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Sex Differences in Variability in General Intelligence: A New Look at the Old Question

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Abstract

The idea that general intelligence may be more variable in males than in females has a long history. In recent years it has been presented as a reason that there is little, if any, mean sex difference in general intelligence, yet males tend to be overrepresented at both the top and bottom ends of its overall, presumably normal, distribution. Clear analysis of the actual distribution of general intelligence based on large and appropriately population-representative samples is rare, however. Using two population-wide surveys of general intelligence in 11-year-olds in Scotland, we showed that there were substantial departures from normality in the distribution, with less variability in the higher range than in the lower. Despite mean IQ-scale scores of 100, modal scores were about 105. Even above modal level, males showed more variability than females. This is consistent with a model of the population distribution of general intelligence as a mixture of two essentially normal distributions, one reflecting normal variation in general intelligence and one refecting normal variation in effects of genetic and environmental conditions involving mental retardation. Though present at the high end of the distribution, sex differences in variability did not appear to account for sex differences in high-level achievement. © 2008 Association for Psychological Science.

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... Taking the variability of scores into account may help explain potential differences in mean scores and better understand the distribution of intelligence scores according to sex. Several studies have indicated a greater variability of intelligence scores for males than for females [19,35], with an overrepresentation of males in the lower and higher tail of the distribution [36][37][38]. Greater male variability in intelligence scores has been historically explained both by biological and environmental factors (for extensive review see [37]) or an interaction between the two sources of sex differences [36]. Looking from the developmental perspective, greater male variability has been demonstrated also for brain structure [39] and several different physical properties that are unrelated or indirectly related to intelligence [40]. ...
... Several studies have indicated a greater variability of intelligence scores for males than for females [19,35], with an overrepresentation of males in the lower and higher tail of the distribution [36][37][38]. Greater male variability in intelligence scores has been historically explained both by biological and environmental factors (for extensive review see [37]) or an interaction between the two sources of sex differences [36]. Looking from the developmental perspective, greater male variability has been demonstrated also for brain structure [39] and several different physical properties that are unrelated or indirectly related to intelligence [40]. ...
... Consistent with the previous findings [19,25,37,38], the current research demonstrated greater boys' variance and the overrepresentation of boys in the lower and higher tail of the distribution when examining the full age range two to eight. Nevertheless, the differences in the IQ score distribution were less pronounced than in the previous studies and less consistent across age. ...
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The aim of this study was to investigate sex similarities and differences in visuospatial and fluid abilities and IQ scores based on those abilities in children aged two to eight. Standardization data from the Snijders-Oomen Nonverbal Intelligence Test for Children aged 2–8 (SON-R 2–8) were used. A representative sample composed of 965 children from the Netherlands and 762 children from Germany was examined. Small but significant mean sex differences favoring girls were observed until age four. At ages six and seven, boys achieved similar cognitive development levels to girls regarding all abilities assessed and outperformed girls on the Mosaics subtest measuring visuospatial cognition. Boys also displayed higher variability rates in performance. The distribution of IQ scores, with the overrepresentation of girls scoring above mean and the overrepresentation of boys scoring below mean in early childhood, altered with age towards parity between the sexes. The results suggest that girls tend to mature earlier with respect to cognitive abilities. During the course of development, however, the differences between girls and boys may become negligible.
... Most commentators agree that sex differences in cognitive aptitudes are too small to explain STEM gender gaps in their entirety, and that sex differences in occupational preferences are a much more important contributor (Ceci et al., 2009;Dekhtyar et al., 2018;Johnson et al., 2008;Wai et al., 2018). Still, the evidence for the cognitive differences is robust, and it is perfectly plausible that they help to shape men and women's career choices and trajectories. ...
... As well as greater male variability in specific cognitive aptitudes, males may be more variable in general cognitive ability or IQ (Deary et al., 2007;Feingold, 1992;Strand et al., 2006). The gold-standard study on this topic is Johnson et al. (2008). Unlike earlier studies, which used potentially unrepresentative samples, Johnson and colleagues utilized IQ data from two population-wide surveys of 11-year-old school children in Scotland. ...
... It is important to emphasize that this could not be a complete explanation of observed STEM gender gaps. As various experts have pointed out, sex differences in variability are not nearly large enough to explain these gaps in their entirety (Hyde, 2014;Johnson et al., 2008;O'Dea et al., 2018). Moreover, variability differences would not explain gender gaps at lower levels of the STEM hierarchy (where extreme abilities are not required), and would not explain why the gaps are larger in some fields than others. ...
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[Now in print; published version here: https://www.researchgate.net/publication/348295173_Men_Women_and_STEM_Why_the_Differences_and_What_Should_Be_Done] It is a well-known and widely lamented fact that men outnumber women in a number of fields in STEM. The most commonly discussed explanations for the gender gaps are discrimination and socialization, and the most common policy prescriptions target those ostensible causes. However, a great deal of evidence in the behavioural sciences suggests that discrimination and socialization are only part of the story. The purpose of this paper is to highlight other aspects of the story: aspects that are commonly overlooked or downplayed. More precisely, the paper has two main aims. The first is to examine the evidence that factors other than workplace discrimination contribute to the gender gaps in STEM. These include relatively large average sex differences in career and lifestyle preferences, and relatively small average differences in cognitive aptitudes – some favouring males, others favouring females – which are associated with progressively larger differences the further above the average one looks. The second aim is to examine the evidence suggesting that these sex differences are not purely a product of social factors but also have a substantial biological (i.e., inherited) component. A more complete picture of the causes of the unequal sex ratios in STEM may productively inform policy discussions.
... Another, smaller study suggested that informant reports of personality may yield higher variance ratios than self-reports, up to about 1.20 (Borkenau et al., 2013b). Large studies of IQ scores found variance ratios of up to 1.20 in children (Arden & Plomin, 2006), and 1.13-1.19 in young adolescents (Johnson et al., 2008). The authors of the latter study also attempted to estimate the non-clinical distribution of IQ, by removing low scores that were likely due to disruptive developmental conditions. ...
... After this correction, the estimated variance ratios decreased to 1.08-1.09 (see Table 1 in Johnson et al., 2008). ...
... Informant reports may yield values as high as 0.09. For IQ scores in adolescents (where the assumption of equal means holds to a close approximation; see Johnson et al., 2008), the lnVR values are 0.06 to 0.09 for the empirical distribution, and 0.04 for the estimated nonclinical distribution. Notably, these effect sizes are very similar to the lnCVR values found in studies of non-human animals; taken together, the available data suggest a plausible range of about 0.02 to 0.09 for traits showing greater male variability. ...
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Harrison et al. (2021) set out to test the greater male variability hypothesis with respect to personality in non-human animals. Based on the non-significant results of their meta-analysis, they concluded that there is no evidence to support the hypothesis, and that biological explanations for greater male variability in human psychological traits should be called into question. Here, we show that these conclusions are unwarranted. Specifically: (a) in mammals, birds, and reptiles/amphibians, the magnitude of the sex differences in variability found in the meta-analysis is entirely in line with previous findings from both humans and non-human animals; (b) the generalized lack of statistical significance does not imply that effect sizes were too small to be considered meaningful, as the study was severely underpowered to detect effect sizes in the plausible range; (c) the results of the meta-analysis can be expected to underestimate the true magnitude of sex differences in the variability of personality, because the behavioral measures employed in most of the original studies contain large amounts of measurement error; and (d) variability effect sizes based on personality scores, latencies, and proportions suffer from lac of statistical validity, adding even more noise to the meta-analysis. In total, Harrison et al.'s study does nothing to disprove the greater male variability hypothesis in mammals, let alone in humans. To the extent that they are valid, the data remain compatible with a wide range of plausible scenarios.
... Most commentators agree that sex differences in cognitive aptitudes are too small to explain STEM gender gaps in their entirety, and that sex differences in occupational preferences are a much more important contributor (Ceci et al., 2009;Dekhtyar et al., 2018;Johnson et al., 2008;Wai et al., 2018). Still, the evidence for the cognitive differences is robust, and it is perfectly plausible that they help to shape men and women's career choices and trajectories. ...
... As well as greater male variability in specific cognitive aptitudes, males may be more variable in general cognitive ability or IQ (Deary et al., 2007;Feingold, 1992;Strand et al., 2006). The gold-standard study on this topic is Johnson et al. (2008). Unlike earlier studies, which used potentially unrepresentative samples, Johnson and colleagues utilized IQ data from two population-wide surveys of 11-year-old school children in Scotland. ...
... It is important to emphasize that this could not be a complete explanation of observed STEM gender gaps. As various experts have pointed out, sex differences in variability are not nearly large enough to explain these gaps in their entirety (Hyde, 2014;Johnson et al., 2008;O'Dea et al., 2018). Moreover, variability differences would not explain gender gaps at lower levels of the STEM hierarchy (where extreme abilities are not required), and would not explain why the gaps are larger in some fields than others. ...
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It is a well-known and widely lamented fact that men outnumber women in a number of fields in STEM (science, technology, engineering and maths). The most commonly discussed explanations for the gender gaps are discrimination and socialization, and the most common policy prescriptions target those ostensible causes. However, a great deal of evidence in the behavioural sciences suggests that discrimination and socialization are only part of the story. The purpose of this paper is to highlight other aspects of the story: aspects that are commonly overlooked or downplayed. More precisely, the paper has two main aims. The first is to examine the evidence that factors other than workplace discrimination contribute to the gender gaps in STEM. These include relatively large average sex differences in career and lifestyle preferences, and relatively small average differences in cognitive aptitudes – some favouring males, others favouring females – which are associated with progressively larger differences the further above the average one looks. The second aim is to examine the evidence suggesting that these sex differences are not purely a product of social factors but also have a substantial biological (i.e. inherited) component. A more complete picture of the causes of the unequal sex ratios in STEM may productively inform policy discussions.
... Gender differences in the distribution of ability scores have become a research topic of interest since Ellis's pioneering thesis on the greater male variability hypothesis, which posits that men show greater interindividual variability than women do in regard to a wide range of physical and psychological attributes (Ellis, 1894(Ellis, /1934, including intellectual abilities (Hedges and Nowell, 1995;Johnson et al., 2008). By highlighting wider variances for men than women in score distributions, this hypothesis is insightful in terms of understanding why men may outnumber women among the highest and the lowest scoring individuals in samples that show trivial gender differences in mean scores (Hyde, 2014;Reilly et al., 2019). ...
... Furthermore, a VR that equals 1.0 represents equal variabilities in both genders (see Feingold, 1992;Hedges and Nowell, 1995). Using this operationalization 1 , many empirical findings have shown that VRs greater than 1.0 were found in general intelligence (Deary et al., 2003;Johnson et al., 2008), 1 This operationalization depends on which variance is used as numerator or denominator. The operationalization used in this study is to facilitate the interpretation of a result in relation to the hypothesis (i.e., greater male variability). ...
... Greater male variability is represented by an excess of men (e.g., a male/female ratio greater than 1.0) at the high (indicating superior performance) and low (indicating inferior performance) extremes of the score distribution (Deary et al., 2003). For example, researchers reported greater representation of men at both the upper and lower extremes of the IQ score distribution (e.g., Deary et al., 2003;Johnson et al., 2008). Similarly, He and Wong (2014) documented greater male representation at both the upper and lower extremes of the score distribution for intellectual overexcitability (boy/girl ratios = 2.44-2.57) ...
