulus sex), four-way interactions on overall and emotional empathy for the documentary stimuli (i.e., participant culture × participant sex × stimulus sex × stimulus emotion), as well as one three-way interaction on perspective-taking of the documentary stimuli (i.e., participant culture × participant sex × stimulus emotion).

The Culture–Sex Interaction Effect

Within each of the aforementioned three- and four-way interactions, there is a culture–sex interaction effect. Moreover, these three- and four-way interactions covered all forms of state empathy examined in this study (i.e., overall empathy, emotional empathy, cognitive empathy, and perspective-taking). On the one hand, the current findings suggest that culture–sex interaction effects in empathy are not restricted to trait empathy (e.g., Zhao et al., 2019) but can expand to state empathy. On the other hand, the current results are similar to the findings of Zhao et al. (2019), suggesting that the culture–sex interaction is significant for inclusive components of empathy (see Melchers et al., 2015 and Lachmann et al. (2018), both of them found the interaction was not significant on cognitive trait empathy). It is worth mentioning that Schmitt (2015) had a theory of “culturally variable sex difference”; as per Schmitt (2015), the culture–sex interaction effect could be a non-negligible phenomenon in a broad range of social and psychological subjects in addition to empathy. Therefore, the culture–sex interaction effect deserves attention from future cross-cultural researchers of sociology and psychology.

However, the culture–sex interaction effect has been ignored by most of the previous investigators of the Western–Asian cultural difference in trait and state empathy (see Tables 13). As noted by Zhao et al. (2019), the culture–sex interaction effect could be an explanation for the inconsistent results among the publications (see Tables 13). Moreover, Zhao et al. (2019) proposed that the magnitude of the Western–Asian cross-cultural differences in trait empathy could be enlarged along with the female ratio of a sample (i.e., a positive correlation with the female%). Both the current study and Zhao et al. (2019) presented supporting evidence for the above notion since the effect size of the cultural difference in trait empathy tends to be larger for female participants relative to male participants.

Participant Culture Effect

Referencing the results of culture–sex interaction in trait empathy (Zhao et al., 2019), the Australian females should be the most empathic among the four culture–sex participant cohorts. Nevertheless, the current findings for state empathy revealed a different trend; that is, the advantages and disadvantages of state empathy are relatively counterbalanced for the participant groups. First, in light of the NimStim stimuli (i.e., task I), Australian participants expressed more cognitive empathy for positive and neutral stimuli (i.e., happiness and neutral-peacefulness). In contrast, Chinese participants reported more emotional empathy for negative emotions (i.e., anger and fear). Second, in light of the documentary stimuli (i.e., task II), the Chinese participants commonly expressed more empathy (i.e., overall empathy, emotional empathy, cognitive empathy, and perspective-taking) than Australian participants. However, Australian participants specifically reported more cognitive empathy for stimuli of male anger than Chinese participants did.

The inconsistency among the findings of trait empathy and state empathy (for NimStim and for documentary stimuli) is intriguing and can be explained by a range of factors. The first factor is social expectation. On the one hand, as per Zhao et al. (2019), Australian females’ higher self-evaluated trait empathy could be largely due to the social expectation placed on them. However, the impact of social expectation on the computer-based evaluations (i.e., state empathy) could be weaker than that on self-report evaluations (i.e., trait empathy) (Baez et al., 2017). More importantly, in the current study, participants were explicitly required to answer each state empathy question according to their inner feelings rather than social justice (see the section “Materials and Methods”). This instruction might have minimized the impact of social expectation on the state empathy tasks. On the other hand, Chinese traditional cultures (e.g., Confucianism and Taoism) honor humility and modesty in individuals (Lin et al., 2018). Hence, Chinese participants could downplay themselves while answering the trait empathy items (i.e., the items enquire ‘‘how good the participant is in empathy’’)12 but might be more objective during responding to state empathy questions (i.e., the questions ask ‘‘how much the participant felt for a given stimulus’’)13. Therefore, Chinese participants may seem to be less empathic than Australian participants in light of trait empathy (i.e., the self-report scales assessed) but not state empathy (i.e., the computer-tasks evaluated).

The second factor is the background information of the stimuli. The current results suggest that when the emotional background information was withheld (i.e., the NimStim stimuli), Australian participants had higher cognitive empathy for neutral and happy stimuli, while Chinese participants showed more emotional empathy for negative emotions. This observation was in agreement with the distinct Asian and Western cultural requirements of emotional expression and suppression. Generally, in Asian societies, negative emotions are expected to be masked (e.g., by a neutral or smiling face) for maintaining interpersonal harmony (Wei et al., 2013). This social rule is different from Western societies, in which externalizing emotions is accepted as an honest way to express oneself (Gross and John, 2003Murata et al., 2012). Consequently, since childhood, Chinese individuals have been trained to decode others’ emotions according to contextual information, as well as trained to be alert to others’ subtle emotional downturns (i.e., watch the “face colors”) (Wang, 2001). Therefore, emotional understanding (i.e., cognitive empathy) for neutral and happy faces without emotional background information could be a challenge for Chinese participants (i.e., as per the Chinese culture, a neutral or happy face by itself could indicate neutral, happy, or masked negative feelings). However, the empathic sensitivity (i.e., emotional empathy) for negative emotions might be more intense for the Chinese than Australian participants (i.e., due to the necessity of watching others’ “face colors” in Chinese society) (e.g., Wang, 2001).

