Monday, November 30, 2020

I Don’t Want You to ‘Believe’ Me. I Want You to Listen. Agnes Callard

I Don’t Want You to ‘Believe’ Me. I Want You to Listen. Agnes Callard. The New York Times, Nov. 30, 2020. https://www.nytimes.com/2020/11/30/opinion/i-dont-want-you-to-believe-me-i-want-you-to-listen.html

I fear that the more I tell you, the less you will understand who I am.


I am not a private person — quite the opposite — but I do have two secrets. The first concerns some Bad Events that happened to me long ago (yes, it’s the sort of thing you are thinking of), and the second is an unrelated Fact about my neurological makeup.

Let me be clear: I am not ashamed of either of these things. Keeping them secret creates, in me, an uncomfortable feeling, as though I were hiding something, as though I were ashamed, and that bugs me all the time, like a scratchy tag in my clothing. But I can’t tell you what The Fact is, because you won’t believe me; and I can't tell you about The Events, because you will.

I have barely told you anything about The Events, but I suspect that you have already started believing. You want to be someone who believes women; you see this as the belief-challenge you have been waiting for; you want to rise to it. When I first told a therapist about The Events, she said: “Of course. In retrospect it makes perfect sense of so many things …”

Later she apologized for this as therapeutic overreach. Even therapists can’t help themselves — they are off to the races, believing and believing. On this topic, so much gets packaged into “being believed” that I fear the more I tell you, the less you will understand me.

I don't want you to think you know the meaning of The Events; I don’t want to be classified as damaged; I don’t want you to feel good about yourself for believing me; I don’t want you to feel sorry for me; and most of all, I don’t want you to praise my courage for “coming forward” or for “surviving.” The prospect of receiving praise or honor for this revelation fills with me with rage — when I imagine your admiration, I immediately imagine throwing it back in your face.

The Fact I’d like to tell you has to do with a difference between how we — you and I — think. But to get specific about this difference, I have to use a word you associate with people who don’t talk, who can’t take care of themselves, whose inner lives seem utterly obscure to you, people who harm themselves, people you struggle to see as human, people whose existence you see as a tragedy.

And you will find this comparison preposterous. You will tell me I shouldn’t use “that word,” you will helpfully offer me milder alternatives. You might acknowledge that I’m “quirky” or “idiosyncratic” — in a good way! — and that a few of those quirks may superficially resemble those people. But I have a professional career, a family. I can’t be like them. (Ask yourself: how much knowledge would you need, really, to be certain of this?)

You might be willing to budge a little if you could hear it from some medical professionals — though one might not be enough. You’d need a second and third opinion. Notice that if I told you I had cancer or diabetes or depression, or for that matter that I was left-handed, you would not insist on seeing my papers. You would not be inclined to think I was faking my left-handedness by having trained myself to use my left hand; or that I resembled depressed people only “in some respects.”

In the case of The Events, you are eager to assign victim status to me; in the case of The Fact, you are wary of assigning it to me. For you, there is only one question: how much suffering can she legitimately lay claim to?

You are so busy trying to answer this question — trying to serve as judge in the pain/suffering/disadvantage Olympics — that you cannot hear anything I am trying to tell you. And that means I can’t talk to you. No one can sincerely assert words whose meaning she knows will be garbled by the lexicon of her interlocutor. I don’t want privacy, but you’ve forced it onto me.

You might wonder why I have to tell you these things. Couldn’t I find a supportive community of people who endured similar Events, and wouldn’t I be believed by other Fact-Bearers? Yes, and individual connections of this kind are very valuable, but at the group level this kind of support has never worked for me.

Being surrounded by people who are supposedly like me inevitably leads me to feel maximally “different.” Probably my failure to benefit from such communities is a sign that I have not suffered so much, and deserve very little victim credit. So be it!

Solidarity is not my thing, openness is. It is a consequence of The Fact, for me, that I lean toward transparency in all contexts: I have to consciously prevent myself from oversharing (even more than I do), and I am honest from necessity rather than virtue.

There is a reason for all of this, which is that I am bad — really bad, you cannot imagine how bad — at figuring things out on my own. If I take too many steps in reasoning without the intervention of another person, I go very far wrong. So I have accustomed myself to reasoning in public as much as I can, to making sure to expose my mistakes to correction.

I know that I don’t know what corner assistance might come from. I don’t want to confide in a select group of people who grumble among themselves about how you misunderstand “us.” I want to talk to you, any and all of you, freely, so you can help me stop misunderstanding myself.

