Sunday, February 28, 2021

Rolf Degen summarizing... Atheism is as much a part of the original state of the human mind as is belief in god

New Cognitive and Cultural Evolutionary Perspectives on Atheism. Thomas J. Coleman III, Kyle Messick, Valerie van Mulukom. In The Routledge Handbook of Evolutionary Approaches to Religion, January 2021. https://psyarxiv.com/ze5mv

Rolf Degen's take: Atheism is as much a part of the original state of the human mind as is belief in god

1. Introduction 

Atheism is a topic that has only recently attracted the attention of evolutionarily minded scholars. In this chapter, we will present the current issues with the study of atheism from an evolutionary perspective. 

Attempts to place atheism into an evolutionary framework have followed a methodological direction that, we argue, may have stymied inquiry thus far: the idea that the best starting place to develop an explanation of atheism is by building on explanations of theism (e.g., Barrett, 2004, 2010; Bering, 2002, 2010; Johnson, 2012; Kalkman, 2013; Norenzayan & Gervais, 2013; Mercier, Krammer, & Shariff, 2018). Under this view, atheism is situated at the low end of a psychological continuum of religiosity and/or is a result of malfunctioning cognitive capacities that, if working normally, would produce religious belief (cf. Caldwell-Harris, 2012; Weekes-Shackleford & Shackleford, 2012). Thus, this stance assumes a priori that humans evolved to become homo religiosus (the idea that humans are inherently god believing creatures) and implies that atheists are either psychological deviants or closet believers (Coleman & Messick, 2019; Shook, 2017). Moreover, this view entails the idea that atheism is an empty signifier and individual atheists are therefore defined by the beliefs or psychological processes that they lack, rather than the ones they have. The problem for this perspective is: How can the absence of something(s) be linked to our evolved psychological endowment? Under this view, the possibility that atheism might be produced, in-part, by its own set of mechanisms (and not just a reversal of “theistic cognition”), or be evolutionary adaptive, would remain unexplored. 

In this chapter, we explore atheism—in its broadest sense—as a product of our evolved species-typical psychology. We build on past scholarship and research, whilst also taking this in several new directions. First, we argue that atheism can be defined in “positive” terms, and then we link this definition to evolved psychological mechanisms. This allows us to explore the phylogeny of atheism, including the possibility that our ancestors exhibited atheistic beliefs. Second, informed by evolutionary psychology, we review the ontogeny of atheism, as well as discussing the development of theistic cognition. Third, we review several adaptive and nonadaptive evolutionary hypotheses for atheism developed by Johnson (2012) and use new evidence to argue in favor of atheism as an adaptive worldview. Fourth, we reflect on the limited ability of existing biophysiological studies to inform current understandings of atheism. In closing, we further extrapolate advantages of this approach, as well as some potential limitations, and discuss future directions for research. Our overall aim is to spark renewed discussion for possible evolutionary perspectives on atheism.


6. The functionally adaptive explanation for atheism

In traditional evolutionary arguments, functional and adaptive traits are carried down to future generations through natural selection (or analogous processes operating at the cultural level; Laland & Brown, 2011). Adaptive traits help with the survival and success of a species. Citing numerous studies suggesting religiosity confers multiple beneficial outcomes, ranging from coping with stress, increasing social relatedness and facilitating social coordination, reducing death anxiety, and increasing psychological well-being and meaning in life, a group of researchers has consistently argued that religion should be considered an adaptive trait (Johnson, 2012, 2016; Laurin, 2017; Norenzayan et al., 2016; Sosis & Alcorta, 2003; Wilson, 2002; Wood & Shaver, 2018)4. Far less attention however has been given to the possibility that atheism might be similarly adaptive (although see Szocik & Messick, 2020; Messick, Szocik, & Langston, 2019; Shults, 2018), and it was not until recently that evidence has accumulated in support of this position however, through a broader set of mechanisms than what is found with religion.

Dominic Johnson (2012) has proposed ten evolutionary hypotheses for the emergence of atheism. There are three non-adaptive hypotheses (no variation, natural variation, unnatural variation), that posit that there either are no real atheists (because everyone has some level of implicit or explicit belief in supernatural agency), or that atheists are a result of a natural distribution of belief, or that a variety of life circumstances could result in the emergence of atheism. The latter two hypotheses essentially outline atheism as being a byproduct, and thus, not as adaptive. The remaining seven explanations proposed by Johnson (2012), he suggests, are adaptive at either the individual or group level.

note 4 There are several reasons to be skeptical of religion as an adaptation, ranging from religion’s incoherence as a trait that could be selected (Richerson & Newson, 2008) to an overestimation of “the degree to which ostensive benefits would be sufficient to permit natural selection to systematically favor religious variants over nonreligious ones” (Kirkpatrick, 2006, p. 167).

