Sex & Gender
Essentialism, Social Justice Orthodoxy, & Heterodoxy
Like most aspects of identity, there are a wide range of views about sex and gender. Essentialist notions of sex/gender conflate biological sex with gender norms of behavior. Rigidly enforced gender norms have historically undermined the individual capacity to be oneself without political or social ramifications for biological men, women, and intersex individuals in most, if not all, human societies.
Developed primarily as a "counter-narrative" to historically dominant, essentialist notions of sex/gender, is the equally extreme notion that gender is a purely social construct untethered from biological sex. This view suggests that gender identity and biological sex are mostly (if not completely) separable from one another, and there are few, if any, meaningful biologically based differences between men and women.
Essentialist notions of sex/gender, like those of race, are epistemologically and ethically untenable. Similarly, the empirical claim that some small proportion of the human population consists of individuals who do not fit neatly into either binary category of male or female, and others who are biologically categorized as one sex but self-identify with the gender norms associated with the other is also well-warranted.
The normative ethical/political claim that citizens of an open, democratic society ought to respect the basic equality and individual rights of all their fellow citizens is also well-warranted. But none of these well-warranted claims forecloses the possibility that (a) there might be significant statistical differences, on average, between biological males and females on socially-relevant traits or (b) that, if such differences exist, genes may contribute to them.
Importantly, moral/political claims about how we ought to treat people who do not fit neatly into the mainstream gender norms are, in important ways, different from empirical claims about the nature of chemical/physical reality and its possible influence on individual and average group differences on phenotypic traits that our society deems important.
Claims about how society ought to be structured and how it ought to respond to such potential differences are also of a different type and, likewise, require normative, reasoned justification. Pathologizing and dismissing dissenters from orthodox positions on these questions is counterproductive.
Similarly, conflating empirical claims and justifications with ethical/political claims and justifications can obfuscate these important distinctions and undermine the credibility of purported experts who make them and institutions that promote them.
"The Google Memo: What Does the Research Say About Gender Differences?" - Sean Stevens, Heterodox Academy
The recent Google Memo on diversity, and the immediate firing of its author, James Damore, have raised a number of questions relevant to the mission of Heterodox Academy. Large corporations deal with many of the same issues that we wrestle with at universities, such as how to seek truth and achieve the kinds of diversity we want, being cognizant that we are tribal creatures often engaged in motivated reasoning, operating within organizations that are at risk of ideological polarization.
[I]n this post, we address the central empirical claim of Damore’s memo, which is contained in its second sentence. Let us quote the first three sentences:
I value diversity and inclusion, am not denying that sexism exists, and don’t endorse using stereotypes. When addressing the gap in representation in the population, we need to look at population level differences in distributions. If we can’t have an honest discussion about this, then we can never truly solve the problem.
The heart of Damore’s memo is a section titled “Possible non-bias causes of the gender gap in tech.” Damore argues that there are “population level differences” between men and women in some psychological or behavioral traits that might influence people’s career choices, and their success in those careers. He illustrates his basic framework for looking at potential “population differences” with this figure:
The recent Google Memo on diversity, and the immediate firing of its author, James Damore, have raised a number of questions relevant to the mission of Heterodox Academy. Large corporations deal with many of the same issues that we wrestle with at universities, such as how to seek truth and achieve the kinds of diversity we want, being cognizant that we are tribal creatures often engaged in motivated reasoning, operating within organizations that are at risk of ideological polarization.
[I]n this post, we address the central empirical claim of Damore’s memo, which is contained in its second sentence. Let us quote the first three sentences:
I value diversity and inclusion, am not denying that sexism exists, and don’t endorse using stereotypes. When addressing the gap in representation in the population, we need to look at population level differences in distributions. If we can’t have an honest discussion about this, then we can never truly solve the problem.
The heart of Damore’s memo is a section titled “Possible non-bias causes of the gender gap in tech.” Damore argues that there are “population level differences” between men and women in some psychological or behavioral traits that might influence people’s career choices, and their success in those careers. He illustrates his basic framework for looking at potential “population differences” with this figure:
Is Damore correct that such “population level differences” exist? It’s very hard to evaluate empirical claims about politicized topics because everyone can “cherry pick” the studies that support their side... The best way to establish the truth in such cases is to examine meta-analyses, which are studies that integrate the findings from many other studies...
We intend this post to be a living document that brings together in one place the best empirically grounded arguments on all sides. It will be updated regularly.
We focus here on research on sex differences in interests, traits, and abilities that might be related to coding/engineering/ STEM. We do not address Damore’s claims about sex differences in traits said to be related to leadership abilities. Leadership is a messy topic, in part because there are many styles of leadership. See Eagly & Johnson, 1990, for a review of sex differences in that literature, and Eagly, Johannesen-Schmidt, & van Engen, 2003for a meta-analysis of gender and leadership style.
In this review, we also do not address Damore’s claims that some gender differences are rooted in biological factors, such as the effect of prenatal hormones on brain development. Meta-analyses cannot tell us the origins of differences. Most researchers studying these questions assume that biology, childhood socialization, and current context interact in complex ways, and most psychologists know that pointing to a biological contribution (such as a genetic or hormonal influence) does not mean that an effect is “hard wired,” unmalleable, or immune to contextual variables (see Eagly & Wood, 2012; this is a point that Damore did not acknowledge).
In this review we focus only on whether “population level differences” exist. ...A company like Google must hire from the existing population of adults. Google and other tech companies can surely take steps that will influence the next generation of boys and girls, but to make progress toward its diversity goals Google must have an accurate understanding of the current population of men and women from which it is trying to recruit. Do population level differences exist between men and women? ...