The truth is that I don’t know the meaning of The Events, for my life. Isn’t it at least possible that they simply don’t have any meaning? Or maybe the meaning will change once I am allowed to speak them out loud? Perhaps I really am scarred for life, but do we have to assume that from the outset?

If I could talk it through, I might have a hope of figuring this out. Because that is mostly how I figure out all the difficult problems of my life: I talk about them to whoever is available, whenever the problems seem relevant to something else I am thinking about; I listen; I rethink; I write; I circle back and write something else; over and over again; and over time I develop a stable picture.

With The Events, I am at sea. For so long I did not even allow myself to speak them to myself. Now that I can, it chafes at me that you have decided that if I want to talk about them with you, I have to follow your rules, and let you trample all over me. Perhaps more people who have experienced Events would talk about them with you if they thought you would do less “believing” and more listening.

Factwise, this is what I want to know: what, if anything, ties together the “superficial” differences in how I dress, how I talk, how my mind jumps around, my repetitive movements, my sensitivities, the kinds of patterns I see and the kinds I miss, my obsessions, my literal-mindedness, my odd oscillations between needing to be alone and needing to be with others, between striking you as charming and coming off as unbearable. Why do I struggle so much to understand which emotion I am feeling? Why am I so bad at predicting what you will find offensive?

The Fact makes me part of a group of people whose boundaries are amorphous; we do not all recognize one another, and even when we do, we are not sure what we have in common. You would like to manage this situation in a very specific way: First, carve off what you take to be the “most severe cases,” and find a cure that prevents any more of them from arising.

Second, assimilate the rest — people like me — as “normal,” or as normal enough, so long as you are sufficiently tolerant and accommodating. But I suspect all the tolerance and accommodation in the world won’t make me normal. Do we have to pretend that I am? Is that the condition on which you are willing to engage with me? And couldn’t a group of people have something in common even if “degree of suffering” isn’t that thing?

I could use your help — not your support, not your approval, not your reassurance but your help as an open and thoughtful audience for these difficult questions. But you won’t help me, because you won’t listen to what I’m trying to say, because all you care about is how much victim status I deserve. You are really letting me down.

Agnes Callard (@AgnesCallard), an associate professor of philosophy at the University of Chicago and the author of “Aspiration: The Agency of Becoming,” writes about public philosophy at The Point magazine.

The topological changes in rich-club organization provide novel insight into sex-specific effects on white matter connections that underlie a potential network mechanism of sex-based differences in cognitive function

Sex Differences in Anatomical Rich-Club and Structural–Functional Coupling in the Human Brain Network. Shuo Zhao, Gongshu Wang, Ting Yan, Jie Xiang, Xuexue Yu, Hong Li, Bin Wang. Cerebral Cortex, bhaa335, Nov 24 2020. https://doi.org/10.1093/cercor/bhaa335

Abstract: Structural and functional differences between the brains of female and male adults have been well documented. However, potential sex differences in the patterns of rich-club organization and the coupling between their structural connectivity (SC) and functional connectivity (FC) remain to be determined. In this study, functional magnetic resonance imaging and diffusion tensor imaging techniques were combined to examine sex differences in rich-club organization. Females had a stronger SC-FC coupling than males. Moreover, stronger SC-FC coupling in the females was primarily located in feeder connections and non–rich-club nodes of the left inferior frontal gyrus and inferior parietal lobe and the right superior frontal gyrus and superior parietal gyrus, whereas higher coupling strength in males was primarily located in rich-club connections and rich-club node of the right insula, and non-rich-club nodes of the left hippocampus and the right parahippocampal gyrus. Sex-specific patterns in correlations were also shown between SC-FC coupling and cognitive function, including working memory and reasoning ability. The topological changes in rich-club organization provide novel insight into sex-specific effects on white matter connections that underlie a potential network mechanism of sex-based differences in cognitive function.

