6
The Male Brain as Systemizer:
The Evidence

Mechanical and Constructional Play

There is a lot of evidence to show that there are big differences in the ways the two sexes play. Boys, even as toddlers, are more interested in cars, trucks, planes, guns, and swords, and the noises that they make while they play tend to be appropriate to these sorts of toys (motor sounds, bangs, and sirens). Even at two years of age, boys show a stronger interest in building blocks and mechanical toys, while girls show a stronger interest in dolls, jewelry, dressing up, and adornment.

In a classic test of this one leaves a choice of toys out on the carpet, and waits to see which ones a child picks. By two years of age, little boys are far more likely to select toy vehicles and building bricks to play with, leaving the dolls to one side. Girls of this age tend to choose the dolls.

As children grow older, one can see the same pattern: boys spend more time engaged in mechanical play (for example, with toy cars) and construction play (for example, building with blocks) than do girls. Boys seem to love putting things together, to build toy towers or towns or vehicles. Often, when they have sat and admired their wonderful construction, they will simply take it apart again. Boys also enjoy playing with toys that have clear functions—things with buttons to press, things that will light up, or devices that will cause another object to move: systems.

Although you might think that this is only true of boys living in a Western or technological society, the same broad pattern has also been found in pre-industrial societies. For example, a study of drawings showed that boys in a pre-industrial society more often drew machines of some kind. They did not draw machines that we are more familiar with, such as electrical devices, but machines that are far more universal, such as tools, weapons, and vehicles.

This interest in the mechanical and the constructional is not simply a sign that boys are more object-oriented, since girls play with some objects (like clay and marker pens) more often than boys. Rather, it seems that boys are more interested in mechanical and constructional systems. They are more interested in systemizing.1 Recall from Chapter 4 that this pattern is seen in twelve-month-old boys, who look longer at a film of cars than do girls, and even in one-day-old baby boys, who look for longer at a mechanical mobile.²

Interestingly, you see the same sort of pattern in the adult workplace, too. Some occupations are almost entirely male. Take, for example, the fields of metalworking, weapon-making, or crafting musical instruments. Or the construction industries, such as boat-building. These occupations are almost always carried out by men, and this sex difference is seen universally, not just in the Western world. This sex difference does not reflect the greater physical strength in males since, in many of these occupations (making a violin or a knife are good examples), strength is not the key factor. The focus of these occupations is on constructing systems.³

How can we draw a link between the observations of infants, children, and adults that I have described? One link is that attention in males and females is being drawn to different aspects of the environment. In one fascinating test, men and women were shown a series of human figures and mechanical objects, using a stereoscope. This equipment allows the human-figure picture and the mechanical-object picture to fall on the same part of the observer’s visual field. The two stimuli compete for the observer’s attention. Guess the results? Male observers reported seeing more mechanical objects than people, compared to the females. Female observers reported seeing more people than mechanical objects, compared to the males. And, of course, mechanical objects are systems.⁴

Math, Physics, and Engineering

Professions (in the industrialized world) such as math, physics, and engineering require high systemizing abilities. In musical-instrument-making, or building a tool or a boat, if one changes a detail in the input to the system, or the operation it performs, the output can be radically affected. So it is in math, physics, or engineering. Change one number in the formula, or the width of the device, and the whole system may no longer work, or may function suboptimally.

Physics and engineering are, of course, the adult equivalent of children’s play with mechanical and constructional toys. Indeed, all the sciences utilize systemizing as their basis, and all are dominated by men. According to a headline in the Times Higher, only three of the 170 living Nobel Prizewinners in science are women.5 In the 1970s the sex ratio of those working in the fields of math, physics, and engineering was about 9:1 (male:female) and this remains the case today. So, too, those fields where math is applied, such as mathematical modeling in economics or statistics.