One of the adaptive hypotheses is the exploitation hypothesis. This hypothesis claims that atheism is adaptive for the individuals only when they are in a position of power. This hypothesis builds off Karl Marx’s claim that religion functions as a tool for the elite to control “the masses,” as the figureheads of a society can exploit religious belief among their denizens to increase their own power, wealth, and status. In its strongest form, this hypothesis assumes that the majority of atheists were or are socio-political elites and have made a “Machiavellian calculation” (p. 59) that their own level of belief only matters to the extent that they can exercise control over their lower status religious adherents. The ecological contingency hypothesis also posits that atheism, like theism, can be adaptive at the individual level, but only in certain settings, as some traits are environment-and context-dependent. For example, this hypothesis assumes that atheists are disposed to a type of rationalist thinking that is more likely to flourish in times of abundance and peace, and that the adaptive components of religious beliefs are costly and more likely to flourish in times of scarcity and warfare. The atheism is a religion hypothesis views atheism as being functionally equivalent to religion. This hypothesis assumes that atheism, as a shared belief and collection of values, can confer the functional benefits associated with religion. This hypothesis will be expanded upon further in the next section. The final individually adaptive hypothesis is the frequency dependency hypothesis. This hypothesis builds off evolutionary game theory, which in turn posits that coexisting traits, such as belief and nonbelief, can be beneficial for one another through competition. In other words, this hypothesis assumes that atheists can receive the benefits of religion without believing, as long as atheism is not overly common.

Finally, Johnson proposes three theories that he claims can explain how atheism can be adaptive at the group level: 1) as a catalyst for the facilitation of the adaptive advantages of belief, 2) through serving to bolster religious belief as a reaction to skepticism, and 3) through atheists being skeptical of religious doctrine which results in the religious ‘toning down’ their doctrine to make it seemingly more credible. As Johnson (see 2012, p. 65) himself notes, these explanations outline atheism as being beneficial for believers, but without clear benefits to the atheists themselves. In other words, the existence of individual atheists is a non-adaptive (but not maladaptive) by-product of religion having been selected at the group level. It is not clear why Johnson labels these as adaptive hypotheses for the group-level selection of atheists, as the position seems to confuse what he argues is selected at the group-level (i.e., religion) for what he argues is the adaptive benefits of atheism at the individual level (i.e., rationality).

Of the ten theories offered by Johnson (2012), we argue that explanations of atheism as a fluke, byproduct of, or bolster for religious adaptations do not sufficiently account for why atheism persists and how it functions. The next section will further outline two perspectives to support this idea: We will argue first that atheism can be adaptive in ways similar to religious belief, and secondly that atheism becomes more prominent when the adaptiveness of religious belief becomes obsolete or redundant through secular societal mechanisms. Both explanations give credence to the functional/adaptive explanation for why atheism exists while recognizing atheism as a phenomenon that is comparable to religion, rather than a side-effect of it. 

The average American user is increasingly integrating politics into social identities, adding political words to describe themselves; they are more likely to describe themselves by their political affiliation than their religious one

Using Twitter Bios to Measure Changes in Self-Identity: Are Americans Defining Themselves More Politically Over Time? Nick Rogers; Jason J. Jones. Journal of Social Computing, Volume 2, Issue 1, March 2021), DOI 10.23919/JSC.2021.0002

Abstract: Are Americans weaving their political views more tightly into the fabric of their self-identity over time? If so, then we might expect partisan disagreements to continue becoming more emotional, tribal, and intractable. Much recent scholarship has speculated that this politicization of Americans' identity is occurring, but there has been little compelling attempt to quantify the phenomenon, largely because the concept of identity is notoriously difficult to measure. We introduce here a methodology, Longitudinal Online Profile Sampling (LOPS), which affords quantifiable insights into the way individuals amend their identity over time. Using this method, we analyze millions of “bios” on the microblogging site Twitter over a 4-year span, and conclude that the average American user is increasingly integrating politics into their social identity. Americans on the site are adding political words to their bios at a higher rate than any other category of words we measured, and are now more likely to describe themselves by their political affiliation than their religious affiliation. The data suggest that this is due to both cohort and individual-level effects.

6 Discussion and Conclusion

To the extent that a person’s Twitter bio is a valid measure of their sense of identity, Americans are defining themselves more saliently by their politics. This is important, because the formation of a group identity tends to change individual behavior in powerful ways. Through the phenomenon of “group polarization”, people who begin with vague, weakly-held opinions tend to become more radical and dogmatic when put into like-minded groups. They also quickly develop hostile feelings towards outgroup members. Rational, evidence-based dissent tends to lose effectiveness within the groups, and in fact make group members even more invested in their original opinion. To what may this increase in prevalence of political group identity be attributed? Is a more politicallyengaged set of people joining Twitter for the first time, making the aggregate site more political than it was in prior years? Or are existing Twitter users amending their profiles to add a political keyword where formerly there were none? In other words, is this a generational/cohort effect, or is change occurring within individual identities? As our data reveal: both. Comparison between the cross-sectional and the longitudinal data suggests that (1) new entrants are more politically-oriented than the older participants they are joining or replacing, and also (2) individual people are amending their identities to be more political. This dual nature of the phenomenon, as well as the effects it is likely to produce, portend a national polarization that is more likely to deepen than subside, in the short term. As Americans define themselves increasingly by their political allegiances, their feelings towards political “others” can be expected to become more negative, and debate on matters of policy will become more emotional and intractable. Traditionally, a solution to the problem of tribalism has been found in the concept of “superordinate goals”. Rival groups can put aside their perceived zerosum differences when presented with a shared obstacle that requires cooperation to surmount. In the Robbers’ Cave experiment, the Rattlers and Eagles were able to work together and even form intergroup friendships, once they were presented with obstacles that required cooperation for shared benefit[37]. Particular to our political context, some experimental research has suggested that priming a national identity (American) can mitigate partisan bias[38]. The attacks of September 11, 2011, for example, led to a period of bipartisan focus on international terrorism. Yet in the current political climate, such agreed-upon goals seem rare. Democrats and Republicans seem to diagnose distinct social maladies from each other, unable to even agree on shared definitions of problems.