Keywords: cognitive function, rich-club organization, SC-FC coupling, sex differences, topological properties

Discussion

We examined changes in the patterns of rich-club organization in structural networks and functional brain dynamics between females and males. The main findings were as follows: 1) We found increased values of the topological properties cost, Eg, Eloc, and strength in male versus female adults. 2) Compared with the male adults, the female adults had a greater strength in the SC-FC coupling. Moreover, the females had a negative correlation between the SC-FC coupling and the cost of the topological properties, whereas the males had a positive correlation between the SC-FC coupling and the cost of the topological properties. 3) Different regions of SC-FC coupling were observed between females and males. A higher SC-FC coupling in the females than males was primarily located in the non-rich-club nodes, including regions of the left IFG and IPL and the right SFG and SPG. A higher SC-FC coupling in the males than females was located not only in the rich-club nodes, including the right INS, but also in non–rich-club nodes, including the left hippocampus and the right PHG. 4) A sex-specific correlation was found between SC-FC coupling in the brain network and cognitive performance. The females had a negative correlation between local SC-FC coupling and working memory, whereas the males had a positive correlation between rich-club SC-FC coupling and reasoning ability. We thus conclude that the pattern differences in the correlations between SC-FC coupling and cognitive function were affected by sex differences, which may help to reveal a potential network mechanism of sex differences in cognitive function.

In this study, when a range of degrees k from 5 to 10 was used, the males had higher rich-club coefficients than the females, which reflected the existence of different rich-club organization in the brain topological properties between females and males. That is, increased effects were found with the topological properties of cost, Eg, Eloc, and strength in the males versus the females. In particular, the strength and cost of feeder and local but not rich-club connections was increased. These findings were consistent with previous studies (e.g., Wang et al. 2019a) that found higher levels of cost, density, and strength among topological properties in males than in females. These differences between males and females exhibited typical rich-club properties, revealing greater global efficiency, local efficiency, and strength in males but a more economical rich-club architecture in females.

Importantly, the present study combined DTI techniques and functional resting-state techniques and found a greater coupling strength in the SC-FC in the females than males. Although previous studies (e.g., Zell et al. 2015Gur and Gur 2017Ritchie et al. 2018) have reported differences between males and females in the topological properties of structural connections or functional connections, the present study provides further evidence for sex differences in the relationship between SC and FC coupling, revealing greater SC-FC coupling strength in females than in males. Compared with males, females had greater coupling strength in the rich-club and local but not feeder SC-FC coupling. Moreover, this strength was associated with the cost of topological properties in the rich-club and local coupling. Specifically, the correlation between SC-FC coupling strength and the cost of local connections was negative with females, whereas the correlation between SC-FC coupling strength and the cost of rich-club connections was positive with males. Therefore, the increase in SC-FC coupling in females was mainly concentrated in rich-club and local connections that correspond to more stringent and less dynamic brain function (Honey et al. 2009van den Heuvel et al. 2009) and influence the cost of rich-club architecture compared to that of males. Previous studies (Collin et al. 2014) have proposed that information integration is influenced by the architecture of neural systems, which may be driven by a potential “trade-off” between cost and communication efficiency, known as the cost-efficiency trade-off of neural circuitry formation. Based on this proposition, the present finding of difference between males and females in SC-FC coupling may contribute to a more accurate understanding of sex differences in the dynamic changes and information integration in brain network structures. Additionally, as previous studies have reported that SC-FC coupling increased with age (Supekar et al. 2010Grayson et al. 2014) and was disrupted in the context of clinical disease (van den Heuvel et al. 2013Collin et al. 2017Wang et al. 2019bCao et al. 2020), the present findings might also provide a future direction to examine the age-related changes and disease-related disruptions in SC-FC coupling in different sexes.

Moreover, a difference in SC-FC coupling was found between females and males in the nodes of the rich-club organization. Specifically, greater SC-FC coupling in the females was primarily located in the non-rich-club nodes, including the left IFG and right SFG in the frontal lobe and the left IPL and right SPG in the parietal lobe, whereas greater SC-FC coupling in the males was located not only in the rich-club nodes, including the right INS, but also in non-rich-club nodes, including the left hippocampus and right PHG. All of these regions are the limbic system. The findings were largely consistent with a previous report that the structural properties of these regions were different between females and males. Gong et al. (2009), using diffusion MRI tractography data, revealed a lower efficiency in the IFG in females than males. However, a higher regional efficiency was shown in females than males in the SPG (Gur et al. 1999). Ritchie et al. (2018) also found a larger brain volume in the right superior parietal region in females than males but no difference in the left inferior parietal region, although a greater connectivity in the IPL was reported by Gong et al. (2011). All of these regions are located in the dorsal frontoparietal network and participate in various functions, including spatial attention (Corbetta and Shulman 2002Fellrath et al. 2016). Additionally, the INS is an important hub region associated with spatial cognition, which exhibited greater connectivity (Gong et al. 2011) but lower FA values (Chou et al. 2011) in males than females. The PHG and hippocampus are located in the limbic system and play an important role in memory. Using the tract-based spatial statistic (TBSS) method, Chou et al. (2010) showed that females had higher FA values in the PHG but lower FA values in the hippocampus. Ritchie et al. (2018) found a higher thickness in the PHG in females, but a higher volume and surface area in males. Based on these findings, our results extend the identification of sex differences to SC-FC coupling. We suggest that the advantage of this approach is the differences in SC-FC coupling in rich-club and non-rich-club nodes between females and males. As previous studies have reported sex differences in cognitive performance, including memory (Harness et al. 2008Levine et al. 2016), spatial attention and spatial cognition (Vaquero et al. 2004Levine et al. 2016), we therefore proposed that SC-FC coupling in females and males in the different nodal regions between rich-club and non-rich-club nodes represents submodular organization for specific functional domains that may exhibit optimized patterns, leading to improved performance in corresponding cognitive functions. However, other characteristics, such as brain volume differences, are also likely to account for sex differences in specific cognitive functions.