[Generally supportive expert commentary:]
"Google Memo: Four Scientists Respond" ...
"Straight talk about sex differences in occupational choices & work-family tradeoffs"
"An in-depth analysis of the crisis at Google" ...
[Generally critical expert commentary:]
"Differences between Men and Women are Vastly Exaggerated"
Critique
Response
"A scientist’s take on the biological claims from... Google anti-diversity manifesto"
“Google manifesto”: Bad biology, ignorance of evolutionary processes, & privilege.
"What the Science Actually Says About Gender Gaps in the Workplace"
[Moderately critical expert commentary:]
"Does biology explain why men outnumber women in tech?" ...
Meta-Analyses and Large Sample Studies...
Meta-analysis is a method of examining the effects found (or not found) in dozens or hundreds of studies, converting the effect sizes to a common scale, and then finding the average across all the studies. It’s a very powerful technique that allows researchers to examine questions such as: Does the effect get larger or smaller as we limit our analysis to only the best-done studies? What broad statements can be made about a body of literature?
Although meta-analysis is a powerful technique, it is not perfect (for an overview of strengths and weaknesses see Rosenthal & DiMatteo, 2001). It would be ideal if a researcher could not only identify, but also obtain all of the relevant data on the phenomenon of interest. However, this is an impossible task for any single meta-analysis to achieve.
Statistically significant findings are more likely to be published (see Rosenthal, 1979), and thus included in meta-analyses, compared to null findings which often remain unpublished. No single meta-analysis will be able to identify all of the relevant studies. This is why we have decided to bring together many meta-analyses in one place.
We have included relevant meta-analyses on sex differences in interests, personality traits, behaviors and abilities that might be related to coding/engineering from 1990 to the present. We also included large cross-national empirical investigations (N > 15,000) and large sample empirical investigations (N > 10,000) of gender differences....
OUR CONCLUSIONS
The research findings are complicated... Nonetheless, we think that the situation can be greatly clarified by distinguishing abilities from interests. We think the following three statements are supported by the research...
1. Gender differences in math/science ability, achievement, and performance are small or nil...
There are two exceptions to this statement:
A) Men (on average) score higher than women on most tests of spatial abilities, but the size of this advantage depends on the task and varies from small to large ... There is at least one spatial task that favors females (spatial location memory... Men also (on average) score higher on mechanical reasoning and tests of mathematical ability, although this latter advantage is small. Women get better grades at all levels of schooling and score higher on a few abilities that are relevant to success in any job (e.g., reading comprehension, writing, social skills). Thus, we assume that this one area of male superiority is not likely to outweigh areas of male inferiority to become a major source of differential outcomes.
B) There is good evidence that men are more variable on a variety of traits, meaning that they are over-represented at both tails of the distribution (i.e., more men at the very bottom, and at the very top), even though there is no gender difference on average. Thus, the pool of potentially qualified applicants for a company like Google is likely to contain more males than females. To be clear, this does not mean that males are more “suited” for STEM jobs. Anyone located in the upper tail of the distributions valued in the hiring process possesses the requisite skills. Although there may be fewer women in that upper tail, the ones who are found there are likely to have several advantages over the men, particularly because they likely have better verbal skills.
2. Gender differences in interest and enjoyment of math, coding, and highly “systemizing” activities are large.
The difference on traits related to preferences for “people vs. things” is found consistently and is very large, with some effect sizes exceeding 1.0 ...
3. Culture and context matter, in complicated ways. Some gender differences have decreased over time as women have achieved greater equality, showing that these differences are responsive to changes in culture and environment. But the cross-national findings sometimes show “paradoxical” effects: progress toward gender equality in rights and opportunities sometimes leads to larger gender differences in some traits and career choices...
In conclusion, based on the meta-analyses we reviewed and the research on the Greater Male Variability Hypothesis, Damore is correct that there are “population level differences in distributions” of traits that are likely to be relevant for understanding gender gaps at Google and other tech firms.
The differences are much larger and more consistent for traits related to interest and enjoyment, rather than ability. This distinction between interest and ability is important because it may address one of the main fears raised by Damore’s critics: that the memo itself will cause Google employees to assume that women are less qualified, or less “suited” for tech jobs, and will therefore lead to more bias against women in tech jobs. But the empirical evidence we have reviewed should have the opposite effect.
Population differences in interest and population differences in variability of abilities may help explain why there are fewer women in the applicant pool, but the women who choose to enter the pool are just as capable as the larger number of men in the pool. This conclusion does not deny that various forms of bias, harassment, and discouragement exist and may contribute to outcome disparities, nor does it imply that the differences in interest are biologically fixed and cannot be changed in future generations.
If our three conclusions are correct then Damore was drawing attention to empirical findings that seem to have been previously unknown or ignored at Google, and which might be helpful to the company as it tries to improve its diversity policies and outcomes...
The research findings are complicated... Nonetheless, we think that the situation can be greatly clarified by distinguishing abilities from interests. We think the following three statements are supported by the research...
1. Gender differences in math/science ability, achievement, and performance are small or nil...
There are two exceptions to this statement:
A) Men (on average) score higher than women on most tests of spatial abilities, but the size of this advantage depends on the task and varies from small to large ... There is at least one spatial task that favors females (spatial location memory... Men also (on average) score higher on mechanical reasoning and tests of mathematical ability, although this latter advantage is small. Women get better grades at all levels of schooling and score higher on a few abilities that are relevant to success in any job (e.g., reading comprehension, writing, social skills). Thus, we assume that this one area of male superiority is not likely to outweigh areas of male inferiority to become a major source of differential outcomes.