In contrast, when the background information was given (i.e., the documentary stimuli), empathy for most of the emotions was promoted for Chinese participants. One exception was the cognitive empathy for the stimuli of male anger. Anger is an intense emotion that disturbs the harmony of interpersonal relationships (de Greck et al., 2012). Influenced by the Confucian Golden Mean philosophy, the Chinese may value social harmony much more than Westerners (Drummond and Quah, 2001de Greck et al., 2012Liu, 2014). In light of Chinese culture, expressing anger could be labeled as lacking in self-control (Kornacki, 2001Kong et al., 2020). In contrast, for Westerners, sincerely expressing emotions could be deemed as a way to enhance interpersonal understanding (Gross and John, 2003Murata et al., 2012). Moreover, de Greck et al. (2012) decoded the neurological basis of Western–Asian cultural differences in empathy for anger. They found that facing ethnic in-group anger, German participants had more brain activation in the cognitive empathy-related brain regions (i.e., the inferior temporal gyrus and middle insula). In contrast, Chinese participants showed more brain activation in the emotional regulation and personal distress-related brain region (i.e., the dorsolateral prefrontal cortex). de Greck et al. (2012) claimed that the Western participants might try to understand the anger; meanwhile, the Chinese participants might attempt to inhibit their aversive feelings stirred up by the anger. Noticeably, some previous researchers of cultural differences in empathy (see Tables 23) adopted the concepts of “negative emotions” or “suffering” (i.e., mixed negative emotions) as emotional stimuli. However, the current results highlight that the participants’ cultural differences in empathy can be qualified by the subtypes of negative emotions.

Ethnic Group Bias

In this study, the dominant trend of ethnic group bias in state empathy was the ethnic in-group bias for negative emotions together with the ethnic out-group bias for positive emotions. These findings were in line with our hypothesis (see the section “Introduction”) as well as the previous observation by Neumann et al. (2013). Specifically, the current Chinese participants exhibited ethnic in-group biases on overall empathy (i.e., the holistic concept of emotional and cognitive empathy) for fear (NimStim stimuli) and sadness (documentary stimuli).

In contrast, the current Australian participants expressed an ethnic out-group bias on overall empathy for happiness (documentary stimuli). These findings cannot be fully explained by either the theory of in-group familiarity (Cao et al., 2015) or the one of out-group hate (Avenanti et al., 2010). Instead, as discussed in the Introduction section, being concerned about in-groups in need (i.e., the in-group bias for negative emotions) and out-groups in a triumphant mood (i.e., the out-group bias for happiness) could be two facets of the “reciprocal altruism” (Trivers, 1971Mathur et al., 2010).

Nevertheless, two exceptions of ethnic group bias in state empathy were identified with the current Chinese participants (both for NimStim stimuli). First, the Chinese participants showed an ethnic out-group bias for the NimStim sadness. Sadness may be perceived as a symbol of powerlessness and low self-esteem (Merten, 2005); an exposure of one’s weakness in front of others without a good reason could be interpreted by Chinese people as “losing face” (i.e., a Chinese word, describing the feeling of embarrassment and shame for oneself as a consequence of unsuitable conduct; Ho, 1976Zhang et al., 2011). Trommsdorff et al. (2007) coined the term “non-acting” to explain the same situation. They stated that in cultures that discourage emotional externalization, individuals might purposely inhibit their reactions to an emotional person so as to “save that person’s face” (Trommsdorff et al., 2007). Therefore, the current Chinese participants might refrain from empathy toward the Asian characters expressing sadness without a good reason (i.e., NimStim stimuli), leading to the out-group bias. However, as long as an emotional background was given for the sadness of the documentary stimuli (e.g., an earthquake or bushfire ruin), the ethnic group bias of the current Chinese participants turned into an ethnic in-group bias.

Second, there was a four-way interaction (i.e., participant culture × participant sex × stimulus ethnicity × stimulus sex) on the overall empathy for NimStim stimuli. Further examination of the four-way interaction showed an ethnic out-group bias with the Chinese female participants on NimStim male stimuli. The reasons for the ethnic out-group bias could be still due to the non-acting strategy (Trommsdorff et al., 2007). Relatively, Western cultures provide more freedom for individuals to express their emotions, while Asian cultures value emotion regulation more (Davis et al., 2012Wei et al., 2013). Moreover, with Chinese and American participants, Davis et al. (2012) found that Chinese male participants expressed the highest emotion regulation, which was in line with their concern that the social pressure on moderating emotions was stronger for Chinese males than the other culture–sex participant groups (i.e., a culture–sex interaction effect in emotion regulation). Hence, the current Chinese female participants might adopt the non-acting strategy to specifically “save the face” of the NimStim Asian male over the NimStim Caucasian male (Trommsdorff et al., 2007). This turned out to be the Chinese female participants’ ethnic out-group bias in empathy. Nonetheless, when the emotional background was illustrated with the emotion (i.e., the documentary stimuli), the ethnic out-group bias for male stimuli was absent from the Chinese female participants. The above results stress that the ethnic group bias may vary among the culture–sex participant groups, which can be moderated by the availability of the background information; however, these possibilities were overlooked by previous researchers (Tables 23).

Sex Group Favor

Sex group favor in empathy was not examined in previous studies summarized in Tables 13. The current results revealed that the main sex group favor was biased to female (i.e., female > male stimuli, see Table 5). This main favor is consistent with a common social consensus, namely, females are more vulnerable and should be treated with extra consideration (i.e., the “ladies first” ideology) (Tuleja, 2012). Nevertheless, some minor variations on the sex favor effect could still be identified among the four culture–sex participant groups. First, in light of the NimStim stimuli, the sex group favor (i.e., female > male stimuli) was only significant with Australian male participants (i.e., the overall empathy for both Caucasian and Asian stimuli, as well as cognitive empathy for Asian stimuli), but not with the other three culture–sex participant groups. Second, in light of the documentary stimuli, the main sex group favor (i.e., female > male stimuli) was identifiable with all culture–sex participant groups. However, this ‘ladies first’ favor in empathy for the documentary stimuli tended to be stronger for the Australian than Chinese participants; this result also supported the notion that sex differentiation is more pronounced in Western than in Asian cultures (Zhao et al., 2019).

