Most Trusted Review Article on Gender Differences - (2023)

This blog post is a companion to our main post: The Google Memo: What Does Research Say About Gender Differences? Please read at least the introduction to this post before proceeding.

When we searched the literature for the most important meta-analyses and the most reliable reviews, we found a review article that stands out from all the others, partly for its depth and scope (it has 41 pages), but mainly for its authorship. It was written by a group of the best psychology experts on these topics, a group assembled to ensure diversity of opinion among the authors. The first author is Diane Halpern, professor emeritus at Claremont McKenna College, former president of the American Psychological Association and author of the bookGender differences in cognitive skills. One author is Janet Shibley Hyde, a professor at the University of Wisconsin-Madison, whose publications generally indicate small and shrinking gender differences (her meta-analyses feature prominently in our main article). Another author is David Geary, author ofMan, woman: the origin of human gender differences, whose publications tend to indicate more substantial effects. (Here's Geary on the Damore memo.) Also on board are Camilla Benbow, an educational psychologist at Vanderbilt University who researches intellectually gifted students and a former vice chair of the President's National Mathematics Advisory Panel (of which Geary was a member). ; Ruben Gura, a clinical psychologist at the University of Pennsylvania who studies brain-behavioral relationships; and Morton Ann Gernsbacher, a professor at the University of Wisconsin-Madison who studies the cognitive and neural mechanisms underlying human communication. She is also past president of the Association for Psychological Science.

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Most Trusted Review Article on Gender Differences - (1)

This august group, this all-star team, came together in part to address the controversy that arose after Lawrence Summers laid out his thoughts in 2005 on the causes of women's underrepresentation in STEM departments at leading universities.

The monograph they produced is great. It is an example of psychology at its finest, taking readers through several voluminous works of literature and showing no trace of prejudice or commitment to any predetermined conclusion. The authors consistently point out that the sex differences we observe often have a biological basis but are not direct indicators of biological processes; they emerge in the course of development in interaction with social processes, norms and stereotypes in different ways across cultures and decades.

We believe this document is the most comprehensive and authoritative explanation currently available. Therefore, we would like to bring this to the attention of anyone interested in Damore's memo or interested in improving diversity policies and the status of women in tech. The full document is available online here. But to make it even more accessible, we've included the full text of its summary below, followed by a summary of its contents, followed by the full text of its conclusion.

Continuing our main blog post's practice of showing text that generally supports Damore's claims in green and text that generally supports his detractors in red. We do this not to show that he was absolutely right or wrong, but to show that the science of sex is complicated; Damore was right that there are differences and that biology is part of the reason for those differences. But it's hard to draw conclusions from these results about why women are underrepresented at Google and in technology more generally. See circular template in section 8 of the document below. We also highlight other important areas of the text.bold. We're doing this to bring attention to other important findings that may not be directly related to the Damore memo controversy.

Quote:Halpern, D.F., Benbow, C.P., Geary, D.C., Gur, R.C., Hyde, J.S., & Gernsbacher, MA (2007). The science of gender differences in science and mathematics.Psychological Science in the Public Interest, 8(1), 1-51.(no doors)


Amid continuing public speculation about the reasons for gender disparities in math and science courses, we present a consensus statement based on the best available scientific evidence about the distributions of abilities among those with the highest levels of achievement and ability. Men are more variable in most quantitative and visuospatial skills, which inevitably leads to more men in high and low skills; the reasons why men tend to be more variable remain elusive. Successful math and science careers require many types of cognitive skills.Women tend to excel in verbal ability, and large differences between women and men are found when tests include handwriting samples.Excelling in science and math requires the ability to communicate effectively and understand abstract ideas, so women's advantage in writing in all academic fields should help address gender differences in standardized math and science tests. An evolutionary account of gender differences in math and science supports the conclusion that while gender differences in math and science performance did not evolve directly, they may be indirectly related to differences in interests and specific brain and cognitive systems. We examine the brain basis for gender differences in science and math, describing consistent effects and identifying numerous possible correlations. Experience alters brain structure and function, so causal claims about brain differences and success in math and science are circular. A wide range of sociocultural forces contribute to gender differences in math and science achievement and skills, including the effects of family, neighborhood, peer, and school influences; Training and experience; and cultural practices. We conclude that early experiences, biological factors, educational policies and cultural context affect the number of women and men pursuing advanced studies in science and mathematics, and that these effects are additive and interact in complex ways. There are no single or simple answers to the complex questions about gender differences in science and math.

paper outline:

