by Isaac CohenOriginally Published: July 30th, 2014This summer, the largest Silicon Valley corporations released their workforce demographic data. The response wasn’t surprising. Despite a plethora of Asian employees, the entire technology industry was roundly excoriated for its stunning deficiency in diversity. Critics’ principal complaint: too many “white males,” too few women.The most relentlessly cited statistic was that women make up only 16% of the tech workforce. At first glance, this looks pretty lame. But once you catch your breath, you realize that most of these jobs require a bachelor’s degree in computer science. Women only earn 18% of such degrees awarded to United States residents. Not such a bad effort, then, by Google and company. Still, that didn’t stop the public shaming. Earnest apologies were issued, and calls were made for reform.Who deserves the brunt of our collective outrage over these lopsided ratios? More importantly, who should be charged with fixing them?One highly controversial theory — the one that got Larry Summers in deep trouble — argues that there are male advantages in math-related cognitive ability, especially at the so-called “right tail” end of the bell curve. But it’s not necessary to hit that third rail, because even the most capable women shy away from engineering and computer science.To my knowledge — I’m biased — no school enrolls more fiercely intelligent women than Yale. Yet even there, women are only 18% of computer science majors. The figures are similar at other high-flying schools that admit the best and the brightest women. Not unexpectedly, the prevailing narrative at Yale is that these numbers reflect some kind of glaring injustice. But what exactly is Yale doing wrong?Some commentators have suggested that women face a culture of sexism in the hard sciences. Since the numbers are similar in all of academia, these allegations are often aimed at the entire ivory tower. At Yale, for example, women make up only 24% of the tenured faculty , with the numbers higher in the humanities (30%) and social sciences (25%) and lower in the physical (11%) and biological (19%) sciences. Pointing the finger at sexism to explain these variations seems both plausible and appealing, but is it warranted?Not really. In fact, despite the mainstream media’s insistence that sexism is rife, there exists very little evidence of pervasive bias. Studies occasionally pop up that point to overt or subtle bias in academic hiring or funding, but they are debunked as often as they are trumpeted . And the discrimination that social scientists claim to demonstrate is rarely strong enough to explain observed disparities.Still, the data must be carefully examined with an open mind. Yale researchers recently asked science faculty at American universities to evaluate fictitious resumes for a lab management position. They found that these professors were slightly less likely to offer mentoring or a job to female applicants for a laboratory management position. And both male and female professors consistently rated otherwise identical applicants named Jennifer as slightly less competent than those named John.Does this mean that academic science is an evil patriarchy? Not necessarily. The study’s response rate (30%) and sample size (n = 127) were both fairly low. That doesn’t invalidate the results, but it is important to reproduce the study with a larger sample, especially in the social sciences . Even then, the results wouldn’t be incontrovertible proof of systemic bias. What occurs in artificial experiments doesn’t necessarily reflect the reality of hiring. Employers in the real world typically have a greater and more varied quantity of information, and decisions in academia are usually made by committee. Such practices help to stem unconscious prejudices.Finally, here’s a question: do men and women in these types of jobs on average actually perform identically and show equal commitment to the job, holding their credentials constant? If not — and that’s a big if — it might be that those doing the hiring are just unconsciously playing the odds, or engaging in what is termed “statistical” or “rational” discrimination. One less controversial example of this kind of “rational” bias is that auto insurance companies tend to charge men higher rates, because they are more likely, on average, to drive recklessly. Of course, this answer won’t make us feel any better if we think that candidates should be judged individually. But in a world of imperfect information where average gender differences are not unknown, it would at least explain why male and female professors were equally likely to be subtly biased against women. Ultimately, though, whether rational bias is at work is an empirical question.Let’s assume, however, that this study’s methodology was flawless and that the observed bias was irrational and not based on any real pattern of statistical differences. Its measured effect was still rather small, on the order of 10%. That’s not an atypical result. Indeed, despite a veritable cottage industry that strives to demonstrate discrimination in various settings, the magnitude of the bias that some researchers claim to measure is routinely quite modest. In the case of women in the hard sciences, the results of studies like these are far too weak to explain observed gaps. Could this discrimination “on the margin” explain the cavernous gender gap in the physical sciences at Yale and similar high-flying places? Almost certainly not.What matters is the relative contribution of discrimination against women, if it exists, compared to the contribution of other causes, such as choices, tastes, interests, preferences, ambitions, and life plans. This point relates to the all-important question of effect size: many factors could be at play, but some could have a much bigger influence. Unfortunately, we would never know that because social scientists often slight the issue of relative magnitudes, and the popular press seems unwilling to press the question. The next time you read an editorial piece that cites social science, remember three words: effect size matters.Novice researchers often enter behavioral psychology convinced of the