B) There is good evidence that men are more variable on a variety of traits, meaning that they are over-represented at both tails of the distribution (i.e., more men at the very bottom, and at the very top), even though there is no gender difference on average. Thus, the pool of potentially qualified applicants for a company like Google is likely to contain more males than females. To be clear, this does not mean that males are more “suited” for STEM jobs. Anyone located in the upper tail of the distributions valued in the hiring process possesses the requisite skills. Although there may be fewer women in that upper tail, the ones who are found there are likely to have several advantages over the men, particularly because they likely have better verbal skills.
2. Gender differences in interest and enjoyment of math, coding, and highly “systemizing” activities are large.
The difference on traits related to preferences for “people vs. things” is found consistently and is very large, with some effect sizes exceeding 1.0 ...
3. Culture and context matter, in complicated ways. Some gender differences have decreased over time as women have achieved greater equality, showing that these differences are responsive to changes in culture and environment. But the cross-national findings sometimes show “paradoxical” effects: progress toward gender equality in rights and opportunities sometimes leads to larger gender differences in some traits and career choices...
In conclusion, based on the meta-analyses we reviewed and the research on the Greater Male Variability Hypothesis, Damore is correct that there are “population level differences in distributions” of traits that are likely to be relevant for understanding gender gaps at Google and other tech firms.
The differences are much larger and more consistent for traits related to interest and enjoyment, rather than ability. This distinction between interest and ability is important because it may address one of the main fears raised by Damore’s critics: that the memo itself will cause Google employees to assume that women are less qualified, or less “suited” for tech jobs, and will therefore lead to more bias against women in tech jobs. But the empirical evidence we have reviewed should have the opposite effect.
Population differences in interest and population differences in variability of abilities may help explain why there are fewer women in the applicant pool, but the women who choose to enter the pool are just as capable as the larger number of men in the pool. This conclusion does not deny that various forms of bias, harassment, and discouragement exist and may contribute to outcome disparities, nor does it imply that the differences in interest are biologically fixed and cannot be changed in future generations.
If our three conclusions are correct then Damore was drawing attention to empirical findings that seem to have been previously unknown or ignored at Google, and which might be helpful to the company as it tries to improve its diversity policies and outcomes...
"The Most Authoritative Review Paper on Gender Differences"
-Sean Stevens, Heterodox Academy
...As we have scanned the literature to find the major meta-analyses and the most authoritative review articles, we have found one review article that stands above all others... It was written by a group of psychology’s top experts on these topics, a group that was put together to ensure a diversity of opinion among the authors... This august group, this all-star team, came together in part to address the controversy that erupted after Lawrence Summers offered his thoughts, in 2005, on the causes of women’s underrepresentation on the faculty in STEM departments at top universities.
The monograph they produced is magnificent. It is an example of psychology at its best, guiding readers through multiple massive literatures, showing no trace of partisan bias or commitment to any pre-ordained conclusion. The authors find, over and over again, that the sex differences we observe often have a biological basis yet are not direct readouts of biological processes; they emerge in the course of development in interaction with social processes, norms, and stereotypes in ways that can vary across cultures and decades.
We think this paper is the most complete and authoritative statement currently available. We therefore want to bring it to the attention of all those who are interested in the Damore memo, or who are interested in improving diversity policies and the status of women in the tech industry. The full paper is available online here...
[T]he science of gender is complicated; Damore was right that there are differences, and that biology is part of the reason for those differences. But it’s tricky to extrapolate out from those findings to conclusions about why women are under-represented at Google and in tech in general...
Citation: Halpern, D.F., Benbow, C.P., Geary, D.C., Gur, R.C., Hyde, J.S., & Gernsbacher, M.A. (2007). The science of sex differences in science and mathematics. Psychological Science in the Public Interest, 8(1), 1-51. ...
Abstract:
Amid ongoing public speculation about the reasons for sex differences in careers in science and mathematics, we present a consensus statement that is based on the best available scientific evidence. Sex differences in science and math achievement and ability are smaller for the mid-range of the abilities distribution than they are for those with the highest levels of achievement and ability. Males are more variable on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes; the reasons why males are often more variable remain elusive. Successful careers in math and science require many types of cognitive abilities.
Females tend to excel in verbal abilities, with large differences between females and males found when assessments include writing samples. High-level achievement in science and math requires the ability to communicate effectively and comprehend abstract ideas, so the female advantage in writing should be helpful in all academic domains.
Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized exams in mathematics and science. An evolutionary account of sex differences in mathematics and science supports the conclusion that, although sex differences in math and science performance have not directly evolved, they could be indirectly related to differences in interests and specific brain and cognitive systems. We review the brain basis for sex differences in science and mathematics, describe consistent effects, and identify numerous possible correlates.
Experience alters brain structures and functioning, so causal statements about brain differences and success in math and science are circular. A wide range of sociocultural forces contribute to sex differences in mathematics and science achievement and ability—including the effects of family, neighborhood, peer, and school influences; training and experience; and cultural practices.
We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways. There are no single or simple answers to the complex questions about sex differences in science and mathematics...
SUMMARY AND CONCLUSIONS
In this review of the current state of the evidence for cognitive and interest differences between the sexes and their putative biological, evolutionary, and social/environmental origins, we have presented a summary of what is known about sex differences and similarities in mathematical and science abilities based on the best available scientific evidence.
