PINKER: Thanks, Liz, for a very stimulating and apposite presentation. A number of comments. I don't dispute a lot of the points you made, but many have lost sight of the datum that we're here to explain in the first place. Basic abilities like knowing that an object is still there when you put a hankie over it, or knowing that one object can't pass through another, are not the kinds of things that distinguish someone who's capable of being a professor of physics or math from someone who isn't. And in many of the cases in which you correctly said that there is no gender difference in kids, there is no gender difference in adults either — such as the give-a-number task and other core abilities. Also, a big concern with all of the null effects that you mentioned is statistical power. Bob Rosenthal 20 years ago pointed out that the vast majority of studies that psychologists do are incapable of detecting the kinds of results they seek, which is why it's so important to have meta-analyses and large sample sizes. I question whether all of the null results that you mentioned can really be justified, and whether they are comparable to the studies done on older kids and adults. One place where I really do disagree with you is in the value of the SAT-M, where the "circle" has amply been broken. This is what people at the College Board are obsessed with. What you are treating as the gold standard is performance in college courses. But the datum we are disputing is not how well boys and girls do in school, or how well men and women do in college, because there we agree there is no male advantage. The phenomenon we really are discussing is performance at the upper levels: getting tenure-track job, getting patents, and so on. And here the analyses have shown that the SAT is not biased against girls. That is, a given increment in SAT score predicts a given increment in the variable of interest to the same extent whether you're male or female. I think there may be a slight difference in which finding each of us is alluding to in talking about differences in grades. I was not suggesting that girls' better grades come about because they take easier courses; they really do get better grades holding courses constant. Rather it's the slight underprediction of grades by the SAT that can be explained in part by class choice and in part by conscientiousness. SPELKE: Well the most recent thing that I've read about this issue is the Gallagher and Kaufman book, Gender Differences in Mathematics, which just came out about a month ago. They report that equating for classes and institutions, and looking just at A students, there's a 21 point SAT math differential; that is to say, for two students getting the same grade of A, the average for the girls on the SAT will have been 21 points lower. That differential is there at every grade level and in all the courses. The SAT people have discussed it as a problem. One of the discussions reached the conclusion that the SAT is still useful, because although it under-predicts girls' performance in college, girls' grades over-predict their performance in college, and if you use the two together you are okay. In fact, they advised that people never take account of the SAT simply by itself, but consider it in relation to grades. When you spoke earlier about the use of GREs in admitting people to grad school, that's in fact what graduate programs do: We consider both grades and GREs. Interestingly, though, in all of the public discussion of the relative advantages of men versus women for math and science, over the last two months, people have not used the SAT in conjunction with grades. When talking about relative ability, they've used the SAT by itself. I think that has led to a distorted conversation about this issue. PINKER: It nonetheless remains true that in the most recent study by Lubinski and Benbow, which showed a fantastic degree of predictive power of the SAT given in 7th grade, there was no difference in predictive power in boys and girls in any of these measures. But let me return to the datum that is at issue here, namely the differential representation of the sexes in physical sciences, mechanical engineering, and mathematics. The fact that men and women are equal overall in spatial abilities, and overall in mathematical abilities, is irrelevant to this. It may be that the particular subtalents in which women excel make them more likely to go into accounting. But the datum we are discussing is not a gender difference in accounting. The datum we are discussing is a gender difference in the physical sciences, engineering, and mathematics. And I suspect that when you look at a range of professions, the size of the sex discrepancy correlates with how much spatial manipulation (not just any kind of spatial cognition) and how much mathematical reasoning (not just any kind of mathematical ability) each of those jobs requires. What about parents' expectations? In the 1970s the model for development was, "as the twig is bent, so grows the branch." — that subtle differences in parents' perceptions early in life can have a lasting effect. You nudge the child in a particular direction and you'll see an effect on his trajectory years later. But there is now an enormous amount of research spearheaded by the behavioral genetics revolution suggesting that that is not true. There may be effects of parental expectations and parental treatment on young children while they're still in the home, but most follow-up studies show that short of outright abuse and neglect, these effects peter out by late adolescence. And studies of adoption and of twins and other sibs reared apart suggest that any effects of the kinds of parenting that are specific to a child simply reflect the preexisting genetic traits of the child, and the additional effect of parenting peters out to nothing. SPELKE: Can I respond to that? I think one thing is different about the gender case, compared to the early socialization effects for other kinds of categories, different styles of parenting, and