Sperm donation: Mostly altruistic, donors favored anonymity; education level, conscientiousness, empathic concern were positively correlated to donation; age, & conservative and religious values were negatively associated

Motivations and Attitudes of Men Towards Sperm Donation: Whom to Donate and Why? João Areias, Jorge Gato & Mariana Moura-Ramos. Sexuality Research and Social Policy, Jan 27 2021. https://rd.springer.com/article/10.1007/s13178-020-00531-0

Abstract

Background: The widespread access to medically assisted reproduction (MAR) techniques for all women, regardless of any infertility diagnosis, has led to an increased, but as yet unmet, demand for sperm donors in Portugal. For this study, we deployed an online survey to explore men’s motivations for donating and their attitudes toward anonymity and donating for specific groups.

Method: The study’s sample comprised men who were eligible to donate sperm (N = 282). The relationships between these factors and participants’ psychological and sociodemographic characteristics were also explored.

Results: The results mostly indicated altruistic reasons for donating, positive attitudes toward anonymity, and a greater willingness to donate to infertile women. Overall, sexual orientation was not associated with the participants’ attitudes and motivations. Age, education level, conscientiousness, empathic concern, and conservative and religious values were associated with the participants’ motivations and attitudes toward sperm donation.

Conclusion: Recruitment campaigns should therefore consider the specific motivations, attitudes, and psychosocial characteristics of potential sperm donors. Indeed, parenthood is a universal right, so sperm donation should be encouraged, regardless of recipients’ fertility status. Clear information about the identifiability of sperm donors should also be provided.

Discussion

The main goal of this study was to highlight what drives men to donate sperm, their attitudes toward anonymity, and their attitudes toward donating for specific groups, as well as to investigate how sexual orientation, psychological traits, and sociodemographic characteristics influence these motivations and attitudes. For reasons of clarity, the results will be discussed in terms of (i) motivations to donate, (ii) attitudes toward anonymity, and (iii) attitudes toward donating for specific groups.

Motivations to Donate

Consistent with the literature, altruistic motivation seems to be the most significant motivation for donating sperm, emphasizing a desire to help childless couples have children (Ekerhovd et al., 2008; Hedrih & Hedrih, 2012; Thijssen et al., 2017; Van der Broeck et al., 2013) and diminishing the role of financial compensation in return for donation (Ekerhovd et al., 2008; Hedrih & Hedrih, 2012; Thijssen et al., 2017). Motivations to donate were generally not associated with the participants’ sexual orientation, except for the motivation of “knowing one’s fertility,” with heterosexual men assigning more importance to this than other men. Non-heterosexual men’s lack of interest in their fertility status may be because they generally show a weaker intent to parent children and anticipate stigma upon achieving parenthood (Gato, Leal, Coimbra, & Tasker, 2020). Furthermore, many non-heterosexual men seem to be unfamiliar with alternative paths to parenthood (Patterson & Riskind, 2010), and some still envisage parenting as a feminine role (Gato & Fontaine, 2017; Pelka, 2009). Nevertheless, future research should further examine the genesis of these differences.

Age was negatively associated with the motivation of “knowing one’s fertility,” with younger men assigning more importance to this motivation. According to Thijssen et al. (2017), this association is expected because younger, childless men have not yet confirmed their fertility status. Furthermore, the men with a lower level of education also valued this motivation more, so future research should explore this association.

Considering the psychological characteristics of the participants, men with higher levels of Conscientiousness assigned more importance to learning their fertility status. People with high levels of conscientiousness may be more motivated to donate based on willingness to pass on their “good genes” (Thijssen et al., 2017), because this will confirm their purpose and usefulness to society and themselves. Similarly, men with higher levels of Conservative values also ascribed more importance to learning their fertility status. This is unsurprising if we consider that more conservative individuals tend to value social order and assign more importance to traditional institutions (Schwartz, 1992, 1994), such as heteronormative families where children generally have a genetic link with their parents.

People with high levels of empathic concern donate in various contexts, and they are compassionate toward others and seem to be oriented toward alleviating the suffering of others in need (Verhaert & Van den Poel, 2011). This explains the positive association between empathic concern and the motivation to help others have a child, as was found in this study. Conversely, religious values were negatively correlated with this motivation. Even though modern Portugal is a secular country, Catholic values still exert a certain influence (Dix, 2010). In our study, the negative association between adherence to religious values and helping someone to have a child may derive from the fact that Catholicism tends to reject alternative family configurations, including the pursuit of pregnancy through MAR (Rubio, 2015).

Attitudes Toward Anonymity

Willingness to be contacted by the child was the least-indicated attitude, differing from the assertions “parents should disclose DI conception with the child” and “the institution where DI was realized can provide information about me to the child, since that information does not identify me.” This finding agrees with research that found that men tend to avoid donation if their identities may be disclosed (Bay et al., 2014; Thijssen et al., 2017). Nevertheless, a relatively positive view about non-anonymous donation was noticeable, because all participants endorsed disclosing DI conception to the child and releasing non-identifying information about the donor. No differences in attitudes toward anonymity were found as a function of sexual orientation, thus contradicting the study of Freeman et al. (2016), which verified that gay and bisexual men, when compared to their heterosexual peers, were more open minded when it came to anonymity and more willing to have contact with children conceived using their sperm. This study’s results refuted our hypotheses about differences between heterosexual and non-heterosexual men for attitudes toward sperm donation.

For sociodemographic characteristics, age was negatively associated with the attitude that “parents should disclose DI conception to the child,” with younger participants subscribing more to this attitude. According to Riggs and Russell (2011), men under the age of 26 preferred identity-release legislation, and this may reflect in the opinion that parents should disclose DI conception to the child. No psychological characteristics were associated with attitudes toward anonymity, perhaps due to the choice of psychological correlates in this study. Future research should therefore include other aspects, such as neuroticism and agreeableness.

Attitudes Toward Donating for Specific Groups

Regarding attitudes toward donating for specific groups, a positive tendency toward donating to all groups was discernible, and this is consistent with the findings of other studies (Bay et al., 2014; Ekerhovd et al., 2008; Thijssen et al., 2017). Nevertheless, donating to heterosexual women with fertility problems was the group regarded the most positively. This may come from the altruistic motivations to donate that participants reported. Indeed, altruism is based on a desire to help someone to have a child (Ekerhovd et al., 2008; Hedrih & Hedrih, 2012; Thijssen et al., 2017; Van der Broeck et al., 2013), and infertile women may be perceived, a priori, as being at a greater disadvantage.

Empathic concern was positively associated with donating to most recipient groups. This likely derives from the fact that people with high levels of empathic concern tend to focus more on alleviating the suffering of others and showing compassion (Verhaert & Van den Poel, 2011). In contrast, adherence to religious values was negatively associated with donating to all groups. As mentioned earlier, this may stem from the influence of Catholic views about family (Rubio, 2015).

Limitations, Future Directions, and Implications for Practice

Like any research endeavor, this study is not without limitations. More than half of our sample was highly educated, so it was not representative of the wider Portuguese population. Additionally, the imbalance in the number of heterosexual and non-heterosexual men may have further compromised the results and prevented us from drawing conclusions about the influence of this variable. The small magnitude of effects (except in the RM ANOVAs) also raised concerns and somewhat limited generalization of the findings.