Some have argued that this is because these disciplines are unfriendly to women. However, the pattern across the different sciences suggests that something more subtle is going on. For example, in one survey conducted by the National Science Foundation in the USA, 23 percent of scientists in biology were women, whereas in physics only 5 percent were women, and in engineering only 3 percent. A similar pattern has been found in other countries. Although there is no evidence that physics and engineering are less friendly to women applicants than biology,⁶ it could be that some pernicious, unconscious sexism operates at the point of selection. For example, interviewers may expect male applicants to make better students, given their experience from teaching male-dominated classes in the past. This would be hard to test as interviewers are hardly going to express any conscious sexism of this kind freely. And if the sexism is unconscious, the interviewers by definition will be unaware of it.

I work at Trinity College Cambridge in England, where there is a wonderful concentration of mathematicians, physicists, and engineers. Chatting at lunch with my colleagues in these disciplines leads me to suspect that if anything, many of them hold the opposite bias: that if they catch a glimpse of a talented female applicant, they try extra hard to accept her into the course, to reverse centuries of discrimination.

A less sexist possible explanation for the sex difference in physics and engineering is that there could be an inadvertent selection bias into these two disciplines if a mathematical reasoning test is used as a selection criterion. This would not be unreasonable on the part of physics and engineering departments, given that mathematical ability is a good predictor of success in these fields. However, it may be math that skews the sex ratio in these fields. Corroborating evidence can be found in the ratio of ten males to every female who perform at the top end of the SAT-M, the Scholastic Aptitude Math Test that is administered nationally to college applicants in the USA.7

An alternative explanation is that there is no external selection bias. Rather, perhaps men and women are simply choosing areas of science where they feel they have greater natural aptitude, or interest. “Choosing” of course is a loaded term here, because the occupations we end up in may not always be the result of any conscious choice but simply the result of opportunities presented. But I use the word “interest” because obviously our choice of occupation may be guided not simply by our aptitude, but also by our preferences and fascinations.

My creative Ph.D. student Johnny Lawson used a test which he called the Physical Prediction Questionnaire (PPQ) to see if there is a sex difference in understanding how levers (input) attached to different mechanisms (cog wheels joined in different ways) affect the movement of rods (output). Would the rods go up or down? Men were better at predicting these outcomes, and this cannot have been related to any sexist interviewers, since the tasks were presented by questionnaire through the mail, and completed by the person alone.⁸

So while not denying the existence of possible social factors that are creating inequalities between male and female scientists at the higher levels, I think we need to remain open to the possibility that, on average, men are more often drawn to pursue these interests.

Let’s have a closer look at math. Boys at school tend to receive lower grades in mathematics than do girls. On the face of it, this looks like counter-evidence for the male brain being a better systemizer. However, although they score lower on accuracy in math, boys tend to score higher on tests of mathematical ability. Teachers will tell you that, on average, girls are the better students, but that boys score higher in exams. Despite their work being less neat, and more erratic, boys tend to see mathematical solutions more readily. No justice, you might think.

Girls do not score worse than boys in all aspects of math ability, though. Across the school years, girls score better in tests of mathematical sentences, and in tests of mathematical reasoning, such as calculation. Some people have wondered if this is because these are math tasks on which it is easier to use verbal strategies. As we saw in Chapter 4, females tend to have better verbal skills. When you look at the math tasks where verbal strategies are arguably less useful (for example, geometry, probability, and statistics), girls score lower than boys.

Sex differences in math have been documented in children as young as seven years old. As psychologist Doreen Kimura points out, the same teachers teach both the calculation (in which girls excel) and mathematical problem-solving (in which boys excel), so it is hard to see how a teacher’s general expectations or teaching style could produce a different pattern of scores in the two sexes. The same argument makes parental expectations a poor explanation of this sex difference.⁹

Cross-cultural studies suggest that, in childhood, there are no sex differences in primary mathematical abilities. These are the aspects of math found in children in all cultures, such as basic counting, numerosity (the idea of more or less), ordinality (the idea of what comes after what), and simple arithmetic (addition and subtraction). The sex differences only emerge in secondary domains. These are the aspects of math that are first encountered at school, such as geometry and mathematical word problems.

