Men were more accurate than women in detecting attraction when they were not interested in their partner compared to when they were interested

The Role of Emotion Projection, Sexual Desire, and Self-Rated Attractiveness in the Sexual Overperception Bias. Iliana Samara, Tom S. Roth & Mariska E. Kret. Archives of Sexual Behavior, Aug 13, 2021. https://rd.springer.com/article/10.1007/s10508-021-02017-5

Abstract: A consistent finding in the literature is that men overperceive sexual interest in women (i.e., sexual overperception bias). Several potential mechanisms have been proposed for this bias, including projecting one’s own interest onto a given partner, sexual desire, and self-rated attractiveness. Here, we examined the influence of these factors in attraction detection accuracy during speed-dates. Sixty-seven participants (34 women) split in four groups went on a total of 10 speed-dates with all opposite-sex members of their group, resulting in 277 dates. The results showed that attraction detection accuracy was reliably predicted by projection of own interest in combination with participant sex. Specifically, men were more accurate than women in detecting attraction when they were not interested in their partner compared to when they were interested. These results are discussed in the wider context of arousal influencing detection of partner attraction.

Discussion

The present study explored the effects of sex, own interest, sexual desire, and self-rated attractiveness in the overperception bias using a naturalistic speed-dating paradigm. Overall, we found that men were more willing to go out with their partner as compared to women. Importantly, our findings illustrate that projection of own interest influences attraction detection, particularly in men. Specifically, men were more accurate in detecting attraction if they were not interested in their partner compared to when they were. Furthermore, when men were interested in their partner, they overperceived interest more than women. However, there was no difference between sexes when participants were not interested in their partner. Women were approximately 50% accurate in detecting attraction, independent of whether they were interested in their partner or not. Sexual desire and self-rated attractiveness did not influence accuracy in detecting attraction. In the section below, we discuss these results in more detail.

First, we found that men were more likely to indicate that they were interested in going out with their partner again compared to women. This is in line with previous literature across different countries and target samples (i.e., university students and general population) showing a consistent pattern in terms of reduced male selectivity (e.g., Asendorpf et al., 2011; Fisman et al., 2006; Kurzban & Weeden, 2005; Lenton & Francesconi, 2010; McClure et al., 2010; Overbeek et al., 2013; Todd et al., 2007). An explanation could be that men wanted to maximize the number of dates that they could get, consistent with EMT (Haselton & Buss, 2000) which suggests that missing a dating opportunity could be more costly for men than for women. Also, the low likelihood of women indicating that they would like to meet their partner again supports previous findings showing that women are typically choosier than men (Todd et al., 2007; Trivers, 1972). In conclusion, we show that men were more likely than women to decide that they would like to go on another date with their partner supporting the notion that men are slightly less picky regarding dating.

It might be argued that the increased tendency of men to respond positively after a date can be explained by the fact that only men had to rotate between partners in our study. This effect was described by Finkel and Eastwick (2009), who showed that the reduced selectivity is nullified when female participants also rotate between partners. However, a recent meta-analysis showed that the female choosiness effect is robust across studies, and that the rotation effect did not moderate female choosiness (Fletcher et al., 2014), nor has been replicated (e.g., Overbeek et al., 2013). It is therefore unlikely that the partner-rotation effect can explain our findings. Nonetheless, future research should examine whether the sex-rotation-setup modulates the relationship between sex and the sexual overperception bias.

Interestingly, we found that men were more accurate when they were not interested in their partner compared to when they were, whereas women were approximately at 50% independent of their interest in their partner. An explanation for this interaction between sex and projection of own interest might be because of a link between choice biases and physiological arousal. Previous research has shown that men can detect changes in genital arousal that indicate sexual arousal within five minutes, and importantly, the correlation between genital arousal and subjective sexual arousal is reliable for men, but not for women (Kukkonen et al., 2007; see also Dekker & Everaerd, 1988). Physiological arousal influences our affective state, which can in turn bias our decisions (Damasio, 1996; see also Storbeck & Clore, 2008). For example, men that were shown sexually arousing stimuli were more likely to indicate that attractive women were sexually aroused than not (Maner et al., 2005) and sexually aroused participants are more likely to engage in risky sexual practices (Ariely & Lowenstein, 2006; Skakoon-Sparling & Cramer, 2021; Skakoon-Sparling et al., 2015). Thus, our findings might suggest that in situations where men were not interested in their partner, this biasing emotional state was not present, thus allowing them to accurately detect that their partner is not interested in them. Indeed, previous research has suggested that cues signaling disinterest might be easier to detect than cues signaling interest, especially in zero-order acquaintance settings (Hall et al., 2015). Given that the concordance between bodily and subjective arousal is not as robust in women, it is not surprising that women were not necessarily biased as much as men in terms of detecting attraction. In conclusion, our findings extend previous evidence showing that accuracy does not only depend on sex or projecting one’s own emotion on a partner, but accuracy is in fact dependent on an interplay between these two factors.