Despite these limitations, however, our findings do have implications for practice. By shedding light on the motivations, attitudes, and characteristics of possible candidate donors, the findings of this study may inform future recruitment campaigns. Indeed, based on these findings, it could be argued that campaigns should target specific motivations, attitudes, and characteristics of potential donors. As Ferguson, Atsma, de Kort, and Veldhuizen (2012) reported in the context of blood donation, emphasizing the positive feelings that are associated with donation can increase donation rates, so a similar concept could be applied in the context of sperm donation. For example, in this study, the most frequently reported motivation to donate was to help someone have a child, which is an altruistic motivation. It may therefore be useful to highlight the altruistic nature of donation in any campaign.

This study also contributes to the view that withdrawing donation anonymity, which took place in Portugal in 2018, may not necessarily affect the number of potential donors, thus reflecting the positive trend toward non-anonymity reported by other studies (Bay et al., 2014; Thijssen et al., 2017). However, given a pattern of disengagement when the disclosed information is too personal or when there is a chance of contact with the child, the issue of anonymity should be further debated and clarified. Future recruitment campaigns should therefore stress that upon release of anonymity, the donor bears no obligation or commitment to the child. Likewise, it is crucial to emphasize that parenthood is a universal right in order to encourage sperm donation for any person or couple, regardless of fertility status or sexual orientation.

We showed that 46% of the variability in sleep duration & 44% of the variability in sleep quality is genetically determined; the remaining variation in the sleep characteristics can mostly be attributed to the unique environment

Heritability of Sleep Duration and Quality: A Systematic Review and Meta-analysis. Desana Kocevska et al. Sleep Medicine Reviews, January 27 2021, 101448. https://doi.org/10.1016/j.smrv.2021.101448

Summary: Epidemiological and interventional research has highlighted sleep as a potentially modifiable risk factor associated with poor physical and mental health. Emerging evidence from (behavioral) genetic research also shows that sleep characteristics are under strong genetic control. With this study we aimed to meta-analyze the literature in this area to quantify the heritability of sleep duration and sleep quality in the general population. We conducted a systematic literature search in 5 online databases on January 24th 2020. Two authors independently screened 5,644 abstracts, and 160 complete articles for the inclusion criteria of twin studies from the general population reporting heritability statistics on sleep duration and/or quality, and written in English. We ultimately included 23 papers (19 independent samples: 45,328 twins between 6 months to 88 years) for sleep duration, and 13 papers (10 independent samples: 39,020 twins between 16 and 95 years) for sleep quality. Collectively, we showed that 46% of the variability in sleep duration and 44% of the variability in sleep quality is genetically determined. The remaining variation in the sleep characteristics can mostly be attributed to the unique environment the twins experience, although the shared environment seemed to play a role for the variability of childhood sleep duration. Meta-analyzed heritability estimates for sleep duration, however, varied substantially with age (17% infancy, 20-52% childhood, 69% adolescence and 42-45% adulthood) and reporter (8% parent-report, 38-52% self-report). Heritability estimates for actigraphic and PSG-estimated sleep were based on few small samples, warranting more research. Our findings highlight the importance of considering genetic influences when aiming to understand the underlying mechanisms contributing to the trajectories of sleep patterns across the lifespan.

Keywords: Behavioral GeneticsSleepGenesHeritabilityInheritance PatternsSleep durationSleep Quality

Check also What Do People Know About the Heritability of Sleep? Juan J. Madrid-Valero, Robert Chapman, Evangelina Bailo, Juan R. Ordoñana, Fatos Selita, Yulia Kovas & Alice M. Gregory. Behavior Genetics, Jan 23 2021. https://www.bipartisanalliance.com/2021/01/most-people-do-not-have-accurate.html

Over just 10 years, both implicit and explicit male-science/female-arts and male-career/female-family stereotypes have shifted toward neutrality, weakening by 13%–19%, in all US regions & several other countries

Patterns of Implicit and Explicit Stereotypes III: Long-Term Change in Gender Stereotypes. Tessa E. S. Charlesworth, Mahzarin R. Banaji. Social Psychological and Personality Science, January 27, 2021. https://doi.org/10.1177/1948550620988425

Rolf Degen's take: "Over just 10 years, both implicit and explicit gender stereotypes have have moved toward neutrality worldwide. https://t.co/BzHPXVKVfg https://t.co/Gmpr9bOxEr"

Abstract: Gender stereotypes are widely shared “collective representations” that link gender groups (e.g., male/female) with roles or attributes (e.g., career/family, science/arts). Such collective stereotypes, especially implicit stereotypes, are assumed to be so deeply embedded in society that they are resistant to change. Yet over the past several decades, shifts in real-world gender roles suggest the possibility that gender stereotypes may also have changed alongside such shifts. The current project tests the patterns of recent gender stereotype change using a decade (2007–2018) of continuously collected data from 1.4 million implicit and explicit tests of gender stereotypes (male-science/female-arts, male-career/female-family). Time series analyses revealed that, over just 10 years, both implicit and explicit male-science/female-arts and male-career/female-family stereotypes have shifted toward neutrality, weakening by 13%–19%. Furthermore, these trends were observed across nearly all demographic groups and in all geographic regions of the United States and several other countries, indicating worldwide shifts in collective implicit and explicit gender stereotypes.

Keywords: implicit social cognition, gender stereotypes, stereotype change, time series analyses (ARIMA)

Following Twitter: Anger, but not the other constructs, was distinctly reflected in followed accounts, and there was some indication of bias in predictions for women but not for racial/ethnic minorities

Predicting Mental Health From Followed Accounts on Twitter. Cory Costello; Sanjay Srivastava; Reza Rejaie; Maureen Zalewski. Psychology (2021) 7 (1): 18731. https://doi.org/10.1525/collabra.18731

Rolf Degen's take: "The accounts you follow on Twitter could shed some light on your mental health. https://t.co/iLPFnX3LCZ https://t.co/wVX3H6ngxm"

Abstract: The past decade has seen rapid growth in research linking stable psychological characteristics (i.e., traits) to digital records of online behavior in Online Social Networks (OSNs) like Facebook and Twitter, which has implications for basic and applied behavioral sciences. Findings indicate that a broad range of psychological characteristics can be predicted from various behavioral residue online, including language used in posts on Facebook (Park et al., 2015) and Twitter (Reece et al., 2017), and which pages a person ‘likes’ on Facebook (e.g., Kosinski, Stillwell, & Graepel, 2013). The present study examined the extent to which the accounts a user follows on Twitter can be used to predict individual differences in self-reported anxiety, depression, post-traumatic stress, and anger. Followed accounts on Twitter offer distinct theoretical and practical advantages for researchers; they are potentially less subject to overt impression management and may better capture passive users. Using an approach designed to minimize overfitting and provide unbiased estimates of predictive accuracy, our results indicate that each of the four constructs can be predicted with modest accuracy (out-of-sample R’s of approximately .2). Exploratory analyses revealed that anger, but not the other constructs, was distinctly reflected in followed accounts, and there was some indication of bias in predictions for women (vs. men) but not for racial/ethnic minorities (vs. majorities). We discuss our results in light of theories linking psychological traits to behavior online, applications seeking to infer psychological characteristics from records of online behavior, and ethical issues such as algorithmic bias and users’ privacy.