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The present study examined gender differences in the distribution of creative abilities through the lens of the greater male variability hypothesis, which postulated that men showed greater interindividual variability than women in both physical and psychological attributes (Ellis, 1894/1934). Two hundred and six (51.9% female) undergraduate students in Hong Kong completed two creativity measures that evaluated different aspects of creativity, including: (a) a divergent thinking test that aimed to assess idea generation and (b) a creative problem-solving test that aimed to assess restructuring ability. The present findings extended the research of greater male variability in creativity by showing that men generally exhibited greater variance than women in the overall distribution of the creativity scores in both divergent thinking and creative problem solving, despite trivial gender differences in mean scores. The findings further enriched the discourse of the greater male variability hypothesis by showing interesting domain-specific gendered patterns: (1) greater male variability was more likely to occur in figural forms of creativity, with larger effect sizes, when compared to the variability in verbal forms of creativity; and (2) mixed gendered patterns were found in the upper tails of the creativity score distribution with respect to the verbal domain but not the figural one, despite greater male representation being consistently observed in the lower tail of the distribution. Possible underlying mechanisms and implications were discussed.
... On huomattu, että miesten osuus erilaisten ilmiöiden kuten älykkyyden, osaamisen tai tulojen ääripäissä on suurempaa kuin naisten osuus (ks. Baye & Monseur, 2016;Johnson, Carothers, & Deary, 2008;O'Dea, Lagisz, Jennions, & Nakagawa, 2018 X-kromosomi on paljon Y-kromosomia suurempi ja sisältää huomattavasti enemmän geenejä kuin Y-kromosomi. Näin X-kromosomin kautta periytyvissä geeneissä ajatellaan olevan suurempi variaatio molempiin suuntiin kuin Y-kromosomin kautta periytyvissä geeneissä. ...
... Jo 150 vuoden ajan (ks. historiastaJohnson, Carothers, & Deary, 2008) ilmiölle on ehdotettu perinnöllisyyteen liittyvää osaselitystä. ...
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In autumn 2018, FINEEC assessed the skills of first-grade pupils at the beginning of their schooling. The assessment was called the starting level measurement. A total of 7,770 pupils from different parts of Finland participated in it in the basic sample. The starting level measurement assessed skills related to mathematics and mother tongue and literature. Its main results were published in the first report in autumn 2019. They were based on assignments that pupils completed at school during their first school weeks. According to the results, pupils’ skills were similar across Finland and showed little variation based on gender, the area of the regional state administrative agency or the language of instruction in the school. However, there were great differences in the skills of individuals. This report describes the link between background factors and the pupil’s skills. In conjunction with the assessment, background information was collected from pupils’ guardians. Background information was obtained on 4,316 pupils. The average of these pupils’ results was 516 points, while it was 500 points for the entire material. This means that background information was missing especially on pupils whose skills were weaker than average. The same risk factors were linked to a weaker-than-average starting level in both mathematics and mother tongue: a decision on intensified or special support issued before starting school, the syllabus of Finnish or Swedish as a second language, close relatives with learning difficulties, birthday towards the end of the year and the guardians’ low educational background. The skills of pupils studying the S2 syllabus (Finnish as the second language) were approximately 80 points lower than the skills of pupils studying Finnish or Swedish as their mother tongue. The impact of one learning difficulty diagnosed in close relatives on the child’s skills was approximately 30 points and the impact of two learning difficulties approximately 50 points. In the material, one out of ten children starting basic education had already been issued a decision on either intensified or special support before starting school. Children in these groups scored approximately 100 points lower in the assignments in both mathematics and mother tongue. One of the factors explaining pupils’ skills was also the educational background of their guardians. If at least one of the guardians in the family had completed a degree in higher education, the pupil’s skills were on average approximately 100 points higher than the skills of pupils whose guardians had not completed an education higher than basic education. The guardians’ high educational background seemed to benefit boys, in particular. The number and diversity of the pupil’s hobbies were also linked with their skills. The hobby most correlating with the skills was reading, which covered both the child reading himself or herself and reading aloud to the child. Based on the survey carried out among the guardians, reading appeared to be a hobby especially in educated families. Children’s early childhood education and care paths were not directly linked with the starting level. Various early childhood education and care paths can produce good skills. However, it seems that the children most benefitting from full-time early childhood education and care are children who have several risk factors predicting a weak starting level. The starting level measurement provided information on pupils’ starting level at the beginning of comprehensive school. It started a longitudinal assessment of learning outcomes in which the development of skills related to mathematics and mother tongue and literature will be followed during basic education. The next assessment of the same pupils’ skills will be carried out at the beginning of grade 3 in autumn 2020 to obtain information on how school increases skills during the first two years of education. Keywords: assessment, basic education, early primary education, evaluation, learning outcomes, literacy, mathematics, mother tongue and literature
... However, Warne (2019) noted that Terman's sample composition was not notably biased, as the population of California at that time was mostly Caucasian, and the overrepresentation of middle-and upper-class families was expected given the positive correlation between intelligence and SES. The same is true for the overrepresentation of males, given males' larger variability in intelligence (e.g., Johnson et al., 2008;Warne, 2019). ...
... In line with research on gender differences in intelligence variance (e.g., Johnson et al., 2008), there were more boys than girls in our gifted sample, whereas there were somewhat more girls than boys among the average-ability students, v 2 (1) ¼ 5.59, p ¼ .018, u ¼ -.06. ...
Article
Terman’s study was the first to systematically document the lives of the intellectually gifted. This cross-sectional study replicates and extends some of Terman’s findings on characteristics of the gifted in childhood, comparing largely unselected samples of gifted ( n = 50) and average-ability ( n = 50) adolescents matched by means of propensity score matching. Students were compared on their school performance (standardized math and reading tests and grades), motivation (math ability self-concept, intrinsic motivation, vocational interests, and educational aspirations), parental educational expectations, students’ evaluation of school instruction (perceived quality and pressure), and subjective well-being. The gifted scored higher on math performance (rank-biserial r = .66/.81), math ability self-concept (.71), intrinsic motivation (.62), and investigative vocational interests (.65). Some smaller differences were found for realistic (.42) and social interests (–.37) and for pressure in math lessons (–.52). Results support Terman’s findings on gifted individuals’ psychological functioning and contradict negative stereotypes about the gifted.
... Geary suggested that heritable and environmentally caused differences in mitochondrial functioning affect the integrity and efficiency of neurons and supporting glia cells and may thus contribute to individual differences in higher-order cognitive functioning and physical health. His theory aimed to account for different phenomena of intelligence research, including the positive manifold (Spearman 1904), the association between intelligence and health (Batty et al. 2007;Deary 2008;Der et al. 2009) 1 , the joint age-related decline in performance across different cognitive domains (Rhemtulla and Tucker-Drob 2011;Salthouse 2009;Salthouse and Ferrer-Caja 2003;Tucker-Drob 2011;Tucker-Drob et al. 2014), and the greater variability in intelligence test scores in males than in females (Hedges and Nowell 1995;Johnson et al. 2008;Wai et al. 2010). As such, Geary's theory is very compelling because it provides an elegant account of many important empirical phenomena of intelligence research. ...
... Geary suggested that heritable and environmentally caused differences in mitochondrial functioning affect the integrity and efficiency of neurons and supporting glia cells and may thus contribute to individual differences in higher-order cognitive functioning and physical health. His theory aimed to account for different phenomena of intelligence research, including the positive manifold (Spearman 1904), the association between intelligence and health (Batty et al. 2007;Deary 2008;Der et al. 2009) 1 , the joint age-related decline in performance across different cognitive domains (Rhemtulla and Tucker-Drob 2011;Salthouse 2009;Salthouse and Ferrer-Caja 2003;Tucker-Drob 2011;Tucker-Drob et al. 2014), and the greater variability in intelligence test scores in males than in females (Hedges and Nowell 1995;Johnson et al. 2008;Wai et al. 2010). As such, Geary's theory is very compelling because it provides an elegant account of many important empirical phenomena of intelligence research. ...
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Geary (2018, 2019) suggested that heritable and environmentally caused differences in mitochondrial functioning affect the integrity and efficiency of neurons and supporting glia cells and may thus contribute to individual differences in higher-order cognitive functioning and physical health. In our comment, we want to pose three questions aimed at different aspects of Geary’s theory that critically evaluate his theory in the light of evidence from neurocognitive, cognitive enhancement, and behavioral genetics research. We question (1) if Geary’s theory explains why certain cognitive processes show a stronger age-related decline than others; (2) if intervention studies in healthy younger adults support the claim that variation in mitochondrial functioning underlies variation in human intelligence; and (3) if predictions arising from the matrilineal heredity of mitochondrial DNA are supported by behavioral genetics research. We come to the conclusion that there are likely many more biological and social factors contributing to variation in human intelligence than mitochondrial functioning.
... This means that not only summary indices of general cognitive ability but also averaging across task within a more specific area of cognitive ability may mask sex differences (Johnson & Bouchard, 2007). Another important finding has been that there is more variance among boys than girls in within-sex IQ-scores (Johnson et al., 2008;Strand et al., 2006). ...
... The above described type of differences in intra-sex variability have been on a common theme in the literature on cognitive abilities, with both men (Hedges & Nowell, 1995) and boys (Johnson et al., 2008;Strand et al., 2006) showing more intra-sex variability. Some research suggests that similar differences may exist in the realm of adult personality traits, with men showing higher intra-sex variability in informant (but not self-) reports of personality (Borkenau et al., 2013). ...
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Some of the most persistently recurring research questions in the fields of personality and social psychology concern sex differences. Although much progress has been made, no research has addressed the basic question of whether there is one general construct of genderedness that runs through various life domains, or whether genderedness is specific to certain domains. In order to determine whether being gender typical in one way goes together with being gender typical also in other ways, we investigated whether 16-year old girls and boys (N = 4106) finishing Finnish elementary school differ in their personality traits, values, cognitive abilities, academic achievement, and educational track. To do this, we updated the gender diagnosticity approach by employing penalized logistic regression to estimate multivariate sex differences based on both binary and continuous variables. The preregistered analysis show that the magnitude of sex differences varies a lot from domain to domain, that narrow measures, such as grade profiles, can be highly accurate in predicting sex, whereas broad measures, such as general cognitive ability, can be useless, and that the correlations between femininity-masculinity scores based on different domains, despite all being positive, are too weak to suggest the existence of a general factor of genderedness. Our more exploratory analyses show that more focus on gender typicality could offer important insights into the role of gender in shaping people’s lives. We discuss how future research could employ the methods we introduce to further our understanding of sex differences and gender typicality in developmental and educational fields.
... It is unclear, for example, whether brain size is a direct proxy for neuron number (discussed in Pietschnig et al., 2015). There is also an apparent paradox that there are substantial sex differences in total brain volume (on the order of 1.41 standard deviations; Ritchie et al., 2018) but litte-to-no sex differences in mean intelligence (Deary, Irwing, Der, & Bates, 2007;Johnson, Carothers, & Deary, 2008;Lakin & Gambrell, 2014;Ritchie et al., 2018). More recent work indicates that multiple brain properties might be required to better explain individual differences in general intelligence, and some of these might be compensatory for differences in overall brain size (Deary, Penke, & Johnson, 2010;Kievit et al., 2012;Kievit et al., 2014;Luders et al., 2004;Ritchie et al., 2015). ...
... Biobank release using the VNR only (Ritchie et al., 2018). Given that the mean differences in intelligence are generally extremely modest or null (Deary, Irwing, Der, & Bates, 2007;Johnson, Carothers, & Deary, 2008;Lakin & Gambrell, 2014;Ritchie et al., 2018), this adds weight to the hypothesis that more specific brain characteristics compensate for the relatively larger brain size difference between males and females. We also ascertained that the g-TBV association belies important heterogeneity at both the global tissue level, and at the regional level across cortex, subcortex and white matter. ...