In this study, we also examined the relationship between SC-FC coupling and cognitive performance in females and males. Specifically, we found a negative correlation between local SC-FC coupling and working memory in the females, whereas a positive correlation was shown between rich-club SC-FC coupling and reasoning ability in the males. Previous studies have reported that males scored significantly higher on reasoning ability (Quereshi and Seitz 1993Lakin 2013) and that females scored significantly higher on working memory (Harness et al. 2008) in cognitive performance. For example, van der Sluis et al. (2006) reported that males scored higher on reasoning ability, while females scored higher on working memory, on the Dutch WAIS-III. Neuroimaging research has also reported sex differences in cognitive performance, including working memory and reasoning ability. Specifically, a meta-analysis study (Hill et al. 2014) found that males had more activity in a distributed network including parietal regions, while females had activity in more limbic regions including the amygdala and hippocampus, as well as prefrontal regions including the right inferior frontal gyrus. Moreover, one team (Ritchie et al. 2018) showed, using a large sample (2750 females and 2466 males), that sex differences in reasoning ability were associated with brain volume and surface area. The present results extended these findings in the SC-FC coupling in the rich-club organization that showed sex differences, suggesting reduced working memory in females and increased reasoning ability in males was associated with the females having less stringent and more dynamic brain function in the local connections, and the males having more stringent and less dynamic brain function in the rich-club connections. Given the importance of working memory and reasoning ability as pivotal cognitive functions in the intellectual domain, these observations suggest that sex differences in SC-FC coupling linked to reduced working memory and increased reasoning ability are closely related to the intellectual domain, potentially helping to explain how and why males and females differ in intelligence and academic achievement. 


Limitations.

The present study has several limitations that should be acknowledged. First, the sample size of subjects was relatively small. Regarding the limitation of the dataset, it is important to validate our findings by replicating our analyses using a larger sample of subjects. Second, in this study, we analyzed the coupling between SC and FC, which was limited to the connections with nonzero SC and FC. Although a strong FC also exists between regions with indirect SC (Honey et al. 2009), there is currently no way to analyze the associations between FC and indirect SC because of the limitations of the method. The aim of this study was simply to investigate differences in SC-FC coupling between females and males. Future research should examine the indirect connections to analyze the SC-FC coupling between females and males. Furthermore, this study did not sufficiently examine the correlations between the strength of the SC-FC coupling and working memory and reasoning ability in females and males. We used LNS and MR scores to examine the correlations between the strength of the SC-FC coupling and working memory and reasoning ability in females and males. Given that LNS and MR measures only the working memory ability to retrieve auditory information and nonverbal spatial reasoning ability, future studies should also evaluate the relationships between visual working memory and verbal reasoning ability.

In summary, this study found that sex significantly affected the rich-club organization of structural networks in individuals with typical development. Differences in the male versus female adults were shown with the topological properties of cost, Eg, Eloc, and strength. Importantly, a greater coupling strength of the SC-FC in females versus males was observed. Moreover, higher SC-FC coupling in the females was primarily located in the non-rich-club nodes, whereas higher SC-FC coupling in the males was located not only in the rich-club but also in non–rich-club nodes. Our results also found different patterns across sexes in the correlations between SC-FC coupling and cognitive function, including working memory and reasoning ability. Our findings of the topological changes in rich-club organization provide novel insight into sex differences on white matter connections that may underlie a potential network mechanism of sex-based differences in cognitive function.