The popular media have sensationalized findings of sex differences, often presenting the latest finding without assessing the quality of the research that it was based on or using ‘‘person on the street interviews’’ about beliefs about sex differences as though they were as valid as a carefully executed program of research (e.g.,Conlin, 2003).
This monograph represents a consensus of expert opinion, from a group of scientists with diverse backgrounds, to the questions about sex and math and science achievement. We addressed questions concerning whether and when (in the lifespan) there are differences between males and females in the cognitive abilities that are important for success in careers requiring aptitude for and achievement in mathematics and science, and the extent to which sex differences in math and science abilities can be attributed to ‘‘innate’’ explanations, socialization, or the way these two types of influences reciprocally influence each other.
In this review, we have focused on a wide range of research in which reasonable data have accumulated that address these issues, which we summarize and draw conclusions from below.
Average Sex Differences in Cognitive Abilities
Psychologists often look for sex differences very early in life as clues to the relative contribution of biological and environmental contributions, reasoning that newborns have had fewer social interactions, so the earlier that sex differences are reliably found, the more likely they are assumed to be biological in origin.
This assumption is not fully supported by the biological literature because, for many species, sex differences are not evident in infancy and often do not emerge until the age of reproductive maturation. The simple distinction between cognitive sex differences that emerge early in life and those that emerge later does not rule out environmental effects, because the uterine environment affects the development of a fetus.
The role of prenatal environmental factors is an excellent example of the interaction of biological and environmental variables, which often become indistinguishable in their effects. It does not necessarily follow that differences found later in life are caused by social or environmental factors, because there are developmental timelines for biological processes, including the timing of puberty, the development of the forebrain, and the aging processes, all of which are also influenced by the environment.
Moreover, the tasks that infants can handle may be qualitatively different from tasks designed for adolescents, even if they are both labeled the same. For example, a verbal or spatial task for an infant is qualitatively different than a verbal or spatial task for an adolescent. With these caveats in mind, the usual finding across tasks is that males and females develop equally well in early cognitive skills that relate to quantitative thinking and knowledge of objects in the environment.
By the end of grade school and beyond, females perform better on assessments of verbal abilities when assessments are heavily weighted with writing and the language-usage items cover topics with which females are familiar; sex differences favoring females are much larger in these conditions than when assessments of verbal abilities do not include writing. In contrast, males excel on certain visuospatial-ability measures. Yet, of all the sex differences in cognitive abilities, differences in quantitative abilities have received the most attention because of the marked differences favoring males at the highest end of the ability distribution and because of their importance in so many occupations.
Male performance is more variable than that of females in quantitative and visuospatial abilities, which means that there are also more males at the low-ability end of these distributions. Because males tend to be more variable, the average difference in performance between females and males for most assessments is smaller than it is at the high- and low-ability tails of the distributions, and the size of the average between-sex difference is larger for tests such as the GRE that are administered to selective samples than it is for less selective tests such as the SAT or a high-school admissions test.
The fact that females achieve higher grades in school-based math and science tests and lower average scores on standardized exams used for college admissions and graduate school may point to differences in the strategies males and females use to solve novel problems (Gallagher & Cahalan, in press) and to the tendency of females to do better in most school contexts (Willingham & Cole,1997). Of course, the factors that enter into earning a high grade in a class are also different from those leading to high test scores on a standardized test.
Sex Differences in Math and Science Performance in the Tails of the Distribution
Substantial evidence suggests that the male advantage in mathematics is largest at the upper end of the ability distribution, a result that could provide important clues to the origin of this sex difference. In addition, a ‘‘tilt’’ favoring visuospatial or mathematical abilities compared to verbal, regardless of level of ability, is more frequently exhibited by males than by females.
Females tend to be more balanced in their ability profiles, which may lead them to choose mathematics or science careers less frequently than their male counterparts do. These differences can be seen as early as adolescence, and, therefore, a greater number of males than females may qualify for advanced training in disciplines that place a premium on mathematical reasoning and/or visuospatial abilities. Any differences that exist are increased if interests and activities that are correlated with abilities are considered.
An Evolutionary Account of Sex Differences in Math and Science
From an evolutionary perspective, sex differences in advanced math and science have not evolved in any direct way but could be indirectly related to differences in interests and to specific brain and cognitive systems that differ for females and males.
Evolutionary theories predict sex differences that arise from patterns of intrasexual competitions (for both males and females) and intersexual choice (for both females and males), including pressures that accompany the male-biased activities of hunters and warriors who traveled long distances in novel territory. Although a large body of data was presented that supports this theory, numerous criticisms have been raised as well. Many of its predictions remain to be tested, although several patterns are consistent with observed differences in interest and ability profiles.
Sex Differences in Brain Structure and Function
Studies of brain structure and function have suggested some potential biological mechanisms for the observed sex differences in ability. In general, females have a higher percentage of gray-matter brain tissue, whereas males have a higher volume of connecting white-matter tissue—with the exception of the splenium of the corpus callosum, which is more bulbous and, thus, larger in females than in males.
Furthermore, male brains show greater volumetric asymmetries than female brains do. The higher white-matter volume seems associated with better spatial performance in males, while the greater bilateral symmetry seems associated with better language processing in females.Although the advent of noninvasive techniques for functional brain imaging has allowed a rapid increase in the number of studies investigating sex differences in the regional functional specialization for cognition, these studies are in their infancy.
Future research of this type should involve larger and more carefully selected sample populations to avoid strong and potentially confounding cohort effects, and should employ longitudinal designs. Finally, hormones have been documented to affect cognition through their organizing effects on the brain.