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The associations between indices of brain structure and measured intelligence are unclear. This is partly because the evidence to-date comes from mostly small and heterogeneous studies. Here, we report brain structure-intelligence associations on a large sample from the UK Biobank study. The overall N = 29,004, with N = 18,426 participants providing both brain MRI and at least one cognitive test, and a complete four-test battery with MRI data available in a minimum N = 7201, depending upon the MRI measure. Participants' age range was 44-81 years (M = 63.13, SD = 7.48). A general factor of intelligence (g) was derived from four varied cognitive tests, accounting for one third of the variance in the cognitive test scores. The association between (age- and sex- corrected) total brain volume and a latent factor of general intelligence is r = 0.276, 95% C.I. = [0.252, 0.300]. A model that incorporated multiple global measures of grey and white matter macro- and microstructure accounted for more than double the g variance in older participants compared to those in middle-age (13.6% and 5. 4%, respectively). There were no sex differences in the magnitude of associations between g and total brain volume or other global aspects of brain structure. The largest brain regional correlates of g were volumes of the insula, frontal, anterior/superior and medial temporal, posterior and paracingulate, lateral occipital cortices, thalamic volume, and the white matter microstructure of thalamic and association fibres, and of the forceps minor. Many of these regions exhibited unique contributions to intelligence, and showed highly stable out of sample prediction.
... In the study by Bian et al., participants seemed to assume that people with very high intelligence are more likely to be males than females. The authors dismissed this belief as a "negative stereotype about women"; they seemed unaware that males are in fact overrepresented at the high end of the IQ distribution (as well as the low end; e.g., Arden & Plomin, 2006;Johnson et al., 2008). 8 A fourth paper by Gruber et al. (2020) was a wide-ranging analysis of gender gaps in academic psychology (e.g., career advancement, salary, grants, publication and citation rates). ...
... In the meantime, the variability hypothesis-a "pernicious hypothesis" for Noddings (1992), a "social Darwinist myth" for Denmark et al. (2008)-has been largely confirmed across species (Reinhold & Engqvist, 2013;Wyman & Rowe, 2014). In humans, larger samples and better analytical techniques have shown that males are systematically more variable than females, both in general intelligence (indexed by IQ) and in most specific cognitive skills (e.g., Arden & Plomin, 2006;Baye & Monseur, 2016;Feingold, 1992;He & Wong, 2011;Johnson et al., 2008;Lohman & Lakin, 2009;Machin & Pekkarinen, 2008). The same applies to many physical and physiological traits (Lehre et al., 2009). ...
... Similar results on U.S. students were found by Lohman and Lakin (2009) and later, Lakin (2013). IQ scores have also shown to reflect the same pattern (Johnson et al. 2008). Finally, assessments of non-cognitive and behavioural domains such as creativity (He et al. 2013;Karowski et al. 2016), sensation seeking (Cross et al. 2011), personality (Borkenau et al. 2013) and aggression (Archer and Mehdikhani 2003) appear subject to the effect. ...
... As a result, many empirical papers avoid proposing an explanation. Johnson et al. (2008) point out that although results have often seemed clear, studies are often attacked on methodological grounds pertaining to sample size, representativeness, sample selectivity and age amongst other things. While it is not our intent to repeat the full history of the greater male variability hypothesis (see Johnson et al. for an in-depth review) we will briefly consider some of the proposed explanations for this effect. ...
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Abstract A recent study by Baye and Monseur (Large Scale Assess Educ 4:1–16, 2016) using large, international educational data sets suggest that the “greater male variation hypothesis” is well supported. Males are often over-represented at the tails of the ability distribution despite similarity in measures of central tendency and the gradual closing of the attainment gap relative to females. In this study, we replicate and expand Baye and Monseur’s work, and explore greater male variability by country using meta-analysis and meta-regression. While we broadly confirm that variability is greater for males internationally, we find that there is significant heterogeneity between countries, and that much of this can be quantified using variables applicable across these assessments (such as test, year, male–female effect size, mean country score and Global Gender Gap Indicators). While it is still not possible to make any causal conclusions regarding why males are more varied than females in academic assessments, it is possible to show that some national level variables effect the magnitude of this variation. Results and suggestions for further work are discussed.
... Adult callosotomy produces the well-known disconnection syndrome, in which the individual is left paradoxically intact, requiring ingenious experiments to reveal the cognitive implications of the severing of the corpus callosum (e.g., Gazzaniga 2005;Gazzaniga et al. 1962Gazzaniga et al. , 1963Gazzaniga et al. , 1965Gazzaniga and Sperry 1967;Sperry 1964). Even here, though, there seems to be individual variation in its effects on, for example, resting state activity (see Johnson et al. 2008;Uddin et al. 2008). This very variability of hemispheric interaction alerts us to its potential. ...
... greater encapsulation, more lateralization) might achieve even deeper mutual modelling and more sophisticated tools to be coordinated between the two hemispheres, but it also risks disrupting even the current level of coordination. There is an inverse relation between brain lateralization and callosal connectivity in males (Aboitiz et al. 1992;Dorion et al. 2000;Witelson and Goldsmith 1991), suggesting that we should see in males a greater variability at both the upper and lower ends of the range of cognitive performance, which is exactly what we do see (Johnson et al. 2008). (See Shillcock et al. 2018, for the relevant cognitive modelling.) ...
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We observe that approaches to intersubjectivity, involving mirror neurons and involving emulation and prediction, have eclipsed discussion of those same mechanisms for achieving coordination between the two hemispheres of the human brain. We explore some of the implications of the suggestion that the mutual modelling of the two situated hemispheres (each hemisphere ‘second guessing’ the other) is a productive place to start in understanding the phylogenetic and ontogenetic development of cognition and of intersubjectivity.
... Girls tend to earn higher school grades than boys, including in STEM subjects 6 , so why does this advantage not transfer into the workforce? The variability hypothesis, also called the greater male variability hypothesis, has been used to explain this apparent contradiction 7 -it is based on the tendency for males to show greater variability than females for psychological traits 8 (and for other traits across multiple species 9 ), leading to relatively fewer females with exceptional ability 10 . However, the gender gap in employment within many highly paid occupations exceeds gender differences in variability (e.g. ...
... However, for comparison with Voyer's 6 results, we have repeated the lnRR analyses using SMD as the effect size. The results for both lnRR and SMD analyses-which are very similar to each other-are presented in the Supplementary Figure 4, and Supplementary 6,8,12,13,16,19,22,25. To assess differences in variance of grades of boys and girls, we used the natural logarithm coefficient of variation ratio (lnCVR) and its associated sampling error variance s 2 lnCVR 35 . ...
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Fewer women than men pursue careers in science, technology, engineering and mathematics (STEM), despite girls outperforming boys at school in the relevant subjects. According to the 'variability hypothesis', this over-representation of males is driven by gender differences in variance; greater male variability leads to greater numbers of men who exceed the performance threshold. Here, we use recent meta-analytic advances to compare gender differences in academic grades from over 1.6 million students. In line with previous studies we find strong evidence for lower variation among girls than boys, and of higher average grades for girls. However, the gender differences in both mean and variance of grades are smaller in STEM than non-STEM subjects, suggesting that greater variability is insufficient to explain male over-representation in STEM. Simulations of these differences suggest the top 10% of a class contains equal numbers of girls and boys in STEM, but more girls in non-STEM subjects.
... I discuss how energy capture and control of oxidative stress may at least partially contribute to the well documented relation between intelligence and health and to age-related declines in health and basic cognitive abilities (Deary, Wright, Harris, Whalley, & Starr, 2004;Salthouse & Ferrer-Caja, 2003). I close with the argument that uniparental inheritance of mitochondrial DNA (mtDNA) contributes to the sex difference in variability in intelligence (Johnson, Carothers, & Deary, 2008;Miller, 2000). The gist of the proposal is shown in Figure 1, and the basic theses as well as key supporting evidence and paths to refute the basic theses are shown in Table 1. ...
... There are, nevertheless, several lines of evidence consistent with a g factor above and beyond fluid intelligence, whether the factor has substance or is a statistical artifact. The first is that scores on psychometric measures of g are highly correlated across test batteries (Johnson, Bouchard, Krueger, McGue, & Gottesman, 2004;Johnson, te Nijenhuis, & Bouchard, 2008). In other words, individuals receive essentially the same g-score independent of the number of fluid intelligence measures included in the test battery. ...
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General intelligence or g is one of the most thoroughly studied concepts in the behavioral sciences. Measures of intelligence are predictive of a wide range of educational, occupational, and life outcomes, including creative productivity and are systematically related to physical health and successful aging. The nexus of relations suggests 1 or several fundamental biological mechanisms underlie g, health, and aging, among other outcomes. Cell-damaging oxidative stress has been proposed as 1 of many potential mechanisms, but the proposal is underdeveloped and does not capture other important mitochondrial functions. I flesh out this proposal and argue that the overall efficiency of mitochondrial functioning is a core component of g; the most fundamental biological mechanism common to all brain and cognitive processes and that contributes to the relations among intelligence, health, and aging. The proposal integrates research on intelligence with models of the centrality of mitochondria to brain development and functioning, neurological diseases, and health more generally. Moreover, the combination of the maternal inheritance of mitochondrial DNA (mtDNA), the evolution of compensatory nuclear DNA, and the inability of evolutionary processes to purge deleterious mtDNA in males may contribute to the sex difference in variability in intelligence and in other cognitive domains. The proposal unifies many now disparate literatures and generates testable predictions for future studies.
... This means that not only summary indices of general cognitive ability but also averaging across task within a more specific area of cognitive ability may mask sex differences (Johnson & Bouchard, 2007). Another important finding has been that there is more variance among boys than girls in withinsex IQ scores (Johnson et al., 2008;Strand et al., 2006). ...
... The above-described type of differences in intra-sex variability has been on a common theme in the literature on cognitive abilities, with both men (Hedges & Nowell, 1995) and boys (Johnson et al., 2008;Strand et al., 2006) showing more intra-sex variability. Some research suggests that similar differences may exist in the realm of adult personality traits, with men showing higher intra-sex variability in informant (but not self-) reports of personality (Borkenau et al., 2013). ...
Article
Some of the most persistently recurring research questions concern sex differences. Despite much progress, limited research has thus far been undertaken to investigate whether there is one general construct of genderedness that runs through various domains of human individuality. In order to determine whether being gender typical in one way goes together with being gender typical also in other ways, we investigated whether 16-year-old Finnish girls and boys ( N = 4106) differ in their personality, values, cognitive abilities, academic achievement, and educational track. To do this, we updated the prediction-focused gender diagnosticity approach by methods of cross-validation for more accurate estimation. The preregistered analysis shows that sex differences vary across domains ( Ds = 0.15–1.48), that fine-grained measures, such as grade profiles, can be accurate in predicting sex (77.5%), whereas some summary indices, such as general cognitive ability, do not perform above-chance (52.4%), and that the genderedness correlations, despite all being positive, are too weak (average partial correlation, r´ = .09, range .03–.34) to support a general factor of genderedness. Our more exploratory analyses show that more focus on gender typicality could offer important insights into the role of gender in shaping people’s lives.
... Another assumption underlying these results is that the distributions of scores, including their variances and covariances, are identical for different demographic groups, an assumption that is questionable (e.g., Johnson, Carothers, & Deary, 2008;Makel, Wai, Peairs, & Putallaz, 2016). Similarly, the assumptions we made regarding upper and lower bounds for factor loadings and correlations have a strong effect on the results. ...