The estimation model complemented the results of the accuracy models. Interestingly, we found that both men and women were likely to overperceive attraction when they were interested in their partner compared to when they were not. Crucially, when men were interested in a partner, they overperceived interest more than women, which likely explains the decreased accuracy exhibited in men. These findings are partially consistent with EMT (Haselton & Buss, 2000). EMT predicts that men would be more likely to overperceive attraction than women. However, our findings highlight that perhaps the effect of being attracted to a given partner should be incorporated as an additional parameter in EMT (Lee et al., 2020), because if men are not interested, they are in fact very likely to be accurate regarding attraction. Thus, our findings support and further extend the EMT framework by showing that the addition of interest in a given partner might be crucial in predicting overperception.

Curiously, we found no effect of sexual desire on attraction detection accuracy. Our results are inconsistent with previous findings (Lee et al., 2020; Perilloux et al., 2012). One reason for this discrepancy could be that previous studies focused on short-term mating strategies, whereas we examined overall sexual desire. It is well known that sociosexuality—the inclination to form short-term relationships (Kinsey et al., 1948)—differs between men and women (Clark & Hatfield, 1989). Importantly, given that sexual desire and sociosexuality are highly correlated (O’Connor et al., 2014), we expected to observe similar findings as Lee et al. (2020). However, in our dataset we found no difference in sexual desire between sexes, whereas in Lee et al. (2020) sociosexuality was significantly higher for men than women (see also Roth et al., 2021). Either due to the differences in instruments or the differences in sample characteristics, we did not find an effect of sexual desire on attraction detection accuracy. Future research should investigate the effect of sexual desire and its association with sociosexuality and sex on attraction detection accuracy.

In addition, we found no effect of self-rated attractiveness on accuracy, in contrast with previous research (Lee et al., 2020; Perilloux et al., 2012). A potential explanation for this finding could be that in the present study, we examined physical attractiveness exclusively. We could therefore only speculate that our sample was similar to previous research in terms of other factors that can constitute attractiveness (e.g., personality). Nevertheless, previous research has shown that personality has negligible effects on both men and women’s desirability (Kurzban & Weeden, 2005). Furthermore, self-rated attractiveness has been found to play a role in overperception together with short-term mating styles (Howell et al., 2012; see also Lee et al., 2020; Perilloux et al., 2012). However, in our sample, most participants indicated they were searching for a long-term relationship. Thus, this pronounced long-term relationship focus might have prevented the interplay between self-attractiveness and mating strategy to emerge.

One crucial point that cannot be disentangled in the context of the present study is whether women and men interpreted the question regarding the wish to go on another date with their partner similarly. Specifically, in previous studies, participants were asked to indicate how sexually interested they were in their partner (Lee et al., 2020; Perilloux et al., 2012). However, in the present study, participants were asked to indicate whether they would like to go on another date with their partner (see also Asendorpf et al., 2011; Overbeek et al., 2013; Todd et al., 2007 for similar setups). It could be argued that this question led female participants to respond to the perceived question of “Are you romantically interested in your partner?” and male participants to respond to the question of “Are you sexually interested in your partner?” Even though this cannot be tested in the present study, it is quite likely that the response pattern would have remained the same. Previous research has shown that romantic interest and sexual interest follow the same sex differences, where women are choosier than men (Fletcher et al., 2014). Crucially, asking about the wish to go on another date rather than sexual interest is a strength of the current study, as it increases its ecological validity, given that it resembles real-life situations more closely (e.g., online dating sites; see Kurzban & Weeden, 2005).

It should be noted that in the present study, we examined only heterosexual participants; therefore, our findings cannot be directly generalizable to non-heterosexual populations. Furthermore, our sample consisted predominantly of university students. University students offer a prime target sample for sexuality research given the greater interaction frequency with opposite-sex partners and the increased necessity to infer sexual interest (Perilloux et al., 2012) and are commonly the primary target for such studies (e.g., Lee et al., 2020). Importantly, most participants in our study were interested in a committed relationship (only 2 participants were not), which limited our ability to investigate whether different mating strategies might influence attraction detection accuracy (e.g., Lee et al., 2020; Perilloux et al., 2012). Crucially, a limitation that stems from the use of a speed-dating setup is that we cannot assess whether the personality characteristics and social skills of our sample are representative of a wider population (Finkel & Eastwick, 2008). Future research should investigate more heterogeneous samples in terms of educational background and age.