Limitations and future inquiry.

Although we believe our method provides a useful, digital-age measure of individual identity that is similar to the seminal Twenty Statements Test, there are imperfections worth noting. First is the potential influence of “bots”. It is wellestablished that Russian intelligence sought in 2016, and continues to seek, to influence American political discourse through the creation of social media accounts that pose as American users and spread divisive (and often fabricated) political content[39]. It is conceivable that our documented increase in prevalence of political keywords in bios is partially attributable to a growing number of these bots. However, our best evidence suggests any such influence is minimal. To investigate this possibility we tested random subsamples of our data using “Botometer”, an automated tool to detect automated “bot” accounts. Almost all accounts received low scores. The mean for accounts in the longitudinal sample was 0.6 on a scale of 0 (probably not a bot) to 5 (probably a bot). The growth rate of botlike accounts fluctuated across our study period and could not account for the increases in political identity reported here. A full account of this analysis is included as the Appendix. A second concern: Are our findings generalizable to the American general public, or is the politicization specific to Twitter users? To be sure, a sample of Twitter users is not the same as a random sample of Americans. In a recent study by Pew Research Genter[40], Twitter users are discovered to be younger, wealthier, and more educated than the United States at large. They are also modestly more liberal and more likely to say that voted in the last election. So it is conceivable that Twitter users are also more likely to adopt political identities than the general population. More data would be necessary to resolve this ambiguity. But we think that a general politicization of social identity is consistent with the other measures of politicization that we referenced in Section 1—voter turnout, affective polarization, cultural sorting, and so on. Further, our sampling method samples tweets rather than users. Users who do not use tweets—who may have an account only to receive information or direct message—are thus not observed. These users may be systematically different from our sample of users who do use tweets, and the present method cannot speak to whether their self-identification is changing or not. A third issue is the construction of our lists of keywords. We were sensitive to the possibility that certain “trendy” keywords could increase in prevalence not because individuals are defining themselves more politically, but rather because the keywords themselves are becoming more popular and supplanting “outdated” keywords that are not in our lists. For example, a hypothetical Twitter user might have had an Obamasupportive “Yes We Can” phrase in their bio in 2015, but swapped it out in 2016 for a “Nasty Woman” reference to Hillary Clinton. Because the former phrase is not in our list, and the latter phrase is, our method would give the misleading impression that the user had “politicized” their bios, when in fact it was political all along. We considered a number of methods that might limit the amount of subjectivity of that process. We searched for an adequate pre-existing keyword set, to no compelling avail. We analyzed the Twitter bios of several dozens of popular political figures, to see what descriptors they commonly employed. To our surprise, these individuals rarely used words that were even implicitly partisan, in their bios . We contemplated various Natural Language Processing techniques, to obtain frequently-used words on political hotbeds such as Reddit’s r/politics subreddit. But ultimately we concluded that the utility of such methods would be outweighed by the drawbacks and complications. Future research may build upon these results by constructing more comprehensive (or selective) banks of keywords. It would also be fruitful to expand upon these descriptive data and incorporate more layered analyses. With demographic information on our Twitter users, for example, we could conduct models to determine which characteristics are most correlated with changes in political identity. We could also analyze the users’ tweets over time (rather than merely their bios), and analyze what sorts of rhetoric tends to portend or reflect a recent change of identity. Continued inquiry on the matter is important: It is crucial to understand the dynamics underlying American political polarization. The stability of a people is dependent on some sense of unifying solidarity. Without it, order is imperiled and chaos invited.

 

Individual Valuing of Social Equality in Political and Personal Relationships: We will sometimes prioritize equality over competing values, but the weight of social equality diminishes when moving from personal to political cases

Individual Valuing of Social Equality in Political and Personal Relationships. Ryan W. Davis & Jessica Preece. Review of Philosophy and Psychology, Feb 28 2021. https://rd.springer.com/article/10.1007/s13164-021-00527-8

Rolf Degen's take: Social equality matters more to people in their personal relationships than in the realm of politics

Abstract: Social egalitarianism holds that individuals ought to have equal power over outcomes within relationships. Egalitarian philosophers have argued for this ideal by appealing to (sometimes implicit) features of political society. This way of grounding the social egalitarian principle renders it dependent on empirical facts about political culture. In particular, egalitarians have argued that social equality matters to citizens in political relationships in a way analogous to the value of equality in a marriage. In this paper, we show how egalitarian philosophers are committed to psychological premises, and then illustrate how to test the social egalitarian’s empirical claims. Using a nationally representative survey experiment, we find that citizens will sometimes prioritize equality over competing values, but that the weight of social equality diminishes when moving from personal to political cases. These findings raise questions for thinking about how to explain the normative significance of social equality.