so forth. The gender differences that we see reflected in parents' differing perceptions are mirrored by differing perceptions that males and females experience throughout their lives. It's not the case that idiosyncratic pairs of parents treat their kids one way, but then as soon as the children leave that environment, other people treat them differently. Rather, what we have in the case of gender is a pervasive pattern that just keeps getting perpetuated in different people. I'm rather a nativist about cognition, and I am tempted to look at that pattern and wonder, did Darwin give us some innately wrong idea about the genders? Professionals in professional contexts show the same patterns of evaluation that parents show in home contexts, and children face those patterns of evaluation, not just when they're young and at home, but continuing through high school, college, and finally with their colleagues on academic faculties. We're dealing here with a much more pervasive effect than the effects of socialization in the other studies that you've written and talked about. PINKER: Regarding bias: as I mentioned at the outset, I don't doubt that bias exists. But the idea that the bias started out from some arbitrary coin flip at the dawn of time and that gender differences have been perpetuated ever since by the existence of that bias is extremely unlikely. In so many cases, as Eagly and the Stereotype-Accuracy people point out, the biases are accurate. Also, there's an irony in these discussion of bias. When we test people in the cognitive psychology lab, and we don't call these base rates "gender," we applaud people when they apply them. If people apply the statistics of a group to an individual case, we call it rational Bayesian reasoning, and congratulate ourselves for getting them to overcome the cognitive illusion of base rate neglect. But when people do the same thing in the case of gender, we treat Bayesian reasoning as a cognitive flaw and base-rate neglect as rational! Now I agree that applying base rates for gender in evaluating individual men and women is a moral flaw; I don't think that base rates ought to be applied in judging individuals in most cases of public decision-making. But the fact that the statistics of a gender are applied does not mean that their origin was arbitrary; it could be statistically sound in some cases. SPELKE: Let me reply to that, because I agree that the origin is not arbitrary, and that the bias is there for an objective reason, but I think you're drawing the wrong conclusion about it. I think the reason there's a bias to think that men have greater natural talent for math and science is that when we look around the world and ask, who's winning the Nobel Prizes and making the great advances in science, what we see, again and again, is men. Although Linda Buck received this year's Nobel Prize in physiology or medicine, for the most part it's overwhelmingly men who are reaching the upper levels of math and science. It's natural to look at that and think, there must be some reason, some inner difference between men and women, which produces this enormous disparity. And I quite agree with you that good statistical reasoning should lead you to think, the next student who comes along, if male, is more likely to join that group of Nobel Prize winners. What I would like to suggest is that we have good reasons to resist this kind of conclusion, and the reasons aren't only moral. Let me just use an analogy, and replay this debate over the biological bases of mathematics and science talent 150 years ago. Let's consider who the 19th century mathematicians and scientists were. They were overwhelmingly male, just as they are today, but also overwhelmingly European, not Asian. You won't see a Chinese face or an Indian face in 19th century science. It would have been tempting to apply this same pattern of statistical reasoning and say, there must be something about European genes that give rise to greater mathematical talent than Asian genes do. If we go back still further, and play this debate in the Renaissance, I think we would be tempted to conclude that Catholic genes make for better science than Jewish genes, because all those Renaissance scientists were Catholic. If you look at those cases, you see what's wrong with this argument. What's wrong with the argument is not that biology is irrelevant. If Galileo had been switched at birth with some baby from the Pisan ghetto, the baby raised by Galileo's parents would not likely have ended up teaching us that the language of physics is mathematics. I think that Galileo's genes had something to do with his achievement, but so did Galileo's cultural and social environment: his nurturing. Genius requires huge amounts of both. If, in that baby switch, Galileo had found himself growing up in the Pisan ghetto, I bet he wouldn't have ended up being the example in this discussion today either. So yes, there are reasons for this statistical bias. But I think we want to step back and ask, why is it that almost all Nobel Prize winners are men today? The answer to that question may be the same reason why all the great scientists in Florence were Christian. PINKER: I think you could take the same phenomenon and come to the opposite conclusion! Say there were really was such a self-reinforcing, self-perpetuating dynamic: a difference originates for reasons that might be arbitrary; people perceive the difference; they perpetuate it by their expectations. Just as bad, you say, is the fact that people don't go into fields in which they don't find enough people like themselves. If so, the dynamic you would expect is that the representation of different genders or ethnic groups should migrate to the extremes. That is, there is a positive feedback loop where if you're in the minority, it will discourage people like you from entering the field, which will mean that there'll be even fewer people in the field, and so on. On either side of this threshold you should get a drift of the percentages in opposite directions.