The current study shed light on several factors that underlie the sexual overperception bias. Given that this bias is linked to the likelihood of assault (Abbey et al., 1998), the study’s findings are crucial in elucidating and reducing miscommunication between the sexes in dating contexts (Perilloux et al., 2012). Crucially, we showed that sex and projection of own interest are intertwined and should not be seen as competing, but rather as complementary explanations. Importantly, our findings cast doubt on previous research suggesting that one’s own interest, sexual desire, and self-rated attractiveness might fully explain the sexual overperception bias (Lee et al., 2020; see also Roth et al., 2021). Therefore, our results not only support the EMT framework, but further suggest that the incorporation of sex differences in projection of own interest might be a useful addition to the EMT framework.

It is misleading to think that psychedelic God experiences tend to dissolve atheist convictions, & that atheist convictions, once dissolved, are replaced with traditional monotheist beliefs

Psychedelic Drugs and Atheism: Debunking the Myths. Wayne Glausser. Religions  Volume 12  Issue 8, 614, August 8 2021. https://doi.org/10.3390/rel12080614

Abstract: Two recent surveys of people who took psychedelic drugs and reported “God experience encounters”, along with successful clinical trials using psychedelic therapy for depression, have given rise to public misconceptions about psychedelics and atheism. Specifically, three inferences have been drawn: (1) that the psychedelic experience tends to dissolve atheist convictions; (2) that atheist convictions, once dissolved, are replaced with traditional monotheist beliefs; and (3) that atheism and depression somehow correlate as afflictions for which psychedelic drugs offer relief. This paper argues, based on analysis of the studies and trials along with relevant supplemental evidence, that each of these popular inferences is substantially misleading. Survey data do not indicate that most psychedelic atheists have cleanly cut ties with their former convictions, and there is strong evidence that they have not traded atheism for traditional monotheism. Both personal testimony and the effectiveness of microdose clinical trials serve to complicate any notion that a psychedelic drug alleviates symptoms of depression by “curing” atheism. The paper then extends its focus to argue that the broader field of neurotheology includes elements that contribute to these popular misconceptions.

Keywords: psychedelic drugs; atheism; monotheism; pantheism; depression; neurotheology

To encourage social distancing during COVID-19, Delta Air Lines did not sell the middle seat on its flights that had them & raised its fares by 15%; therefore, passengers paid $23 to prevent a stranger from sitting next to them

The value of space during a pandemic. Max J. HymanaIan Savage. Economics Letters, August 11 2021, 110039. https://doi.org/10.1016/j.econlet.2021.110039

Highlights

• Delta Air Lines did not sell the middle seat in 2020 during the COVID-19 pandemic.

• Its principal rivals sold all seats starting in July 2020.

• Delta raised its fares by 15%.

• Passengers paid $23 to prevent a stranger from sitting next to them.

• Delta had to operate more flights, so this was not a profit-enhancing strategy.

Abstract: To encourage social distancing during the COVID-19 pandemic, Delta Air Lines did not sell the middle seat on its flights that had them. In the second half of 2020 its principal rivals, American Airlines and United Airlines, continued to sell the middle seat. Analysis of U.S. Department of Transportation airline ticket data on 1,358 domestic routes finds that Delta raised its fares by 15%. Therefore, passengers paid $23 to prevent a stranger from sitting next to them.

Keywords: AviationPandemicPrice discrimination

Intelligence was the single strongest predictor of political tolerance, with larger effects than education, openness to experience, ideology, and threat

Cognitive ability is a powerful predictor of political tolerance. Stig Hebbelstrup Rye Rasmussen, Steven Ludeke. Journal of Personality, August 12 2021. https://doi.org/10.1111/jopy.12667

Abstract

Objectives: Despite the broad appeal of abstract notions of political tolerance, people vary in the degree to which they support the political rights of groups they dislike. Prior research highlighted the relevance of individual differences in the cognitive domain, claiming the application of general tolerance ideals to specific situations is a cognitively demanding task. Curiously, this work has overwhelmingly focused on differences in cognitive style, largely neglecting differences in cognitive ability, despite compelling conceptual linkages. We remedy this shortcoming.

Methods: We explore diverse predictors of tolerance using survey data in two large samples from Denmark (N = 805) and the United States (N=1603).

Results: Cognitive ability was the single strongest predictor of political tolerance, with larger effects than education, openness to experience, ideology, and threat. The cognitively-demanding nature of tolerance judgments was further supported by results showing cognitive ability predicted tolerance best when extending such tolerance was hardest. Additional small-sample panel results demonstrated substantial four-year stability of political tolerance, informing future work on the origins of political tolerance.

Conclusions: Our observation of a potent role for cognitive ability in tolerance supports cognitively-oriented accounts of tolerance judgments, and highlights the need for further exploration of cognitive ability within the political domain.