The strong underrepresentation of women in math-related fields is more pronounced in more egalitarian & more developed countries; could be due to stronger stereotypes relating math primarily to men in those societies

Gender stereotypes can explain the gender-equality paradox. Thomas Breda et al. Proceedings of the National Academy of Sciences, November 23, 2020. https://doi.org/10.1073/pnas.2008704117

Significance: Recent research has found that the strong underrepresentation of women in math-related fields is more pronounced in more egalitarian and more developed countries. This pattern has been called the “gender-equality paradox.” We show that stereotypes relating math primarily to men are actually stronger in more egalitarian and more developed countries and that they mediate the link between development and segregation across fields of study. The mechanisms connecting socioeconomic development to the strengthening of these stereotypes and the gendering of math-related fields are discussed. Results suggest that gender occupational segregation can be reduced but will not decrease by itself as societies become more developed. Appropriate policies are therefore needed to limit this segregation or its impact on gender inequality.

Abstract: The so-called “gender-equality paradox” is the fact that gender segregation across occupations is more pronounced in more egalitarian and more developed countries. Some scholars have explained this paradox by the existence of deeply rooted or intrinsic gender differences in preferences that materialize more easily in countries where economic constraints are more limited. In line with a strand of research in sociology, we show instead that it can be explained by cross-country differences in essentialist gender norms regarding math aptitudes and appropriate occupational choices. To this aim, we propose a measure of the prevalence and extent of internalization of the stereotype that “math is not for girls” at the country level. This is done using individual-level data on the math attitudes of 300,000 15-y-old female and male students in 64 countries. The stereotype associating math to men is stronger in more egalitarian and developed countries. It is also strongly associated with various measures of female underrepresentation in math-intensive fields and can therefore entirely explain the gender-equality paradox. We suggest that economic development and gender equality in rights go hand-in-hand with a reshaping rather than a suppression of gender norms, with the emergence of new and more horizontal forms of social differentiation across genders.

Keywords: gender gap in STEMgender stereotypessocioeconomic development


Check also Sex Differences in Anatomical Rich-Club and Structural–Functional Coupling in the Human Brain Network. Shuo Zhao, Gongshu Wang, Ting Yan, Jie Xiang, Xuexue Yu, Hong Li, Bin Wang. Cerebral Cortex, bhaa335, Nov 24 2020.  https://www.bipartisanalliance.com/2020/11/the-topological-changes-in-rich-club.html

Psychiatric disorders: While many factors contribute to risk, epidemiological evidence suggests that the genetic contribution carries the highest risk burden; the increased rates are nonspecific

Risk in Relatives, Heritability, SNP-Based Heritability, and Genetic Correlations in Psychiatric Disorders: A Review. Bart M.L. Baselmans et al. Biological Psychiatry, Volume 89, Issue 1, January 1 2021, Pages 11-19. https://doi.org/10.1016/j.biopsych.2020.05.034

Rolf Degen's take: https://twitter.com/DegenRolf/status/1333344147185541120

Abstract: The genetic contribution to psychiatric disorders is observed through the increased rates of disorders in the relatives of those diagnosed with disorders. These increased rates are observed to be nonspecific; for example, children of those with schizophrenia have increased rates of schizophrenia but also a broad range of other psychiatric diagnoses. While many factors contribute to risk, epidemiological evidence suggests that the genetic contribution carries the highest risk burden. The patterns of inheritance are consistent with a polygenic architecture of many contributing risk loci. The genetic studies of the past decade have provided empirical evidence identifying thousands of DNA variants associated with psychiatric disorders. Here, we describe how these latest results are consistent with observations from epidemiology. We provide an R tool (CHARRGe) to calculate genetic parameters from epidemiological parameters and vice versa. We discuss how the single nucleotide polymorphism–based estimates of heritability and genetic correlation relate to those estimated from family records.

Keywords: Family register dataGenetic correlationGWASHeritabilityPsychiatric geneticsRisk in relatives

Conclusions

In this capstone narrative, we bring together the methods and results that summarize the genetic contribution to psychiatric disorders and the genetic relationship between them. We note that we use the common assumption that psychiatric disorder diagnosis definitions are underpinned by a consistent polygenic biology. If this is not true—for example, if a single clinical diagnosis is allocated to one or more independent or correlated biological diseases—then further thought is needed to interpret the estimates of heritability and genetic correlation. Such a scenario could explain (41), in part, the large difference between heritability and SNP-based heritability (Figure 1) in addition to contributions from rare variants and low LD between genotyped and causal variants. Previously, we concluded that only with large GWAS sample sizes and extensive clinical data (40,41) would we have the information needed to examine this interesting question. Despite this caveat, multiple results from GWAS data confirm that individuals allocated a specific diagnosis are genetically more similar, on average, than those allocated other diagnoses (i.e., heritabilities of individual disorders are greater than co-heritabilities between disorders) (Figure S2 in Supplement 2).