Third, the opposite sex group favor (i.e., the “alpha male” ideology) was also presented in the current results, particularly with the Australian participants. On the one hand, Australian male participants expressed more overall empathy for male happiness of the documentary stimuli (i.e., a male runner in the marathon) than the female ones (i.e., a bride in the wedding ceremony). Intriguingly, toward the same stimuli, the Australian female participants’ sex favor on the overall empathy was biased to female (i.e., the bride’s happiness > the male runner’s happiness). In contrast, Chinese female and Chinese male participants showed non-significant sex favor on the overall empathy for happiness (i.e., the bride’s happiness = the male runner’s happiness). Besides further stressing that sex differentiation can be more polarized in Western than in Asian cultures, the above results are in line with the stereotype of Australian males (i.e., the ‘Sporting Manhood in Australia’; Adair et al., 19971998).

On the other hand, Australian female participants’ sex group favors on overall empathy for the documentary stimuli of anger and sadness were biased to male (i.e., male > female stimuli; see Supplementary Document 1 for the stimuli’s background information). Teague (2014) evaluated empathic accuracies with three ethnic groups of Americans (viz., Caucasian, African, and Chinese). Teague found that relative to the male participants, the female participants of all three ethnic groups tended to be more sensitive to negative emotions (e.g., anger and sadness) expressed by Caucasian characters (i.e., the main ethnicity of the country) (Teague, 2014, see pp. 107–108). Moreover, relative to African male participants, the African female participants were hypersensitive to in-group anger and sadness (i.e., expressed by African characters). In contrast, Chinese female and Chinese male participants’ reactions toward in-group anger and sadness (i.e., expressed by Chinese characters) were relatively similar. Results of Teague (2014) and the current study imply that sex group difference and sex group favor in empathy for negative emotions may be relevant to social vulnerability, and the female vulnerability may be more obvious in Western than Asian societies. Nevertheless, since Teague (2014) did not split the stimuli according to stimulus sex, whether females in Western societies were specifically sensitive to male negative emotions was not definitive. Nevertheless, the current results indicate that Western females may be more empathic toward male anger and sadness than female ones. The sex group favor in empathy, especially the sex favor against common consensus (i.e., the alpha male ideology), is worthy of further investigation.

Limitations and Further Studies

The current study has several limitations. First, the sample size was small. Conclusions regarding the interaction effects in state empathy need to be replicated based on a larger sample size. Second, only university students were recruited in this study, and hence, the current findings might not be extended to the general populations of Australia and China. Third, in this study, the ethnic group bias and sex group favor were only explored in terms of state empathy but not trait empathy (i.e., the EQ and IRI items do not examine these phenomena). Further researchers might consider investigating these phenomena in trait empathy using self-report questionnaires. However, it should be noted that participants can interpret questions regarding ethnic group bias and sex group favor as tapping into racism and sexism. Consequently, participants may respond to these questions according to social desirability (i.e., without racism and sexism). Fourth, it should be noted that the empathic accuracies of some emotions (e.g., fear, surprise, and neutral-peacefulness) were low in the current study (see Supplementary Document 1). Result interpretations for these emotions with a low empathic accuracy should be done with care. Fifth, questions of state empathy presented in the current computer-based tasks could still be categorized as subjective (e.g., “I felt _____the feeling of the main character”) although they were comparatively more objective than the self-report items of trait empathy (i.e., the EQ and IRI items). The culture–sex interaction, ethnic group bias, and sex group favor effects ought to be verified by more objective techniques, such as brain imaging or physiological measurements (see Neumann and Westbury, 2011Neumann et al., 2015). Sixth, to date, the culture–sex interaction effect in empathy with adult participants has been identified by Melchers et al. (2015) (i.e., Germans vs. Chinese), Zhao et al. (2019) (i.e., Australians vs. Chinese), as well as the current study (i.e., Australians vs. Chinese). It is noteworthy that the Asian participants of these three studies were all Chinese. Thereby, it is essential to verify in further investigations whether the culture–sex interaction in empathy can be generalized to other Asian cultures; in other words, whether the culture–sex interaction effect is a common phenomenon of the Western–Asian contrast or is a specific term to the Western–Chinese contrast14.

In addition, some limitations of the current computer-based tasks of state empathy should be elaborated. Firstly, the current participants’ attitudes toward the other ethnicity (e.g., whether they had out-group hate) were not collected. The current authors deemed that out-group hate might not be a serious issue in the current case since both Australian and Chinese participants expressed the ethnic out-group bias in state empathy. Nevertheless, it is highly recommended for further investigators to record participants’ attitudes toward other ethnicities to elaborate on this topic. Secondly, each component of state empathy was evaluated by a single item (e.g., “I felt _____ the feeling of the main character. 1 = not at all to 9 = very strongly”, for emotional state empathy). The single-item design (i.e., also used by all previous investigations, see Tables 23) could be criticized as not sufficiently reliable to capture the relatively stable psychological traits of empathy. A multi-item evaluation of state empathy ought to be considered in future investigations. Thirdly, participants’ state empathy could be confounded by stimulus traits (e.g., age, clothing, and attractiveness of the character), which were not controlled in the current examinations. Fourthly, we did not directly compare the results of state empathy for NimStim stimuli with that for the documentary stimuli (i.e., tasks I and II, respectively) to evaluate the impact of background information on empathy. It should be noted that the stimuli of tasks I and II were different in several important aspects, including the availability of background information, the facial expressivity of the main characters, and more importantly, whether the characters expressed an emotion naturally. To evaluate the impact of background information on empathy, a future investigation with better-manipulated stimuli is necessary (i.e., an identical facial expression with different background information). Fifthly, regarding the stimuli of task II, we chose documentary photos of naturally expressed emotions with matched background information across Western and Asian stimuli (see details in Supplementary Document 1). Alternatively, researchers can do a computer manipulation on the facial expressions of those main characters to get a standard facial expression across Western and Asian stimuli. However, we are concerned that computer-modified facial expressions may change the social meaning and the biological validity of the stimuli. It is because emotional expressivity naturally differs between cultures (Rychlowska et al., 2015). Under the same situation, Westerners’ facial expressions could be more exaggerated than Asians’ (e.g., laughing or smiling at their wedding party). Hence, a standard happy face deemed so by Westerners could seem ecstatic to Asians. Therefore, we recommend documentary photos (i.e., naturally expressed emotions) rather than computer-manipulated ones. Finally, it should be stressed that due to the small sample size, the current investigation may not provide enough statistical power to reveal all subtle interaction effects on state empathy. Further investigation with a larger sample size is highly recommended.