Keywords:emotions, social network analysis, online social networks, machine learning, data science, mental health

Discussion

Our central aim was to understand how mental health is reflected in network connections in social media. We did so by estimating how well individual differences in mental health can be predicted from the accounts that people follow on Twitter. The results showed that it is possible to do so with moderate accuracy. We selected models in training data using 10-fold cross-validation, and then we estimated the models’ performance in new data that was kept completely separate from training, where model Rs of approximately .2 were observed. Although these models were somewhat accurate, when we examined which features were weighted as important for prediction, we did not find them to be readily interpretable with respect to prior theories or broad themes of the mental health constructs we predicted.

Mental Health and the Curation of Social Media Experiences

This study demonstrated that mental health is reflected in the accounts people follow to at least a small extent. The design and data alone cannot support strong causal inferences. One interpretation that we find plausible is that the results reflect selection processes. The list of accounts that a Twitter user follows is a product of decisions made by the user. Those decisions are the primary way that a user creates their personalized experience on the platform: when a user browses Twitter, a majority of what they see is content from the accounts they previously decided to follow. It is thus possible that different mental health symptoms affect the kind of experience people want to have on Twitter, thus impacting their followed-account list. The straightforward ways this could play-out that we discussed at the outset of this paper – e.g., face-valid information-seeking via mental health support or advocacy groups, homophily (following others who display similar mental health symptoms), or emotion regulation strategies – did not seem to be supported. Instead, the accounts with high importance scores were celebrities, sports figures, media outlets, and other people and entities from popular culture. In some rare instances, these hinted towards homophily or a similar mechanism: for example, one account with a high importance score for depression was emo-rapper Lil Peep, who was open about his struggles with depression before his untimely death. More often, however, the connections were even less obvious, and few patterns emerged across the variety of highly important predictors. Other approaches, such as qualitative interviews or experiments that manipulate different account features, may be more promising in the future for shedding light on this question.

Causality in the other direction is also plausible: perhaps following certain accounts affects users’ mental health. For example, accounts that frequently tweet depressing or angry content might elicit depression or anger in their followers in a way that endures past a single browsing session. The two causal directions are not mutually exclusive and could reflect person-situation transactional processes, whereby individual differences in mental health lead to online experiences that then reinforce the pre-existing individual differences, mirroring longitudinal findings of such reciprocal person-environment transactions in personality development (Le et al., 2014; Roberts et al., 2003). Future longitudinal studies could help elucidate whether similar processes occur with mental health and social media use.

In a set of exploratory analyses, we probed the extent to which the predicted scores were capturing specific versus general features of psychopathology. The followed-account scores that were constructed to predict anger captured variance that was unique to that construct; but for depression, anxiety, and post-traumatic stress, we did not see evidence of specificity. One possible explanation is that followed accounts primarily capture a more general psychopathology factor (Lahey et al., 2012; Tackett et al., 2013) but anger also has distinct features that are also relevant. Another possibility is that followed accounts can distinguish between internalizing and externalizing symptoms, and anger appeared to show specificity since it was the only externalizing symptom we examined. The present work cannot distinguish between these possibilities, but future work including more externalizing symptoms may be helpful in differentiating between these and other possibilities.

Relevance for Applications

What does this degree of accuracy – a correlation between predicted and observed scores of approximately .2 – mean for potential applications? First, it’s worth noting that our conclusions are limited to twitter users that meet our minimal activity thresholds (25 tweets, 25 followers, 25 followed accounts), so they may not be applicable to twitter users as a whole, including truly passive users that might follow accounts but not tweet (at all). Even among the users that do meet these thresholds, we do not believe these models are accurate enough for use in individual-level diagnostic applications, as they would provide a highly uncertain, error-prone estimate of any single individual’s mental health status. At best, a correlation of that size might be useful in applications that rely on aggregates of large amounts of data. For example, this approach could be applied to population mental health research to characterize trends in accounts from the same region or with other features in common.

A caveat is that the goal of the present study was to focus on followed accounts – not to maximize predictive power by using all available information. It may be possible to achieve greater predictive accuracy by integrating analyses of followed accounts with complementary approaches that use tweet language and other data. In addition, more advanced approaches that would be tractable in larger datasets, such as training vector embeddings for followed accounts (analogous to word2vec embeddings; Mikolov et al., 2006), could help increase accuracy and should be investigated in the future. Likewise, it may be possible to leverage findings from recent work identifying clusters or communities of high in-degree accounts (Motamedi et al., 2020, 2018) to identify important accounts or calculate aggregate community scores, as opposed to the bottom-up approaches to filtering and aggregating accounts used in this study. Future work can examine the extent to which these different modifications to our procedure maximize predictive accuracy.

Another important caveat to consider with respect to possible applications of this work is that this approach is more suited to studying more stable individual differences in mental health rather than dynamic, within-person fluctuations or responses to specific events. This was an aim that was reflected in the design of this study – for example, the wording of the mental health measures covered a broader time span than just the moment of data collection. Followed accounts are likely to be a less dynamic cue than other cues available on social media (e.g., language used in posts). This is not to say that network ties are unrelated to dynamic states entirely, and that possibility could be explored with different methods. For example, rather than focusing on whether accounts are followed or not, researchers could use engagements with accounts (such as liking or retweeting) to predict momentary reports of mental health symptomatology, or they could track users over time to measure new follows added after an event. The present work can only speak indirectly to these possibilities, but exploring approaches that dynamically link network ties to psychological states is a promising future direction for this work.

The present results, and the possibility of even higher predictive accuracy or greater temporal resolution with more sophisticated methods, raise important questions about privacy. The input to the prediction algorithm developed in this paper – a list of followed accounts – is publicly available for every Twitter user by default, and it is only hidden if a user sets their entire account to “private.” It is unlikely that users have considered how this information could be used to infer their mental health status or other sensitive topics. Indeed, even people who deliberately refrain from self-disclosing about their mental health online may be inadvertently providing information that could be the basis of algorithmic estimates, a possibility highlighted by the often less-than-straightforward accounts that the algorithms appeared to use in their predictions. With time, technological advancement, and research, these predictions might become even more accurate using similarly non-obvious cues in their predictions, though we cannot say how much more. In this way, the present findings are relevant for individuals to make informed decisions about whether and how to use social media. Likewise, they speak to broader issues of ethics, policy, and technology regulation at a systemic level (e.g., Tufekci, 2020). The possibility of a business, government, or other organization putting their considerable resources into using public social media data to construct profiles of users’ mental health may have useful applications in public health research, but it simultaneously raises concerns about how that may be misused. Our results suggest that accuracy is too low for such utopic or dystopic ends presently, but they highlight the possibilities, and the need for in-depth discussions about data, computation, privacy, and ethics.

Predictive Bias

Predictive algorithms can be biased with respect to gender, race, ethnicity, and other demographics, which can create and reinforce social inequality when those algorithms are used to conduct basic research or in applications (Mullainathan, 2019). When we probed for evidence of predictive bias for gender, we found somewhat inconclusive results. There was more of a pattern of bias in the smaller holdout dataset than in the combined data. In the holdout data, women showed higher observed levels of internalizing symptoms (depression, anxiety, and post-traumatic stress) than men with the same model-predicted scores. In the larger combined dataset, only post-traumatic stress showed this effect, and to a much smaller magnitude. Confidence bands in both datasets often ranged from no effect to moderately large effects in one or both directions. All together, we took this as suggestive but inconclusive evidence that the models may have been biased. If the pattern is not spurious, one possible reason may stem from the fact that the sample had more men than women. If men’s and women’s mental health status is associated with which accounts they follow, but the specific accounts vary systematically by gender, then overrepresentation of men in the training data could have resulted in overrepresentation of their followed accounts in the algorithm.