Article
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Educational psychology is replete with verbal or qualitative definitions through which students can be considered members of categories, such as learning disabled, autistic, or gifted. These conceptions carry quantitative implications regarding the incidence rates of the phenomena they describe. To be scientifically useful, such definitions should have sufficient specificity and internal consistency. We analyzed four influential definitions of giftedness and assessed their internal consistency by computing the giftedness rate implied by each. Results reveal that the proportion of individuals who meet the standard of giftedness under some definitions is unrealistically high (e.g., >75% in some conditions). The implication of this work is that the rigor and internal self-consistency of educational concepts requires improvement. The field must carefully consider the quantitative implications of its concepts, statements, and definitions. An Open Science Framework project page containing R code, a technical appendix, and all figures and tables from this paper is available at https://osf.io/6e7g9/.
... Furthermore, some evidence suggests males tend to be more variable with regards to intelligence compared to females (e.g., Johnson et al., 2008;2009). Greater variability in intelligence in a pooled sample that is potentially less variable on psychopathic traits and skewed towards the higher end of the distribution for that construct could all be contributing to the lack of an association for males. ...
Article
Substantial research has investigated the association between intelligence and psychopathic traits. The findings to date have been inconsistent and have not always considered the multi-dimensional nature of psychopathic traits. Moreover, there has been a tendency to confuse psychopathy with other closely related, clinically significant disorders. The current study represents a meta-analysis conducted to evaluate the direction and magnitude of the association of intelligence with global psychopathy, as well as its factors and facets, and related disorders (Antisocial Personality Disorder, Conduct Disorder, and Oppositional Defiant Disorder). Our analyses revealed a small, significant, negative relationship between intelligence and total psychopathy (r = -.07, p = .001). Analysis of factors and facets found differential associations, including both significant positive (e.g., interpersonal facet) and negative (e.g., affective facet) associations, further affirming that psychopathy is a multi-dimensional construct. Additionally, intelligence was negatively associated with Antisocial Personality Disorder (r = -.13, p = .001) and Conduct Disorder (r = -.13, p = .001), but positively with Oppositional Defiant Disorder (r = .06, p = .001). There was significant heterogeneity across studies for most effects, but the results of moderator analyses were inconsistent. Finally, bias analyses did not find significant evidence for publication bias or outsized effects of outliers.
... Empirically, males have been found to show larger variance than females in a majority of traits, including most dimensions of personality (except neuroticism; see Del Giudice, 2015), general intelligence (e.g., Arden & Plomin, 2006;Dykiert et al., 2009;Johnson et al., 2008), specific cognitive skills (e.g., Bessudnov & Makarov, 2015;Hyde et al., 2008;Lakin, 2013;Wai et al., 2018), brain size (e.g., Ritchie et al., 2018;Wierenga et al., 2017), and many other bodily and physiological features (see Del Lehre et al., 2009). In the human literature, this is known as the "greater male variability hypothesis" (for a historical perspective see Feingold, 1992), but the same general pattern is apparent in most sexually reproducing species (Wyman & Rowe, 2014;Del Giudice et al., 2018). ...
Chapter
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This chapter offers a concise, systematic introduction to quantification in sex differences research. The chapter reviews the main methods used to measure sex differences and similarities, including standardized distances (Cohen’s d and Mahalanobis’ D), indices of overlap, variance ratios, and tail ratios. Some less common approaches (e.g., relative distribution methods, taxometrics) are also reviewed and discussed. The chapter examines the strengths and limitations of each method, considers various statistical and methodological factors that may either inflate or deflate the size of sex differences, and discusses the available options to minimize their influence. Other topics addressed include the effective visualization of sex differences/similarities, and the rationale for treating sex as a binary variable despite the complexities of sex-related identity and behavior.
... Therefore, males usually demonstrate a wider distribution than females do. The greater male variability hypothesis accounts for the greater numbers of males falling at both the upper and lower extremes of the distribution of abilities (Feingold, 1992;Johnson et al., 2008). Such a hypothesis has been proven to be useful in understanding many real-world phenomena in which men are much more heavily represented than women at both the highest and lowest levels of ability or achievement in many domains or areas Hyde and Mertz, 2009;Hyde, 2014). ...
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The relationship between sex and creativity remains an unresolved research question. The present study aimed to approach this question through the lens of the developmental theory of sex differences in intelligence, which posits a dynamic pattern of sex differences in intellectual abilities from female superiority in childhood and early adolescence to male superiority starting at 16 years of age. A total of 775 participants from three age groups (i.e., children, adolescents, and emerging adults) completed a 4-year longitudinal study comprising four assessments of creative thinking at 1-year intervals. Creative thinking was assessed with the Test for Creative Thinking-Drawing Production. While the results revealed female superiority in childhood and early adolescence, male superiority was not found in adolescence and emerging adulthood. Rather, greater sex similarities and greater male variability were found based on mean and variability analyses, respectively. This study elucidated the link between sex and creativity by (1) taking a developmental perspective, (2) employing a 4-year longitudinal design in three age groups (i.e., children, adolescents, and emerging adults), and (3) analyzing sex differences based on both mean and variability analyses.
... Lindberg, et al., 2010;Machin & Pekkarinen, 2008;Penner, 2008;Hyde & Mertz, 2009). First introduced by Ellis (1974) in his study of institutionalized men and women with severe intellectual challenges, the greater male variability hypothesis posits that men represent more variability than women on several personality traits and psychological constructs (Benjamin, 1990;Hollingworth, 1914;Johnson, Carothers, & Deary, 2008;Thorndike, 1910). However, some previous research findings imply that higher male variability is mutable (e.g. ...
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Women’s underrepresentation in mathematics-related careers continues to concern policymakers, economists, and educators. This study addressed the issue by examining data from two international databases, namely IEA’s Trends in International Mathematics and Science Study 2015, and the World Economic Forum’s Global Gender Gap Report 2017. Using country as the unit for our observations and meta-analysis techniques, the question of gender mathematics differences was investigated using standardized mean difference comparisons and variance ratios. Fourth- and eighth-grade girls and boys were also compared in terms of the number of students who reached the advanced international benchmark. The findings mostly supported previous findings in the related literature; no statistically significant large differences were observed comparing the performance of girls and boys in mathematics achievement and the number of high achievers. Moreover, boys were found to have more variability in mathematics achievement than girls. This finding further isolates the potential cause of women’s underrepresentation in mathematics-related careers as policies driven by implicit and explicit cultural biases.
... Indeed, high ability individuals have higher odds to reach a higher social status (e.g., through more successful educational careers (Deary, Strand, Smith, & Fernandes, 2007)) and ability is partly heritable (Bouchard Jr, 2004), although this relationship seems to be complex (Turkheimer, Haley, Waldron, d'Onofrio, & Gottesman, 2003). Similarly, male intelligence scores have been found to have larger variability, leading them to be overrepresented both in the upper and lower end of the intelligence distribution (Arden & Plomin, 2006;Dykiert, Gale, & Deary, 2009;Hedges & Nowell, 1995;Johnson, Carothers, & Deary, 2008), although this finding has been disputed as well (Irwing & Lynn, 2005;Spelke, 2005). A second drawback of these studies is that teacher nominations were usually registered within a context of gifted program selection. ...
Article
Accurate teacher judgments of student cognitive ability are crucial to effective instruction. Building on a large survey among 7th graders and their teachers, this study considers which student characteristics affect teacher and peer recognition of high ability students. High ability judgments by teachers were found to depend more on everyday school achievement (GPA) than on cognitive ability (IQ) itself, even when teachers were urged to distinguish between achievement and ability. Girls were less likely to be perceived as highly able than boys with similar levels of ability. Parental educational level affected high ability judgment, but only through its relation with school achievement. Both the most engaged and the most bored students were more frequently selected as highly able students. Similarly, peer judgments of highly able classmates depended, net of cognitive ability, on everyday school achievement, perceived engagement and disengagement, and gender, with girls being less likely to be judged as highly able.
... variability hypothesis (Johnson, Carothers, & Deary, 2008;Shields, 1982). Although variance across individuals is higher among boys than girls, there is no reason to believe that individual variance is higher for boys than for girls. ...
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This paper uses detailed register information on students in lower secondary school in Norway to study the importance of the second moment of individual grade distribution: grade variance. Students receive discrete-value grades from 1 to 6 in the same 13 subjects, and the grade point average (GPA) is used to determine entrance into upper secondary school. This leads to a limited number of possible GPA values and the within-GPA-value variation in grades is used to investigate the association between grade variance and educational attainment. Grade variance is found to be negatively associated with educational attainment across the grade distribution and for both genders. US data confirm this finding. Results suggests that being a generalist with similar skills across subjects predicts educational attainment and that educational institutions may benefit from considering more than just grade point average when making admission decisions.
... With regard to gender, there is a long-lasting tradition pointing to the superiority of males in STEM-related subjects (e.g., math, engineering) over females (Wai et al., 2010;Lakin, 2013) but these findings are far from being conclusive as girls appear to have higher school grades in STEM subjects compared to males (Voyer and Voyer, 2014). Interestingly, and regardless of the empirical evidence, males dominate these fields professionally, and potential explanations put forth include (a) females conform to stereotype threat (Spencer et al., 2016), and (b) the variability hypothesis (Johnson et al., 2008). With regard to the stereotype threat, females tend to behave for rather than against gender stereotypes being fearful of the risk of backlash (Rudman and Phelan, 2008). ...
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The main aim of the present study was to investigate the presence of Differential Item Functioning (DIF) using a latent class (LC) analysis approach. Particularly, we examined potential sources of DIF in relation to gender. Data came from 6,265 Saudi Arabia students, who completed a high-stakes standardized admission test for university entrance. The results from a Latent Class Analysis (LCA) revealed a three-class solution (i.e., high, average, and low scorers). Then, to better understand the nature of the emerging classes and the characteristics of the people who comprise them, we applied a new stepwise approach, using the Multiple Indicator Multiple Causes (MIMIC) model. The model identified both uniform and non-uniform DIF effects for several items across all scales of the test, although, for the majority of them, the DIF effect sizes were negligible. Findings from this study have important implications for both measurement quality and interpretation of the results. Particularly, results showed that gender is a potential source of DIF for latent class indicators; thus, it is important to include those direct effects in the latent class regression model, to obtain unbiased estimates not only for the measurement parameters but also of the structural parameters. Ignoring these effects might lead to misspecification of the latent classes in terms of both the size and the characteristics of each class, which in turn, could lead to misinterpretations of the obtained latent class results. Implications of the results for practice are discussed.
... These data support the generally accepted conclusion that males are more variable in quantitative and visual-spatial abilities, with more males at both high-and low-ability ends of test scores. In a large-scale study of sex differences in variability, Johnson, Carothers, and Deary (2008) found that males are more variable, with greater variability at the low end of the distribution than at the high end, which reflects a greater incidence of intellectual disability among males. These authors concluded that sex differences at the high end of the distribution of intelligence scores cannot account for sex differences in high-level achievement. ...
Chapter
The ways in which women and men differ in intelligence and specific cognitive abilities are among psychology’s most heated controversies. Massive amounts of data show that although there are some on average differences in specific cognitive abilities, there is considerable overlap in the male and female distributions. There are no sex differences in general intelligence – standardized IQ tests were written to show no differences, and separate assessments that were not written with this criterion show no differences in general intelligence. There are more males in some categories of mental disability that are genetically linked, but there are no genetic explanations for differential achievement at the high end of the distributions. Average between-sex differences on specific cognitive abilities – notably reading and writing (female advantage) and some mathematical and visuospatial abilities (male advantage) – often show considerable cross-cultural variation in effect size. Additionally, there have been changes over time so that any conclusions about this controversial topic that we make today may need to be revised in the future.