Rolf Degen summarizing... Even inaccurate gossip can discipline people to behave prosocially, by fueling worries about reputation

Direct and Indirect Reciprocity among Individuals and Groups. Angelo Romano, Ali Seyhun Saral, Junhui Wu. Current Opinion in Psychology, August 13 2021. https://doi.org/10.1016/j.copsyc.2021.08.003

• Behavioral experiments support the predictive power of direct and indirect reciprocity.

• Reciprocity helps explain the effects of group membership, gossip, and third-party punishment on prosocial behavior.

• Group membership serves as a heuristic for expected partner’s prosocial behavior and anticipated future interactions.

• Gossip promotes prosocial behavior via an increased concern for reputation and expected partner’s prosocial behavior.

• Costly third-party punishment serves to deter potential defectors and maintain a positive reputation.

Abstract: Direct and indirect reciprocity are two fundamental mechanisms that promote prosocial behavior within groups and across societies. Here, we review recent work that illustrates how a (direct and indirect) reciprocity framework can illuminate our understanding of several factors related to prosocial behavior—namely group membership, gossip, and third-party punishment. We propose that each of these factors can promote prosocial behavior via proximate psychological mechanisms related to direct and indirect reciprocity: reputational concern, expectations, and anticipation of future interaction. Finally, we discuss the implications of adopting such a framework and highlight a number of avenues for future research.

Keywords: Direct reciprocityIndirect reciprocityCooperationProsocial behaviorReview

4. Third-party punishment

Another factor promoting prosocial behavior in social interactions is third-party punishment (Figure 1B). While second-party punishment can be considered a clear instance of negative reciprocity under the anticipation of future interaction [37], third-party punishment represents a more interesting case as the importance for a direct and indirect reciprocity framework may not be clear at first glance. In fact, prominent studies have found that uninterested third parties often punish defectors by incurring a personal cost, and this in turn promotes prosocial behavior among defectors [38]. Thus, third-party punishment can also be conceptualized as a form of prosocial behavior that promotes prosocial behavior in others. However, whether third-party punishment is always prosocial in nature is still debated [39]. Theoretical accounts in line with a reciprocity framework hypothesize that third-party punishment is used as (a) a tool to manage reputation even in one-shot interactions (e.g., to signal trustworthiness to potential future partners) [40,41], and (b) a way to avoid the mistreatment by the defector whom the third party may encounter in the future [19].

Recent research supports the potential role of psychological mechanisms related to a reciprocity framework in explaining why people engage in third-party punishment. For example, previous research found robust evidence that participants who witness a distant stranger being insulted by another person only punish the insulter when observed by other bystanders and when they are concerned about their reputation [42]. By contrast, in anonymous situations people intervene less when a stranger is insulted, compared to a friend or a close other [42]. Moreover, in support of a reciprocity framework, recent research found that people report more moral outrage in response to defection when they cannot signal their trustworthiness through direct prosociality, again suggesting that third-party punishment can be used as a tool to upregulate the punisher’s own reputation [40]. In line with this, across 24 studies, researchers found that the opportunity to gain reputational and partner choice benefits explain why third-parties may prefer compensation over punishment [43]. Reciprocal interactions also seem to be important in the evolution of parochial third-party punishment (i.e., the tendency to punish more harshly outgroup members, compared to ingroup members) [44]. A recent longitudinal study documenting punishment responses to norm violations in daily life also suggests that people upregulate their punishment in situations where their reputation is at stake [45].

Conservative ideologies have been suggested to correlate with elevated sensitivity to threat, but we do not support such association; rather, elevated anxiety may increase concerns about social inequality & the environment

Clinical symptoms of anxiety disorders as predictors of political attitudes: A prospective cohort study. Vilja Helminen, Marko Elovainio, Markus Jokela. International Journal of Psychology, August 13 2021. https://doi.org/10.1002/ijop.12796

Abstract: Conservative political ideologies have been suggested to correlate with elevated sensitivity to threat. However, it is unclear whether the associations between threat sensitivity and political attitudes can be observed with clinical measures of mental health. We examined how anxiety disorders predicted attitudes on several political issues. Participants were 7253 individuals from the 1958 British Birth Cohort study. Symptoms of generalised anxiety disorder, phobia and panic were assessed in a clinical interview at age 44, and opinions about political issues were self-reported by the participants 6 years later. Anxiety symptoms were associated with higher concerns about economic inequality, preservation of the environment, distrust in politics and lower work ethic. No associations were observed with racist or authoritarian attitudes, or support for traditional family values. We also assessed how political attitudes at ages 33 and 42 predicted anxiety disorder symptoms at age 44, revealing a possible bidirectional association between concern for economic inequality and anxiety disorder symptoms. These findings do not support an association between conservative political attitudes and elevated threat sensitivity. Rather, elevated anxiety may increase concerns about social inequality and the environment.