Recent research on sexual orientation and sexual fluidity illustrates distinctions among subtypes of same-gender sexuality (such as mostly-heterosexuality, bisexuality, and exclusive same-gender experience)

The New Genetic Evidence on Same-Gender Sexuality: Implications for Sexual Fluidity and Multiple Forms of Sexual Diversity

The New Genetic Evidence on Same-Gender Sexuality: Implications for Sexual Fluidity and Multiple Forms of Sexual Diversity. Lisa M. Diamond. The Journal of Sex Research, Feb 23 2021, https://doi.org/10.1080/00224499.2021.1879721

h/t David Schmitt: genes associated with ever engaging in same-gender sexual behavior differed from the genes associated with one’s relative proportion of same-gender to other-gender behavior...findings speak to distinctions among subtypes of same-gender sexuality

Abstrct: In September of 2019, the largest-ever (N = 477,522) genome-wide-association study of same-gender sexuality was published in Science. The primary finding was that multiple genes are significantly associated with ever engaging in same-gender sexual behavior, accounting for between 8–25% of variance in this outcome. Yet an additional finding of this study, which received less attention, has more potential to transform our current understanding of same-gender sexuality: Specifically, the genes associated with ever engaging in same-gender sexual behavior differed from the genes associated with one’s relative proportion of same-gender to other-gender behavior. I review recent research on sexual orientation and sexual fluidity to illustrate how these findings speak to longstanding questions regarding distinctions among subtypes of same-gender sexuality (such as mostly-heterosexuality, bisexuality, and exclusive same-gender experience). I conclude by outlining directions for future research on the multiple causes and correlates of same-gender expression.


From 2016... Facial expressions and other behavioral responses to pleasant and unpleasant tastes in cats (Felis silvestris catus)

From 2016... Facial expressions and other behavioral responses to pleasant and unpleasant tastes in cats (Felis silvestris catus). Michaela Hanson et al. Applied Animal Behaviour Science, Volume 181, August 2016, Pages 129-136. https://doi.org/10.1016/j.applanim.2016.05.031

Rolf Degen's take: Science has also documented the “pleasure” face in cats, a relaxed expression with the eyes half closed

Highlights

• Cats display distinct facial expressions to pleasant and unpleasant tastes.

• No masking effect of a pleasant taste on an unpleasant taste was observed.

• Behavioral responses may be more informative than consumption data concerning taste.

Abstract: The goal of the present study was to assess how cats react to tastes previously reported to be preferred or avoided relative to water. To this end, the facial and behavioral reactions of 13 cats to different concentrations of l-Proline and quinine monohydrochloride (QHCl) as well as mixtures with different concentrations of the two substances were assessed using a two-bottle preference test of short duration. The cats were videotaped and the frequency and duration of different behaviors were analyzed. Significant differences in the cats’ behavior in response to the taste quality of the different solutions included, but were not limited to, Tongue Protrusions (p < 0.039), Mouth smacks (p = 0.008) and Nose Licks (p = 0.011) with four different stimulus concentrations. The cats responded to preferred taste by keeping their Eyes half-closed (p = 0.017) for significantly longer periods of time with four different stimulus concentrations compared to a water control. When encountering mixtures containing l-Proline and QHCl the cats performed Tongue protrusion gapes (p < 0.038) significantly more frequently with three different stimulus concentrations compared to an l-Proline control. A stepwise increase in the concentration of l-Proline from 5 mM to 500 mM in mixtures with 50 μM QHCl did not overcome the negative impact of the bitter taste on intake. The results of the present study suggest that behavioral responses provide an additional dimension and may be more informative than consumption data alone to assess whether cats perceive tastes as pleasant or unpleasant. Thus, the analysis of behavioral responses to different taste qualities may be a useful tool to assess and improve the acceptance of commercial food by cats.

Keywords: BehaviorCatFelis silvestris catusTaste reactivityl-ProlineQuinine monohydrochloride


Shoplift is common, we eat a few of the customer's fries when delivering food to them, we overcharge buyers in computer repairs or fish markets... New study: Field experiments on dishonesty and stealing

Field experiments on dishonesty and stealing: what have we learned in the last 40 years? Hugo S. Gomes, David P. Farrington, Ivy N. Defoe & Ângela Maia. Journal of Experimental Criminology, Feb 27 2021. https://rd.springer.com/article/10.1007/s11292-021-09459-w

Rolf Degen's take: The Price is not Right: In the five field experiments conducted so far, buyers were overcharged for the goods

Abstract

Objectives: Field experiments combine the benefits of the experimental method and the study of human behavior in real-life settings, providing high internal and external validity. This article aims to review the field experimental evidence on the causes of offending.

Methods: We carried out a systematic search for field experiments studying stealing or monetary dishonesty reported since 1979.

Results: The search process resulted in 60 field experiments conducted within multiple fields of study, mainly in economics and management, which were grouped into four categories: Fraudulent/ dishonest behavior, Stealing, Keeping money, and Shoplifting.

Conclusions: The reviewed studies provide a wide variety of methods and techniques that allow the real-world study of influences on offending and dishonest behavior. We hope that this summary will inspire criminologists to design and carry out realistic field experiments to test theories of offending, so that criminology can become an experimental science.