... We found a male-female genetic correlation close to unity. We also found nearly identical SNP heritability estimates for men and women, which is consistent with partial dosage compensation (that is, on average the per-allele effect sizes are smaller in women) and indicates that any contribution of common variants on the X chro- mosome to sex differences in the normal-range variance of cogni- tive phenotypes 19 is quantitatively negligible. ...
Article
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Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.
... Also, in both extremes (scores < 200 and >800), the number of boys is twice that of girls. This fits with the greater male variability hypothesis discussed by, e.g., Baye and Monseur (2016), Johnson, Carothers, and Deary (2008), Machin and Pekkarinen (2008), and O'Dea and collegues (2018). However, the number of ultimately performing pupils is rather small. ...
Article
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A national-level dataset (n = 7770) at grade 1 of primary school is re-analyzed to study preconditions in proficiency in mathematical concepts, operations and mathematical abstractions and thinking. The focus is on those pupils whose preconditions are so low that they are below the first measurable level of proficiency in the common framework with reference to mathematics (CFM). At the beginning of school, these pupils may not be familiar with, e.g., the concepts of numbers 1-10, they may not be aware of the consecutive nature of numbers, and they have no or very limited understanding of the basic concepts of length, mass, volume, and time. A somewhat surprising finding is that the key factor explaining the absolute low proficiency in mathematics appeared to be a low proficiency in listening comprehension. This variable alone explains 41% of the probability of belonging to the group of pupils who are not able to show proficiency enough to reach the lowest level in any of the criteria. It is understandable that, if language skills are underdeveloped in general, a child is not expected to master the specific mathematical vocabulary either and, hence, the low score in a test of preconceptions in mathematics too. Other variables predicting the absolute low level or preconditions of mathematics are the decision on intensified or special support, status of Finnish or Swedish as second language, and negative attitudes toward mathematics.
... For a diverse set of human traits and behaviors, males are often reported to show greater variability than females (Hyde 2014). This sex difference has been noted for aspects of personality (Borkenau, McCrae, and Terracciano 2013), cognitive abilities (Arden and Plomin 2006;Johnson, Carothers, and Deary 2008;Roalf et al. 2014), and school achievement (Baye and Monseur 2016). A fundamental question is to what degree these sex differences are related to genetic mechanisms or social factors, or their interactions. ...
Article
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For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
... There are many other ways to interrogate brain differences, beyond overall brain size, which, on its own, is not informative about the brain's complexity. For example, the fact that there are substantial sex differences in brain size [74] but very small or no sex differences in mean intelligence [75,76] is likely to be because multiple aspects of the brain's structure, function, and connectivity are compensatory for any apparent brain size difference. Notably, there do not appear to be sex differences in the size of the brain-intelligence correlation [73,74]. ...
Article
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Individual differences in human intelligence, as assessed using cognitive test scores, have a well-replicated, hierarchical phenotypic covariance structure. They are substantially stable across the life course, and are predictive of educational, social, and health outcomes. From this solid phenotypic foundation and importance for life, comes an interest in the environmental, social, and genetic aetiologies of intelligence, and in the foundations of intelligence differences in brain structure and functioning. Here, we summarise and critique the last 10 years or so of molecular genetic (DNA-based) research on intelligence, including the discovery of genetic loci associated with intelligence, DNA-based heritability, and intelligence’s genetic correlations with other traits. We summarise new brain imaging-intelligence findings, including whole-brain associations and grey and white matter associations. We summarise regional brain imaging associations with intelligence and interpret these with respect to theoretical accounts. We address research that combines genetics and brain imaging in studying intelligence differences. There are new, though modest, associations in all these areas, and mechanistic accounts are lacking. We attempt to identify growing points that might contribute toward a more integrated ‘systems biology’ account of some of the between-individual differences in intelligence.
... A recent review suggests there are few, if any, replicable differences between sexes apart from these omnibus measures (Eliot et al., 2021), although alternate interpretations of this review highlight the importance of small effect sizes over time (Hirnstein & Hausmann, 2021) and methodological shortcomings of previous work (Williams et al. 2021). Second, like most physical and psychological variables (e.g., Hyde, 2014;Lehre et al., 2009;Johnson et al., 2008), males show greater variability than females in both global and regional indices of brain structure, which is consistent across the lifespan (Wierenga et al., 2018;2020). Third, there is some evidence that males and females tend to exhibit slightly different patterns of development with regard to morphometry (Kaczkurkin et al., 2018); for example, females tend to reach peak cortical surface area and total brain volume at a younger age than males (Raznahan et al., 2011). ...
Article
Introduction: Males and females tend to exhibit small but reliable differences in personality traits and indices of psychopathology that are relatively stable over time and across cultures. Previous work suggests that sex differences in brain structure account for differences in domains of cognition. Methods: We used data from the Human Connectome Project (N = 1098) to test whether sex differences in brain morphometry account for observed differences in the personality traits neuroticism and agreeableness, as well as symptoms of internalizing and externalizing psychopathology. We operationalized brain morphometry in three ways: omnibus measures (e.g., total gray matter volume), Glasser regions defined through a multi-modal parcellation approach, and Desikan regions defined by structural features of the brain. Results: Most expected sex differences in personality, psychopathology, and brain morphometry were observed, but the statistical mediation analyses were null: sex differences in brain morphometry did not account for sex differences in personality or psychopathology. Conclusions: Men and women tend to exhibit meaningful differences in personality and psychopathology, as well as in omnibus morphometry and regional morphometric differences as defined by the Glasser and Desikan atlases, but these morphometric differences appear unrelated to the psychological differences.
... We also did not find associations with the more severe MDD cases by taking only those with recurrent MDD in the GS subsample (see Sections 3.2.1 and 3.2.3). Although we found no relationship with MDD, there was however significant relationships with cognition base on the general cognitive ability (gfactor) in both GS subsample and UKB (Johnson, Carothers, & Deary, 2008). The clusters also showed significant relationships with some other specific tests mainly in the domains of reasoning (Matrix in GS subsample and VNR in UKB) and processing speed (WAIS-III UK DSy score in GS subsample and Reaction Time Task in UKB). ...
Article
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There is increasing interest in using data-driven unsupervised methods to identify structural underpinnings of common mental illnesses, including Major Depressive Disorder (MDD) and associated traits such as cognition. However, studies are often limited to severe clinical cases with small sample sizes and most do not include replication. Here, we examine two relatively large samples with structural magnetic resonance imaging (MRI), measures of lifetime MDD and cognitive variables: Generation Scotland (GS subsample, N = 980), and UK Biobank (UKB, N = 8900); for discovery and replication, using an exploratory approach. Regional measures of FreeSurfer derived cortical thickness (CT), cortical surface area (CSA), cortical volume (CV) and subcortical volume (subCV) were input into a clustering process, controlling for common covariates. The main analysis steps involved constructing participant K-nearest neighbour graphs, and graph partitioning with Markov Stability to determine optimal clustering of participants. Resultant clusters were i) checked whether they were replicated in an independent cohort, and ii) tested for associations with depression status, and cognitive measures. Participants separated into two clusters based on structural brain measurements in GS subsample, with large Cohen’s d effect sizes between clusters in higher order cortical regions, commonly associated with executive function and decision making. Clustering was replicated in the UKB sample, with high correlations of cluster effect sizes for CT, CSA, CV and subCV between cohorts across regions. The identified clusters were not significantly different with respect to MDD case-control status in either cohort (GS subsample: pFDR = 0.2239 − 0.6585; UKB: pFDR = 0.2003 − 0.7690). Significant differences in general cognitive ability were, however, found between the clusters for both datasets; for CSA, CV, subCV (GS subsample: d = 0.2529 − 0.3490, pFDR < 0.005; UKB: d = 0.0868 − 0.1070, pFDR < 0.005). Our results suggest that there are replicable natural groupings of participants based on cortical and subcortical brain measures, which may be related to differences in cognitive performance, but not to the MDD case-control status.
... The greater male variability hypothesis states that males are more variable than females across a variety of psychological and physical characteristics. The greater male variability hypothesis states that males are more variable than females across a variety of psychological and physical characteristics (Ellis, 1894) and is widely supported by a range of human (e.g., Johnson, Carothers, & Deary, 2008;Ju, Duan, & You, 2015;Karwowski et al., 2016;Lehre, Lehre, Laake, & Danbolt, 2009;Wierenga et al., 2019) and animal (e.g., Branch et al., 2020;DeCasien, Sherwood, Schapiro, & Higham, 2020) studies. Although the mechanisms behind the greater male variability hypothesis exceed the scope of the present study, our findings further support greater male variability, which extends well beyond brain measures. ...
Article
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Few neuroimaging studies are sufficiently large to adequately describe population-wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large-scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.
... The aim of our meta-analysis is to uncover such hidden differences by studying gender differences in the variability of three fundamental economic preferences: time, risk, and social preference. The greater male variability (GMV) hypothesis posits that men are characterized by greater variability in many attributes because differentiation had survival value for men but not for women (11)(12)(13). According to this perspective, males and females of many species faced different adaptive problems that resulted in sex-differentiated psychological adaptations (14). ...
Article
Gender differences in time, risk, and social preferences are important determinants of differential choices of men and women, with broad implications for gender-specific social and economic outcomes. To better understand the shape and form of gender differences in preferences, researchers have traditionally examined the mean differences between the two genders. We present an alternative perspective of greater male variability in preferences. In a meta-analysis of experimental economics studies with more than 50,000 individuals in 97 samples, we find converging evidence for greater male variability in time, risk, and social preferences. In some cases, we find greater male variability in addition to mean differences; in some cases, we only find greater male variability. Our findings suggest that theories of gender differences are incomplete if they fail to consider how the complex interaction of between-gender differences and within-gender variability determines differential choices and outcomes between women and men.
... Here, we conduct the first comprehensive test of the greater male variability and estrus-mediated variability hypotheses in mice (Figure 2; Reinhold and Engqvist, 2013;Johnson et al., 2008; Figure 1 continued ratio of SD), lnCVR (the ratio of CV or relative variance) provides a more general measure of the difference in variability between two groups (mean-adjusted variability ratio). The online version of this article includes the following figure supplement(s) for figure 1: . ...
Article
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Biomedical and clinical sciences are experiencing a renewed interest in the fact that males and females differ in many anatomic, physiological, and behavioral traits. Sex differences in trait variability, however, are yet to receive similar recognition. In medical science, mammalian females are assumed to have higher trait variability due to estrous cycles (the 'estrus-mediated variability hypothesis'); historically in biomedical research, females have been excluded for this reason. Contrastingly, evolutionary theory and associated data support the 'greater male variability hypothesis'. Here, we test these competing hypotheses in 218 traits measured in 26,900 mice, using meta-analysis methods. Neither hypothesis could universally explain patterns in trait variability. Sex-bias in variability was trait-dependent. While greater male variability was found in morphological traits, females were much more variable in immunological traits. Sex-specific variability has eco-evolutionary ramifications including sex-dependent responses to climate change, as well as statistical implications including power analysis considering sex difference in variance.
... Larkin (2013) obtained results in the same vein with verbal, non-verbal and numerical reasoning tests. In contrast, on the basis of the results of a general intelligence test taken by almost all Scottish children aged 11 years, Johnson and al. (2008) observed a skewed distribution of intellectual performance where boys are primarily overrepresented at the lower levels compared to girls. Lynn (1994), meanwhile, speculated that the lack of difference between men and women from the perspective of general intelligence concealed the differences varying with age. ...