DISCUSSION

We examined whether clinically assessed anxiety disorders (generalised anxiety disorder, phobia and panic disorder) were longitudinally related to political attitudes and vice versa. Higher scores on anxiety symptoms were associated with higher concerns about economic inequality, distrust in politics, environmental concern, as well as lower work ethic. These associations were observed particularly with symptoms of generalised anxiety disorder (GAD) and phobia, whereas symptoms of panic disorder did not have independent associations with political attitudes. Most of these associations were small in magnitude (B < 0.20). Higher concern about inequality assessed years before the clinical interview also predicted higher likelihood of GAD and phobia symptoms, suggesting a possible bidirectional association.

The findings suggest that the previously reported associations between threat sensitivity and political ideology (e.g., Jost et al., 2003; Onraet et al., 2013) may not generalise to clinical measures of anxiety disorders or may be limited to only some political and cultural contexts. In fact, the current associations between anxiety disorders and political attitudes were opposite to the hypothesis of conservatism and heightened threat sensitivity, because concerns about inequality and the environment tend to be associated with liberal and left-wing political ideology (e.g., Cheng et al., 2012; Poortinga et al., 2011), and these attitudes were associated with higher scores on anxiety disorders. Lower work ethic and distrust in politics were also associated with anxiety disorders. Lower work ethic would probably be related to more liberal than conservative attitudes, whereas distrust in politics is more ambiguous—insofar as it reflects a distrust towards governmental decision making, it might represent more conservative than liberal attitudes on the conservative–liberal axis.

Based on the theory of motivated cognition (Jost et al., 2003), we would have expected the anxiety symptoms to predict more racist attitudes, more authoritarian leanings and more support for traditional family values, but these attitudes were not associated with anxiety disorder symptoms. Our results are in contrast to the study by Hatemi et al. (2013) in which clinically assessed social phobia was associated with more negative out-group attitudes. Our lack of specific measure of social phobia, or differences in the measurement of racism and out-group attitudes, might explain the differing results. However, our findings are in line with the few studies that have concluded that anxiety might not lead to more conservative political attitudes (e.g., Huddy et al., 2005; Ray & Najman, 1987). At least two recent studies (Bakker et al., 2020; Osmundsen et al., 2019) also found no support for the link between conservatism and threat reactivity using psychophysiological measures, which casts further doubt on the motivated social cognition explanation of conservatism.

It is also worth noting that there is evidence indicating that the association between threat sensitivity and political orientation is a far more complex phenomenon than the theory of motivated cognition suggests. A recent cross-cultural study by Brandt et al. (2021) found that the way feelings of threat affect political orientation might depend on the type of threat and content of political beliefs under study, and there also seems to be significant variation between countries in how these associations manifest. In our study, the political attitudes at age 50 were measured in 2008–2009 when economic issues were very salient in the wake of the global financial crisis and economic recession in Great Britain. This might have amplified the relevance of perceived economic inequality and would be in line with the findings of Brandt et al. (2021) that economic threats are generally associated with more left-leaning attitudes in the economic domain.

Most notably, in the recent study by Brandt et al. (2021), the associations between different types of threats and different political beliefs were not consistent between countries, with the threat being associated with more right-wing beliefs in some countries and more left-wing beliefs in others. Especially in this light, our findings might indeed reflect a phenomenon constrained to a specific country, period of time, or political context, rather than more generalisable associations between threat sensitivity and political attitudes. This makes our sample the most pressing limitation of our study, as it included only a specific birth cohort from Great Britain.

Regarding study limitations, the CIS-R queried the participants about their anxiety symptoms experienced in the past week, which might have weighted the assessment of anxiety symptoms towards short-term symptoms and not long-term dispositions. However, many measures of mental health that assess symptoms in past weeks or months show considerable rank-order stability between individuals (e.g., GHQ), so clinical measures do not measure only transient psychological states but also more persistent trait-like dispositions. Fourth, the observational study design does not allow us to make causal conclusions. Indeed, our findings suggest that the associations between anxiety disorders and political attitudes may be bidirectional, and at least one previous study (Hatemi et al., 2013) found evidence of a genetic correlation. Thus, it is yet unclear whether anxiety disorders cause differences in political attitudes, or whether they represent the result of common causes.

Together the current findings do not provide evidence to support the theory of motivated social cognition (Jost et al., 2003; Jost et al., 2007) according to which more conservative attitudes would reflect heightened threat sensitivity. Clinically assessed symptoms of anxiety disorders were not associated with conservative political attitudes in the British cohort under examination. Rather, they were either unrelated to beliefs that correlate with conservative vs. liberal ideology (e.g., racist and authoritarian attitudes and traditional family values) or they predicted more liberal or left-leaning attitudes of concerns over economic inequality and preserving the environment, as well as lower work ethic and higher distrust in politics.