We found little to no evidence of bias with respect to race or ethnicity. The relative lack of bias is initially reassuring, but it should be considered alongside two caveats. First, it is possible that there is some amount of bias that we were unable to detect with the numbers of racial and ethnic minority participants in this dataset. This possibility is highlighted by the confidence bands, which (like gender) tended to range from no effect to moderately large effects. Second, it is possible that collapsing into White vs. non-White is obscuring algorithmic bias that is specific to various racial and ethnic identities. Our decision to combine minority racial and ethnic groups was based on the limitations of the available data, and it necessarily collapses across many substantively important differences.

In any future work to extend or apply the followed-accounts prediction method we present in this study, we strongly encourage researchers to attend carefully to the potential for algorithmic bias. We also hope that this work helps demonstrate how well-established psychometric methods for studying predictive bias can be integrated with modern machine learning methods.

Considering Generalizability At Two Levels of Abstraction

To what extent would the conclusions of this study apply in other settings? There are at least two ways to consider generalizability in this context. The first form of generalizability is a more abstract one, associated with the approach. Would it be possible to obtain similar predictive accuracy by applying this modeling approach to new data drawn from a different population, context, or time, developing a culturally-tuned algorithm for that new setting? We believe the results are likely to be generalizable in this sense. We used cross-validation and out-of-sample testing to safeguard against capitalizing on chance in estimates of accuracy. If the general principle holds that Twitter following decisions are associated with mental health, we expect that it would be possible to create predictive algorithms in a similar way in other settings.

A second, more specific way to think about generalizability is whether the particular prediction algorithms we trained in this study would generalize to entirely new samples from different settings. This is a much higher bar, and we are more skeptical that the models trained in this study would meet it. The fact that the models were not interpretable suggests that they may not have been picking up on theoretically central, universally relevant features of psychopathology. Instead, they might be picking up on real, but potentially fleeting, links between psychopathology and Twitter behavior. By analogy, consider differences between a self-report item like, “I frequently feel sad,” and an item like, “I frequently listen to Joy Division.” The first item would probably be endorsed by depressed people in a wide variety of contexts, populations, and historical eras. The second item, however, is deeply culturally embedded – it if is reflective of depression at all, that association would be highly specific to a particular group of people at a particular cultural moment. Even setting aside that Twitter itself is a product of a specific cultural and historical context, our inspection of the followed accounts suggests that they are not reflecting enduring features of psychopathology in a direct, face-valid sense. The associations with particular accounts were real in this data, but as cultural trends change, they may fade while new ones emerge.

Our results cannot speak to this form of generalizability directly, and it would require a new sample and different design to effectively speak to this. One possibility would be to collect several very different samples (e.g., sampled in different years), train models with each, and then evaluate cross-sample predictive accuracy. This would be a much stricter test of accuracy, but it would provide better justification for using model-derived scores in research or application. Such an approach might also be useful for distinguishing which accounts or features of accounts are predictive because of fleeting cultural factors, and which ones reflect stable and cross-contextually consistent associations with psychopathology.

Stereotypes About Nihilists Are Overwhelmingly Negative; unlike atheists, who are seen as competent, no positive stereotypes emerged for nihilists

Scott, Matthew. 2021. “Stereotypes About Nihilists Are Overwhelmingly Negative.” PsyArXiv. January 26. doi:10.31234/osf.io/g2yd8

Abstract: Existential nihilism is on the rise in modern societies, but no previous work has investigated the social psychology of seeing no meaning in life. In the current research, five studies (N = 1,634) show that targets’ existential nihilist beliefs elicit a range of negative stereotypes about personality traits, commonly valued social traits, and targets’ ability to perform basic adaptive social tasks. Results demonstrate that these negative stereotypes are mediated by belief that the target is depressed more than the belief the target is non-religious or that the target does not plan for the future. Unlike atheists, who are seen as competent, no positive stereotypes emerged for nihilists, suggesting both future research and interventions aimed at updating false beliefs about nihilists.

Rolf Degen summarizing... Large-scale study of information behavior in times of coronavirus provides the umpteenth evidence that people do not entrench themselves in echo chambers

COVID-19 Echo Chambers: Examining the Impact of Conservative and Liberal News Sources on Risk Perception and Response. Kenneth A. Lachlan, Emily Hutter, and Christine Gilbert. Health Security, Jan 19 2021. https://doi.org/10.1089/hs.2020.0176

Rolf Degen's take: Rolf Degen on Twitter: "Large-scale study of information behavior in times of coronavirus provides the umpteenth evidence that people do not entrench themselves in echo chambers. https://t.co/8wZpV5otWk https://t.co/5f8eFQe3Co"

Abstract: The coronavirus disease 2019 (COVID-19) pandemic has created substantial challenges for public health officials who must communicate pandemic-related risks and recommendations to the public. Their efforts have been further hampered by the politicization of the pandemic, including media outlets that question the seriousness and necessity of protective actions. The availability of highly politicized news from online platforms has led to concerns about the notion of “echo chambers,” whereby users are exposed only to information that conforms to and reinforces their existing beliefs. Using a sample of 5,000 US residents, we explored their information-seeking tendencies, reliance on conservative and liberal online media, risk perceptions, and mitigation behaviors. The results of our study suggest that risk perceptions may vary across preferences for conservative or liberal bias; however, our results do not support differences in the mitigation behavior across patterns of media use. Further, our findings do not support the notion of echo chambers, but rather suggest that people with lower information-seeking behavior may be more strongly influenced by politicized COVID-19 news. Risk estimates converge at higher levels of information seeking, suggesting that high information seekers consume news from sources across the political spectrum. These results are discussed in terms of their theoretical implications for the study of online echo chambers and their practical implications for public health officials and emergency managers.

Discussion

The findings for Hypothesis 1—that information seeking does not motivate general risk perception—were somewhat unexpected given a lengthy history of research connecting information seeking to perceptions of risk severity. The findings for Hypothesis 2—that information seeking does not motivate mitigation—are also puzzling given a long history of research connecting risk information to protective action. This may be a product of the relative simplicity of CDC guidelines, and the fact that suggestions like wearing a facemask and washing one's hands do not require a great deal of effort. While CDC guidelines have shifted over the course of the pandemic, the individual-level recommendations captured here were fairly consistent during the time data was collected (April through June 2020). The mean across this outcome variable was fairly high for the entire sample (M = 6.11; SD = 1.36 on a 7-point scale), suggesting there may simply have been little variance in the outcome. Hypothesis 3—that information seeking would predict specific estimates of risk—was supported by our analysis. This can perhaps be traced to the underlying processes surrounding information seeking through websites. Whether seeking information from conservative or liberal sources, information seeking requires some degree of active processing. It may be that heavy information seekers, by definition, engage in active processing and are, therefore, better able to encode risks and process them into specific estimates of infection, health risk, and mortality.

Findings for the research question—concerning the moderating effect of reliance on conservative and liberal websites—may shed further light on the findings for all 3 hypotheses and are the most interesting and impactful findings in this study. With regard to echo chambers, our findings for the research question largely indicate that higher information seekers did not experience attitudinal polarization; in fact, across all 3 outcome variables the risk estimates for those reliant on liberal and conservative news content converged at higher levels of information seeking. In other words, lower information seekers, those reliant on conservative sources, reported the lowest levels of risk probability, whereas those reliant on liberal sources reported the highest (Figures 1, 2, and 3). At high levels of information seeking these differences disappear. Accordingly, the impact of information seeking on risk estimates is higher among those reliant on conservative websites, since they have further to go to converge; this is evident in the standardized conditional effects (Tables 1, 2, and 3).