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Many representations are circulating on the differences in cognitive skills according to gender. These social representations influence the attitudes of parents and teachers and can have important consequences in terms of educational guidance. The WISC-V gave us the opportunity to exa- mine these representations based on the performances of a large sample of children between 6 to 16, representative of the French population. WISC-V standardization data did not support the stereotypes that cir- culate about the intellectual skills of girls and boys. Some statistically si- gnificant differences were observed, but were generally small with no practical implications. The only biggest difference was to the advantage of girls. It concerns performance in speed tasks that require a high control of attention and oculomotor coordination.
... Men are characterized by higher variability than women on almost all biological and psychological traits (e.g., Ritchie et al. 2018). Previous studies demonstrated that the males' variance in intelligence tests is higher than females' variability (see Wai et al. 2010or Johnson et al. 2008, for an overview). The same pattern was found in creativity tests, both among children (Karwowski et al. 2016b) and adults (He and Wong 2011). ...
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This paper provides a meta-analytic update on the relationship between intelligence and divergent thinking (DT), as research on this topic has increased, and methods have diversified since Kim’s meta-analysis in 2005. A three-level meta-analysis was used to analyze 875 correlation coefficients from 112 studies with an overall N = 33,897. The overall effect showed a significant positive correlation of r = .25. This increase of the correlation as compared to prior meta-analytic findings (Kim 2005) could be attributed to the correction of attenuation because a difference between effect sizes prior-Kim vs. post-Kim was non-significant. Different moderators such as scoring methods, instructional settings, intelligence facets, and task modality were tested together with theoretically relevant interactions between some of these factors. These moderation analyses showed that the intelligence–DT relationship can be higher (up to r = .31–.37) when employing test-like assessments coupled with be-creative instructions, and considering DT originality scores. The facet of intelligence (g vs. gf vs. gc) did not affect the correlation between intelligence and DT. Furthermore, we found two significant sample characteristics: a) average sample age was positively associated with the intelligence–DT correlation, and b) the intelligence–DT correlation decreased for samples with increasing percentages of females in the samples. Finally, inter-moderator correlations were checked to take potential confounding into account, and also publication bias was assessed. This meta-analysis provides a comprehensive picture of current research and possible research gaps. Theoretical implications, as well as recommendations for future research, are discussed.
... Larkin (2013) obtient des résultats allant dans le même sens avec des épreuves de raisonnement verbal, non verbal et numérique. Par contre, Johnson et al. (2008) observent, sur la base des résultats à un test d'intelligence générale, passé par la quasi-totalité des enfants écossais âgés de 11 ans, une distribution asymétrique des performances intellectuelles où les garçons sont surreprésentés par rapport aux filles principalement dans les niveaux les plus faibles. Lynn (1994), quant à lui, avance l'hypothèse que l'absence de différence entre les hommes et les femmes du point de vue de l'intelligence générale masquerait des différences variant en fonction de l'âge. ...
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De nombreuses représentations circulent à propos des différences de compétences cognitives en fonction du genre. Ces représentations sociales influencent les attitudes des parents et des enseignants, et peuvent avoir d'importantes conséquences en termes d'orientation scolaire. La publication du WISC-V nous offre l'opportunité d'examiner ces représentations sur la base des performances d'un important échantillon de jeunes de six à 16 ans représentatif de la population française. Les données d'étalonnage du WISC-V ne confirment pas les stéréotypes qui circulent à propos de compétences intellectuelles des filles et des garçons. Quelques différences statistiquement significa-tives subsistent, mais elles sont généralement d'ampleur réduite, sans implication pratique. La seule différence de taille plus importante est à l'avantage des filles. Elle concerne les performances dans les tâches de vitesse de traitement qui demandent un important contrôle de l'attention et de la coordination oculomotrice. Many representations are circulating on the differences in cognitive skills according to gender. These social representations influence the attitudes of parents and teachers and can have important consequences in terms of educational guidance. The WISC-V gave us the opportunity to examine these representations based on the performances of a large sample of children between 6 to 16, representative of the French population. WISC-V standardization data did not support the stereotypes that circulate about the intellectual skills of girls and boys. Some statistically significant differences were observed, but were generally small with no practical implications. The only biggest difference was to the advantage of girls. It concerns performance in speed tasks that require a high control of attention and oculomotor coordination.
... This reasoning is used to support what has often been referred to as greater male variability. The greater-male-variability hypothesis, the origins of which lie with Charles Darwin, was that males are more likely to be found in both the upper and lower tails of the distribution of a number of physical, cognitive, and behavioral characteristics, because differentiation had survival value (Archer & Mehdikhani, 2003;Johnson, Carothers, & Deary, 2008). For example, Lehre, Lehre, Laake, and Danbolt (2009) showed that male adults had more intrasex variance in a wide range of characteristics, including weight (13% more variance), height (25%), 60-m-dash times (44%), and blood parameters such as cholesterol (50%) and triglycerides (55%). ...
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Do men and women differ systematically in their cooperation behaviors? Researchers have long grappled with this question, and studies have returned equivocal results. We developed an evolutionary perspective according to which men are characterized by greater intrasex variability in cooperation as a result of sex-differentiated psychological adaptations. We tested our hypothesis in two meta-analyses. The first involved the raw data of 40 samples from 23 social-dilemma studies with 8,123 participants. Findings provided strong support for our perspective. Whereas we found that the two sexes do not differ in average cooperation levels, men are much more likely to behave either selfishly or altruistically, whereas women are more likely to be moderately cooperative. We confirmed our findings in a second meta-analytic study of 28 samples from 23 studies of organizational citizenship behavior with 13,985 participants. Our results highlight the importance of taking intrasex variability into consideration when studying sex differences in cooperation and suggest important future research directions.
... My point in the original article was that the uniparental inheritance of mtDNA could contribute to the greater variation in intelligence among males than females (Johnson et al. 2008), and especially contribute to the over-representation of males at the lower end of the distribution. This is because uniparental inheritance means that mutations that disadvantage males but are neutral or beneficial to females cannot not be eliminated by natural selection (Beekman et al. 2014). ...
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In response to commentaries, I address questions regarding the proposal that general intelligence (g) is a manifestation of the functioning of intramodular and intermodular brain networks undergirded by the efficiency of mitochondrial functioning (Geary 2018). The core issues include the relative contribution of mitochondrial functioning to individual differences in g; studies that can be used to test associated hypotheses; and, the adaptive function of intelligence from an evolutionary perspective. I attempt to address these and related issues, as well as note areas in which other issues remain to be addressed.
... Interestingly, that gender differences in academic verbal and mathematical skills diminished in the last decades, but still were detectable [17,18]. At the same time, the summarized cognitive indexes as the verbal or non-verbal intelligence quotients or g-factors are commonly equal in females and males [3,19,20]. ...
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The gender differences in verbal and visuospatial cognitive domains and mathematics are well known and documented in psychometric research. Nevertheless, the findings in this field are consistent predominantly for academic but not for neuropsychological studies. Here we present the results of the retrospective analysis of the data of our five neuropsychological studies, conducted in cardiologic and psychiatric patient cohorts. We intended to analyze the consistency of gender effects in similar patient populations and to determine the possible co-factors, which may increase or diminish the intergroup differences in cognition in males and females. In all five studies we used the core battery of tests (Digit Span, Digit Symbol and Block Design) in the variable combination with other tests, sensitive to global mental status, intelligence, memory and leaning, verbal fluency, psychomotor speed, executive functions The most consistent pattern of gender differences with the advantage of females in verbal fluency and psychomotor speed tests and the advantage of males in the visuospatial reconstruction test was observed in the youngest psychiatric patient cohort (mean age – 31 years). Our data are consistent with the previous findings of prominent hormonal effects on the performance on verbal fluency, visual rotation and motor speed. Nevertheless, the partial gender effects on cognitive functioning with the advantage of females on Digit Symbol or the advantage of males on Block Design were observed in older cardiologic patient populations as well. The inconsistency of gender effects on the cognitive performance in older patient populations may be the consequence of the concomitant effects of aging and pathological processes on brain functioning, which may confound the gender effects. Overall, these findings support the recommendation to analyze the neuropsychological data of females and males separately, especially when using tests with high sensitivity to gender effects in young and hormone-replacement therapy patient populations.
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The Greater Male Variability Hypothesis (GMVH) suggests that males demonstrate greater variability than females and are overrepresented in the lowest and highest ranges of cognitive ability. Several studies have found evidence for the GMVH in creative performance, yet nearly all have used the same task (i.e., Test of Creative Thinking Drawing-Production) limiting inference to a single domain and modality of creative ability. In two studies, we examine the GMVH in relation to performance by adults (Study 1; N = 120) on a creative writing task and by adolescents (Study 2; N = 529) on a creative drawing task, as well as figural and verbal divergent thinking tasks. The variability of scores did not differ substantively between males and females on any of the tasks in either study and the pattern of the proportions of males and females in different regions of the distribution of scores was inconsistent across tasks. Although males received significantly greater mean scores than females on the verbal divergent thinking task in Study 2, no significant mean differences were found for any other task. Overall, our results do not support the GMVH and suggest that, if any, gender differences in creative variability are likely inconsistent across domains and tasks.
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Sex and gender matter in all aspects of life. Humans exhibit sexual dimorphism in anatomy, physiology, but also pathology. Many of the differences are due to sex chromosomes and, thus, genetics, other due to endocrine factors such as sex hormones, some are of social origin. Over the past decades, huge number of scientific studies have revealed striking sex differences of the human brain with remarkable behavioral and cognitive consequences. Prenatal and postnatal testosterone influence brain structures and functions, respectively. Cognitive sex differences include especially certain spatial and language tasks, but they also affect many other aspects of the neurotypical brain. Sex differences of the brain are also relevant for the pathogenesis of neuropsychiatric disorders such as autism spectrum disorders, which are much more prevalent in the male population. Structural dimorphism in the human brain was well-described, but recent controversies now question its importance. On the other hand, solid evidence exists regarding gender differences in several brain functions. This review tries to summarize the current understanding of the complexity of the effects of testosterone on brain with special focus on their role in the known sex differences in healthy individuals and people in the autism spectrum.
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Kane and Mertz's 2012 AMS Notices article "Debunking Myths about Gender and Mathematics Performance" claims to have debunked the greater male variability hypothesis with respect to mathematics abilities. The logical and statistical arguments supporting their claim, however, which are being widely cited in the scientific literature, contain fundamental errors. The methodology is critically flawed, the main logical premise is false, and the article omits reference to numerous published scientific research articles that contradict its findings. Most critically, Kane and Mertz's final conclusion that their data are inconsistent with the greater male variability hypothesis is wrong. The goal of the present note is to correct the scientific record with respect to those claims.
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The study [in Finnish] is part of a longitudinal research. Same students were followed from 3rd grade of primary education to the end of upper secondary level. The data was collected by EDUFI and FINEEC during 2005–2015. The data consists of 3896 students and the target group consists of mathematically high-achieving students. Total number of them is 292 (7,5 %). Definition of high-achieving students is based on success in the mathematics examination of 9th grade. In addition to math examinations it has been gathered information about students’ individual-, school- and home-related factors. The study examines the relationship between these factors and the choice between upper secondary vocational education and general upper secondary school. The aim is to investigate how high-achieving students’ mathematical competence develop during these studies and which factors are related to development. Decision tree analysis (DTA) and regression analysis were used to analyse the data. The results indicated that 60,0 % of mathematically high-achieving students were also high-achieving students at the end of upper secondary level. The individual-related factors were explanatory factors for mathematical success at the upper secondary level. Positive attitudes towards mathematics and strong mathematical competence in basic education predicted excellent success in mathematics later. The competence of high-achieving student most likely decreased if a student didn’t go to the general upper secondary school or didn’t complete at least 11 mathematics courses. They, who performed excellently in their studies of mother tongue in 9th grade, most likely applied to the general upper secondary school.
