Sex differences in the right tail of cognitive abilities: An update and cross cultural extension

Talent denied: Equity and excellence gaps in STEMM

In principle, there could be STEMM talent everywhere if there were sufficient and adequate opportunities and learning resources everywhere. The reality, however, is that the likelihood of developing one's talent in STEMM is tied to membership in social groups. In this contribution, we explore the implications of this statement with multiple examples for different social groups and for different stages of talent development. We propose an educational framework model for analyzing equity gaps in STEMM talent development that identifies and systematizes the unequal and inequitable distribution of resources and opportunities as the proximal cause of the emergence of such equity gaps. Furthermore, we discuss important aspects for closing equity gaps in STEMM talent development. We argue that-similar to public health approaches-the focus in establishing equity in STEMM talent development should be on prevention rather than intervention. We discuss the importance of the cooperation of societal subsystems and argue for the use of adequate methods of disparity detection for creating equal opportunities. We also outline why preventive strategies are crucial for the creation of resource parity and explain why outcome standards should be considered obligatory.

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 (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.