In short, these findings run counter to the notion of echo chambers, and more closely approximate the argument of Messing and Westwood35—that those who engage in high levels of information seeking likely gather information from a range of sources. It may also be the case that high information seekers draw from a range of platforms and may be more open to information that does not align with (or challenges) existing attitudes and beliefs. This would also explain the failure to find a relationship between information seeking and both general risk perception and mitigation (Hypotheses 1 and 2). If high information seekers draw from liberal and conservative news sources, they would likely be exposed to or open to a range of perspectives, including those suggesting high risk and the need to take protective action. This exposure could potentially weaken direct effects between overall information seeking and the variable outcomes.

If politicized underreporting of the threats associated with COVID-19 is a concern, the lower information seekers may be more at risk, as this is where clear differences are evident in risk estimation by source preference. This finding is particularly alarming when considering Slater's25 arguments concerning polarization spirals; if low information seekers with polarized conservative opinions consume congenial information about the pandemic, and only congenial information, they may be likely to double down on their positions concerning specific risk estimates and become even more inclined to seek information that affirms those positions.

Although this is a single study in a highly specified context, health officials may wish to consider these findings when countering misinformation and understatements of risk. The most impressionable audiences may be those who seek the least amount of information and are, therefore, susceptible to information that confirms their biases. Identifying and segmenting these audiences along media preferences and demographic and social strata may enable health officials to target risk messages to those least likely to actively seek information.

People asks for cosmetic surgery because conference video displays, inter alia, one’s emotions in real-time, which may cause a person to notice expression lines and wrinkles which they do not see in the mirror

Zooming into Cosmetic Procedures During the COVID-19 Pandemic: The Provider’s Perspective. Shauna M. Rice et al. International Journal of Women's Dermatology, January 12 2021. https://doi.org/10.1016/j.ijwd.2021.01.012

Abstract: The COVID-19 pandemic has seen a massive shift towards virtual living, with video-conferencing now a primary means of communication for both work and social events. Individuals are finding themselves staring at their own video reflection often for hours a day, scrutinizing a distorted image on screen and developing a negative self-perception. This survey study of over 100 board-certified dermatologists across the country elucidates a new problem of “Zoom Dysmorphia” where patients are seeking cosmetic procedures in order to improve their distorted appearance on video-conferencing calls.

Discussion:

Despite the COVID-19 pandemic limiting in-person office visits and stalling many elective procedures, dermatology cosmetic consults are on the rise relative to pre-pandemic times. With people now spending record amounts of time on virtual platforms seeing their virtual image, they are becoming more critical of their features and inquiring about cosmetic improvements. In this survey study of over 100 board certified dermatologists from across the country, over 50% indicated a relative rise in cosmetic consultations within their practices despite the state of the pandemic (Figure 1). Even more notable is that 86% of respondents report their patients are referencing video-conferencing as a reason for their new cosmetic concerns (Figure 2). Other studies have noted similar results, with one recent survey of the general public showing that of those who previously did not have an interest in facial cosmetic treatments, 40% now plan to pursue treatments based on concerns from their video-conferencing appearance alone (Cristel et al, 2020).

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According to surveyed dermatologists, neuromodulating agents such as Botox and Dysport, filler injections, and laser treatments were noted as the most frequently requested cosmetic procedures reaching their offices. In a time where more invasive aesthetic surgical procedures are restricted for concern of unnecessary virus spread, higher interest in minimally invasive procedures is expected. Patients appear to be the most concerned with regions from the neck up, most notably the forehead/glabella, eyes, neck, and hair. Specific concerns include upper face wrinkles, circles/bags under the eyes, dark spots, and neck sagging (Figure 3). Concerns below the neck were much less frequently reported, with body contouring and cellulite treatments noted to be on the rise by less than 10% of surveyed dermatologists. Interestingly, an analysis of Google search trends during the COVID-19 pandemic showed an increase in search terms such as “acne” and “hair loss” (Kutlu, 2020). Authors of that analysis attributed the search trend to the association of acne and hair loss with anxiety and depression, psychological conditions weighing heavily on many quarantined individuals. Numerous other factors may also play a role, such as mask-occlusion causing acne mechanica as well as the association of telogen effluvium with COVID-19 infection (add citation). Our results show the trend may also be due to the fact that people are now becoming more aware of their appearance, scrutinizing their features from the neck up as they see their video reflection daily.

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Of concern to providers is that patients are requesting more procedures as a result of increased video-conferencing, which has been shown in the literature to reflect a distorted facial appearance. This is causing concern for aspects of appearance that may not truly require correction or to the extent that the patient fears. Of even greater concern is the mental health aspect that is uncovered in this study, that 82.7% of surveyed providers report their patients feeling more displeased with their appearance now than ever before (Figure 4). The psychological response to the COVID-19 pandemic has been understandably negative, but why are patients so unhappy particularly with their appearance on Zoom? Studies have shown that those with higher levels of engagement on social media have higher levels of body dissatisfaction and depression (Shome et al., 2020, Woods and Scott, 2016). For example, one study showed that when instructed to upload photos to social media, most participants noted a decrease in self-confidence and an increase in desire to undergo cosmetic surgery (Shome et al,2020). Although Zoom may not be considered social media, it does necessitate that people expose themselves in a virtual manner for which many are unaccustomed. Zoom adds an additional level of complexity by displaying one’s emotions in real-time, leading us to watch ourselves speak and react to others, which may cause a person to notice expression lines and wrinkles which they are not used to seeing while looking in the mirror. Additionally, one’s reflection is displayed side by side to other members of the call, allowing for easy comparison and self-judgment.

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The distorting effects of webcams could also contribute to the observed trend in cosmetic consults, as patients remain unaware of how cameras can distort and degrade video quality and inaccurately represent one’s true appearance. For instance, camera angle and focal distance make a difference in the image that appears on screen. A 2018 study found that a portrait taken from 12 inches away increases perceived nose size by about 30% when compared to an image taken at 5 feet (Ward et al, 2018). With webcams often recording at shorter focal lengths, the result is an overall more rounded face, wider set eyes, broader nose, taller forehead and disappearing ears obscured by cheeks (Trebicky et al, 2016). Moreover, video calls condense life into a 2D image, leading a graded shadow along a curved surface such as the nose to appear as a flat, darkened area instead (Lu and Bartlett, 2016). This illusion may exacerbate the appearance of facial dark spots and bring unnecessary concern to users.

Combining these elements with the current trends in cosmetic consults, it is apparent that Zoom, although a useful and necessary tool for maintaining productivity during quarantine, has introduced individuals to an unfamiliar virtual environment. This increased self-exposure and distorted image on screen may be causing patients to develop thoughts of BDD, with a tendency to be preoccupied with a real or imagined physical defects and causing functional impairment. These patients often seek cosmetic procedures to improve their perceived appearance, yet are rarely satisfied with the results, ending up in a cycle of self-dissatisfaction. Approximately 9-14% of patients in general dermatology clinics have a diagnosis of BDD, and within the cosmetic surgery setting, the prevalence is thought to be even higher (Vashi, 2016). With anxiety disorders on the rise due to factors related to the pandemic, BDD is an important consideration in patient evaluations. Elucidating the limitations of webcams and examining the trends of this new virtual world, we can better serve our patients by screening for such dysmorphic thoughts and connecting patients with appropriate counseling. Prior to the pandemic, patients presented to their aesthetic physicians hoping to look more like their filtered Snapchat selfies; we have now entered an era in which people are forced to confront a distorted and often unflattering rendition of themselves for hours a day on Zoom, distorted reflection, promoting the phenomenon of “Zoom Dysmorphia.”