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A greater frequency of left-handedness among males than females has been observed in general populations. Past studies have explained this difference with reference to males’ greater susceptibility to adverse birth events, while more recent studies have identified other contributing factors. On January 16, 2020, U.S. senators signed an oath to act impartially during the president’s impeachment trial. This televised event allowed direct comparison of the proportion of right-handedness and left-handedness in a professionally accomplished sample of males and females. As expected, no sex difference in the proportion of left-handed senators was found, although the small sample size offered low statistical power. Replicating this finding with a larger sample would support the view that left-handedness among select groups of males is linked to genetic factors.
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Few neuroimaging studies are sufficiently large to adequately describe population-wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40 028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry - the non-linear scaling relationship between a region and brain size (e.g., Total Brain Volume) across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |std. beta|= 0.13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. This large scale-study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.
Chapter
This chapter covers general intelligence, also known as g factor. This refers to a critical cognitive ability that has been well characterized by cognitive neuroscientists and psychologists. It is one of the most pervasive concepts in psychology. It is measured by psychological tests and is often stated in the form of intelligence quotient (IQ). Historically, general intelligence is regarded as the best individual predictor of achievement across all academic domains.
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Biomedical and clinical sciences are experiencing a renewed interest in the fact that males and females differ in many anatomic, physiological, and behavioral traits. Sex differences in trait variability, however, are yet to receive similar recognition. In medical science, mammalian females are assumed to have higher trait variability due to estrus cycles (the "estrus-mediated variability hypothesis"); historically in biomedical research, females have been excluded for this reason. Contrastingly, evolutionary theory and associated data support the "greater male variability hypothesis". Here, we test these competing hypotheses in 218 traits measured in over 27,000 mice, using meta-analysis methods. Neither hypothesis could universally explain patterns in trait variability. Sex-bias in variability was trait-dependent. While greater male variability was found in morphological traits, females were much more variable in immunological traits. We discuss the importance of sex-specific trait variability in relation to their eco-evolutionary ramifications (e.g., sex-dependent responses and adaptations to climate change) and statistical implications (e.g., power analysis considering sex difference in variance).
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The notion that men are more variable than women has become embedded into scientific thinking. For mental traits like personality, greater male variability has been partly attributed to biology, underpinned by claims that there is generally greater variation among males than females in non-human animals due to stronger sexual selection on males. However, evidence for greater male variability is limited to morphological traits, and there is little information regarding sex differences in personality-like behaviours for non-human animals. Here, we meta-analysed sex differences in means and variances for over 2100 effects (204 studies) from 220 species (covering five broad taxonomic groups) across five personality traits: boldness, aggression, activity, sociality and exploration. We also tested if sexual size dimorphism, a proxy for sex-specific sexual selection, explains variation in the magnitude of sex differences in personality. We found no significant differences in personality between the sexes. In addition, sexual size dimorphism did not explain variation in the magnitude of the observed sex differences in the mean or variance in personality for any taxonomic group. In sum, we find no evidence for widespread sex differences in variability in non-human animal personality.
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Real-life outcomes for men and women suggest the existence of cognitive sex differences, but the evidence for a sex difference in general intelligence is equivocal. Here, we examine the role of spatial ability for IQ test performance, in light of the developmental hypothesis that male performance increases more than female across adolescence. Using longitudinal data from Block and Block data set on the Wechsler scales and the rod-and-frame test (RFT) for ages 4 (N = 108), 11 (N = 101), and 18 years (N = 100), we find that males' performance becomes greater than females' with age, both on IQ and the RFT. At 18 years of age, males' mean IQ and RFT score was 116.4 and 4.05 (lower scores representing less error), as compared to111.5 and 7.85 for females. Importantly, we found that the RFT mediates the sex difference in IQ, and that the factor loadings of the RFT on the g factor increases with age, from −0.06 at age 4 to −0.52 at 11 and −0.67 at age 18. In conclusion, g becomes more integrative of spatial ability across time and this finding may explain sex differences in g after puberty and potentially has interesting implications for the understanding of the development of intelligence. One important direction for future research is to incorporate biologically based pubertal neural changes into our understanding of developmental sex differences in intelligence.
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Empirical data suggest that there is at most a very small sex difference in general mental ability, but men clearly perform better on visuospatial tasks while women clearly perform better on tests of verbal usage and perceptual speed. In this study, we integrated these overall findings with predictions based on the Verbal–Perceptual–Rotation (VPR) model ([Johnson, W., and Bouchard, T. J. (2005a). Constructive replication of the visual–perceptual–image rotation (VPR) model in Thurstone's (1941) battery of 60 tests of mental ability. Intelligence, 33, 417–430.; Johnson, W., and Bouchard, T. J. (2005b). The structure of human intelligence: It's verbal, perceptual, and image rotation (VPR), not fluid and crystallized. Intelligence, 33. 393–416.]) of the structure of mental abilities. We examined the structure of abilities after removing the effects of general intelligence, identifying three underlying dimensions termed rotation–verbal, focus–diffusion, and memory. Substantial sex differences appeared to lie along all three dimensions, with men more likely to be positioned towards the rotation and focus poles of those dimensions, and women displaying generally greater memory. At the level of specific ability tests, there were greater sex differences in residual than full test scores, providing evidence that general intelligence serves as an all-purpose problem solving ability that masks sex differences in more specialized abilities. The residual ability factors we identified showed strong genetic influences comparable to those for full abilities, indicating that the residual abilities have some basis in brain structure and function.
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Examines research using a classic, influential experiment conducted by Goldberg (1968), showing that women were likely to rate male authors (e.g., John T. McKay) more favorably than female authors (e.g., Joan T. McKay) of identical articles. Although replications of this study have been inconclusive, Goldberg's research is still frequently cited as demonstrating an evaluative bias against women. A quantitative meta-analysis of research using Goldberg's experimental paradigm shows that the average difference between ratings of men and women is negligible. Furthermore, although the effect sizes are not homogeneous, the difference remains negligible when other factors such as sex of subject or year of publication are taken into consideration. Several explanations for the heterogeneity of effect sizes and the inconsistency of findings are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Gender differences for a nationally representative sample of American college graduates obtained from the Baccalaureate and Beyond 1993-94 study were examined on the Scholastic Aptitude Test and the American College Test, taken at the age of approximately 18 years, and on grades obtained in college at the ages of approximately 18-22 years. It was found that males obtained significantly higher means on the two tests for college entrance and that females obtained significantly higher grades while in college.
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In 1992, it was reported by Ankney and Rushton that males have larger average brain size than females even when allowance is made for body size. It is known that brain size is associated with intelligence, and it would therefore be expected that males would have higher intelligence than females. Yet it has been universally maintained that there is no difference in intelligence between the sexes. It is proposed that this anomaly can be resolved by a developmental theory of sex differences in intelligence which states that girls mature more rapidly in brain size and neurological development than boys up to the age of 15 years. The faster maturation of girls up to this age compensates for their smaller brain size with the result that sex differences in intelligence are very small, except for some of the spatial abilities. From the age of 16 years onwards, the growth rate of girls decelerates relative to that of boys. The effect of this is that a discernible male advantage of about 4 IQ points develops from the age of 16 into adulthood, consistent with the larger average male brain size. This paper presents new evidence on the developmental theory of sex differences in intelligence and discusses alternative attempts to deal with the anomaly by Ankney (1995), Mackintosh (1996), and Jensen (1998).
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This study examined gender bias on job performance in work settings where confounding variables (e. g., organizational level, experience, education) were cautiously taken into consideration to ensure fair comparisons. Although previous meta-analyses examined gender biases on evaluations, findings in tightly controlled laboratory environments may differ from those in highly complicated field studies. We found little evidence of overall gender bias in performance appraisals in nonconfounded field studies. However, there were significant pro-male biases when only men served as raters. Measure-specific gender stereotypicality, instead of genera! stereotypicality about the job, produced gender bias in performance appraisal. Masculine measures produced pro-male bias, and feminine measures produced pro-female bias.
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In a heterogeneous sample of 436 adult individuals who completed 42 mental ability tests, we evaluated the relative statistical performance of three major psychometric models of human intelligence—the Cattell–Horn fluid-crystallized model, Vernon's verbal–perceptual model, and Carroll's three-strata model. The verbal–perceptual model fit significantly better than the other two. We improved it by adding memory and higher-order image rotation factors. The results provide evidence for a four-stratum model with a g factor and three third-stratum factors. The model is consistent with the idea of coordination of function across brain regions and with the known importance of brain laterality in intellectual performance. We argue that this model is theoretically superior to the fluid-crystallized model and highlight the importance of image rotation in human intellectual function.
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This study meta-analytically tested hypotheses concerning factors that affect sex discrimination in simulated employment contexts. These hypotheses, derived from the social psychological literature on stereotyping, predicted that salience of applicant sex, job sex-type, sex of rater, and amount of job-relevant information would affect discrimination against female and male applicants. Generally, the hypotheses concerning job sex-type and job-relevant information were supported. Female and male applicants received lower ratings when being considered for an opposite-sex-type job, and the difference between ratings of males and females decreased as more job-relevant information was provided. However, ratings of males and females did not differ as hypothesized in regard to salience of sex and rater sex. The research and practice implications of these results are discussed.
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Professionals in the fields of mental retardation and giftedness have much to teach each other as well as the field of human development in general. Examining the commonalities and differences between the fields in social issues, definitions, developmental differences from the norm, values and policy issues, and educational and long-term implications deepens insights about both normal and deviant development. The authors stress the importance of individual differences in the differential design of educational strategies and the application of approaches developed with specialized populations to normally developing children. Current social inequalities affect both of these fields in particular ways. Finally, numerous research agendas can be enhanced by including representatives of both ends of the normal curve.
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Contemporary research on sex differences in intellectual abilities has focused on male-female differences in average performance, implicitly assuming homogeneity of variance. To examine the validity of that assumption, this article examined sex differences in variability on the national norms of several standardized test batteries. Males were consistently more variable than females in quantitative reasoning, spatial visualization, spelling, and general knowledge. Because these sex differences in variability were coupled with corresponding sex differences in means, it was demonstrated that sex differences in variability and sex differences in central tendency have to be considered together to form correct conclusions about the magnitude of cognitive gender differences.
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In the current resurgence of interest in the biological basis of animal behavior and social organization, the ideas and questions pursued by Charles Darwin remain fresh and insightful. This is especially true of The Descent of Man and Selection in Relation to Sex, Darwin's second most important work. This edition is a facsimile reprint of the first printing of the first edition (1871), not previously available in paperback. The work is divided into two parts. Part One marshals behavioral and morphological evidence to argue that humans evolved from other animals. Darwin shoes that human mental and emotional capacities, far from making human beings unique, are evidence of an animal origin and evolutionary development. Part Two is an extended discussion of the differences between the sexes of many species and how they arose as a result of selection. Here Darwin lays the foundation for much contemporary research by arguing that many characteristics of animals have evolved not in response to the selective pressures exerted by their physical and biological environment, but rather to confer an advantage in sexual competition. These two themes are drawn together in two final chapters on the role of sexual selection in humans. In their Introduction, Professors Bonner and May discuss the place of The Descent in its own time and relation to current work in biology and other disciplines.