  1. introduction
  2. define terms
    • sex and gender
    • biological and innate
    • skills and performance
    • intelligence and IQ
    • The test score disparity
    • The size of an effect
  3. The what, when, and where of gender differences in math and science performance
  4. Mean gender differences in cognitive abilities
    • Cognitive gender differences in childhood
    • verbal skills
    • average verbal ability
    • variability in verbal skills
    • visuospatial skills
    • Visual-spatial skills and computer games.
    • quantitative skills
    • Trends over time in average skills
    • Racial and Ethnic Differences in Average Skills
    • A taxonomy of medium-capacity cognitive processes
  5. Gender differences in math and science skills at the tails of the distribution
    • Gender differences in distributions and variances
    • Gender differences in mathematical thinking among gifted students
    • Gender differences in higher education
    • Gender differences in professional development
    • Visual spatial ability and careers in math and science
    • Additional factors influencing gender differences in gifted students' career choices
  6. An evolutionary explanation of sex differences in math and science
    • sexual selection
    • sex hormones
    • variation within sex
    • Development
    • An evolutionary understanding of human sex differences
    • sexual selection
    • Sex hormones and cognitive gender differences
    • variation within sex
    • Development
    • Critique of evolutionary explanations of sex differences in science and mathematics
  7. Sex differences in brain structure and function.
    • Gender differences in brain structure.
    • Sex differences in brain volume
    • Sex differences in the structure of the corpus callosum
    • The need for evolutionary and longitudinal studies
    • Gender differences in brain function
    • Sex differences in cerebral blood flow
    • Sex differences in brain glucose metabolism
    • Gender differences in neurotransmitter function
    • Brain imaging, math and science
    • Speculative hypotheses about the relationship of neural structures to science and mathematics
    • single sex schools
  8. The biopsychosocial model: an integration of nature and nurture
  9. Sociocultural forces, sex, math and science.
    • Influences from family, neighborhood, peers, and society
    • stereotype threat
    • training studies
    • cross-cultural analysis
    • Sociocultural influences on work culture
    • Gender discrimination and professional success
    • female roles
  10. Summary and conclusions (see below for full text)
    • Mean gender differences in cognitive abilities
    • Gender differences in math and science performance at the tails of the distribution
    • An evolutionary explanation of sex differences in math and science
    • Sex differences in brain structure and function.
    • Sociocultural factors, gender, and math and science skills


In this review of the current state of evidence on cognitive and interest differences between the sexes and their putative biological, developmental, and social/environmental origins, we present a summary of what is known about gender differences and similarities in abilities. science Based on the best scientific knowledge available.The popular media sensationalized gender difference findings, often presenting the latest findings without assessing the quality of the research they are based on, or using "street interviews" about beliefs about gender differences as if they were as valid as a poll. carefully conducted research program (eg Conlin, 2003).This monograph represents a consensus of expert opinion from a group of scholars from diverse backgrounds on gender issues and achievement in mathematics and science.We investigated whether and when (across the life course) there are differences between men and women in cognitive abilities that are important for success in mathematical and scientific performance and aptitude occupations, and the extent to which gender differences in mathematics and abilities Mathematical scientists they can be “innate”. ' explanations, socialization, or the ways in which these two types of influences affect each other. In this review, we focus on a wide range of research that has accumulated reasonable data addressing these questions, from which we summarize and draw conclusions.

Mean gender 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, arguing that newborns had fewer social interactions. Therefore, the earlier sex differences are reliably found, the more likely they are to be considered biological. This assumption is not fully supported by the biological literature, as sex differences are not apparent in many species during childhood and often do not become apparent until adulthood. age of reproductive maturation. Simply distinguishing between cognitive sex differences that appear early in life and those that appear later in life does not rule out environmental influences, since the uterine environment influences fetal development.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 the differences found later in life are caused by social or environmental factors, as there are developmental timelines for biological processes, including the timing of puberty, forebrain development, and aging processes, all of which are also present and affected. by the environment. . Furthermore, the tasks infants may perform may be qualitatively different from tasks assigned to adolescents, even though both are labeled as the same. For example, a verbal or spatial task for an infant is qualitatively different from a verbal or spatial task for an adolescent. With these caveats in mind, the common finding in any task is that men and women perform equally well on early cognitive skills related to quantitative reasoning and knowledge of objects in the environment.

By the end of primary school and beyond, women perform better on assessments of verbal skills when the assessment leans heavily toward writing and language use tasks cover topics with which women are familiar; Gender differences favoring women are much greater under these conditions than when the assessment of verbal ability does not include writing. In contrast, men excel in certain visuospatial skills. However, of all the sex differences in cognitive ability, differences in quantitative ability have attracted the most attention because of the marked differences that favor men at the upper end of the ability distribution and because of their importance in many occupations.