Sociocultural Factors, Sex, and Math and Science Abilities
Sociocultural forces also influence sex differences in math and science abilities, academic-course choices, occupational choices, and occupational success in math and science careers. Compared with girls, boys seem to benefit more from enriched neighborhoods and to be hurt more by deprived neighborhoods. Schools certainly influence students’ learning and performance; research has documented systematic, subtle differences in the ways that teachers treat males compared with the ways they treat females in math and science classrooms.
Cross-cultural research demonstrates that the magnitude of sex differences in math performance varies across nations. In no country is the overall sex difference large prior to the end of secondary school, when the size of the sex difference begins to increase, although larger differences sometimes emerge earlier in specific mathematical areas (e.g., geometry).
Moreover, the magnitude of the sex difference correlates negatively with measures of gender equality in the country. Many women in math and science areas do report significant sex discrimination, and these experiences likely shape the direction their careers take. Finally, women’s roles may be part of the equation, as women still bear more responsibility for child care than do men and they work fewer hours. It also seems that being successful in a nontraditional career, such as engineering, may penalize women in the marriage market.
Closing comment, from Stevens and Haidt:
The Damore memo has elicited a great deal of controversy. In most written commentaries, you can tell what conclusions the author will reach after reading the first few sentences. Our goal in our posts here at Heterodox Academy is to help those who sincerely want to figure out the truth, and who therefore want to read competing analyses, and analyses by groups of experts that included some viewpoint diversity. When passions run high, viewpoint diversity is most needed.
As John Stuart Mill wrote, in On Liberty:
[T]he only way in which a human being can make some approach to knowing the whole of a subject, is by hearing what can be said about it by persons of every variety of opinion, and studying all modes in which it can be looked at by every character of mind. No wise man ever acquired his wisdom in any mode but this; nor is it in the nature of human intellect to become wise in any other manner.
...............
"The Greater Male Variability Hypothesis – An Addendum to our post on the Google Memo"
"Sex differences in the Big Five personality factors: Testing an evolutionary hypothesis" - Sergey V. Budaev
Sex differences in the Big Five personality structure… were examined in a student population (N=528) using factor analytic and covariance structure analysis techniques. An evolutionary hypothesis was tested, that the factor which lies between classical Agreeableness vs. Hostility and Neuroticism vs. Emotional Stability is the basic dimension of dominance-related aggressiveness maintained by frequency-dependent selection. The hypothesis predicts that this factor should explain more variance in males than in females. It was found that females were characterized by higher scores on the factor of Agreeableness and low Emotional Stability vs. Hostility and high Emotional Stability. As predicted, the factor of Agreeableness and low Emotional Stability explained significantly more variance in males than in females, both absolutely and in relation to other personality factors. The between-sex differences in personality factors are discussed in relation to studies of temperament, dominance and aggressiveness in non-human animals…
A consensus appeared during recent decades concerning the number and nature of the basic personality factors. The prevailing view postulates (see Digman, 1990; Goldberg, 1993) that human personality variation may be summarized by five major dimensions known as the Big Five: Extraversion..., Neuroticism vs. Emotional Stability, Agreeableness,
Conscientiousness and Intellect (or Openness to Experience).
The extreme ubiquity and stability of the Big Five personality dimensions may suggest that they have an important
adaptive significance (Buss, 1991): it is known that high levels of individual variability can be maintained by natural selection by means of density- or frequency-dependent mechanisms
(Krebs and Davies, 1993; also see Wilson et al., 1994 for risk-taking). Many behavioral and cognitive processes traditionally studied by psychologists have evolved through natural
selection to meet specific adaptive needs of our ancestors (Barkow et al., 1992). However, although the patterns of individual variability cannot be a priori considered an exception, at present it is not known what features of personality structure and to what extent, depend on the action of adaptive and non-adaptive (e.g. physiological or genetic constraints) mechanisms.
Sex differences in personality and temperament have been documented in many empirical studies (Buss and Plomin, 1984; Eysenck and Eysenck, 1985; Zuckerman, 1994; see also a recent meta-analysis by Feingold, 1994). There is no doubt that they have evolved in context of the major activities which influenced fitness of our ancestral species, such as social dominance, social exchange, mate choice etc. (Buss, 1991; Barkow et al., 1992). In most mammalian species, including Homo sapiens, males tend to be physically larger, more aggressive, dominance-oriented, risk-prone and exhibit lower investment in offspring than females; this is adaptive and reflects different reproductive strategies of the two sexes (Daly and Wilson, 1983; Eibl-Eibesfeldt, 1989).
As long as patterns of individual differences in aggressiveness are considered, there is a close correspondence between the dimensions of personality and aggression. Specifically, two basic dimensions of aggressive behavior were identified in humans, ``Emotional Responsivity'' and ``Proneness to Aggression'' and these dimensions are nearly isomorphic with Neuroticism and Agreeableness factors of the Big Five model (Caprara et al., 1994). Furthermore, a few studies (e.g. Caprara and Perugini, 1994; Ashton et al., 1998) have… [identified] a factor of high Emotional Stability and Hostility (as well as a factor of high Emotional Stability and Agreeableness). Also, the study of Zuckerman et al. (1988) revealed two coherent clusters of traits in the high Psychoticism – high Neuroticism and high Psychoticism – low Neuroticism quadrants, which seem to be related to, respectively, psychopathic and dominance-related aggression.