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Based upon experiences with most kinds of meth ods of psychological measurement, this article presents comments on a variety of uses, including psychophys ics, scaling, testing, and factor analysis. Some diffi culties are pointed out, some faults are mentioned, and a variety of applications are discussed, some of them unusual.
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Reviews the book "Intelligence Refrained: Multiple Intelligence in the 21st Century" (see record 1999-04335-000 ), stating that this book is the latest in several amplifications of Howard Gardner's Theories of Multiple Intelligences (TMI), as first set forth in "Frames of Mind" (1993). The basic proposition of TMI is that the concept of "intelligence" should be applied to a much broader arena than the behaviors evaluated in a three-hour mental test. Why have many psychologists, and especially psychometricians, ignored TMI? Gardner argues that conventional students of intelligence have defined their topic too narrowly, as an analysis of the behaviors exhibited during Drop in From the Sky (DIFS) testing. He acknowledges that psychometricians have done a reasonably good job of accounting for those behaviors. His criticism of psychometricians is that the behaviors they study are simply too narrowly defined to qualify as human intelligence. In this critique, the reviewer addresses two questions: Is TMI an acceptable scientific theory and is the evidence for successes in schools that follow Gardner's recommendations evidence for the validity of TMI as a guide to educators? (PsycINFO Database Record (c) 2016 APA, all rights reserved)
Article
Females and males show different average patterns of academic achievement and scores on cognitive ability tests. Females obtain higher grades in school, score much higher on tests of writing and content-area tests on which the questions are similar to material that was learned in school, attain a majority of college degrees, and are closing the gap in many careers that were traditionally male. By contrast, males score higher on standardized tests of mathematics and science that are not directly tied to their school curriculum, show a large advantage on visuospatial tests (especially those that involve judgments of velocity and navigation through three-dimensional space), and are much more knowledgeable about geography and politics. A cognitive-process taxonomy can shed light on these differences.
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This review provides an account of the Study of Mathematically Precocious Youth (SMPY) after 35 years of longitudinal research. Findings from recent 20-year follow-ups from three cohorts, plus 5- or 10-year findings from all five SMPY cohorts (totaling more than 5,000 participants), are presented. SMPY has devoted particular attention to uncovering personal antecedents necessary for the development of exceptional math-science careers and to developing educational interventions to facilitate learning among intellectually precocious youth. Along with mathematical gifts, high levels of spatial ability, investigative interests, and theoretical values form a particularly promising aptitude complex indicative of potential for developing scientific expertise and of sustained commitment to scientific pursuits. Special educational opportunities, however, can markedly enhance the development of talent. Moreover, extraordinary scientific accomplishments require extraordinary commitment both in and outside of school. The theory of work adjustment (TWA) is useful in conceptualizing talent identification and development and bridging interconnections among educational, counseling, and industrial psychology. The lens of TWA can clarify how some sex differences emerge in educational settings and the world of work. For example, in the SMPY cohorts, although more mathematically precocious males than females entered math-science careers, this does not necessarily imply a loss of talent because the women secured similar proportions of advanced degrees and high-level careers in areas more correspondent with the multidimensionality of their ability-preference pattern (e.g., administration, law, medicine, and the social sciences). By their mid-30s, the men and women appeared to be happy with their life choices and viewed themselves as equally successful (and objective measures support these subjective impressions). Given the ever-increasing importance of quantitative and scientific reasoning skills in modern cultures, when mathematically gifted individuals choose to pursue careers outside engineering and the physical sciences, it should be seen as a contribution to society, not a loss of talent. © 2006 Association for Psychological Science.
Chapter
A great deal of naive faith is conventionally put in the power of selective advantage to explain everything. The great virtue of this present book, over and above the lucidity of the exposition, is the frankness with which it questions fashionable assumptions on the topic of why sexual reproduction in so frequent a phenomenon when it wastes resources by producing males.The book is in ten chapters. After an initial survey of the scope of the inquiry, which provides an extended synopsis to the whole book, we have two chapters dealing with various aspects of sex and recombination. Special attention is paid to the significance of lag load, the neutral-gene controversy, the rates of hard and soft selection, and the operation of Muller's ratchet. The fourth chapter is largely concerned with accounting for successful parthenogenetic higher organisms. Sex and recombination are taken up again in the next three chapters which include a discussion on whether chiasmata are really necessary, and the selective role of linkage disequilibrium. The evolution of hermaphroditism is treated in chapter 8. It is not clear why monecy should reach such a high frequency in North American temperate forest, nor are the various circumstances under which hermaphroditism has evolved in animals apparent. Sex ratio is considered in chapter 9. The difficult subject of sexual selection is approached using the concept of evolutionarily stable strategy. The final chapter deals with sex and mutation rate.The author is to be complimented on the way in which he has made a peculiarly difficult theoretical enquiry accessible to the general biological reader.
Article
The Educational Testing Service (ETS) Gender Study is the result of 4 years of work by several researchers using data from more than 400 tests and other measures from more than 1,500 data sets involving millions of students. The study focuses on nationally representative samples that cut across grades (ages), academic subjects, and years in order to control factors that may have introduced confusion and contradictory results into previous studies of gender differences in educational settings. Results indicate that gender differences are not quite as expected. For nationally representative samples of 12th graders, the gender differences are quite small for most subjects, small to medium for a few subjects, and quite symmetrical for females and males. There is not a dominant picture of one gender excelling academically, and in fact, the average performance difference across all subjects is essentially zero. The familiar mathematics and science advantage for males was found to be quite small, significantly smaller than 30 years ago. However, a language advantage for females has remained largely unchanged over that time period. Also, gender differences for component skills of academic disciplines were often different than for the discipline as a whole. Gender differences were shown to change as students grew older and moved to higher grades. Patterns of gender differences in performance are similar to patterns of differences in interests and out-of-school activities, suggesting that a broad constellation of events relates to observed differences. Results show larger gender differences for self-selected groups taking high-stakes tests than for nationally representative samples, reflecting primarily the wider spread of male scores. Results indicate that neither guessing, speededness, nor the multiple-choice format per se accounts for the gender differences. However, results on presently used open-ended questions sometimes reflected no gender effect and sometimes reflected effects in which females' performances exceeded those of males and vice versa. Implications of these findings are discussed. A list of 67 resources for further reading is included. (Contains 8 figures and 19 endnotes.) (SLD)
Article
This article argues that the differences between 2 groups in means and variances must be examined together because left- and right-tail ratios (expressing group differences in proportions of low and high scores, respectively) are asymmetrical when distributions differ in both central tendency and dispersion. The point was illustrated by an analysis of tail effect sizes from the Differential Aptitude Tests, which found that sex differences—and the developmental trends in those differences—were generally different at the left tail than at the right tail. The implications of the additive effects of group differences in central tendency and variability for both descriptive analyses and theory testing in primary research and meta-analysis are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Reviews The revision of the Stanford-Binet scale: an analysis of the standardization data (see record 1942-03329-000). This is a companion and supplementary volume to Terman and Merrill's Measuring Intelligence. Essentially, it is a presentation, summary, and analysis of the data upon the basis of which the 1937 revision of the Stanford-Binet scale was constructed and standardized. Except for Chapter 1, the book was written entirely by McNemar, who is certainly to be commended for the compact and succinct form in which the material is presented. A minimum of long-winded discussion and speculation makes the book much easier to read than one might have anticipated. In summarizing the material in this monograph, I should like to express the opinion that the New Revision is the most useful and is certainly the best constructed instrument for measuring the intelligence of children which we now possess. It represents an achievement of first rank; and one of which all psychologists, no matter what their persuasion, may well be proud. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Analysis of data from 3 studies that have been cited as indicating support for the structure-of-intellect (SI) theory demonstrates that Procrustean factoring methods can be used to provide results that appear to support randomly determined theories. Such results can be obtained even though (a) variables were reliable and presumably interrelated in lawful ways; (b) factors were required to be orthogonal; (c) factor loadings used in interpretation were required to be at least .30; and (d) S sample numbers were as large as 175, 205, and 240. Findings are interpreted as indicating that the factor-analytic support for SI theory is not compelling because it is not appreciably better than the support that can be provided for theories generated by random procedures. (32 ref.) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
"Frequency distributions obtained on applying intelligence tests to large samples of the school population are analyzed, and compared with those given by the formulae for the commoner types of frequency curve. It is noted that the distributions actually observed are more asymmetrical and have longer tails than that described by the normal curve. The best fit is give by a curve of Type IV: this is in fact the type of distribution we should expect if (as has been argued in earlier papers) individual differences in general ability are determined partly by multifactorial and partly by unifactorial inheritance. It follows that the usual assumption of normality leads to a gross underestimate of the number of highly gifted individuals. The conclusions thus drawn are confirmed by a study of data from other sources; and various practical corollaries are deduced." (19 ref.) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Investigates the variability of the sexes in mental capacities by comparing school achievement of 62,219 boys and girls (13 yrs of age) from 20 cities. The results showed a slightly greater variability for the boys and girls made better school progress. However, the coefficient of variability was very small and therefore, it would be safer to consider boys and girls to be alike in mental variability. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
Considers that J. P. Guilford's (see PA, Vol 53:Issue 1) reply to the authors' criticisms of his factor analysis of his structure-of-intellect model has failed to come to grips with evidence indicating that if the number of targeted variables for each factor is 3 or fewer, Procrustes factoring provides no better evidence for structure-of-intellect theory than for any of an infinity of other arbitrarily determined theories. Under these conditions factors can be rotated in such a way as to suggest support for almost any desired solution, and one such solution can be that labeled a replication. Hence the factorial invariance claimed under such conditions can indicate only consistency in the researcher and his methods, not in the phenomena studied. (16 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
A survey of the literature on the nature and extent of individual variation with stress upon cultural causes of such variation. Harvard Book List (edited) 1938 #142 (PsycINFO Database Record (c) 2012 APA, all rights reserved)
—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 differ-ences 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.
Article
Two experiments examined motivations underlying the common finding that females present themselves more modestly than males in achievement situations. In Study 1, 388 first-year college students, primarily European-Americans, predicted their first semester grade point averages (GPAs) in one of 3 public and 2 private conditions, which varied the salience of modesty concerns and/or concerns about the others' feelings. In the public conditions combined, but not in the private conditions, women's predictions were lower than men's, although there were no gender differences in actual GPA. The public condition in which the others' feelings and modesty concerns were made salient accounted for this difference between men and women. In Study 2, 230 first-year college students predicted their first-semester GPAs in private, in public to a nonvulnerable other, or in public to a vulnerable other (someone who supposedly had earned a low GPA). Women's estimates were lower than men's in the latter condition only and lower than their estimates in the other conditions. These results suggest that relational motivations, rather than a simple lack of self-confidence or modesty alone, are a factor in gender differences in self-presentation of achievement.
Article
A cross-cultural quantitative review of contemporary findings of gender differences in variability in verbal, mathematical, and spatial abilities was conducted to assess the generalizability of U.S. findings that (a) males are more variable than females in mathematical and spatial abilities, and (b) the sexes are equally variable in verbal ability. No consistent gender differences (variance ratios) were found across countries in any of the three broad ability domains. Instead, males were more variable than females in some nations and females were more variable than males in other nations. Thus, the well-established U.S. findings of consistently greater male variability in mathematical and spatial abilities were not invariant across cultures and nations.