Study suggests that women may have greater cognitive reserve but faster cognitive decline than men, which could contribute to sex differences in late-life dementia

Sex Differences in Cognitive Decline Among US Adults. Deborah A. Levine et al. JAMA Netw Open. 2021;4(2):e210169. February 25, 2021, doi:10.1001/jamanetworkopen.2021.0169

h/t David Schmitt women have greater cognitive reserve but faster later-life cognitive decline than men. Evidence suggests that dementia incidence in Europe and the US has declined over the past 25 years, but declines were less in women than in men


Key Points

Question  Does the risk of cognitive decline among US adults vary by sex?

Findings  In this cohort study using pooled data from 26 088 participants, women, compared with men, had higher baseline performance in global cognition, executive function, and memory. Women, compared with men, had significantly faster declines in global cognition and executive function, but not memory.

Meaning  These findings suggest that women may have greater cognitive reserve but faster cognitive decline than men.

Abstract: Importance  Sex differences in dementia risk are unclear, but some studies have found greater risk for women.

Objective  To determine associations between sex and cognitive decline in order to better understand sex differences in dementia risk.

Design, Setting, and Participants  This cohort study used pooled analysis of individual participant data from 5 cohort studies for years 1971 to 2017: Atherosclerosis Risk in Communities Study, Coronary Artery Risk Development in Young Adults Study, Cardiovascular Health Study, Framingham Offspring Study, and Northern Manhattan Study. Linear mixed-effects models were used to estimate changes in each continuous cognitive outcome over time by sex. Data analysis was completed from March 2019 to October 2020.

Exposure  Sex.

Main Outcomes and Measures  The primary outcome was change in global cognition. Secondary outcomes were change in memory and executive function. Outcomes were standardized as t scores (mean [SD], 50 [10]); a 1-point difference represents a 0.1-SD difference in cognition.

Results  Among 34 349 participants, 26 088 who self-reported Black or White race, were free of stroke and dementia, and had covariate data at or before the first cognitive assessment were included for analysis. Median (interquartile range) follow-up was 7.9 (5.3-20.5) years. There were 11 775 (44.7%) men (median [interquartile range] age, 58 [51-66] years at first cognitive assessment; 2229 [18.9%] Black) and 14 313 women (median [interquartile range] age, 58 [51-67] years at first cognitive assessment; 3636 [25.4%] Black). Women had significantly higher baseline performance than men in global cognition (2.20 points higher; 95% CI, 2.04 to 2.35 points; P < .001), executive function (2.13 points higher; 95% CI, 1.98 to 2.29 points; P < .001), and memory (1.89 points higher; 95% CI, 1.72 to 2.06 points; P < .001). Compared with men, women had significantly faster declines in global cognition (−0.07 points/y faster; 95% CI, −0.08 to −0.05 points/y; P < .001) and executive function (−0.06 points/y faster; 95% CI, −0.07 to −0.05 points/y; P < .001). Men and women had similar declines in memory (−0.004 points/y faster; 95% CI, −0.023 to 0.014; P = .61).

Conclusions and Relevance  The results of this cohort study suggest that women may have greater cognitive reserve but faster cognitive decline than men, which could contribute to sex differences in late-life dementia.

Discussion

Among 26 088 individuals pooled from 5 prospective cohort studies, women had higher baseline performance than men in global cognition, executive function, and memory. Women, compared with men, had significantly faster declines in global cognition and executive function but not memory. These sex differences persisted after accounting for the influence of age, race, education, and cumulative mean BP.

Our results provide evidence suggesting that women have greater cognitive reserve but faster cognitive decline than men, independent of sex differences in cardiovascular risk factors and educational years. Previous studies31 have shown that women have higher initial scores on most types of cognitive tests except those measuring visuospatial ability. Few studies have examined sex differences in cognitive trajectories in population-based cohorts of cognitively normal Black and White individuals. A 2016 study31 of older adults in Baltimore (mean ages 64-70 years) found that men had steeper rates of decline on 4 of 12 cognitive tests (mental status [Mini Mental State Examination], perceptuomotor speed and integration, visual memory, and visuospatial ability) but no sex differences in declines on 8 of 12 cognitive tests (verbal learning and memory, object recognition and semantic retrieval, fluent language production, attention, working memory and set-shifting, perceptuomotor speed, and executive function). Similarly, we found no sex differences in verbal learning and memory; but, in contrast, we found that women had faster cognitive decline in global cognitive performance and executive function than men. These latter results might differ because we included young and middle-aged adults (mean age 58 years). Our findings are consistent with studies showing that women with mild cognitive impairment or AD have faster decline in global cognition than men.32,33

Our results of sex differences in cognitive decline were consistent across most cohorts. The potential reasons for the finding of slower cognitive decline in women in the Framingham Offspring Study are unclear and might be due to socioeconomic, life stress, geographic, and environmental factors as well as cohort differences in sampling strategies, eligibility criteria, and cognitive tests. Although our finding that declines in memory do not differ by sex are consistent with other studies,31 the finding is surprising because memory decline is the clinical hallmark of AD, a common cause of dementia,1 and some studies suggest that women have higher incidence of AD.4-6 One explanation is that women manifest verbal memory declines at more advanced stages of neurodegenerative disease than men owing to women having greater initial verbal memory scores and cognitive reserve.34,35 However, evidence against this explanation is that women in our study had faster declines in global cognition and executive function despite having higher initial levels of these measures. Another explanation is that the memory measure was less sensitive than the global cognition and executive function measures to detect sex differences in cognitive decline.