Since sex differences in math only appear later in childhood, you might be tempted to conclude that this shows the role of culture and education in producing sex differences. However, cross-cultural studies reveal the same pattern of sex differences worldwide. Girls perform better at the calculation and computational components of math tests; boys perform better at mathematical problem-solving. This is seen across cultures as diverse as those in the USA, Thailand, Taiwan, and Japan.¹⁰ So if it is just a matter of culture, why should most cultures be producing the same pattern?

I mentioned earlier that a sex difference is also seen in the math component of the Scholastic Aptitude Test (SAT-M). Males on average score fifty points higher than females on this test. When the results are examined by bands, the sex differences become more marked as one approaches the highest bands. For example, if you look at all those people who score above 500, you find a sex ratio of 2:1 (men to women). If you look at those people scoring above 600, you find a sex ratio of 6:1. And by the time you look at those people scoring above 700, the sex ratio is 13:1 (men to women).

Understanding Other Systems

Let’s leave math to one side and think about other examples of systemizing. Systemizing involves the prediction of output from a system when you apply some variable operation on the input. Have a look at the Water Level Task, originally devised by Swiss child psychologist Jean Piaget. The result he obtained may shock you. You show someone a bottle, tipped at an angle, and ask that person to predict the water level. Women more often draw the water level aligned with the tilt of the bottle, whereas the true water level, no matter what the tilt of the bottle, will always be horizontal.12

The same male advantage is seen in another similar test, the Rod and Frame Test. You sit the person being tested in a darkened room, and show them a 3-D model of a luminous rectangle (the frame) with a luminous rod inside it. The rectangle is rotated to different orientations, and you ask the person to position the rod so that it is vertical. Your sense of the vertical should be an absolute judgment, or perhaps relative to your sense of your body’s verticality. Certainly, changing the tilt of the frame should not affect the tilt of the rod, if you understand the meaning of verticality. If your judgment of verticality is influenced by the tilt of the frame, you are said to be “field dependent”: your judgment is easily swayed by (irrelevant) input from the surrounding context. If you are not influenced by the tilt of the frame, you are said to be “field independent”: your understanding takes account only of the relevant factors intrinsic to that system. Most studies show that females are more field dependent. In plain English, it means that women are relatively more distracted by irrelevant cues, rather than considering the system in isolation. They are more likely than men to say (erroneously) that the rod is upright if it is aligned with its frame.¹³

An item from the Adult Embedded Figures Test
fig 6.

Consider next the Embedded Figures Test. (An example of the Adult Embedded Figures Test is shown in Figure 6.) In this test someone is asked to look at a simple shape (the target), and to pick it out from a more complex pattern (the background in which it is embedded). On average, males are quicker and more accurate in locating the target from the larger, complex pattern.¹⁴ This can be seen as a systemizing test because the target shape can only fit into its slot in one way; in other words, there is a rule that describes this relationship. If you think of the complex background pattern as a car engine, for example, and the target as a component part, it is only possible to fit the part into the engine in one way in order to complete the system.

Attention to Detail

The above tasks require not only an understanding of the system but also attention to relevant detail and an ability to ignore irrelevant detail. This is indeed a general feature of systemizing—not the only factor, but a necessary part of it—and it proves to be the case that attention to relevant detail is superior in men.

Men, on average, are also better at detecting a particular feature (static or moving). For example, if someone is shown a film of a forest and asked whether they can detect any movements created by an animal or person in that forest, one finds that most men and boys are better able to spot movement than are girls and women.15

Systems Under Changing
Orientation or Topography

Another frequently used measure is the Mental Rotation Test. You show someone two shapes and ask them whether one of the shapes is a rotation or a mirror image of the other. Men are both quicker and more accurate at this test than are women. This sex difference can even be seen in children as young as five who are set a rotation task using a clock face, or are asked to judge if Teddy has the same arm raised when he is rotated. The male advantage has been found in many different cultures in the UK, the USA, Africa, the East Indies, and Asia. This test involves systemizing because one has to run the input through an operation (a rotation) to predict the output.16 The test may benefit from good visualization skills, but at a minimum one also has to keep track of rules of the type if operation a, then b changes to c.