We found that surprisingly, children as young as age 4 viewed morally bad people as less happy than morally good people, even if the characters all have positive subjective states

Yang, F., Knobe, J., & Dunham, Y. (2021). Happiness is from the soul: The nature and origins of our happiness concept. Journal of Experimental Psychology: General, 150(2), 276–288, Jan 2021. https://doi.org/10.1037/xge0000790

Rolf Degen's take: Rolf Degen on Twitter: "Even at young age, children proceed from the assumption that bad people are not happy. https://t.co/ae5VyZyma4 https://t.co/Ky4uX2sLbc"

Abstract: What is happiness? Is happiness about feeling good or about being good? Across 5 studies, we explored the nature and origins of our happiness concept developmentally and cross-linguistically. We found that surprisingly, children as young as age 4 viewed morally bad people as less happy than morally good people, even if the characters all have positive subjective states (Study 1). Moral character did not affect attributions of physical traits (Study 2) and was more powerfully weighted than subjective states in attributions of happiness (Study 3). Moreover, moral character but not intelligence influenced children and adults’ happiness attributions (Study 4). Finally, Chinese people responded similarly when attributing happiness with 2 words, despite one (“Gao Xing”) being substantially more descriptive than the other (“Kuai Le”) (Study 5). Therefore, we found that moral judgment plays a relatively unique role in happiness attributions, which is surprisingly early emerging and largely independent of linguistic and cultural influences, and thus likely reflects a fundamental cognitive feature of the mind.

We investigate the often-stated, but disputed claim in the political science and political communication literature that increasing media choice widens inequalities in political knowledge, & find little support

Increased Media Choice and Political Knowledge Gaps: A Comparative Longitudinal Study of 18 Established Democracies 1995-2015. Atle Haugsgjerd, Stine Hesstvedt, & Rune Karlsen. Political Communication, Jan 25 2021. https://doi.org/10.1080/10584609.2020.1868633

ABSTRACT: We investigate the often-stated, but disputed claim in the political science and political communication literature that increasing media choice widens inequalities in political knowledge. The assumption is that in a high-choice media environment, the politically interested will consume more news while the uninterested will avoid such content, leading, in turn, to widening differences in political knowledge. Although previous studies show that high media choice increases political knowledge gaps in the United States, comparative longitudinal evidence is currently lacking. To fill this gap, we draw on data from four rounds of the Comparative Study of Electoral Systems. Overall, we do not find general support for the high-choice knowledge gap thesis. In most countries, there is no indication that inequality in political knowledge has increased over time. Building on recent insights from political communication research, we question key assumptions of the high choice knowledge gap thesis.

KEYWORDS: Political knowledgehigh choiceknowledge gapsincreasing political knowledge inequalitynews avoidance

Discussion and Conclusion

Overall, we do not find support for the high-choice knowledge gap thesis as a general theory. Contrary to the high-choice thesis, our analyses provided little evidence that inequality in political knowledge increases over time, and increased Internet use and broadband access had no effect on knowledge inequality. Further, longitudinal analysis of Norwegian data showed that knowledge was not increasingly stratified by political interest and education from 1997 to 2017. The comparative multilevel analysis also indicated that education has not become a stronger predictor of political knowledge over time or in contexts with high levels of Internet use or broadband access. Overall, the results thus suggest that although increased media choice facilitates increasing personalization of media consumption, this does not necessarily mean that the information-poor escape the constant flow of political news coverage and that knowledge inequalities in high-choice societies increase accordingly.

In the theoretical section, we noted newer strands of research that help to clarify these results. In particular, we highlighted the “infrastructural” view of media use, suggesting that individual preferences are less pivotal than assumed in arguing for the high-choice knowledge gap (e.g., Webster, 2014, pp. 23–48). Preferences are constrained by channel repertoires (Taneja et al., 2012) and situational factors (Wonneberger et al., 2011), as well as by the architecture of the digital political communication system (Taneja et al., 2018). On this view, traditional and digital media infrastructures limit the extent to which people (willingly or unwillingly) avoid news about politics and current affairs. Indeed, there is empirical evidence that the inadvertent audience has not disappeared (e.g., Fletcher & Nielsen, 2018; Thorson, 2020), and the longitudinal evidence for increasing news avoidance is inconclusive (Karlsen et al., 2020; Strömbäck et al., 2013). In short, more choice does not necessarily lead to more news avoidance and increasing knowledge gaps.

In this article, we have focused mainly on the development of knowledge about party positions. As it reflects voters’ basic understanding of the political system, this form of knowledge is essential to the ability to navigate the political landscape, and it is reassuring to find that inequalities do not increase as media platforms multiply. Our analysis of factual knowledge questions – which capture citizens’ dynamic knowledge about current issues covered by the media – yielded largely similar results. However, we would like to emphasize that we do not consider these results conclusive in terms of how increasing media choice affects inequalities in political knowledge. Future research should explore inequalities in different types of political knowledge, including policy knowledge as well as more general political information (cf. Barabas et al., 2014). The lack of variables on media use is also an important shortcoming in the present study. The opportunity to link media consumption and political knowledge would have offered a more comprehensive picture of the impact of media preferences in societies transitioning to high choice. Unfortunately, the lack of relevant data makes this type of longitudinal study difficult to conduct. Panel-studies that include content preferences and media use should, however, provide valuable insights. Richer and more detailed measures of media system fragmentation would also be highly valuable. Nevertheless, we believe the present study provides a good point of departure for such future work.

Another important task for future research is to dig deeper into how specific groups react to the changing media environment. In their seminal work, Tichenor et al. (1970, pp. 159–60) argued that when mass media information increases, “segments of the population with higher socioeconomic status tend to acquire this information at a faster rate than the lower status segments, so that the gap in knowledge between these segments tends to increase rather than decrease”. In contrast to the high-choice thesis, they contended that when the relative difference between the information-rich and the information-poor increases, the latter do not necessarily become less knowledgeable (Tichenor et al., 1970, p. 160). In line with this proposition, we found that political knowledge in most countries is more or less stable for the lowest quintile of citizens. 22 One possible reason for this pattern is that a preference for one genre rather than another (e.g., entertainment over news) can lead to increased consumption of the preferred genre without reducing consumption of the other (e.g., Webster, 2014). Time spent on media consumption is not necessarily a zero-sum game, and different types of media consumption might increase simultaneously (Newell et al., 2008). A reformulation of the high-choice knowledge gap thesis along these lines may provide a better understanding of contemporary political knowledge dynamics. It could also serve to guide future research on how people with little political interest and resources relate to and learn from the different types of news made available by current digital media systems.