blank slate thesis. They believe that little boys and girls are born tabula rasa. Parents, teachers, and society then proceed to mold children’s interests, talents, and temperaments towards the dominant gender stereotypes.Tenured faculty members have a word for blank slate proponents: “childless.”That joke is funny because, despite the suffocating aura of political correctness that pervades today’s public discourse on gender and group differences generally, many people — including academics — still retain a glimmer of common sense. Even the most stalwart defender of the progressive order will admit, after a few drinks, that the pure “social construct” theory of gender is an idea so implausible that only intellectuals could believe it. But she won’t dare say so in public. On this subject the mainstream media — that shallow forum of modern thought — has deeply dug in its heels. Non-physical or behavioral differences between the sexes have become the mokita of our era; they are the “truth we all know but agree not to talk about.”Well, thanks to the media, we might not even actually know about the research that reveals such differences. The problem today is no longer just “lies, lies, and damned statistics.” Instead, the crucial sins are those of omission. Certain types of findings are routinely ignored, slighted, or repressed . Social science that points to discrimination is shouted from the rooftops, but research that casts doubt on such sources or identifies other causes is hastily shoved under the rug. One longstanding study carried out at John Hopkins by Camilla Benbow and David Lubinski suggests that gender differences in interests, tastes, lifestyle preferences, and goals are a significant driver of skewed gender ratios in STEM fields. Benbow and Lubinski followed the 20-year educational and career outcomes of nearly 3,000 girls and boys who were identified in their early teens as profoundly gifted in mathematical reasoning ability, and thus most prepared and encouraged to study STEM subjects. What they found is revealing.Participants of both sexes mostly viewed themselves as “successful in their chosen professions,” and men and women didn’t vary significantly in satisfaction with their careers, even when career as a homemaker was included. When the participants ranked their lifestyle and work preferences, there were no sex differences in the importance of “continuing to develop my intellectual interests,” “continuing to develop my skills/talents,” “having leisure time to enjoy avocational interests,” or “having time to socialize,” among others.Yet some gender disparities stood out. Men placed greater importance than women on “being successful in my line of work,” “inventing or creating something that will have an impact,” and “having lots of money.” Women stressed “having strong friendships,” “living close to parents and relatives,” and “having children.” Overall, men appeared to emphasize career success while women sought balance. The sexes were similar in self-esteem and other self-concept indicators. Most importantly, men and women, on average, entered different fields and professions, and they varied in how they chose to allocate their time. More recent evidence confirms that men and women of formidable talent don’t make the same educational choices. Last year, women were still seriously underrepresented among those enrolled in Harvard and MIT online courses, including computer science (19%), circuits and electronics (9%), and elements of structures, a physics course with a side of linear programming (5%). Women who do take these courses get the same grades, and they actually have higher completion rates than their male counterparts. But on average, even in the privacy of their own homes and without the pressures and publicity of the classroom, they don’t seem as eager to develop these skills. Another striking study suggesting that men and women may not have identical tastes and interests is rarely, if ever, discussed in the media. Researchers looking at the distribution of childcare in families of assistant professors with small children found that most of the study subjects believed that husbands and wives should share childcare equally. Yet even the men with such beliefs still did much less childcare relative to their spouses than female professors.One reason for the prevailing discrepancy may have been that women simply like childcare more than men do. Female professors reported that they enjoyed childcare much more than male professors. The gender gap in enjoyment of childrearing was not associated with gender role attitudes or leave-taking. Rather, it seemed to reflect genuine differences in how professionally committed men and women felt about the day-to-day experience of taking care of kids.Some people may find these results discomfiting. Resistors are tempted to set up a straw man: “Are you saying you want women to be 1950s housewives again?” But that’s not what these data imply. It helps to remember, as Steven Pinker has written , that “equity feminism is a moral doctrine about equal treatment that makes no commitments regarding open empirical issues in psychology or biology.” This sort of common sense feminism, which stresses equality of choice over equality of outcome, tends to get lost in the breast-beating over diversity.In an effort to account for observed gender disparities in a “gender neutral” way, diversity hawks resort to the fanciful notion that we literally swim through an “ether” of sexism. I call this the “ether politics” of gender. The phrase is disconcertingly apt. I asked one of my friends on the Left to explain it, and she actually made swimming motions with her arms. Is this the best we can do?According to “ether” sexism, parents, teachers, and our entire culture create — often unknowingly — a noxious miasma that contributes to a systematic and early barrage of gendered, subliminal messages. This effectively discourages women from doing anything that doesn’t fit with hoary notions of femininity. Does an invisible, ineffable fog of oppression truly engulf modern American women? The evidence is increasingly strained and far-fetched.For one thing, the “ether” theory isn’t completely impervious to