Gift givers (vs. nongivers) subsequently made more selfish decisions at their friends' expense; giving a gift to one's romantic partner changes givers' interpretation of which behaviors constitute questionable fidelity

Are people more selfish after giving gifts? Evan Polman  Zoe Y. Lu. Journal of Behavioral Decision Making, May 18 2021. https://doi.org/10.1002/bdm.2252

Abstract: How people choose gifts is a widely studied topic, but what happens next is largely understudied. In two preregistered studies, one field experiment, and an analysis of secondary data, we show that giving gifts has a dark side, as it can negatively affect subsequent interpersonal behavior between givers and receivers. In Study 1, we found that giving a gift to one's romantic partner changes givers' interpretation of which behaviors constitute infidelity. Specifically, we found that givers (vs. nongivers) classified their questionable behaviors (e.g., sending a flirtatious text to someone other than their partner) less as a form of cheating on their partner. In Study 2, we examined how politely participants behave when delivering bad news to a friend. We found that givers (vs. nongivers) wrote significantly less polite messages to their friend. In Study 3, we tested real gifts that people give to friends and found givers (vs. nongivers) subsequently made more selfish decisions at their friends' expense. In all, our research refines the oft‐cited axiomatic assumption that gift giving strengthens relationships and illuminates the potential for future research to examine how decision making can alter interpersonal, romantic relationships.


Lab: A Chronic Lack of Perceived Low Personal Control Increases Women and Men’s Self-Reported Preference for High-Status Characteristics When Selecting Romantic Partners

A Chronic Lack of Perceived Low Personal Control Increases Women and Men’s Self-Reported Preference for High-Status Characteristics When Selecting Romantic Partners in Simulated Dating Situations. Joris Lammers, Roland Imhoff. Social Psychological and Personality Science, May 18, 2021. https://doi.org/10.1177/19485506211016309

Abstract: The question what people desire in their romantic partner has hitherto been dominated by a focus on gender. It has been repeatedly found that, when asked what they find important in selecting a partner, women indicate that they find status more important compared to men. Across five studies, we move beyond gender and base ourselves on general theories of control deprivation to test the effect of differences in perceived personal control on stated partner preferences. We find that low-control people—both women and men—value characteristics associated with status more in romantic partners at the expense of other desirable traits (Study 1a and 1b). Furthermore, in simulated dating settings, low-control people make corresponding dating choices and prefer hypothetical high-status partners over low- (Study 2a) or average-status partners (Study 2b). Our final study suggests a beneficial aspect: Thoughts of dating a high-status partner can repair low-control people’s feelings of control (Study 3).

Keywords: romantic relations, mating preferences, partner selection, personal control, status, gender


The Scams Among Us: Who Falls Prey and Why

The Scams Among Us: Who Falls Prey and Why. Yaniv Hanoch, Stacey Wood. Current Directions in Psychological Science, May 17, 2021. https://doi.org/10.1177/0963721421995489

Abstract: Not a week goes by without stories about scams appearing in popular media outlets. Given the ease with which scams can be circulated, they have become one of the most common crimes globally, inflicting high emotional, financial, and psychological tolls on millions of individuals. Despite their profound and pervasive impact, researchers know relatively little about why some individuals fall victim to scams but others remain immune to the techniques utilized by scammers to lure potential victims. For example, research thus far provides mixed results about the impact of demographic characteristics (e.g., age) as well as personality variables (e.g., risk taking) on individuals’ susceptibility to scams. Even less is known about how the nature or type of scam affects an individual’s susceptibility. Gaining a deeper understanding of these issues is the key to being able to develop preventive programs and reduce the prevalence of victimization. Here, we discuss some promising directions, existing gaps in current knowledge, and the need for decision scientists to address this important problem.

Keywords demographic variables, fraud, individual differences, risk factors, scams, susceptibility

Scams present a multidimensional and dynamic problem. Scammers attack individuals of all backgrounds, in every corner of the world, and with novel and changing techniques and lures. Given that there are millions of scam victims every year, there is a pressing need to identify what factors render individuals more vulnerable to scam solicitations and, more important, what preventive measures can be used to alleviate this problem. Most, if not all, of the advice that exists has not been tested; nor does it seem to work—as is evident in the increased number of victims. Psychologists, as well as other behavioral scientists, have insight and training that place them perfectly to tackle this problem.

Despite the valuable knowledge gained from the studies presented here, there is plenty of room for a wide range of further work to be conducted. First, there is a growing need to develop theoretical frameworks—ones that incorporate cognitive abilities, neurological insights, and personality research—that can advance understanding of scam susceptibility. Empirical researchers, moreover, must improve the external validity of their work and conceive ways to conduct more realistic and natural field studies (e.g., Ebner et al., 2018). Furthermore, because little is known about how to reduce scam compliance, there is an urgent need to conduct research in this area that will make it possible to develop decision aids and other tools to reduce scam compliance. Although many sources on the Internet offer valuable advice (see Table 1), many people fail to follow it (e.g., use 123456 as their password). Whether nudges or other behavior-modification techniques can improve adherence to these simple rules is, likewise, an open question. Given the complex nature of the problem, closer collaborations among researchers in different disciplines (e.g., computer scientists and psychologists) is likely to be fruitful. Finally, given the emotional effect of scams, clinical work is needed to advance understanding about the impact of fraud on victims’ psychological well-being and how to help them.