Reading maps is another everyday test of systemizing—you have to operate on 3-D input in order to predict how it will appear in 2-D. Consider also how we tend to think of the train network, highways, waterways, aviation, and other route-based maps as traffic “systems.” In these examples, one motorway (the input) leads into another (the output), or one river (the input) flows into another (the output). So you can predict, using simple if-then rules, where a given route will take you. If I turn left at Junction 12 (the operation), I leave the M11 (input) and end up on the Barton Road (output). The flow of traffic (its speed and density) can also be understood as a system.

In one study, children were asked to describe if they would be turning left or right at a particular intersection on a city map, to reach a particular destination. To make it a touch harder, they were not allowed to rotate the map. (Try this next time you are out in a new area, if you can stop yourself turning the road atlas around.) Boys performed at a higher level than girls.

If you ask people to put together a 3-D mechanical apparatus in an assembly task, on average men score higher than women. And in relation to construction tests, boys are also better at constructing block buildings from 2-D blueprints.

Men can also learn a route in fewer trials, just from looking at a map, correctly recalling more details about direction and distance. If you ask boys to make a map of an area that they have only visited once, their maps are more accurately laid out in terms of the features in the environment, for example, showing which landmark is south-east of another. If you score these maps as either disorganized or organized, more of the boys’ maps are classified as organized. More of the girls’ maps make serious errors in the location of important landmarks.

The boys tend to emphasize directions, routes, or roads, whereas the girls tend to emphasize specific landmarks (the corner shop, for example). These two strategies—using directional cues versus using landmark cues—have been widely studied. The directional strategy is an instance of understanding space as a geometric system, and the focus on roads or routes is an instance of considering space in terms of another system, in this case a transport system.17

You might wonder if this reflects a less accurate visual memory in women, rather than a less accurate understanding of the system. In fact, women do better on one aspect of visuospatial memory, namely the ability to remember the relative locations of objects. This is tested in the following way: men and women are shown an array of objects for one minute, and then are given two sheets of paper with objects drawn on them. On the first sheet are all the objects they were shown originally, together with some that they were not. They are asked to name the objects that they were shown originally. On the second sheet are all the original items, but some of them have been sneakily moved to a different position. They are then asked to name the objects that have moved.

Women do better at both of these tasks. And if men and women are asked to turn over two cards to find matching pairs, correct pairs then being removed from the array, women succeed in finding all the matching pairs in fewer trials. Women can also recall more details about landmarks and street names from maps. So there is clearly nothing wrong with their memory for the important components. Rather, their spontaneous recall of the systematic properties of maps (for example, geometric or network aspects) is not as good as men’s.18

In another study, people were shown a map of an unfamiliar town (a made-up one). They were then tested on their ability to learn a route within this fictional town—how good they were at being taxi-drivers, if you will. Results showed that men learned the route more quickly (they needed less time and fewer attempts) and made fewer errors. Once again, women tended to recall more landmarks, while the men had a better directional understanding of the map. Other studies have found similar results. For example, take a group of children (even as young as eight) to a new area, give them a map, and then later ask them to reconstruct the map of the area through drawing. You will find that the girls include more landmarks, while the boys include more routes (roads, and so on). If you repeat the experiment with a second group of children but this time give them just half the map and interrupt their tour of the area (to make the test a bit tougher), boys are still better at recalling the relative positions of places. The two sexes seem to be approaching the task very differently. The male brain puts the features into a geometric or network system; the female brain marks the features descriptively.

Let’s put it a little more concretely. If you are shown a route from A to B to C, and you are a systemizer, you might work out that it would be quicker (and shorter) to go from C straight back to A, without needing to take a route via B at all. To do this, you would have to work out the compass directions, which comprise the system. For example, if C is north-east of A, then A must be south-west of C. If you are not a systemizer and simply stick to your landmark strategy, how would you get back from C to A? You would have to retrace your path via B, since that was your key landmark on the way from A to C (you would turn left at B). These are clearly two very different strategies and the former is significantly more powerful.19