evidence. We can test for coercive socialization, or at least try to. In 1991, one meta-analysis of 172 studies found virtually no disparity in how parents mold the social behavior or abilities of boys and girls. There was no evidence overall of “parents making any consistent difference” by gender in the areas of “encouragement of achievement,” “restrictiveness,” “disciplinary strictness,” “warmth,” and “encouragement of dependence.” In fact, four studies found that in many Western countries, parents as a whole encouraged achievement more in girls than in boys. That pattern fits with women’s growing edge in academic rank and college completion.For some sex-stereotypical behaviors, such as playing with dolls or trucks, parents (and especially dads) show a mild tendency to shape children’s behaviors in conventional ways. But, as the authors point out, this observation could reflect a parental response to children’s pre-existing play preferences, which show up quite early. None of the studies rule out that possibility. All in all, there were no signs of an oppressive or restrictive fog. Differences in parental socialization of boys and girls were non-existent at best and modest at worst.Twenty-three years after that study, here is the reality: the mainstream media, the powers that be in higher education, and — most importantly — the parents and families of college-bound women are all but begging them to study the hard sciences. We live in an age of aggressive parental pampering and cheerleading. Many of the women at schools like Yale come from liberal, relatively elite families who would love to see their daughters enter fields like math, computer science, engineering, and physics. So the notion that today’s cultural message is that women “can’t do science and math” just doesn’t fit with the prevailing zeitgeist.What families encourage institutions like Yale reinforce. Academia is a blinding beacon of modern liberalism, and when it comes to an all-consuming progressive ethos, it really is true that, as we say: “There’s no place like Yale.” The advanced introductory computer science course at Yale, CS 201, is taught by two brilliant female professors, and the department’s latest hire is a woman. Legions of math-savvy women enroll at Yale every year. The doors to computer science courses are wide open. The notion that women face large discriminatory barriers in the sciences at Yale and schools like it just looks, to an ordinary undergraduate like me, simply preposterous. The courses are there — I’m in them. The professors are busy, but they’re eager to help. The opportunities are endless, and they are there for the taking. Despite these realities, the consensus is that Yale and its students should all be ashamed. It’s hard to see why.Another aspect of the “ether” account of male-dominated STEM ratios rests on the assertion that academic science and the tech industry are “institutionally sexist.” The idea is that these sectors are made up mostly of men and that both endeavors exemplify and reward what are traditionally thought of as “male values”: competitiveness, aggressive risk-taking, staunch meritocracy, obsessive focus, and a relative lack of work-life balance. Feminists argue that these attributes make the hard sciences unwelcoming and unattractive to women.The belief that those traits that make for success in science and technology are inherently “masculine,” rather than simply human, is far from universally shared, and it is belied by generations of distinguished female scientists. Yet it’s worth asking to what extent we could drain the scientific enterprise of its so-called “masculine” elements and still maintain its quality, rigor, creativity, and output. As long as long hours, hard work, and zealous dedication pay scientific dividends — and they do — men and women who are pushing the hardest will likely achieve the most and rise to the top. Thus, real achievement in science will probably always require intense focus and drive.Do we even know how to design a system in which that’s not the case? Many institutions and companies are attempting to make some changes , but ultimately no one really knows how to eliminate all the elements that purportedly keep women away. And where is the guarantee that, if we somehow manage to make science more “feminine” — which will almost certainly be a costly, meddlesome, and uncertain process — women will flock to the field in greater numbers? Reality may well disappoint, and the ratios may not approach anything like the exalted ideal of 50-50.In any event, the tech sector is famously innovative and keenly interested in finding good workers and keeping them happy. Rather than imposing heavy-handed solutions backed by special interest groups and bureaucrats, why not let these industries find the best way forward for themselves?Nonetheless, there is no getting around the fact that, as Benbow and Lubinski suggest, ultra-capable, math-savvy women have a different profile of interests, on average, than their male counterparts, at least for now. For every woman who chooses law or medicine, one fewer will enter computer science. There will always be many brilliant women in hard science fields, but that doesn’t mean that the ratios will ever be balanced.And why should we want them to be? For all the talk of empowerment, it is odd that so many still doubt women’s capacity to choose their own careers. It’s worth noting that many of the women who complain about the dearth of women in science don’t themselves enter these fields. It’s “science for thee, but not for me.” Does it occur to them that their personal choices do nothing to increase the number of female scientists? And would those critics admit to making their own life decisions under duress?Above all, the eternal quest for diversity threatens to distract us from the core mission of the scientific enterprise: to acquire knowledge, to explain nature, to discover physical truths, and to innovate and invent. When the brakes on a Chevrolet Volt fail, what surely won’t matter is whether their design team looked like America. The adamant declarations of some feminist critics notwithstanding, science does not need more women. Science needs more scientists.