Now, there is an alternative model. At many points in history, arbitrary barriers against the entry of genders and races and ethnic groups to various professions were removed. And as soon as the barrier was removed, far from the statistical underrepresentation perpetuating or exaggerating itself, as you predict, the floodgates open, and the formerly underrepresented people reaches some natural level. It's the Jackie Robinson effect in baseball. In the case of gender and science, remember what our datum is. It's not that women are under-represented in professions in general or in the sciences in general: in many professions women are perfectly well represented, such as being a veterinarian, in which the majority of recent graduates are women by a long shot. If you go back fifty years or a hundred years, there would have been virtually no veterinarians who were women. That underrepresentation did not perpetuate itself via the positive feedback loop that you allude to. SPELKE: I'm glad you brought up the case of the basketball and baseball players. I think it's interesting to ask, what distinguishes these cases, where you remove the overt discrimination and within a very short period of time the differential disappears, from other cases, where you remove the overt discrimination and the covert discrimination continues? In the athletic cases where discrimination disappears quickly, there are clear, objective measures of success. Whatever people think about the capacities of a black player, if he is hitting the ball out of the park, he is going to get credit for a home run. That is not the case in science. In science, the judgments are subjective, every step of the way. Who's really talented? Who deserves bigger lab space? Who should get the next fellowship? Who should get promoted to tenure? These decisions are not based on clear and objective criteria. These are the cases where you see discrimination persisting. You see it in academia. You see it in Claudia Goldin's studies of orchestra auditions, which also involve subtle judgments: Who's the more emotive, sensitive player? If you know that the players are male or female, you're going pick mostly men, but if the players are behind a screen, you'll start picking more women. PINKER: But that makes the wrong prediction: the harder the science, the greater the participation of women! We find exactly the opposite: it's the most subjective fields within academia — the social sciences, the humanities, the helping professions — that have the greatest representation of women. This follows exactly from the choices that women express in what gives them satisfaction in life. But it goes in the opposite direction to the prediction you made about the role of objective criteria in bringing about gender equity. Surely it's physics, and not, say, sociology, that has the more objective criteria for success. SPELKE: Let me just say one thing, because I didn't say much in the talk at all, about this issue of motives, and biological differences in motives. That's been a less controversial issue, but I think it's an important one, and most of your examples were concerned with it. I think it's a really interesting possibility that the forces that were active in our evolutionary past have led men and women to evolve somewhat differing concerns. But to jump from that possibility into the present, and draw conclusions about what people's motives will be for pursuing one or another career, is way too big a stretch. As we both agree, the kinds of careers people pursue now, the kinds of choices they make, are radically different from anything that anybody faced back in the Pleistocene. It is anything but clear how motives that evolved then translate into a modern context. Let me just give one example of this. You've suggested, as a hypothesis, that because of sexual selection and also parental investment issues, men are selected to be more competitive, and women are selected to be more nurturant. Suppose that hypothesis is true. If we want to use it to make predictions about desires for careers in math and science, we're going to have to answer a question that I think is wide open right now. What makes for better motives in a scientist? What kind of motives are more likely to lead to good science: Competitive motives, like the motive J. D. Watson described in The Double Helix, to get the structure of DNA before Linus Pauling did? Or nurturant motives of the kind that Doug Melton has described recently to explain why he's going into stem cell research: to find a cure for juvenile diabetes, which his children suffer from? I think it's anything but clear how motives from our past translate into modern contexts. We would need to do the experiment, getting rid of discrimination and social pressures, in order to find out.