Seduction of the Superman: For fifty years GB Shaw expressed a desire for state liquidation of recalcitrant or incorrigibly unproductive citizens in the hope of clearing the ground for a higher kind of human creature

The Utopian Imagination of George Bernard Shaw: Totalitarianism and the Seduction of the Superman. Matthew B Yde. PhD Thesis, Ohio State Univ, 2011. https://etd.ohiolink.edu/apexprod/rws_etd/send_file/send?accession=osu1313083659&disposition=inline

Abstract: Playwright George Bernard Shaw has a reputation as a humanitarian, an indefatigable seeker of justice and, in his own words, a ―world betterer. But this reputation is difficult to reconcile with his support for the totalitarian regimes and dictators that emerged after the First World War, which is not so well known. This enthusiasm is usually dismissed as an expression of Shaw‘s well known propensity for comic exaggeration and hyperbole, his pugnacious rhetoric, his love of paradox, and especially his addiction to antagonizing the British political establishment. However, as I believe this dissertation proves, Shaw‘s support was genuine, rooted in his powerful desire for absolute control over the unruly and chaotic, in a deep psychological longing for perfection. Shaw expressed rigid control over his own bodily instincts, and looked for political rulers of strong will and utopian designs to exercise similar control over unruly social elements.

It is occasionally stated that Shaw‘s support for totalitarianism grew out of his frustration with nineteenth century liberalism, which ineffectually culminated in a disastrous world war. Yet close analysis to two of Shaw‘s Major Critical Essays from the 1890s shows that even then Shaw expressed a desire for a ruthless man of action unencumbered by the burden of conscience to come on the scene and establish a new world order, to initiate the utopian epoch. Indeed, a further analysis of a number of plays from before the war shows the impulse to be persistent and undeniable. This dissertation attempts to reveal the genuineness of Shaw‘s totalitarianism by looking at his plays and prefaces, articles, speeches and letters, but is especially concerned to analyze the utopian desire that runs through so many of Shaw‘s plays, looking at his political and eugenic utopianism as it is expressed in his drama and comparing it to his political totalitarianism. Shaw considered himself a ―revolutionary writer, and his activity as a socialist agitator, propagandist for Creative Evolution, and world famous playwright must be seen as growing out of the same utopian impulse. For fifty years Shaw expressed a desire for state liquidation of recalcitrant or incorrigibly unproductive citizens in the hope of clearing the ground for a ―higher kind of human creature. While Shaw knew that the public was not ready to act on such controversial ideas, he did hope that by disseminating his ideas through highly entertaining plays and essays they would take root in the mind and be activated later by the power of the will. This is how Lamarckian evolution works, and his method is a species of Fabian permeation. As Keegan says in John Bull’s Other Island, ―every jest is an earnest in the womb of time. By looking closely at Shaw‘s plays and connecting them to his political activity, we will see that for Shaw the dictators were provisional supermen clearing the way for the advent of the real supermen who would come later, such as we see in the utopian plays that Shaw wrote in the last three decades of his life.


The age of peak earnings increased from the late 30s to the mid-50s; a great share of this shift is explained by increased employment in decision-intensive occupations, which have longer and more gradual periods of earnings growth

The Growing Importance of Decision-Making on the Job. David J. Deming. NBER Working Paper 28733, April 2021. DOI 10.3386/w28733

Abstract: Machines increasingly replace people in routine job tasks. The remaining tasks require workers to make open-ended decisions and to have “soft” skills such as problem-solving, critical thinking and adaptability. This paper documents growing demand for decision-making and explores the consequences for life-cycle earnings. Career earnings growth in the U.S. more than doubled between 1960 and 2017, and the age of peak earnings increased from the late 30s to the mid-50s. I show that a substantial share of this shift is explained by increased employment in decision-intensive occupations, which have longer and more gradual periods of earnings growth. To understand these patterns, I develop a model that nests decision-making in a standard human capital framework. Workers predict the output of uncertain, context-dependent actions. Experience reduces prediction error, improving a worker’s ability to adapt using data from similar decisions they have made in the past. Experience takes longer to accumulate in high variance, non-routine jobs. I test the predictions of the model using data from the three waves of the NLS. Life-cycle wage growth in decision-intensive occupations has increased over time, and it has increased relatively more for highly-skilled workers.


Contrary to what old criminology studies said, those who underwent physical training and scored higher on physical fitness test are less likely to engage in deviance, supporting self-control theory

Tai, K., Liu, Y., Pitesa, M., Lim, S., Tong, Y. K., & Arvey, R. (2021). Fit to be good: Physical fitness is negatively associated with deviance. Journal of Applied Psychology. Advance online publication. https://doi.org/10.1037/apl0000916

Abstract: While modern organizations generate economic value, they also produce negative externalities in terms of human physical fitness, such that workers globally are becoming physically unfit. In the current research, we focus on a significant but overlooked indirect cost that lack of physical fitness entails—deviance. In contrast to early (and methodologically limited) research in criminology, which suggests that physically fit people are more likely to behave in a deviant manner, we draw on self-control theory to suggest the opposite: That physically fit people are less likely to engage in deviance. In Study 1, we assembled a dataset on 50 metropolitan areas in the U.S. spanning a 9-year period, and found that physical fitness index of a metropolitan area is negatively related to deviance in that area in a concurrent as well as time-lagged fashion. We complemented this aggregate-level theory test with two studies testing the theory at the individual level. In Study 2, we collected multi-source data from 3,925 military recruits who underwent physical training and found that those who score higher on physical fitness test are less likely to engage in deviance. Study 3 conceptually replicated the effect with both concurrent and time-lagged models using a five-wave longitudinal design in a sample of employees working in service roles, and also found that ego depletion mediates the effect of physical activity on workplace deviance. We speculate on economic implications of the observed relationship between physical fitness and deviance and discuss its relevance for organizations and public policy.