Our analysis emphasises the need for multiple clinical and non-clinical measures of threat sensitivity, and more detailed measures of political attitudes than the conservative–liberal axis, to better evaluate the psychological underpinnings of political attitudes and ideologies. Although the association between threat and political orientation has been examined in a significant number of studies, there are multiple aspects that have not been given enough attention. As there is recent evidence that the association depends on the type of threat as well as the type of political beliefs (Brandt et al., 2021), future studies could examine if there are differences in how susceptible individuals are to different types of threat, and how this in turn might affect their political leanings. As previously mentioned, there is also evidence suggesting that the way feelings of threat affect political orientation differs significantly across countries. As the majority of the previous studies regarding the association between threat and political orientation have been conducted in the United States or western Europe, little is yet known about how the cultural and political context might affect this phenomenon. Some studies have identified factors such as ideological constraint, the economic conditions and the ideological status quo as important determinants of how threat is associated with political orientation (e.g., Malka et al., 2014), but at least one large cross-cultural study failed to find significant support for any consistent effects of country characteristics (Brandt et al., 2021). This highlights the urgent need for both, studies using more diverse cross-cultural samples, as well as a larger and more diverse body of research examining this phenomenon in more detail while taking into account the specific political and cultural settings.

The 10 pct most active tweeters (based upon lifetime tweets) generate 81pct of all tweets

Using Administrative Records and Survey Data to Construct Samples of Tweeters and Tweets. Adam G Hughes, Stefan D McCabe, William R Hobbs, Emma Remy, Sono Shah, David M J Lazer. Public Opinion Quarterly, nfab020, August 5 2021. https://doi.org/10.1093/poq/nfab020

Abstract: Social media data can provide new insights into political phenomena, but users do not always represent people, posts and accounts are not typically linked to demographic variables for use as statistical controls or in subgroup comparisons, and activities on social media can be difficult to interpret. For data scientists, adding demographic variables and comparisons to closed-ended survey responses have the potential to improve interpretations of inferences drawn from social media—for example, through comparisons of online expressions and survey responses, and by assessing associations with offline outcomes like voting. For survey methodologists, adding social media data to surveys allows for rich behavioral measurements, including comparisons of public expressions with attitudes elicited in a structured survey. Here, we evaluate two popular forms of linkages—administrative and survey—focusing on two questions: How does the method of creating a sample of Twitter users affect its behavioral and demographic profile? What are the relative advantages of each of these methods? Our analyses illustrate where and to what extent the sample based on administrative data diverges in demographic and partisan composition from surveyed Twitter users who report being registered to vote. Despite demographic differences, each linkage method results in behaviorally similar samples, especially in activity levels; however, conventionally sized surveys are likely to lack the statistical power to study subgroups and heterogeneity (e.g., comparing conversations of Democrats and Republicans) within even highly salient political topics. We conclude by developing general recommendations for researchers looking to study social media by linking accounts with external benchmark data sources.

Genetic influences were strongest in education and weakest in income, and always strongest among those with the most advantaged socioeconomic background, independent of the socioeconomic indicator used

Socioeconomic Background and Gene–Environment Interplay in Social Stratification across the Early Life Course. Jani Erola, Hannu Lehti, Tina Baier, Aleksi Karhula. European Sociological Review, jcab026, August 4 2021. https://doi.org/10.1093/esr/jcab026

Abstract: To what extent are differences in education, occupational standing, and income attributable to genes, and do genetic influences differ by parents’ socioeconomic standing? When in a children’s life course does parents’ socioeconomic standing matter for genetic influences, and for which of the outcomes, fixed at the different stages of the attainment process, do they matter most? We studied these research questions using Finnish register-based data on 6,529 pairs of twins born between 1975 and 1986. We applied genetically sensitive variance decompositions and took gene–environment interactions into account. Since zygosity was unknown, we compared same-sex and opposite-sex twins to estimate the proportion of genetic variation. Genetic influences were strongest in education and weakest in income, and always strongest among those with the most advantaged socioeconomic background, independent of the socioeconomic indicator used. We found that the shared environment influences were negligible for all outcomes. Parental social background measured early during childhood was associated with weaker interactions with genetic influences. Genetic influences on children’s occupation were largely mediated through their education, whereas for genetic influences on income, mediation through education and occupational standing made little difference. Interestingly, we found that non-shared environment influences were greater among the advantaged families and that this pattern was consistent across outcomes. Stratification scholars should therefore emphasize the importance of the non-shared environment as one of the drivers of the intergenerational transmission of social inequalities.