If the observed sex differences in declines in global cognition and executive function are causal, then they would be clinically significant, equivalent to 5 to 6 years of cognitive aging. The faster declines in mean cognitive scores associated with female sex can be related to approximate equivalent changes in years of brain or cognitive aging by calculating the ratio of slope coefficients for female sex and baseline age on cognition. Experts have defined clinically meaningful cognitive decline as a decline in cognitive function of 0.5 or more SDs from baseline cognitive scores.36-38 Women will reach the threshold of a 0.5-SD decrease from the baseline score 4.72 years faster than men for global cognition, 1.97 years faster for executive function, and 0.24 years faster for memory (eTable 7 in the Supplement). Based on this approach, sex differences in cognitive declines are clinically meaningful. Declines in global cognition and executive function markedly raise the risk of death, dementia, and functional disability.39-41 Diagnosis of the clinical syndrome of dementia/neurocognitive disorder requires cognitive decline by history and objective measurement.42 Our findings that women have faster declines in global cognition and executive function mean women would have greater risk than men for being diagnosed with dementia based on objectively measured cognitive decline. Our findings that women had higher initial cognitive scores suggest informants and clinicians might not observe significant cognitive decline in women until substantial loss and impairment has occurred.

Studies have consistently found evidence of sex differences in baseline cognitive functioning with women demonstrating stronger verbal cognitive skills than men, but men demonstrating stronger visuospatial skills than women (eg, mental rotations).31,43 Reasons for these sex differences are complex and likely influenced by biological (eg, sex hormones), genetic (eg, APOE), and social and cultural factors.43 While sex differences in cognitive reserve might also be associated with differences in life course risk factors such as vascular risk,44 education, and health behaviors such as smoking and exercise,45 our findings of sex differences in baseline cognitive performance independent of these factors suggest that additional contributors and biological pathways play a role.

Women might have faster cognitive decline than men because of differences in sex hormones, structural brain development, genetics, psychosocial factors, lifestyle factors, functional connectivity, and tau pathology.45-47 Women might have greater burden of small vessel disease, including white matter hyperintensity volume, and less axonal structural integrity that in turn leads to faster cognitive decline particularly in executive function and processing speed.48,49 Women also appear to have lower gray matter volume,50 so they might be more vulnerable to both the accelerated gray volume loss that occurs with aging and the differential volume loss in specific brain regions that occurs with neurodegenerative diseases.51 Recent studies suggest that women develop greater neurofibrillary degeneration, brain parenchymal loss, and cognitive decline.52-54 Our results suggest that women’s greater cognitive reserve might enable them to withstand greater AD-pathology than men.

Strengths and Limitations

Our study has several strengths. By pooling 5 large, high-quality cohorts, we had longitudinal cognitive assessments and vascular risk factor measurements in a large number of Black and White individuals who were young, middle-aged, and older-aged to estimate cognitive trajectories in men and women. We had repeated cognitive measures during up to 21 years of follow-up. The cohort studies included in our study systematically measured major cognitive domains important for daily, occupational, and social functioning: global cognition, executive function, and memory. Our findings were consistent across cohorts.

This study also has several limitations. While we adjusted for educational years, we could not adjust for educational quality, literacy, other socioeconomic factors,10 or depressive symptoms, because not all cohorts had these data at or before the first cognitive assessment. However, studies suggest that socioeconomic factors tend to influence initial cognitive scores (ie, intercepts) rather than the change in cognitive scores over time (slopes).55,56 Selective attrition of cognitively impaired participants could underestimate the rate of cognitive decline57 or not.58 Estimating the potential clinical impact of sex differences in cognitive decline by correlating it with decline due to aging is a common approach, but it does not directly measure clinical impact, and a clinically meaningful change might vary by an individual’s age, educational quality, race, and baseline cognition.59 There were no sex differences in participants excluded because of stroke or dementia before first cognitive assessment, so this would not influence sex differences in cognitive decline (eTable 8 in the Supplement).

We did not study incident dementia because some cohort studies lacked this information. By design, we did not adjust for baseline cognition. We also did not study any particular age interval associated with greatest risk of sex-related cognitive decline. Heterogeneity of the association of sex with cognitive decline between cohorts might have affected the statistical validity of the summary estimate of the effect in the pooled cohort. Smaller sample size and fewer cognitive assessments might have reduced precision of estimates of cognitive decline in executive function and memory (ie, the secondary outcomes). We did not have information on participants’ instrumental activities of daily living, family history of dementia, and hormone replacement therapy use. While the assumption that participants’ postmortem cognitive data are missing at random might lead to immortal cohort bias and underestimate memory declines,60 it is valid to answer the research question quantifying sex differences in cognitive trajectories through study follow-up. Women might have had a greater likelihood of regressing to a lower value than men at follow-up because they had higher baseline cognitive function than men. Using a fixed effect for cohorts might have produced conservative estimates of sex effects on cognitive slopes.

