The cause of sex-related ability tilt is irrelevant with regard to the consequences on STEM employment. Whether due to socialization alone, innate ability alone, some combination of the two, or causes we don't understand, the outcome is the same and the consequences are the same.
In my experience, qualitative arguments of the form above rarely change people's minds but a quantitative model will help.
The question asked is the causal network that contributes to mathematical genius and the distribution of contributing causal factors within the population -- P(genius | factors)
Various factors are clearly involved: P(genius | intelligence), P(genius | hard work), P(genius | self-confidence), and so on.
If we accept that those functions are probably not uniformly distributed and that some have a stronger impact than others, we can see that most arguments can be reduced to describing those functions or describing the distributions of those factors among the population.
Where most educated people's intuitions lead them astray is that the experience of segregation in higher education and employment has led them to vastly underestimate the actual variance in factors like intelligence, hard work and self-confidence among people.
Vanishingly few individual actually possess the right combination of factors required for mathematic genius.
That's an entirely reasonable skeptical point of view to take in the absence of other evidence. However, this question has also been examined. Using typical measures of socioeconomic status (e.g. an index of education + income), one finds that controlling for socioeconomic status does little to explain the black-white IQ gap. There is a sizable gap at every level of socioeconomic status. Data: http://sites.biology.duke.edu/rausher/Hm2.jpg
The article's author also wrote a book advocating a universal basic income, “In Our Hands: A Plan to Replace the Welfare State,” which was first published in 2006. In that book he allows that services for the disabled would need to be retained and could not be replaced with a UBI.
>Or consider the unemployed young man who fathers a child. Today, society is unable to make him shoulder responsibility. Under a UBI, a judge could order part of his monthly grant to be extracted for child support before he ever sees it. The lesson wouldn’t be lost on his male friends.
> Or consider teenage girls from poor neighborhoods who have friends turning 21. They watch—and learn—as some of their older friends use their new monthly income to rent their own apartments, buy nice clothes or pay for tuition, while others have to use the money to pay for diapers and baby food, still living with their mothers because they need help with day care.
The author seems to be proposing that child support for 3 children can/should be taken from their fathers' UBI grants. Therefore, the mother would receive a larger grant based on her number of children.
(1) "Shalizi’s first error is his assertion that cognitive tests correlate with each other because IQ test makers exclude tests that do not fit the positive [correlation matrix]. In fact, more or less the opposite is true. ... Cognitive tests correlate because all of them truly share one or more sources of variance."
(2) "Shalizi’s second error is to disregard the large body of evidence that has been presented in support of g as a unidimensional scale of human psychological differences. The g factor is not just about the positive [correlation matrix]. A broad network of findings related to both social and biological variables indicates that people do in fact vary, both phenotypically and genetically, along this continuum that can be revealed by psychometric tests of intelligence and that has has widespread significance in human affairs."
(3) "Shalizi’s third error is to think that were it shown that g is not a unitary variable neurobiologically, it would refute the concept of g. However, for most purposes, brain physiology is not the most relevant level of analysis of human intelligence. What matters is that g is a remarkably powerful and robust variable that has great explanatory force in understanding human behavior. Thus g exists at the behavioral level regardless of what its neurobiological underpinnings are like."
Conclusion: "In many ways, criticisms of g like Shalizi’s amount to “sure, it works in practice, but I don’t think it works in theory”. Shalizi faults g for being a “black box theory” that does not provide a mechanistic explanation of the workings of intelligence, disparaging psychometric measurement of intelligence as a mere “stop-gap” rather than a genuine scientific breakthrough. However, the fact that psychometricians have traditionally been primarily interested in validity and reliability is a feature, not a bug. Intelligence testing, unlike most fields of psychology and social science, is highly practical, being widely applied to diagnose learning problems and medical conditions and to select students and employees. What is important is that IQ tests reliably measure an important human characteristic, not the particular underlying neurobiological mechanisms."