Discussion and Conclusions

In this article, we have presented our findings on the gene–environment interplay over the early life course in education, occupational standing, and income. In summary, our study highlights five findings. First, our baseline findings for education, occupational status, and income show that the relative importance of shared environmental influences was negligible. This challenges previous findings on the substantial influence of the shared environment on education (Branigan, McCallum and Freese, 2013). The results differ from those of earlier studies in Finland studying older cohorts but are similar to those in Norway involving more recent cohorts with similar institutional settings (Silventoinen et al., 2004; Nisén et al., 2013; Ørstavik et al., 2014; Lyngstad, Ystrøm and Zambrana, 2017). For income, the result is in line with a previous Finnish study (Hyytinen et al., 2019). There have been no previous studies on genetic influences in ISEI in Finland, and, to our knowledge, very few elsewhere.

Second, we find that genetic influences are strongest among the most advantaged families. This partly confirms our first hypothesis: There is no linear relationship between the strength of genetic influences and the quality of the family environment, and the differences between the other groups of families are small. Thus, the enhancement mechanism seems to work principally at the top end of the social spectrum. A similar pattern has been found in previous studies studying the social stratification of genetic influences using twin data (Baier and Lang, 2019).

Third, the social stratification of genetic influences is to some extent depending on the age at which parental SES is observed. In contrast to our expectations, parental social background measured early during childhood led to weaker interactions with genetic influences. This finding is an important addition to previous research on the role of socioeconomic rearing environment at different stages of the early life course. It suggests that the average contribution SES would be more or less constant across childhood and youth (Erola, Jalonen and Lehti, 2016). If gene-environment interactions were not taken into account, we would miss the life-course-specific pattern. It may be that parents have not reached their final level of socioeconomic attainment during children’s early childhood, and once parents have achieved that, their status reflects more accurately their genetic potential. If this is the case, the differences we observe in the association between family background and genetic influences according to children’s age can follow from gene–environment correlation related to parent’s socioeconomic attainment. For future research, the results suggest that in order to fully account for stratification according to parental educational and socioeconomic characteristics in genetic influences, one should prefer indicators of parental SES that are observed later than during early childhood.

Fourth, in line with our third hypothesis, we found that the contribution of socioeconomic parental characteristics to genetic influences is stronger the earlier the maturity of an outcome is reached. More specifically, parental characteristics matter mostly for the genetic influences in education, and for occupational standing mostly because it is mediated by their children’s education. Notably, in the case of income, stratification by parental characteristics was weak even before their children’s own education was considered. This is striking: It suggests that nearly all of the factors behind parents’ success or failure in terms of their observed socioeconomic outcomes cannot on average explain that much of how their children succeed economically by age 32–36.

Finally, the results showed the stronger importance of the non-shared environment among the children of parents of high SES. This result was consistent across the three outcomes as well as the indicators of parental SES, and aligned with previous studies showing that socioeconomic outcomes within families differ more strongly among advantaged children (Goldstein and Warren, 2000; Heflin and Pattillo, 2006). A possible explanation can be borrowed from research on stratified parenting (Lareau, 2011; Kalil, Ryan and Corey, 2012) showing that parents of higher social status make more child-specific investments based on their children’s individual talents or particular weaknesses that can accentuate differences among their children (Baier, 2019). However, similar findings could also result from the multiplicative processes if advantaged parents or the children themselves prefer differential treatment. For example, the same innate talent in math could lead to different educational and career pathways and could encourage careers in either business or academia.

Our results also contribute to the broader discussion on equality of opportunity. As comparative research has shown that social background matters relatively little in Finland, this could lead one to expect that the genetic influences in attainment should also be particularly strong. To some extent, the results are in line with this: The shared environment alone matters very little compared to the results on older birth cohorts in Finland (Silventoinen et al., 2004; Branigan, McCallum and Freese, 2013; Nisén et al., 2013). However, there is an addition: the comparison of outcomes shows that a negligible impact of shared environmental influences does not mean that only the impact of genes would automatically become stronger; it can also change the differences due to the non-shared environment. To date, the role of non-shared environmental influences has barely been discussed in the literature on genetic influences in socioeconomic attainment (as a notable exception, see Beam and Turkheimer, 2013). These channels nonetheless appear to be relevant for intergenerational socioeconomic transmission processes.

A caveat regarding the data is that we could not follow income as long as would have been preferable (until over age 40); we only covered log mean income from at age 32–36. It may be that the stronger role of genes in the incomes of the highly educated parents we observe now reflects their children’s improved chances to fulfil their own genetic potential, rather than the parents’ investments for their children. If this is the case, the genetic influences on income would become even stronger later. Furthermore, the immediate family context is not the only environment that we are exposed to during childhood and youth. Extended families, schools, or neighbourhoods could have also contributed to the gene–environment interplay. Also a detailed analysis of gender differences was beyond the scope of our study.