Men's performance is more variable than women's in terms of quantitative and visuospatial skills, which means that there are also more men at the lower end of these distributions. Because men tend to be more variable, the mean difference in performance between women and men is smaller on most assessments than at the extreme ends of the high- and low-ability distributions, and the magnitude of the mean difference in Gender is greater on tests such as the GRE, which are sampled more selectively than less selective tests like the SAT or a high school entrance test. The fact that women scored higher and lower grade point averages on school tests in math and science on the standardized tests used for college and graduate admission may indicate differences in the strategies used by men and women to solve new problems. (Gallagher & Cahalan, in press). ) and the tendency of women to perform better in most academic contexts (Willingham & Cole, 1997). Of course, the factors for getting a good grade in a class are different than those for getting high scores on a standardized test.

Gender differences in math and science performance at the tails of the distribution

Substantial evidence suggests that male math advantage is greatest at the higher end of the ability distribution, a finding that may provide important clues to the origin of this gender gap. Furthermore, a 'bias' favoring visuospatial or mathematical skills over verbal skills, regardless of skill level, is exhibited more often by men than by women. Women tend to be more balanced in their skill profiles, which may mean they are less likely to choose math or science courses than their male counterparts. These differences are already evident in adolescence and therefore more men than women may qualify to continue their education in subjects where mathematical reasoning and/or visuospatial skills are emphasized. Existing differences are magnified when interests and activities that correlate with abilities are taken into account.

An evolutionary explanation of sex differences in math and science

From an evolutionary perspective, gender differences in math and advanced science did not evolve directly, but may be indirectly related to differences in interest and specific cognitive and brain systems that differ in women and men. Evolutionary theories predict sex differences arising from patterns of intrasexual competition (for both males and females) and intersex choices (for both females and males), including the pressures that accompany the male activities of hunters and warriors who have traveled long distances in new territories . While a large amount of data has been presented to support this theory, there have also been numerous criticisms. Many of their predictions have yet to be tested, although several patterns are consistent with observed differences in interest and skill profiles.

Sex differences in brain structure and function.

Studies of brain structure and function have suggested some potential biological mechanisms for observed gender differences in performance. In general, females have a greater proportion of brain tissue that is gray matter, whereas males have a greater volume of connective tissue that is white matter, with the exception of the splenium of the corpus callosum, which is more bulbous and therefore larger in females than females. than in females. men.

Furthermore, male brains exhibit greater volumetric asymmetries than female brains. Greater white matter volume appears to be related to better spatial performance in men, while greater bilateral symmetry appears to be related to better language processing in women. functional specialization for cognition, these studies are still in their infancy. Future research of this type should include larger, carefully selected sample populations to avoid strong and potentially confounding cohort effects, and should use longitudinal designs. Finally, hormones have been documented to affect cognition through their organizing effects in the brain.

Sociocultural factors, gender, and math and science skills

Sociocultural forces also influence gender differences in math and science skills, academic course choices, career choices, and professional success in math and science. Compared to girls, boys seem to benefit more from rich neighborhoods and suffer more from poor neighborhoods. Schools certainly influence student learning and performance; Research has documented both systematic and subtle differences in the way math and science teachers treat men compared to the way they treat women. Cross-cultural research shows that the magnitude of the gender gap in math performance varies from country to country.

In no country is the overall gender disparity large before the end of secondary education, when the size of the gender gap starts to widen, although sometimes the greatest disparities appear earlier in certain mathematical domains (eg geometry). Gender differences are negatively correlated with gender equality. policies in the country. Many women in math and science report significant gender discrimination, and these experiences likely shape the direction their careers take. Finally, women's roles can be part of the equation, as women still have more childcare responsibilities than men and work fewer hours. It also appears that success in a non-traditional career such as engineering can put women at a disadvantage in the marriage market.

Concluding remarks from Stevens and Haidt:

Damore's memo generated a lot of controversy. In most written comments, you can see what conclusions the author comes to after reading the first few sentences. Our goal in our contributions here at Heterodox Academy is to help those who sincerely want to discover the truth and who therefore want to read competitive analysis and think tank reviews that contain a certain diversity of viewpoints. When passions rise, diversity of views is most needed.

As John Stuart Mill wrote in On Liberty:

The only way in which a man can approach a subject as a whole is by listening to what people of all opinions can say about it, and studying all the ways in which it can be seen by all the characters of the mind. No sage ever attained his wisdom otherwise than in this way; Nor is it the nature of the human intellect to become wise in any other way.


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