Understanding the genetic contribution to common disease is a foundation for many other research directions. It is outside the scope of this review to focus on the utility of the estimates of heritability and genetic correlation in detail. Estimates of SNP-based heritability help to guide whether efforts to increase GWAS sample sizes should continue, as they provide an upper limit on the combined effects of individual associated loci. Estimates of heritability and SNP-based heritability provide guidelines of maximum future accuracy of risk prediction applied to people whose disease status is not yet known. Genetic correlations can be used to determine how much the accuracy of the risk prediction can be improved by drawing on information from correlated traits, which perhaps are available in much larger samples than for the primary disorder itself (68). Here, we have focused on genetic correlations between psychiatric disorders, an approach that is likely to reflect pleiotropy (same causal variants affecting more than one disorder). However, genetic correlations can also be estimated between psychiatric disorders and other common diseases, or between psychiatric disorders and traits measurable in the population (such as educational attainment or smoking status), and these estimates could reflect causal relationships, which have been long-discussed in the psychiatric epidemiology literature (69). In the past 5 years, results from GWASs have allowed causal relationships using putative exposure traits and psychiatric disorders to be explored, as well as those between psychiatric disorders and subsequent metabolic disease, using the Mendelian randomization approach. The application of Mendelian randomization to psychiatric disorders has been discussed elsewhere (70) and is an exciting tool in psychiatry (as long as studies are well powered) to investigate putative causal relationships that are impossible or unethical to address through clinical trials. As an example, we recently showed that although there is considerable pleiotropy between genetic variants for vitamin D and psychiatric disorders, there is no evidence of a causal relationship (71). Such analyses contribute hard data to a long discussion in psychiatric epidemiology (72,73). Finally, we hope that our Supplementary materials, including Rmarkdown script and CHARRGe Shiny application (https://shiny.cnsgenomics.com/CHARRGe/), are useful to others both in research and as teaching and learning aids.

Who Mismanages Student Loans and Why? Loan management is worse for men & minorities

Cornaggia, Kimberly Rodgers and Xia, Han, Who Mismanages Student Loans and Why? (August 21, 2020). SSRN: http://dx.doi.org/10.2139/ssrn.3686937

Abstract: With a license to use individually identifiable information on student loan borrowers, we find that a majority of distressed student borrowers manage their debt sub-optimally and that suboptimal debt management is associated with higher loan delinquency. Cross-sectional analysis indicates that loan (mis)management varies significantly across student gender, ethnicity, and age. We test several potential selection-based explanations for such demographic variation in student loan management, including variation in students’ overconfidence, consumption preferences and discount rates, and aversion to administrative paperwork. Motivated by federal and state allegations against student loan servicers, we also test for the presence of treatment effects. Overall, the empirical evidence supports the conclusion that loan servicers’ differential treatment across borrowers play an important role in student loan outcomes.

Keywords: Student loans, Student demographics, Household finance, Loan servicers

JEL Classification: D14, H52, H81, I22, I28




An Investigation Across 105 Countries of Gender Differences in the Five Factor Model of Personality: Men score higher in Emotional Stability (the more individualist the country, the more stable) & lower in Agreeableness

International Comparison of Gender Differences in the Five Factor Model of Personality: An Investigation Across 105 Countries. Sara A. Murphy, Peter A. Fisher, Chet Robie. Journal of Research in Personality, 104047, Nov 29 2020. https://doi.org/10.1016/j.jrp.2020.104047

Abstract: Researchers have been interested in cross-cultural gender differences in personality for decades. Early research on the five factor (FFM) model of personality focused on estimating the difference between men and women on personality dimensions, however results have varied. Using a large cross-country sample of personality data and advanced analytic techniques, we uncover accurate estimates of cross-country gender differences in personality. Relatively small (δÌ¿^ < |.10|) cross-country gender differences emerged on most FFM dimensions, with the largest differences emerging for Emotional Stability (δÌ¿^ = .38) and Agreeableness (δÌ¿^ = -.17). After controlling for socioeconomic indicators, gender indicators, and Type I error, only country-level Individualism accounted for unique variance in effect size differences for Emotional Stability. Implications and future directions are discussed.

Keywords: Gender; Personality; Five-Factor Model; Cross-cultural; Cross-country