Thus, the broad factor which lies between Neuroticism and Agreeableness, may represent the basic dimension of dominance-oriented aggressive behavior in humans, which reflects adaptive individual differences and is presumably maintained by frequency-dependent selection. Indeed, in most animal species social dominance is associated not with just a high level of basic aggressiveness, but rather with a combination of aggressiveness and boldness (an analogue of Emotional Stability and Novelty Seeking), so that boldness often correlates with aggressiveness (Archer, 1988)…
The present analysis clearly confirmed the hypothesis concerning the pattern of sex differences in the Big Five personality factors. First, females showed, on average, significantly higher scores on the Agreeableness and low Emotional Stability factor than did males. Second, the differences between males and females were maximized along this factor and were not significant on all other factors except Extraversion, on which they were much smaller (but if
Extraversion is considered as ``boldness'', such sex difference is also expected on evolutionary grounds and is often found in non-humans). Third, the personality factor patterns did not
differ between males and females and the same Big Five dimensions were extracted in both.
Yet, there were significant structural differences: the factor Agreeableness and low Emotional Stability accounted for more variance in males than in females, both in absolute value and in relation to other factors of the Big Five model. All this suggests that the factor Agreeableness and Low Emotional Stability (vs. Hostility and high Emotional Stability) is an important axis, reflecting adaptive individual differences in dominance-related aggressiveness in the human species, maintained by frequency-dependent selection mechanisms.
It is important to note, however, that the PRF Dominance scale did not correlate with the factor Agreeableness and low Emotional Stability… Accordingly, this axis seems to be related to one's potential ability to dominate others and his/her predisposition to exploit them callously. However, it is unrelated to the actual tendency to be… bold… From the evolutionary viewpoint, the behavioral traits that promote dominance need not necessarily involve conscious willingness and aggressiveness (including instrumental aggression) would facilitate social dominance in our ancestral species. Even so, the PRF Dominance scale showed the largest magnitude of sex differences among the four markers of Extraversion.
As in most mammals, human males tend to be physically larger, more aggressive (both verbally and physically), risk-prone and engage in more dominance contests, which is
consistent across cultures (Daly and Wilson, 1983; Eibl-Eibesfeldt, 1989). This is mirrored in personality differences: it is commonly observed that males show higher levels of
aggressiveness, assertiveness and self-esteem but lower levels of anxiety, trust and tender-mindedness, especially nurturance (see Feingold, 1994). Very similar trends were observed in many nonhuman primates (e.g. Buirski et al., 1978; McGuire et al., 1994).
Thus, the broad personality factor which lies between Neuroticism and Agreeableness… may represent the basic dimension of dominance-oriented aggressive behavior in
humans. In majority of animal species social dominance is associated not with just a high level of basic aggressiveness, but rather with a combination of aggressiveness and emotional
stability, so that the latter typically correlates with aggressiveness (see Archer, 1988 for an extensive review)…
Even though aggressiveness itself is likely to be an important prerequisite for social dominance, emotional stability and stress resistance is required to maintain high status for more or less prolonged time. For example, dominant and subordinate baboons show dissimilar stress responsiveness reflected in different levels and dynamics of cortisol (Sapolsky, 1990, 1993). Similar trends were observed in inhibited and bold children (Kagan et al., 1988).
Finally, according to the psychophysiological model developed by Mazur (1994), dominance relationships are formed through manipulation of stress during the contest, so that the
individual who ``outstresses'' the opponent becomes the winner. Also important is that, to have an adaptive function, the trait must show nonzero heritability and many studies have shown that aggressiveness, neuroticism-anxiety and dominance tendencies have relatively high heritability levels (Plomin, 1986; Eaves et al., 1989).
If the factor of Agreeableness and low Emotional Stability really represents the basic dimension of dominance-related aggressiveness, it might be mediated to some extent by
testosterone level. As discussed in the recent review by Mazur and Booth (1998), there is evidence that circulating levels of this hormone correlates with aggressiveness, dominance,
antisocial behavior, as well as with responses to social challenge and stress resistance.
However, this link is highly variable between studies (Archer, 1991) and preliminary results from an ongoing meta-analysis (Archer, personal communication) indicate that dominance does not correlate better than aggressiveness. If this inconsistency at least in part depends on the use of scales which are only weakly related to dominance-related aggressiveness, it might be expected that the rotated personality factor of Agreeableness and low Emotional Stability could exhibit a more stable relationship with testosterone. Special analysis is necessary, however.
Finally, low poles of the two rotated dimensions, Agreeableness and low Emotional Stability
and Agreeableness and high Emotional Stability, seem to represent two types of sociopathy.
The high scores on hostility and high emotional stability resemble the description of primary sociopathy – cold and detached, with manipulative style of interpersonal relationships, Machiavellianism and lack of social emotions, whereas high scores on hostility and low emotional stability are similar to secondary sociopathy – psychopathy and antisocial behavior with no deficit in social emotions, such as anxiety, shame and guilt (Mealey, 1995; secondary psychopaths show increased levels of anxiety and guilt, see Gudjonsson and Roberts, 1983). In accord with the present results, sociopathy is significantly more common in males (see Mealey, 1995 and commentaries therein). Furthermore, it has been suggested (Archer, 1995), that primary sociopathy could be related to dominant behavior and represent an alternative frequency-dependent strategy with relatively high reproductive success, whereas the secondary sociopathy may be related to submissive behavior and, in the evolutionary sense, to ``making the best of a bad job''. Thus, primary sociopathy might be conceived as an exaggerated dominance tendency: propensity to control others, to obtain power or influence, in order to ultimately achieve high priority to valued resources.