Moreover, it may be that our method of estimating genetic influences by comparing same and different sex twins led to a bias in the results; for instance, previous twin studies on education in Finland have found a substantive effect of shared influences that we did not observe. Testing our hypotheses with increasingly available molecular genomic data could shed light on the mechanisms involved; for instance, in the context of the third hypothesis on mediation, direct measures for genetic influences relevant for education, occupation, and income would allow us to test directly to what extent the same genetic influences contribute to each outcome.

In sum, the results underline the value of studying the gene–environment interplay for a better understanding of intergenerational socioeconomic inequalities. Clearly, genetic inheritance plays a key role in this and should be more strongly integrated into stratification research. Importantly, the results show that our theoretical assumptions about the relationship between social inequalities, genes, and shared and non-shared environments are still relatively underdeveloped, especially regarding the importance and role of the non-shared environment. In the future, one of the key tasks of research on intergenerational social mobility and attainment should be the development of better theories on the relationship between gene–environment interplay and its implications for equality of opportunity. The latter goal calls for comparisons of results by applying similar research designs across multiple nations.

A new study challenges assumptions about energy expenditure by people, including the idea that metabolism slows at middle age

Daily energy expenditure through the human life course. Herman Pontzer et al. Science  Aug 13 2021:Vol. 373, Issue 6556, pp. 808-812. DOI: 10.1126/science.abe5017

A lifetime of change

Measurements of total and basal energy in a large cohort of subjects at ages spanning from before birth to old age document distinct changes that occur during a human lifetime. Pontzer et al. report that energy expenditure (adjusted for weight) in neonates was like that of adults but increased substantially in the first year of life (see the Perspective by Rhoads and Anderson). It then gradually declined until young individuals reached adult characteristics, which were maintained from age 20 to 60 years. Older individuals showed reduced energy expenditure. Tissue metabolism thus appears not to be constant but rather to undergo transitions at critical junctures.

Abstract: Total daily energy expenditure (“total expenditure”) reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass–adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

Popular version: What We Think We Know About Metabolism May Be Wrong. https://www.nytimes.com/2021/08/12/health/metabolism-weight-aging.html

At around age 5, children become gradually capable of strategically using prosocial acts to achieve ulterior goals such as to improve their reputation, to be chosen as social partners, to elicit reciprocity, & to navigate interpersonal obligations

The development of prosocial behavior – from sympathy to strategy. Sebastian Grueneisen, Felix Warneken. Current Opinion in Psychology, August 12 2021. https://doi.org/10.1016/j.copsyc.2021.08.005

Abstract: Children act prosocially already in their first years of life. Research has shown that this early prosociality is mostly motivated by sympathy for others, but that, over the course of development, children’s prosocial behaviors become more varied, more selective, and more motivationally and cognitively complex. Here, we review recent evidence showing that, starting at around age 5, children become gradually capable of strategically using prosocial acts as instrumental means to achieve ulterior goals such as to improve their reputation, to be chosen as social partners, to elicit reciprocity, and to navigate interpersonal obligations. Children’s sympathy-based prosociality is thus being extended and reshaped into a behavioral repertoire that enables individuals to pursue and balance altruistic, mutualistic, and selfish motives.

Keywords: Prosocial behaviorchildrencooperationstrategicaltruism

From 2020... People living with close others (children or romantic partners) experienced better well-being before and during the pandemic’s first 6 months

From 2020... The Benefits of Living with Close Others: A Longitudinal Examination of Mental Health Before and During a Global Stressor. Sisson NM, Willroth EC, Le BM, Ford BQ. PsyArXiv, Dec 1 2020. DOI: 10.31234/osf.io/v9mc4. https://europepmc.org/article/ppr/ppr321868

Abstract: For better or worse, the people we live with may exert a powerful influence on our mental health, perhaps especially during times of stress. The COVID-19 pandemic—a large-scale stressor that prompted health recommendations to stay home to reduce disease spread—provided a unique context for examining how the people we share our homes with may shape our mental health. A seven-wave longitudinal study assessed mental health month-to-month before and during the pandemic (February through September, 2020) in two diverse samples of U.S. adults (N = 656; N = 544). Pre-registered analyses demonstrated that people living with close others (children and/or romantic partners) experienced better well-being before and during the pandemic’s first six months. These groups also experienced unique increases in ill-being during the pandemic’s onset, but parents’ ill-being also recovered more quickly. These findings highlight the crucial protective function of close relationships for mental health both generally and amidst a pandemic.