People over-estimate COVID-19 risks, and those over-estimates were consistently related to stronger support for continuing restrictions past vaccinations

Graso, Maja. 2021. “Over-estimation of Covid-19 Risks to Healthy and Non-elderly Predict Support for Continuing Restrictions Past Vaccinations.” PsyArXiv. May 17. doi:10.31234/osf.io/bg54x

Abstract: I test the possibility that people who provide higher estimates of negative consequences of Covid-19 (e.g., hospitalizations, deaths, and threats to children) will be more likely to support the ‘new normal’; continuation of restrictions for an undefined period of time starting with wide-spread access to vaccines and completed vaccinations of vulnerable people. Results based on N = 1,233 from April, 2021 suggested that people over-estimate Covid-19 risks, and those over-estimates were consistently related to stronger support for continuing restrictions. This relationship emerged in four different samples, using core and supplementary risk estimations, and persisted after controlling for Covid-19 denialism, political ideology, and personal concern of contracting Covid-19. People were also more likely to support continuing restrictions if they believed there is scientific consensus on Covid-19 matters, even on issues where there is none (e.g., wearing masks while driving alone). The study concludes with a discussion of the ethical implications of letting both over- and under-estimation of Covid-19 go uncorrected. Just as it is important to combat misinformation that leads people to disregard health mandates, it is crucial to examine the real possibility that people’s support for continuing risk mitigation practices may also not be based on accurate information.


Monday, May 17, 2021

The Sexual Mind: Exploring the Origins of Arousal

The Sexual Mind: Exploring the Origins of Arousal. Osmo Kontula, May 2021 (Finnish 2017). https://www.vaestoliitto.fi/uploads/2021/05/ccafc96b-sexual-mind_final.pdf

The sexual mind

The sexual mind is always active during the course of our daily lives – if we allow this for ourselves. A substantial portion of the processing of sexually evocative situations takes place in the subconscious. Our awareness of them depends partially on whether we are prepared in the given circumstances and moment to allow ourselves to have sexually charged thoughts. The mind may block this awareness because it is fastened onto something else – perhaps a grave or serious problem that immerses us.

New things are constantly being introduced in our sexual lives, for us to ponder in our various life situations and seek novel ways to implement. Many of us would like to discover ways to increase the pleasure we feel. Others wonder how they might preserve even the smallest spark of passion in their long-term relationship. Many others crave confirmation that they are sexually normal – whatever that means for each individual. Some want solutions to sexual problems, while others would like to understand why their minds and bodies do not travel in tandem with their own expectations of their sexual desire, or with their partner’s desire. The sexual mind presents a major challenge and an enormous opportunity.

The mind is the conduit to the awakening of sexual interest and desire, and launches our individual processes of sexual arousal. The mind comprises both our conscious and unconscious interest in sexual matters. Exploring our own sexual mind helps to open new pathways to sexuality that often remain unknown even to ourselves. The exploration also gives us a deeper understanding of our sexual motives. 

Sexuality is present in our lives from the moment of birth until death. Each of us is an expert in our own sexuality. It is therefore strange that we know the least and have the least awareness of the very things that are most important to us in terms of sexuality – for example, why we are especially captivated by certain sexual phenomena and not others, and why some of them are nearly irresistible to us. [...]

Substantial percentages of people do not want to receive information even when it bears on health, sustainability, & consumer welfare; , substantial percentages of people also do want to receive that information

Sunstein, Cass R. and Reisch, Lucia and Kaiser, Micha, What Do People Want to Know? Information Avoidance and Food Policy Implications (May 4, 2021). SSRN: https://ssrn.com/abstract=3839513

Abstract: What information would people like to have? What information would they prefer to avoid? How does the provision of information bear on welfare? And what does this mean for food policy? Representative surveys in eleven nations find that substantial percentages of people do not want to receive information even when it bears on health, sustainability, and consumer welfare. Nonetheless, substantial percentages of people also do want to receive that information, and people’s willingness to pay for information, contingent on their wanting it, is mostly higher than people’s willingness to pay not to receive information, contingent on their not wanting it. We develop a model and estimate the welfare effects of information provision. We find substantial benefits and costs, with the former outweighing the latter. The results suggest that in principle, policymakers should take both instrumental and hedonic effects into account when deciding whether to impose disclosure requirements for food, whether the domain involves health, safety, or moral considerations. If policymakers fail to consider either instrumental or hedonic effects, and if they fail to consider the magnitude of those effects, they will not capture the welfare consequences of disclosure requirements. Our evidence has concrete implications for how to think about, and capture, the welfare consequences of such requirements with respect to food.

Keywords: Information avoidance, information seeking, willingness to pay, belief-based utility

JEL Classification: D00, D9, D11, D90, D91


The uses and abuses of tree thinking in cultural evolution

The uses and abuses of tree thinking in cultural evolution. Cara L. Evans, Simon J. Greenhill, Joseph Watts, Johann-Mattis List, Carlos A. Botero, Russell D. Gray and Kathryn R. Kirby. Philosophical Transactions of the Royal Society B: Biological Sciences, July 5 2021, Volume 376Issue 1828, online May 17 2021, https://doi.org/10.1098/rstb.2020.0056

Abstract: Modern phylogenetic methods are increasingly being used to address questions about macro-level patterns in cultural evolution. These methods can illuminate the unobservable histories of cultural traits and identify the evolutionary drivers of trait change over time, but their application is not without pitfalls. Here, we outline the current scope of research in cultural tree thinking, highlighting a toolkit of best practices to navigate and avoid the pitfalls and ‘abuses' associated with their application. We emphasize two principles that support the appropriate application of phylogenetic methodologies in cross-cultural research: researchers should (1) draw on multiple lines of evidence when deciding if and which types of phylogenetic methods and models are suitable for their cross-cultural data, and (2) carefully consider how different cultural traits might have different evolutionary histories across space and time. When used appropriately phylogenetic methods can provide powerful insights into the processes of evolutionary change that have shaped the broad patterns of human history.