Several studies corroborate this view, indicating that psychopathy correlates with hostile dominance (i.e. dominance and lack of nurturance, very similar to the present factor of Hostility and Emotional Stability vs. Agreeableness and low Emotional Stability, see Hoyenga, 1995 for references) and is a two-dimensional construct (Newman et al., 1985).
Sex differences in the Big Five personality structure… were examined in a student population (N=528) using factor analytic and covariance structure analysis techniques. An evolutionary hypothesis was tested, that the factor which lies between classical Agreeableness vs. Hostility and Neuroticism vs. Emotional Stability is the basic dimension of dominance-related aggressiveness maintained by frequency-dependent selection. The hypothesis predicts that this factor should explain more variance in males than in females. It was found that females were characterized by higher scores on the factor of Agreeableness and low Emotional Stability vs. Hostility and high Emotional Stability. As predicted, the factor of Agreeableness and low Emotional Stability explained significantly more variance in males than in females, both absolutely and in relation to other personality factors. The between-sex differences in personality factors are discussed in relation to studies of temperament, dominance and aggressiveness in non-human animals…
A consensus appeared during recent decades concerning the number and nature of the basic personality factors. The prevailing view postulates (see Digman, 1990; Goldberg, 1993) that human personality variation may be summarized by five major dimensions known as the Big Five: Extraversion..., Neuroticism vs. Emotional Stability, Agreeableness,
Conscientiousness and Intellect (or Openness to Experience).
The extreme ubiquity and stability of the Big Five personality dimensions may suggest that they have an important
adaptive significance (Buss, 1991): it is known that high levels of individual variability can be maintained by natural selection by means of density- or frequency-dependent mechanisms
(Krebs and Davies, 1993; also see Wilson et al., 1994 for risk-taking). Many behavioral and cognitive processes traditionally studied by psychologists have evolved through natural
selection to meet specific adaptive needs of our ancestors (Barkow et al., 1992). However, although the patterns of individual variability cannot be a priori considered an exception, at present it is not known what features of personality structure and to what extent, depend on the action of adaptive and non-adaptive (e.g. physiological or genetic constraints) mechanisms.
Sex differences in personality and temperament have been documented in many empirical studies (Buss and Plomin, 1984; Eysenck and Eysenck, 1985; Zuckerman, 1994; see also a recent meta-analysis by Feingold, 1994). There is no doubt that they have evolved in context of the major activities which influenced fitness of our ancestral species, such as social dominance, social exchange, mate choice etc. (Buss, 1991; Barkow et al., 1992). In most mammalian species, including Homo sapiens, males tend to be physically larger, more aggressive, dominance-oriented, risk-prone and exhibit lower investment in offspring than females; this is adaptive and reflects different reproductive strategies of the two sexes (Daly and Wilson, 1983; Eibl-Eibesfeldt, 1989).
As long as patterns of individual differences in aggressiveness are considered, there is a close correspondence between the dimensions of personality and aggression. Specifically, two basic dimensions of aggressive behavior were identified in humans, ``Emotional Responsivity'' and ``Proneness to Aggression'' and these dimensions are nearly isomorphic with Neuroticism and Agreeableness factors of the Big Five model (Caprara et al., 1994). Furthermore, a few studies (e.g. Caprara and Perugini, 1994; Ashton et al., 1998) have… [identified] a factor of high Emotional Stability and Hostility (as well as a factor of high Emotional Stability and Agreeableness). Also, the study of Zuckerman et al. (1988) revealed two coherent clusters of traits in the high Psychoticism – high Neuroticism and high Psychoticism – low Neuroticism quadrants, which seem to be related to, respectively, psychopathic and dominance-related aggression.
Thus, the broad factor which lies between Neuroticism and Agreeableness, may represent the basic dimension of dominance-oriented aggressive behavior in humans, which reflects adaptive individual differences and is presumably maintained by frequency-dependent selection. Indeed, in most animal species social dominance is associated not with just a high level of basic aggressiveness, but rather with a combination of aggressiveness and boldness (an analogue of Emotional Stability and Novelty Seeking), so that boldness often correlates with aggressiveness (Archer, 1988)…
The present analysis clearly confirmed the hypothesis concerning the pattern of sex differences in the Big Five personality factors. First, females showed, on average, significantly higher scores on the Agreeableness and low Emotional Stability factor than did males. Second, the differences between males and females were maximized along this factor and were not significant on all other factors except Extraversion, on which they were much smaller (but if
Extraversion is considered as ``boldness'', such sex difference is also expected on evolutionary grounds and is often found in non-humans). Third, the personality factor patterns did not
differ between males and females and the same Big Five dimensions were extracted in both.
Yet, there were significant structural differences: the factor Agreeableness and low Emotional Stability accounted for more variance in males than in females, both in absolute value and in relation to other factors of the Big Five model. All this suggests that the factor Agreeableness and Low Emotional Stability (vs. Hostility and high Emotional Stability) is an important axis, reflecting adaptive individual differences in dominance-related aggressiveness in the human species, maintained by frequency-dependent selection mechanisms.
It is important to note, however, that the PRF Dominance scale did not correlate with the factor Agreeableness and low Emotional Stability… Accordingly, this axis seems to be related to one's potential ability to dominate others and his/her predisposition to exploit them callously. However, it is unrelated to the actual tendency to be… bold… From the evolutionary viewpoint, the behavioral traits that promote dominance need not necessarily involve conscious willingness and aggressiveness (including instrumental aggression) would facilitate social dominance in our ancestral species. Even so, the PRF Dominance scale showed the largest magnitude of sex differences among the four markers of Extraversion.