Cross‐sex shifts in two brain imaging phenotypes and their relation to polygenic scores for same‐sex sexual behavior: A study of 18,645 individuals from the UK Biobank

Cross‐sex shifts in two brain imaging phenotypes and their relation to polygenic scores for same‐sex sexual behavior: A study of 18,645 individuals from the UK Biobank. Christoph Abé  Alexander Lebedev  Ruyue Zhang  Lina Jonsson  Sarah E. Bergen  Martin Ingvar  Mikael Landén  Qazi Rahman. Human Brain Mapping, February 26 2021. https://doi.org/10.1002/hbm.25370

Abstract: Genetic and hormonal factors have been suggested to influence human sexual orientation. Previous studied proposed brain differences related to sexual orientation and that these follow cross‐sex shifted patterns. However, the neurobiological correlates of sexual orientation and how genetic factors relate to brain structural variation remains largely unexplored. Using the largest neuroimaging‐genetics dataset available on same‐sex sexual behavior (SSB) (n = 18,645), we employed a data‐driven multivariate classification algorithm (PLS) on magnetic resonance imaging data from two imaging modalities to extract brain covariance patterns related to sex. Through analyses of latent variables, we tested for SSB‐related cross‐sex shifts in such patterns. Using genotype data, polygenic scores reflecting the genetic predisposition for SSB were computed and tested for associations with neuroimaging outcomes. Patterns important for classifying between males and females were less pronounced in non‐heterosexuals. Predominantly in non‐heterosexual females, multivariate brain patterns as represented by latent variables were shifted toward the opposite sex. Complementary univariate analyses revealed region specific SSB‐related differences in both males and females. Polygenic scores for SSB were associated with volume of lateral occipital and temporo‐occipital cortices. The present large‐scale study demonstrates multivariate neuroanatomical correlates of SSB, and tentatively suggests that genetic factors related to SSB may contribute to structural variation in certain brain structures. These findings support a neurobiological basis to the differences in human sexuality.

4 DISCUSSION

In this large‐scale study on SSB, we used brain imaging phenotypes from two imaging modalities and a multivariate classification algorithm to extract independent brain covariance patterns related to sex. We then tested for SSB related cross‐sex shifts in such patterns. For the first time, we also examined whether polygenic scores for SSB relate to brain imaging phenotypes.

Our results showed that the PLS classifier was effective in classifying males and females, and that patterns important for classification were less pronounced in non‐heterosexual individuals, indicative of a cross‐sex shift. The analysis of LVs demonstrated that one (LV1) displayed a sex‐by‐SSB interaction. This interaction remained following adjustment for potential confounding variables, including psychiatric diagnoses and victimization experiences, and was driven by the fact that nHeF showed larger LV1 scores than HeF. Since males showed the largest LV scores, this indicates an SSB‐related cross‐sex shift in multivariate brain patterns predominantly in females. This shift in LV1 was not observed in males, which could potentially arise because SSB‐related differences in males might have less of a covarying nature, regionally differ, be more focal, or less pronounced (smaller effect size) compared to females, as indicated by secondary univariate analyses (Figure 6). However, these differences could also be explained by the fact that the SSB measure does not capture all aspects of sexual orientation. While SSB correlates highly with other components of sexual orientation, nHeF and nHeM in our sample may differ in other components such as sexual attractions, sexual identity labels, or romantic attractions (J. M. Bailey et al., 2016). Hence, we cannot exclude the presence of sub‐groups among non‐heterosexual individuals. In line with that notion, in an explorative analysis excluding individuals with one or two reported lifetime same‐sex partners (see Supporting Information), the peak of the LV1 distribution in nHeM was shifted toward smaller values (the mean of females), indicating that a sub‐group of nHeM (e.g., those with more same‐sex partners) may show a more female‐like multivariate brain pattern. However, this effect requires further investigation. Nevertheless, our findings suggest sexuality‐related variation in multivariate brain data, supporting the utility of data‐driven classification and that multivariate pattern analyses are effective at identifying such associations on group level, at least in females.

Our neuroanatomical findings support a number of previous small‐scale reports of sexual orientation‐related differences (Abé et al., 2014; Abé et al., 2018; Manzouri & Savic, 2018a2018b; Ponseti et al., 2007; Savic & Lindström, 2008) in that they indicate SSB‐related cross‐sex shifts in brain imaging phenotypes. Intriguingly, the calcarine sulcus (part of the visual cortex) appears to be the most consistently reported structure showing sexual orientation‐related differences (Abé et al., 2014; Abé et al., 2018; Manzouri & Savic, 2018b), which is consistent with results from our secondary univariate analyses (ROI approach: Figure 6, and whole brain analysis: Data S2). We did not replicate sexual orientation differences in the anterior cingulate cortex (Manzouri & Savic, 2018a2018b) and hippocampus (Abé et al., 2014) in males. Cross‐sex shifts in brain data are also consistent with a large body of empirical findings demonstrating cross‐sex shifted patterns of gender‐related behavior, cognitive ability (in tasks that typically differ between the sexes), and certain personality traits (Allen & Robson, 2020; Bailey et al., 2016; Li et al., 2017; Rieger et al., 2008; Xu et al., 2017). However, there is considerable overlap in the distribution of LV‐scores between the groups, and the magnitude of the effects for SSB‐related brain differences seem smaller than those reported for the aforementioned behavioral traits. Notably, effect sizes for SSB‐related differences in cortical volumes were also smaller than those of sex differences (Table S3, Data S2).