Although our findings do not support the high-choice thesis in general, we did find some evidence of increasing inequality in the United States. This result related mainly to information-poor citizens becoming less knowledgeable. On the one hand, the finding aligns well with Prior’s seminal US studies (2005, 2007), as well as with previous studies of media systems and political knowledge that report striking differences between the United States and all other countries (e.g., Aalberg & Curran, 2012). On the other hand, these results must be treated with caution. Most importantly, our main dependent variable relies on citizens’ placement of parties on the left-right scale, which is a less familiar concept in the United States compared to other countries in our sample. Our analysis of factual knowledge questions did not identify a similar increase in inequalities. One interpretation of these different results relates to affective polarization processes in the US. Increasing media fragmentation in the US is intertwined with political polarization of the media, and since the turn of this century, negative sentiments toward opposing parties and their voters have grown considerably (Hetherington & Rudolph. 2018). Hence, due to partisan media, a strong focus on misinformation and fake news (e.g., Allcott & Gentzkow, 2017; Lazer et al., 2018) and affective polarization in the electorate (Iyengar et al., 2019), voters might perceive parties as increasingly ideologically extreme, and therefore increasingly misplace these parties on the left right scale.

Overall, our results suggest that a high-choice media environment does not necessarily lead to a widening political knowledge divide between the information-poor and the information-rich. Although encouraging from a democratic perspective, this finding should nevertheless prompt us to think harder about how greater media choice influences media use, and in turn, political knowledge inequality. As the political communication systems of established democracies undergo rapid change, it becomes crucial to improve our understanding of these matters, both empirically and theoretically. This article identifies a number of avenues for future research in this regard. We should also keep in mind that for much of the study period, the choice was between television and radio channels, traditional newspapers, online text pages and low-quality online videos. The present media systems dominated by 24/7 on-demand and high-quality video content offer quite different choices. In this environment, news and current affairs must always compete with favorite television shows or movies. Perhaps the era of real choice has just begun?

Sometimes, individuals strategically avoid information to hold particular beliefs or to take certain actions—such as behaving selfishly—with lower image costs; more important are a desire to avoid interpersonal tradeoffs or bad news, & laziness

Information Avoidance and Image Concerns. Christine L. Exley & Judd B. Kessler. NBER Working Paper 28376, January 2021. DOI 10.3386/w28376. https://www.nber.org/papers/w28376

Abstract: A rich literature finds that individuals avoid information, even information that is instrumental to their choices. A common hypothesis posits that individuals strategically avoid information to hold particular beliefs or to take certain actions—such as behaving selfishly—with lower image costs. Building off of the classic “moral wiggle room” design, this paper provides the first direct test of whether individuals avoid information because of image concerns. We analyze data from 4,626 experimental subjects. We find that image concerns play a role in driving information avoidance, but a role that is substantially smaller than the common approach in the literature would suggest. The large majority (66% to 81%) of information avoidance remains when image concerns cannot drive avoidance. We find evidence for other reasons why individuals avoid information, such as a desire to avoid interpersonal tradeoffs, a desire to avoid bad news, laziness, inattention, and confusion.

On the worldviews of the new tech elite: A social group that shares particular views of the world, which in this case means meritocratic, missionary, and inconsistent democratic ideology

Brockmann H, Drews W, Torpey J (2021) A class for itself? On the worldviews of the new tech elite. PLoS ONE 16(1): e0244071. https://doi.org/10.1371/journal.pone.0244071

Abstract: The emergence of a new tech elite in Silicon Valley and beyond raises questions about the economic reach, political influence, and social importance of this group. How do these inordinately influential people think about the world and about our common future? In this paper, we test a) whether members of the tech elite share a common, meritocratic view of the world, b) whether they have a “mission” for the future, and c) how they view democracy as a political system. Our data set consists of information about the 100 richest people in the tech world, according to Forbes, and rests on their published pronouncements on Twitter, as well as on their statements on the websites of their philanthropic endeavors. Automated “bag-of-words” text and sentiment analyses reveal that the tech elite has a more meritocratic view of the world than the general US Twitter-using population. The tech elite also frequently promise to “make the world a better place,” but they do not differ from other extremely wealthy people in this respect. However, their relationship to democracy is contradictory. Based on these results, we conclude that the tech elite may be thought of as a “class for itself” in Marx’s sense—a social group that shares particular views of the world, which in this case means meritocratic, missionary, and inconsistent democratic ideology.

Discussion

The rapid dissemination of digital technologies catapulted the founders of large IT enterprises into the top ranks of wealth and power. Given their position of influence in contemporary and (probably) future societies, this paper explores the worldviews of the new tech elite. We focus on the richest 100 persons in tech identified by Forbes magazine. Elite research usually suffers from low to no response rates. Targeting a super-elite exacerbates the problem. In fact, we approached everyone from our list but got only one face-to-face interview. To circumnavigate this problematic access to data, we explored the digital traces of tech elite entrepreneurs to assess their distinctiveness relative to the general population and to other elites. To our knowledge, this is the first attempt to study tech elites with digitized text data. Social scientists have started to use social media data to scale ideologies of political elites, or citizens, but not of economic leaders [e.g., 84].

Specifically, we examine the worldviews of the IT tech elite with a simple “bag of words” approach. We hypothesized first that, as products of a society with strong meritocratic beliefs and frequently of elite institutions of higher education, the tech elite would see this world and future worlds in meritocratic terms. Our analysis of a large sample of their statements on Twitter (Tweets), relative to the general US Twitter-using population, indeed found that the tech elite tend to speak more frequently about merit-related topics and to more frequently use words that bespeak achievement-related concerns. They also speak more expansively and positively about the future than the general Twitter-using population. Our first hypothesis, proposing that the tech elite would see the world and the future in meritocratic, self-affirming, or even self-serving terms, was thus confirmed.

This paper provides a basis to directly test whether and how meritocratic beliefs translate into declining social mobility or even social closure in future research. A coherent, divisive and legitimizing social ideology is often seen as an important ingredient for class awareness and self-interested behavior [85]. “Career Funneling” at the most selective universities into tech jobs which are perceived as high status may provide a further explanation as to why tech clusters in Silicon Valley (re)produce a “class for itself” [e.g., 86].

Next, we hypothesized that the tech elite saw its endeavors in “entrepreneurial technoscience” as driven by a desire to “make the world a better place”—that is, that it is “mission-driven.” We tested this hypothesis by comparing the philanthropic statements of members of the tech elite vis-a-vis the Giving Pledge and websites of their own foundations. In addition to comparing across elites, we compared age cohorts within the tech elite to see whether their ideas about “making the world a better place” and about philanthropy varied.

On this basis we found that the members of the tech elite were more likely than the other Pledgers to have an expansive and positive vision of philanthropic endeavor. The tech elite does, indeed, appear to have strong, positive sentiments toward the idea of “making the world a better place.” Is this a “religious” inclination? Insofar as one can say based on these data, the answer to this question is “no.” The tech elite in particular tended toward a more secular outlook. In addition, we found that the different age cohorts within the tech elite tended to stress different secular missions in regard to their philanthropic activities: the oldest, “hardware” generation emphasized “research”; the middle, “software” generation most often cited “school”; and the youngest, “internet” generation most frequently used the word “can,” a reflection perhaps of their youthful enthusiasm. In any case, educational and cultural missions aim to shape the public interest.

This leads to hypothesis 3, which examines the relationship of the tech elite to politics. It proposes that members of the elite have a contradictory relationship with democracy because market success and financial wealth should tend to entail worldviews and arguably activities (including philanthropic activities) that sidestep democratic representation. We found no statistically significant differences in whether or not the tech elite saw a positive relationship between power and money, or between power and democracy, as compared to the members of the US Twitter-using population. Yet, the tech elite denied that there is a positive connection between democracy and money, something that is logically inconsistent with the previous correlations and that is not shared by ordinary US Twitter users, who see the existence of a nexus between democracy and money.