1. Introduction

Theories of cultural evolution are built on the observation that cultural features undergo innovation, modification and transmission. Over time, these processes have generated remarkable variation in human cultures. Humans speak around 7000 distinct languages, affiliate with hundreds of religions, employ a range of kinship systems, engage in an array of subsistence practices and adhere to a bewildering number of social conventions [1]. Phylogenetic methods provide a powerful approach to studying macro-evolutionary patterns of innovation, modification and transmission [2–4]. Their application to human culture has helped reinvigorate cross-cultural comparative research but has also been subject to criticism—both valid and misguided.

Phylogenies, also known as evolutionary trees, represent the common ancestry of populations and the splitting events that have occurred over the course of their history. Phylogenetic methods encompass a broad family of mathematical approaches that can be used to construct, analyse and incorporate phylogenies (figure 1). Originally developed to study the evolution of biological organisms, these methods offer a general toolkit with the potential to provide answers to a range of cultural evolutionary questions.

Figure 1. Phylogenetic methods that can be used to study cultural macro-evolution. Black arrows indicate that the preceding methodological steps are directly incorporated in later methods: (a) tree construction [5] is required for all subsequent steps; (b) testing for phylogenetic signal (e.g. [6–8]) forms an integral part of phylogenetic regression (e.g. [9–11]), which in turn forms the basis of phylogenetic path analysis which can identify causal relationships; (c) ancestral state reconstruction (e.g. [12]), estimated in conjunction with rates of trait change and transformation (e.g. [13,14]), is required for models of trait correlation [15–17] and diversification ([18,19]; but see [20]). Red arrows indicate that suitable tests of phylogenetic signal (i.e. that the trait data fit sufficiently to the history inferred by the tree) should be conducted by the researcher before using methods detailed in (c); (see also §2). Shading: grey shading indicates methods that both assume and require inferred historical relationships between the cultural units (tree taxa) to sufficiently reflect the history of the trait; green shading denotes methods that detect and quantify tree-like structure in cross-cultural data; blue shading denotes methods that detect and control for tree-like data structure among societies, but do not require it.

An important distinction in cultural phylogenetics research is between methods of building trees (i.e. reconstructing the histories of cultural units based on assumptions of vertical transmission of cultural features (traits); figure 1a) and methods that use previously constructed trees in models that investigate the evolution and distribution of other cultural traits (figure 1b-c). A further important division in tree thinking occurs between those methods and questions that simply detect and control for tree-like structure when examining variation in cross-cultural data (e.g. What does the distribution of traits among societies tell us about the history of those societies and/or traits? Does horizontal or vertical transmission better explain the observed distribution of traits?figure 1b), and those methods that require that the modelled data are tree-like (i.e. methods that ask: What was the ancestral form of a cultural feature?figure 1c).

Phylogenetic methods offer exciting possibilities for a wide range of questions, only some of which explicitly require tree-like data. For data that are sufficiently tree-like, one of the strongest appeals of phylogenetic methods is that they offer the possibility to illuminate the unobservable past. Phylogenetic methods can reconstruct the ancestry of a vertically transmitted trait from the evolutionary signatures detected in its present-day distribution, even when archaeological records are entirely unavailable. However, despite this exciting potential, debate continues over how best to integrate cultural heterogeneity, disentangle the signatures of vertical transmission, horizontal diffusion and local socio-ecological drivers, and demonstrate that a cultural trait exhibits enough tree-like structure to justify using methods that reconstruct its evolutionary past.

Here, we review the application of phylogenetic methods in cross-cultural research. We focus specifically on the questions researchers should ask in order to avoid common methodological pitfalls when (i) deciding about the units of the underlying cultural data, (ii) constructing trees and (iii) assuming tree-like transmission of other cultural features. Throughout, we outline a series of best practices and highlight emerging methods that promise to advance our understanding of macro-evolutionary patterns of mechanism and causation in culture.


Girls know how to choose: Fathers lived in larger cities, had higher education, were heavier and taller , more attractive & masculine, had lighter eyes, darker hair, & were more agreeable, conscientious, & emotionally stable than non-fathers

She Always Steps in the Same River: Similarity Among Long-Term Partners in Their Demographic, Physical, and Personality Characteristics. Zuzana Štěrbová, Petr Tureček and Karel Kleisner. Front. Psychol., February 5 2019. https://doi.org/10.3389/fpsyg.2019.00052

Abstract: In mate choice, individuals consider a wide pool of potential partners. It has been found that people have certain preferences, but intraindividual stability of mate choice over time remains little explored. We tested individual consistency of mate choice with respect to a number of demographic, physical, and personality characteristics. Only mothers were recruited for this study, because we wanted to find out not only whether women choose long-term partners with certain characteristics but also whether the father of their child(ren) differs from their other long-term (ex-)partners. Women (N = 537) of 19–45 years of age indicated the demographic, physical (by using image stimuli), and personality characteristics of all of their long-term partners (partners per respondent: mean = 2.98, SD = 1.32). Then we compared the average difference between an individual’s long-term partners with the expected average difference using a permutation test. We also evaluated differences between partners who had children with the participants (fathers) and other long-term partners (non-fathers) using permutation tests and mixed-effect models. Our results revealed that women choose long-term partners consistently with respect to all types of characteristics. Although effect sizes for the individual characteristics were rather weak, maximal cumulative effect size for all characteristics together was high, which suggests that relatively low effect sizes were caused by high variability with low correlations between characteristics, and not by inconsistent mate choice. Furthermore, we found that despite some differences between partners, fathers of participants’ child(ren) do fit their ‘type’. These results suggest that mate choice may be guided by relatively stable but to some degree flexible preferences, which makes mate choice cognitively less demanding and less time-consuming. Further longitudinal studies are needed to confirm this conclusion.