Building and Copying a System

Children’s play with Legos is another good example to look at, because Lego bricks can be combined and recombined into an infinite number of systems. In this case the systems involve an understanding of what will support what, as well as the design and redesign of buildings or objects. And as the toy industry knows, boys love it. As young as three, boys are also faster at copying 3-D models of outsized Lego pieces, and older boys, from age nine, are better at imagining what a 3-D object will look like if it is laid out flat. Boys are also better at constructing a 3-D structure from just an aerial and frontal view in a picture. These examples of male superiority in systemizing abilities are reported right across the age range.20

Systemizing Object Motion:
Playing Darts and Catching Balls

In Chapter 5, we mentioned another class of system, motor systems. Systemizing in this case includes things such as perfecting your swing with a golf club, or your technique with a squash racquet, or your finger speed on a musical instrument, or flying a kite, or juggling. If you understand the physics of the system, the ball will end up exactly where you want it (in that little area in the corner of the squash court where the other guy has no chance of returning it), or each note in a rapid sequence on the piano will end up of equal pressure and volume, or that wrist action will flip the kite into a beautiful figure of eight. Is there any evidence that males are better at this kind of systemizing?

If you are asked to throw objects at a target, such as playing darts, men are more accurate in such throwing accuracy. My favorite example is frisbeethrowing. Men are also better at intercepting balls flung from a launcher. Equally, if people are asked to judge which of two moving objects is traveling faster, on average men are more accurate. They are also better at estimating when an object moving toward them will hit them. In one study, the object could only be seen, not heard, and the task was to say when the object would arrive. In a related study, judging object velocity from sound alone also revealed a male advantage. This must be systemizing par excellence. Presumably the systemizer is analyzing the auditory input in terms of how it correlates with speed.21

Could all this just be a male advantage in motor skills? This explanation does not hold, since if one designs a motor task that involves minimal or no systemizing, such as simple “fine-motor” accuracy, women actually score better than men. An example of this kind of task involves asking men and women to put pegs into holes as rapidly as possible (the Purdue Peg Board Task).²²

Classification and
Organizable Systems

What about organizable systems? In one unusual study, people were asked to classify over a hundred examples of local specimens into related species. The people who took part in this experiment were the Aguaruna, a tribal people living in the forest in northern Peru. The following results were found: men’s classification systems had more sub-categories (in other words, they introduced greater differentiation) and more consistency. More striking, the criteria that the Aguaruna men used to decide which animals belonged together more closely resembled the taxonomic criteria used by Western (mostly male) biologists. Another culture that has been studied is that of the Itza-Maya, in Guatemala. Here, as in the Peruvian example, men used a more complex set of criteria to classify local animals. Women were more likely to use “static” morphological features (such as the color or shape of the animal’s body); men were more likely to use a cluster of related features (such as the animal’s habitat, diet and even their relationship to humans).23

You will remember from Chapter 2 that Alex enjoyed collecting things from a very early age. Studies of children’s rituals support the idea that boys are more into collecting and focusing on the fine differences between the components of their collection. Nick Hornby presents an interesting account of the male mind in his book Fever Pitch, in which the author documents his obsession with the details of the soccer club he supports. His obsession does not simply involve knowing the names of players in his team (Arsenal) but all of the club’s characteristics, such as knowing the players’ goal averages and the scores of matches, going back years.

In sports enthusiasts, you see at work the combination of an organizable system (classifying players or teams), a rule-based system (the rules of the game), a motoric system (the techniques behind skill), and a statistical system (statistic information). Four forms of systemizing converging on one topic (sport). If men enjoy systemizing, no wonder they cannot get enough of league sports. My recent experience watching a baseball game in Toronto (the Blue Jays versus the Red Sox) persuades me that the trivial information people collect about their team’s players is not restricted to an English obsession with soccer. In baseball you keep track of the pitcher’s ERA (earned runs average), the players’ RBI (runs batted in), and many other fascinating and constantly shifting statistics.

In Nick Hornby’s novel, High Fidelity, the male protagonist is obsessed with his record collection, and works in a second-hand-record shop catering for (almost all male) customers searching for that one missing item in their collections of music. The character’s main leisure pursuit is listening to his favorite records and making his own compilation recordings, putting together his own lists of songs according to type (ten best blues songs, ten best jazz songs, ten best Irish folk songs, and so on).