As in most mammals, human males tend to be physically larger, more aggressive (both verbally and physically), risk-prone and engage in more dominance contests, which is
consistent across cultures (Daly and Wilson, 1983; Eibl-Eibesfeldt, 1989). This is mirrored in personality differences: it is commonly observed that males show higher levels of
aggressiveness, assertiveness and self-esteem but lower levels of anxiety, trust and tender-mindedness, especially nurturance (see Feingold, 1994). Very similar trends were observed in many nonhuman primates (e.g. Buirski et al., 1978; McGuire et al., 1994).
Thus, the broad personality factor which lies between Neuroticism and Agreeableness… may represent the basic dimension of dominance-oriented aggressive behavior in
humans. In majority of animal species social dominance is associated not with just a high level of basic aggressiveness, but rather with a combination of aggressiveness and emotional
stability, so that the latter typically correlates with aggressiveness (see Archer, 1988 for an extensive review)…
Even though aggressiveness itself is likely to be an important prerequisite for social dominance, emotional stability and stress resistance is required to maintain high status for more or less prolonged time. For example, dominant and subordinate baboons show dissimilar stress responsiveness reflected in different levels and dynamics of cortisol (Sapolsky, 1990, 1993). Similar trends were observed in inhibited and bold children (Kagan et al., 1988).
Finally, according to the psychophysiological model developed by Mazur (1994), dominance relationships are formed through manipulation of stress during the contest, so that the
individual who ``outstresses'' the opponent becomes the winner. Also important is that, to have an adaptive function, the trait must show nonzero heritability and many studies have shown that aggressiveness, neuroticism-anxiety and dominance tendencies have relatively high heritability levels (Plomin, 1986; Eaves et al., 1989).
If the factor of Agreeableness and low Emotional Stability really represents the basic dimension of dominance-related aggressiveness, it might be mediated to some extent by
testosterone level. As discussed in the recent review by Mazur and Booth (1998), there is evidence that circulating levels of this hormone correlates with aggressiveness, dominance,
antisocial behavior, as well as with responses to social challenge and stress resistance.
However, this link is highly variable between studies (Archer, 1991) and preliminary results from an ongoing meta-analysis (Archer, personal communication) indicate that dominance does not correlate better than aggressiveness. If this inconsistency at least in part depends on the use of scales which are only weakly related to dominance-related aggressiveness, it might be expected that the rotated personality factor of Agreeableness and low Emotional Stability could exhibit a more stable relationship with testosterone. Special analysis is necessary, however.
Finally, low poles of the two rotated dimensions, Agreeableness and low Emotional Stability
and Agreeableness and high Emotional Stability, seem to represent two types of sociopathy.
The high scores on hostility and high emotional stability resemble the description of primary sociopathy – cold and detached, with manipulative style of interpersonal relationships, Machiavellianism and lack of social emotions, whereas high scores on hostility and low emotional stability are similar to secondary sociopathy – psychopathy and antisocial behavior with no deficit in social emotions, such as anxiety, shame and guilt (Mealey, 1995; secondary psychopaths show increased levels of anxiety and guilt, see Gudjonsson and Roberts, 1983). In accord with the present results, sociopathy is significantly more common in males (see Mealey, 1995 and commentaries therein). Furthermore, it has been suggested (Archer, 1995), that primary sociopathy could be related to dominant behavior and represent an alternative frequency-dependent strategy with relatively high reproductive success, whereas the secondary sociopathy may be related to submissive behavior and, in the evolutionary sense, to ``making the best of a bad job''. Thus, primary sociopathy might be conceived as an exaggerated dominance tendency: propensity to control others, to obtain power or influence, in order to ultimately achieve high priority to valued resources.
Several studies corroborate this view, indicating that psychopathy correlates with hostile dominance (i.e. dominance and lack of nurturance, very similar to the present factor of Hostility and Emotional Stability vs. Agreeableness and low Emotional Stability, see Hoyenga, 1995 for references) and is a two-dimensional construct (Newman et al., 1985).
"Sex differences and sex similarities in disgust sensitivity," Tybura, et al.
Across two studies, we test for sex differences in the factor structure, factor loadings, concurrent validity, and means of the Three Domain Disgust Scale. In Study 1, we find that the Three Domain Disgust Scale has indistinguishable factor structure and factor loadings for men and women. In Study 2, we find a small sex difference in sensitivity to pathogen and moral disgust and a large sex difference in sensitivity to sexual disgust, with women more sensitive to disgust across domains. However, correlations between Three Domain Disgust Scale factors and the five factors and 30 facets of the NEO Personality Inventory were indistinguishable between the sexes. These findings suggest that, despite mean sex differences in disgust sensitivity, the Three Domain Disgust Scale measures similar constructs in men and women. Implications for understanding the constructs measured by the Three Domain Disgust Scale are discussed.
Across two studies, we test for sex differences in the factor structure, factor loadings, concurrent validity, and means of the Three Domain Disgust Scale. In Study 1, we find that the Three Domain Disgust Scale has indistinguishable factor structure and factor loadings for men and women. In Study 2, we find a small sex difference in sensitivity to pathogen and moral disgust and a large sex difference in sensitivity to sexual disgust, with women more sensitive to disgust across domains. However, correlations between Three Domain Disgust Scale factors and the five factors and 30 facets of the NEO Personality Inventory were indistinguishable between the sexes. These findings suggest that, despite mean sex differences in disgust sensitivity, the Three Domain Disgust Scale measures similar constructs in men and women. Implications for understanding the constructs measured by the Three Domain Disgust Scale are discussed.