Finally, we aim to determine directly whether the tech elite constitutes a “class for itself” in the sense that we can predict statistically whether a person is a member of the tech elite or not. Machine learning models indicate that we can do so quite accurately (> 80%). Hence, the tech elite appears to be more than simply a part of the capitalist class in the broad sense of sharing “ownership of the means of production.” Rather, members of the tech elite communicate similar worldviews and clearly form a distinct fraction of the capitalist class.

This study constitutes a first exploratory step in the analysis of the tech elite. We highlight three limitations that may inspire future research. First, we haven’t been able in this research to trace everybody from our sample on Twitter and on foundation websites. Twitter is a competitor to other social media platforms like Facebook, Snapchat, Google Techies or WeChat. It is also blocked in China. Also, there is a digital divide between younger and older tech entrepreneurs. The majority of our “hardware” cohort does not use Twitter. For these reasons, the results may be less robust for older members of the tech elite and for Chinese members. Still, we can account for this selectivity and reach higher “response rates” than conventional random samples in elite studies [e.g., 45].

Secondly, we cannot rule out that the Twitter accounts are managed by professional PR experts. Still, we have replicated the analysis with Tweets from non-tech members of the Giving Pledge and see systematic differences between both privileged groups, who can equally afford professional support. Thus, the tech elite communicates differently, and even if the tech elite employs professional support these people are presumably articulating the views of their wealthy clients.

Finally, our insights into the democratic worldviews of the tech elite remain limited. We do not know if the tech elite’s denial of a relationship between democracy and money is strategic communication or, in fact, their actual belief. Future research will have to explore this further. Social science research into social media use of political elites provides a promising roadmap for analyzing elite ideologies [e.g., 87, 88] and how they shape elite political behavior through donations and other exertions of financial power.

In conclusion, our research contributes to closing a research gap in societies with rising inequalities. We find that the 100 richest members of the tech world reveal distinctive attitudes that set them apart both from the general population and from other wealthy elites. As the companies they have created occupy a commanding position in the emerging tech-based economy, their views of our situation are likely to be of disproportionate significance. As a group, they are meritocratically inclined, concerned with the well-being of their fellow human beings, and relatively supportive of democratic society. Yet their position in a democratic system is contradictory: as a result of their enormous wealth, they have disproportionate influence over how discretionary income is spent. One need not be opposed to philanthropy to see that there is a problem here. Future research will have to address whether the attitudes of this unusual group change over time, and whether policies can be found to bring their opportunities to shape social outcomes in line with a democratic social order.

Consistently growing outside of the relationship in ways that are not shared with a romantic partner may reduce feelings of closeness and connection, and ultimately passion

Carswell, K. L., Muise, A., Harasymchuk, C., Horne, R. M., Visserman, M. L., & Impett, E. A. (2021). Growing desire or growing apart? Consequences of personal self-expansion for romantic passion. Journal of Personality and Social Psychology, Jan 2021. https://doi.org/10.1037/pspi0000357

Abstract: Romantic passion represents one of the most fragile and elusive elements of relationship quality but one that is increasingly valued and tied to relationship and individual well-being. We provide the first examination of whether experiencing personal self-expansion—positive self-change and personal growth without a romantic partner—is a critical predictor of passion. Previous research has almost exclusively examined the consequences of couples’ sharing novel experiences (i.e., relational self-expansion) on romantic relationships. Instead, the consequences of personal self-expansion for romantic relationships remain largely unexamined even though most positive self-growth may occur without a romantic partner (e.g., at work). We investigated the consequences of personal self-expansion for passion in three studies including two 21-day experience sampling studies of community couples and a study in a context likely to elicit heightened personal self-expansion: during job relocation. Within-person increases in daily personal self-expansion were associated with greater passion through greater positive emotions (Studies 1 and 2). In contrast, high between-person levels of personal self-expansion were associated with lower passion through lower levels of intimacy, suggesting that individuals may drift apart from their partners with more chronic personal self-expansion (Studies 1, 2, and 3). That is, consistently growing outside of the relationship in ways that are not shared with a romantic partner may reduce feelings of closeness and connection, and ultimately passion. Results also suggest that chronic personal self-expansion may be a double-edged sword for individual well-being, simultaneously associated with lower passion, but greater fulfillment of competence needs. Results controlled for relational self-expansion and time together.

Indonesia: Women in self-choice marriages had more offspring (controlling for marriage duration) than woman in arranged marriages

Arranged Marriage, Partner Traits and Parental Investment: Examining the Reproductive Compensation Hypothesis in Humans. Annemarie M. Hasnain. Master Thesis, Boise State Univ, August 5 2020. https://scholarworks.boisestate.edu/cgi/viewcontent.cgi?article=2873&context=td

Abstract: Both sexes choose mates based on qualities that will enhance offspring viability and quality. In some cases individuals are forced to reproduce with less desirable mates which has been shown to result in lower quality offspring. The Reproductive Compensation Hypothesis (RCH) predicts that parents who mate under constraint will increase their reproductive effort and investment in offspring to compensate for lowered offspring viability. Evidence for the RCH has been found in several animal species; however it has not been examined in humans. One possible type of mate choice constraint in humans is that of arranged marriage in which parents or others choose mates for individuals. In order to test the RCH, I examine whether there are differences in both partner traits between women in arranged marriages and those in self-choice marriages, and differences in parental investment between women in arranged and self-choice marriages using data from the Indonesian Family Life Survey. Except for husband’s education level, no differences were found in mate characteristics between the husbands of women in self-choice marriages and those in arranged marriages. Marriage type did not significantly correlate with parental investment except for number of live births. This correlation, however, was not in the predicated direction. Results show that women in self-choice marriages had more offspring (controlling for marriage duration) than woman in arranged marriages. It is possible that arranged marriage is not a true constraint on mate choice or that parental investment measures used in this study need to be more refined.

Sex Differences in Spatial Activity & Anxiety Levels, COVID-19: Women minimize their mobility & outdoor contacts; men's wariness was less associated with the novel virus threat, but to potentical economic losses

Sex Differences in Spatial Activity and Anxiety Levels in the COVID-19 Pandemic from Evolutionary Perspective. Olga Semenova, Julia Apalkova and Marina Butovskaya. Sustainability 2021, 13(3), 1110; January 21 2021. https://doi.org/10.3390/su13031110

Abstract: Despite the enforced lockdown regime in late March 2019 in Russia, the phenomenon of the continued virus spreading highlighted the importance of studies investigating the range of biosocial attributes and spectrum of individual motivations underlying the permanent presence of the substantial level of spatial activity. For this matter, we conducted a set of surveys between March and June 2020 (N = 492). We found that an individual’s health attitude is the most consistent factor explaining mobility differences. However, our data suggested that wariness largely determines adequate health attitudes; hence, a higher level of wariness indirectly reduced individual mobility. Comparative analysis revealed the critical biosocial differences between the two sexes, potentially rooted in the human evolutionary past. Females were predisposed to express more wariness in the face of new environmental risks; therefore, they minimize their mobility and outdoor contacts. In contrast to them, the general level of spatial activity reported by males was significantly higher. Wariness in the males’ sample was less associated with the novel virus threat, but to a great extent, it was predicted by the potential economic losses variable. These findings correspond to the evolutionary predictions of sexual specialization and the division of family roles.

Keywords: pandemic; sexual selection; spatial activity; risk-taking behavior; anxiety; health attitude