The imaging variables that loaded most strongly on LV1 (displaying the sex‐by‐SSB interaction) were measures of regional volumes in prefrontal, parietal, and occipital (including visual) cortices. In the context of SSB, the visual cortex is involved in visual perception and processing of sexual stimuli (Georgiadis & Kringelbach, 2012). Prefrontal areas are involved in the integration of sensory information and reward‐value representation of sexual stimuli (Georgiadis & Kringelbach, 2012). Together with the precuneus, involved in self‐referential processes (Cavanna & Trimble, 2006), these areas are also recruited during visuo‐spatial processing and selective visual attention (Cavanna & Trimble, 2006; Georgiadis & Kringelbach, 2012; Paneri & Gregoriou, 2017; Posner & Gilbert, 1999). However, this study does not allow conclusions about causality or the brain regions' functional involvement. It requires further testing how differences in brain structure relate to SSB. Note that although volumes of those brain regions that tended to successfully predict group membership largely overlap with those previously reported in other studies, in contrast to direct group comparisons in univariate analyses, PLS results should not necessarily be interpreted as evidence of structural differences between the groups, but rather as generalized covariance patterns in the brain data that discriminate between them. Another important finding is that while LV1 appeared to capture the hypothesized cross‐sex shift, LV2 appeared to capture a main effect of SSB. This may indicate that SSB‐related multivariate brain patterns may exist that do not follow a cross‐sex shift and are similar in both nHeM and nHeF (regardless of sex). It is also noteworthy that cortical volumetric measures showed the highest loadings, whereas those of subcortical structures and DTI‐based FA values were close to zero, indicating that sex‐related brain phenotype variation may be more pronounced in gray matter than white matter or subcortical measures.

The causes of sexual orientation‐related differences in brain structure are as yet unknown. Both genetic and non‐genetic factors have been proposed to play a role, with the most prominent hypothesis involving prenatal androgen influences (Bailey et al., 2016; Kevin, Khytam, & David, 2018). Genetic influences are modest based on existing twin models and molecular genetic studies (Bailey et al., 2000; Bailey et al., 2016; Ganna & Verweij, 2019; Langstrom et al., 2010) and are almost certainly polygenic in nature (Ganna & Verweij, 2019). Here, we investigated genetic influences on brain phenotypes by testing the associations between polygenic scores for SSB (PS‐SSB) and brain imaging phenotypes. Whereas PS‐SSB did not seem to predict multivariate brain patterns (LVs), we found that PS‐SSB was associated with cortical volumes in individual brain regions. These associations were observed mainly in lateral occipital and temporo‐occipital cortex. In lateral occipital cortex, higher PS‐SSB was associated with lower volumes in both males and females. In temporo‐occipital cortex, higher PS‐SSB was associated with lower cortical volumes in nHeM and larger volumes nHeF. These findings tentatively indicate that genetic factors related to SSB are associated with variation in some cortical structures and that a higher genetic predisposition to SSB has the opposite effect on cortical volume in males and females who reported SSB. These associations were small and PS‐SSB explained little of the variance in brain structure. Notably, we did not find significant genetic correlations in complementary analyses linking previously published SSB and brain phenotype GWASs (Elliott et al., 2018; Ganna & Verweij, 2019). Therefore, these genetic associations should be treated with caution, and additional factors are likely to explain brain variation associated with human sexuality. Mechanisms responsible for how genetic factors influence brain structure, function, and in turn behavior are complex and multi‐factorial. Given the general limitations of the applied methodology (see below), these cannot be derived from this study. We also want to note that, given the wide and overlapping range of LVs and PS‐SSB, as well as the weak classification performance when solely predicting SSB (AUC = 0.57), the present results cannot be used to predict an individual's sexual orientation based on genetic or neuroimaging data.

Understanding the appeal of libertarianism: Gender and race differences in the endorsement of libertarian principles

Understanding the appeal of libertarianism: Gender and race differences in the endorsement of libertarian principles. Mary‐Kate Lizotte  Thomas Warren. Analyses of Social Issues and Public Policy, February 26 2021. https://doi.org/10.1111/asap.12237

Abstract: There is a stereotype of libertarians being young, college educated, white men and that the Libertarian Party lacks appeal among women and individuals of color. There is a great deal of research investigating gender differences in public opinion on a number of issues including the provision of government resources and government spending (Barnes and Cassese; Howell and Day). Nevertheless, there is no work specifically investigating why women and nonwhites do not find libertarianism appealing. We test several hypotheses using 2016 American National Election Study data and 2013 PRRI data. We find a sizeable and significant gender gap and race gap in support for libertarian principles. We investigate several explanations for these gaps finding moderate support for self‐interest, racial attitudes, and egalitarianism as reasons for women and African Americans being less supportive of Libertarian Principles. We believe that the modest success of and media attention garnered by Ron Paul and Rand Paul in recent years along with the success of the Libertarian Party presidential ticket in 2016 highlights the need to understand who is drawn to libertarianism and why.