Results


Mate choice consistency was higher than expected in all assessed qualities except for facial masculinity and beardedness. Difference between observed and expected consistency was statistically significant in most qualities, but effect sizes differed substantially. While consistency of mate choice in residence or weight was substantial, it was only medium-sized or small with respect to hair or eye color. Complete results are summarized in Table 1 and Figure 1.

Table 1. Mate choice consistency: complete results.
Figure 1. Visualization of permutation tests of mate choice consistency centered around observed image and normalized along the SD of expected image distribution. Difference between the observed and expected value is expressed in standard deviations from the expected value distribution. The higher the bell curve above the Observed image value, the higher the actual mate choice consistency. Bell curve below Observed image value indicates a trait where the observed mate choice was less consistent than expected.

The average effect size was highest in demographic variables, but none of the pairwise comparisons between groups of variables (demographic, physical, and psychological) was statistically significant (p > 0.1). Permutation test results are visualized in Figure 1. All sample sizes and descriptive statistics of all variables are listed in the Appendix. The different estimates of effect size were highly correlated. The proportion of males who had to be relocated between respondents correlated with the variance accounted for by the respondent at 0.93, whereby a linear model of relationship between these two measures supports the idea that the latter is approximately double of the former. The slope in the model where respondent-attributable variance regressed on the proportion of partners to relocate was 2.08 (95% CI = 1.72–2.45) with minimal (not significantly different from 0) intercept of -0.18 (95% CI = -3.19–2.83). Results yielded by the simple Pearson correlation correlated at 0.91 with the percentage of partners to relocate and at 0.98 with respondent-attributable variance. All of these measures can be thus treated as functionally equivalent.

Links between pairs of partners’ qualities are summarized in Table 2. In total, 103 out of 210 correlations were significant even after Benjamini–Hochberg correction for multiple comparisons. Maximal cumulative effect size was 50.95% (expressed in the proportion of partners to switch between individuals). The first 10 variables ordered according to their unique contribution starting with the highest (residence, weight, relative height, age difference, attractiveness, hair color, openness, BMI, height, agreeableness, in this order) explained 48.30% of partner assignment. The other 11 variables contributed little (their unique contributions were less than 1%) or not at all (after the inclusion of all other variables, facial masculinity and beardedness failed to show any positive numbers). Full results are visualized in Figure 2.

Table 2. Relations between investigated qualities of romantic partners expressed in shared effect sizes and Pearson correlations.
Figure 2. Visualization of maximal cumulative effect size. Variables are added in order given by maximal unique contribution to overall consistency.

Reaching maximal possible effect size suggests that adding yet other variables to a similar model of cumulative consistency would add little to our current sum. On the other hand, it is conceivable that one might select precisely those variables which are not intercorrelated and explain a majority of mate choice consistency in just a handful independent dimensions. In theory, complex interaction patterns may lead to an even higher cumulative effect size since 50% of partners to relocate as an effect size limit applies to a single variable with two levels and represents the difference between maximal and minimal consistency (i.e., not maximal and expected). The high proportion of significantly correlated pairs of variables (49%), does, however, fit well within the impression of a substantial redundancy in our model.

Permutation test of changes in mate choice consistency revealed that fathers are significantly exceptional amongst participants’ long-term partners in beardedness, muscularity, hirsuteness, extraversion, and openness. The average image without these individuals was lower than the image in permutation runs where an equivalent proportion of random partners (i.e., fathers and non-fathers) was excluded. Fathers were not significantly typical long-term partners in any of the assessed qualities. Complete results of these tests are summarized in Table 3 and visualization is provided in Figure 3.

Table 3. Permutation test of father exceptionality, complete results.
Figure 3. Visualization of permutation tests of father exceptionality centered around the observed image when fathers were excluded from the sample of partners and normalized along the SD of expected image distribution in such a situation. Difference between observed and expected values is expressed in standard deviations of expected value distribution. The higher the bell curve above the observed image value, the more exceptional were the fathers among the long-term partners of an individual. Bell curve below the observed image value indicates a trait where fathers were more typical representatives of an individual’s long-term partners.

In qualities where fathers were indicated as exceptional individuals (except for extraversion), mean trait values differed between fathers and non-fathers, while variances differed in beardedness, muscularity, and hirsuteness. Fathers were more bearded, hairier, more muscular, and showed a higher openness to experience. These differences might explain the overall exceptionality of fathers except for extraversion. It seems that fathers are outliers within partner sets even where the group means and variances of father and non-father sets do not differ. Moreover, fathers lived in larger cities, had higher education, were heavier and taller (although relatively, their height was closer to the height of respondents), more attractive and masculine, had lighter eyes, darker hair, more masculine faces, and were more agreeable, conscientious, and emotionally stable than non-fathers.

Group variances differed in several qualities. Fathers were significantly more variable than non-fathers with respect to age difference from the respondent and less variable in attractiveness, masculinity (general and facial), BMI, conscientiousness, and agreeableness. It seems that along these variables, either or both of the extremes are not the right for the ‘father material’. A graphic overview which compares densities that indicate differences between group means and variances is presented in Figure 4. Complete results in a textual form are listed in Table 4.

Figure 4. Visualization of differences between fathers and non-fathers. Significance of difference between group means and variances is estimated from mixed effect models with respondent ID treated as a random factor. Significance levels are indicated as follows: ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001.
Table 4. Results of Mixed effect models comparing father/non-father means and variances.