Steve Stewart-Williams Quotes

Several studies have concluded that tests of implicit bias (in particular, the Implicit Association Test or IAT) have poor test-retest reliability, and fail to predict discriminatory behaviour. Furthermore, though interventions may change people’s implicit biases to some degree – or do so, at least, in the short-term – the effects of such changes on behaviour are trivially small or non-existent, even in the immediate wake of the intervention.

In the quest to promote women in STEM, academics and activists may sometimes inadvertently overstate the ubiquity of bias and discrimination against women in this sector. An unintended consequence may be to scare away some women who would otherwise be interested in a STEM career... If women are given the impression that the STEM workplace is a hotbed of sexism and an unwelcome place for women, many might quite understandably decide to look for other fields in which to make their mark.

Real-world data going back to the 1980s suggest that, although fewer women apply for jobs in fields such as maths, physics, chemistry, biology, and engineering, those who do apply are no less likely to be interviewed and no less likely to be offered the job. On the contrary, they are generally more likely to be.

[T]he evidence for discrimination in STEM is considerably more mixed than is often assumed. Certainly, many studies have found evidence of anti-female discrimination in STEM. At the same time, however, many other studies have failed to find such discrimination, or have found discrimination in favour of women.

[A] large meta-analysis by Xu et al. (N = 254,231) concluded that gay men tend to have spatial and linguistic abilities comparable to those of straight women, whereas lesbians tend to have spatial abilities comparable to those of straight men (but female-typical linguistic abilities)... Gay men were presumably subject to essentially the same gender-specific social forces as straight men, and lesbians the same gender-specific social forces as straight women. As such, the near-reversal of the usual spatial vs. language pattern is hard to reconcile with the claim that this pattern is due largely to social forces.

[Sociocultural] explanations are vulnerable to a number of criticisms. To begin with, it is unclear to what extent current social influences actually point in the direction these explanations presuppose. According to one study, by four years of age, girls tend to assume that boys are academically inferior, and by seven, boys assume the same thing. Similarly, teachers tend to view their female students as superior at maths and reading, even when aptitude tests indicate that the boys are doing better. Popular culture often mirrors these trends, with girls depicted as academically superior to boys (consider, for instance, Bart and Lisa from The Simpsons, and Ron and Hermione from the Harry Potter series.

[A]mong the minority of people who possess exceptional mathematical abilities, the women are more likely to possess exceptional language abilities as well. This means that mathematically gifted women have more vocational options than their male counterparts, and consequently that fewer mathematically gifted women end up pursuing a STEM career. To the extent that this explains the gender gap in maths-intensive fields, the gap results not from mathematically gifted women having fewer options, but rather from them having more.

First, the claim is not that men perform better than women in every cognitive domain. On the contrary, men perform better in some domains whereas women perform better in others. The best-known examples are that men score higher than women on most tests of spatial ability, whereas women score higher than men on most tests of language ability, including verbal comprehension, reading, and writing... Second, even in areas where men do perform better, the claim is not that all men – or even most – perform better than all or most women. As with occupational preferences, members of both sexes vary enormously in every cognitive aptitude, and the distribution for men overlaps almost entirely with that for women. However, for some aptitudes, the distribution for one sex is shifted somewhat to the right of that for the other, such that the average score for the former is somewhat higher. In saying this, it’s worth stressing that the average score does not describe all members of the group, or even the typical member, but merely represents the central tendency within a broad array of scores. Most people fall above or below the average. Third, the claim is not that these cognitive sex differences are especially large. On the contrary, at the centre of the distribution, they tend to be quite small. The only reason they matter at all is that even small differences at the mean are associated with progressively larger differences the further from the mean one looks... Fourth, the claim is not that women lack the cognitive talents to make it in STEM. Most people lack the cognitive talents, and of those who do possess them, some are men and some are women.

[T]he same sex differences in occupational preferences have been found in every society where psychologists have looked for them. In one large study (N ≈ 200,000), Lippa found the differences in 53 out of 53 nations: a level of cross-cultural unanimity almost unheard of within psychology.

Sex differences in occupational preferences and priorities suggest one possible reason that more men than women go into maths-intensive STEM fields. The reason, put simply, is that more men than women want to go into these fields.

[I]f we make the reasonable ballpark assumption that people working in a given field tend to come from the 25% of people most interested in that field, sex differences in occupational interests would account for the entirety of the engineering gender gap and much of the gap in science and mathematics.

Members of both sexes can be found at every point on the things vs. people continuum; however, more men than women exhibit a stronger interest in things, whereas more women than men exhibit a stronger interest in people... To get an intuitive sense of the magnitude of the difference, if one were to pick pairs of people at random, one man and one woman, the man would be more things-oriented than the woman around 75% of the time.

[This] 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.

Whether a trait is natural or unnatural is irrelevant to the question of whether it’s good. Moral worth should be judged not in terms of the naturalness of a trait, but rather in terms of how that trait impacts the wellbeing of everyone affected by it. Thus, violence is natural but bad, medicine unnatural but good.

As memetic evolution picked up steam, humans were transformed. No longer were we devices designed solely to pass on our genes. Suddenly, we became hybrid creatures, torn between passing on our genes and passing on our memes. This vision of our species helps to explain much of what most puzzled the alien scientist: our moral systems, our religions, our art and music and science. Cultural evolution is the key to unravelling the deepest mysteries of the human animal.