Such an interest in classification and organization involves systemizing because one is confronted with a mass of input (for example, dogs, players, songs) and one has to generate one’s own categories (to predict how each dog, player, or song will behave). The categories are therefore not just a way of organizing information into lists: they are more than that. The categories (for example, marsupials) are the operations performed on the input (for example, koala) which then predict the output (for example, has a pouch). The more finely differentiated your categories, the better your system of prediction will be.

Knowing that the erne is not just an eagle but a sea eagle will allow you to predict its habitat, its prey, and its behavior more accurately. Knowing that this snake is poisonous and that snake is not will allow you to react with fear to the right animal. Knowing that this pitcher has a higher earned runs average allows you to predict which team is likely to win the game. Knowing that this musician is a 1970s Czech rock musician allows you to predict which section of the music store you will find his album in.

The world’s leading birdwatcher, according to the Guinness Book of Records, was a woman, Phoebe Snetsinger, the American ornithologist. This might appear to contradict the claim that males are more prone to collect things and compile lists of facts. As it turns out, Phoebe was the exception to the rule. Most birdwatchers, trainspotters, and plane-spotters are male. Cath Jeffs is an ornithologist and project officer with the Royal Society for the Protection of Birds, and was interviewed by the Guardian newspaper:

Birding is still very male—it’s all about collecting information and obsessively putting it into lists. Women just can’t get that passionate about lists, can they? . . . It can be very stressful with all these men around. If a bird is supposed to appear and they miss it, things can get tense. Pretty often fights break out, usually because someone has made a noise and scared away a really rare species before everyone’s had a chance to record it.24

But the existence of some female birdwatchers in no way undermines the theory, because the claim is only that, on average, males will be more strongly drawn to systemize (birds, or any other aspect of the environment) compared to females. Part of what we will also need to explain, however, are such exceptions, as well as these differences between the majority of each sex. Why is this particular woman a talented physicist or an obsessive plane-spotter? Why is this particular man a wonderful counselor or a caring nurse? I will look at possible reasons for these exceptions later in the book.

The Systemizing Quotient (SQ)

In this chapter we have seen a pattern emerging: on average, males seem be drawn more strongly to many different aspects of systemizing—machines, mathematics, maps, birdwatching, and sports statistics, to name just a few. To draw these ostensibly varied types of systemizing together, my research team and I designed the Systemizing Quotient (or SQ). The SQ gives an individual a total score based on how strongly drawn they are to systemize each of these aspects of the world. It may come as no surprise to learn that men score significantly higher than females on the SQ (Appendix 3).²⁵

Male and female scores in systemizing
fig 7.

Babies: The Ultimate Test

Before we leave this part of the journey—our voyage into systemizing—it is worth perhaps just thinking about how early we see sex differences in this domain. Recall that in the Cambridge study reported in Chapter 4, we found that one-day-old boys looked longer at a mechanical mobile (a system with predictable laws of motion) than at a person’s face (an object that is next to impossible to systemize). Even on the first day of life, a subtle trace is evident of what we see magnified later in development. This is signaling that from birth, boys’ attention is being drawn more strongly to a non-personal system, while girls’ attention is being drawn more strongly to a face.²⁶ Recall also that at one year old, boys showed a stronger preference to watch a video of cars (predictable mechanical systems) than to watch a film showing a talking head (with the sound switched off). One-year-old girls showed the opposite preference.²⁷

These sex differences are therefore present very early in life. There has hardly been any opportunity for socialization and experience to shape these sex differences. We of course know that, with time, culture and socialization do play a role in determining if you develop a male brain (stronger interest in systems) or a female brain (stronger interest in empathy). But these studies of infancy strongly suggest that biology may also partly determine this.

We have deferred the question of causality for long enough. We have reached a certain point on our journey where we now have to leave the safe path of behavioral differences, and turn into the rocky terrain where we confront what is causing these sex differences, head on.