Why the West Rules--For Now (25 page)

Read Why the West Rules--For Now Online

Authors: Ian Morris

Tags: #History, #Modern, #General, #Business & Economics, #International, #Economics

The index satisfies Einstein’s rule, since three traits is probably as simple as the UN can make things while still capturing what human development means. Economists still find a lot not to like about it, though. Most obviously, life expectancy, education, and income are not the only things we could measure. They have the advantage of being relatively easy to define and document (some potential traits, like happiness, would be much harder), but there are certainly other things we could look at (say employment rates, nutrition, or housing) that might generate different scores. Even economists who agree that the UN’s traits are the best ones sometimes balk at conflating them into a single human development score; they are like apples and oranges, these economists say, and bundling them together is ridiculous. Other economists are comfortable both with the variables chosen and with conflating them, but do not like the way the UN statisticians weight each trait. The scores may look objective, these economists point out, but in reality they are highly subjective. Still other critics reject the very idea of scoring human development. It creates the impression, they say, that Norwegians are 97.1 percent of the way toward ultimate bliss, and 2.9 times as blissful as people in Sierra Leone—both of which seem, well, unlikely.

But despite all the criticisms, the human development index has proved enormously useful. It has helped relief agencies target their funds on the countries where they can do most good, and even the critics tend to agree that the simple fact of having an index moves the debates forward by making everything more explicit. An index of social development across the last fifteen-thousand-plus years faces all the
same problems as the UN’s index (and then some), but it also, I think, offers some similar advantages.

Like the UN economists, we should aim to follow Einstein’s rule. The index must measure as few dimensions of society as possible (keep it simple) while still capturing the main features of social development as defined above (don’t make it
too
simple). Each dimension of society that we measure should satisfy six rather obvious criteria. First, it must be relevant: that is, it must tell us something about social development. Second, it must be culture-independent: we might, for example, think that the quality of literature and art are useful measures of social development, but judgments in these matters are notoriously culture-bound. Third, traits must be independent of one another—if, for instance, we use the number of people in a state and the amount of wealth in that state as traits, we should not use per capita wealth as a third trait, because it is just a product of the first two traits. Fourth, traits must be adequately documented. This is a real problem when we look back thousands of years, because the available evidence varies so much. Especially in the distant past, we simply do not know much about some potentially useful traits. Fifth, traits must be reliable, meaning that experts more or less agree on what the evidence says. Sixth, traits must be convenient. This may be the least important criterion, but the harder it is to get evidence for something or the longer it takes to calculate results, the less useful that trait is.

There is no such thing as a perfect trait. Each trait we might choose inevitably performs better on some of these criteria than on others. But after spending many months now looking into the options, I have settled on four traits that I think do quite well on all six criteria. They do not add up to a comprehensive picture of Eastern and Western society, any more than the UN’s traits of life expectancy, education, and income tell us everything there is to know about Norway or Sierra Leone. But they do give us a pretty good snapshot of social development, showing us the long-term patterns that need to be explained if we are to know why the West rules.

My first trait is energy capture. Without being able to extract energy from plants and animals to feed soldiers and sailors who did little farming themselves, from wind and coal to carry ships to China, and from explosives to hurl shells at the Chinese garrison, the British would
never have reached Tinghai in 1840 and blown it to pieces. Energy capture is fundamental to social development—so much so that back in the 1940s the celebrated anthropologist Leslie White proposed reducing all human history to a single equation:
E
x
T

C
, he pronounced, where
E
stands for energy,
T
for technology, and
C
for culture.

This is not quite as philistine as it sounds. White was not really suggesting that multiplying energy by technology tells us all we might want to know about Confucius and Plato or artists like the Dutch Old Master Rembrandt and the Chinese landscape painter Fan Kuan. When White spoke of “culture” he in fact meant something rather like what I am calling social development. But even so, his formulation is too simple for our purposes. To explain Tinghai we need to know more.

All the energy capture in the world would not have taken a British squadron to Tinghai if they had not been able to organize it. Queen Victoria’s minions had to be able to raise troops, pay and supply them, get them to follow leaders, and carry out a host of other tricky jobs. We need to measure this organizational capacity. Up to a point organizational capacity overlaps with Spencer’s old idea of differentiation, but neo-evolutionists learned in the 1960s that it is almost impossible to measure differentiation directly, or even to define it in a way that will satisfy critics. We need a proxy, something closely related to organizational capacity but easier to measure.

The one I have chosen is urbanism. Perhaps that will seem odd; after all, the fact that London was a big place does not directly reflect Lord Melbourne’s revenue flows or the Royal Navy’s command structure. On further reflection, though, I hope the choice will seem less odd. It took astonishing organization to support a city of 3 million people. Someone had to get food and water in and waste products out, provide work, maintain law and order, put out fires, and perform all the other tasks that go on, day in, day out, in every great city.

It is certainly true that some of the world’s biggest cities today are dysfunctional nightmares, riddled with crime, squalor, and disease. But that, of course, has been true of most big cities throughout history. Rome had a million residents in the first century
BCE
; it also had street gangs that sometimes brought government to a halt and death rates so high that more than a thousand country folk had to migrate into Rome every month just to make up the numbers. Yet for all Rome’s foulness (brilliantly evoked in the 2006 HBO television series
Rome
), the organization
needed to keep the city going was vastly beyond anything any earlier society could have managed—just as running Lagos (population 11 million) or Mumbai (population 19 million), let alone Tokyo (population 35 million), would have been far beyond the Roman Empire’s capabilities.

This is why social scientists regularly use urbanism as a rough guide to organizational capacity. It is not a perfect measure, but it is certainly a useful rough guide. In our case, the size of a society’s largest cities has the extra advantage that we can trace it not only in the official statistics produced in the last few hundred years but also in the archaeological record, allowing us to get an approximate sense of levels of organization all the way back to the Ice Age.

As well as generating physical energy and organizing it, the British of course also had to process and communicate prodigious amounts of information. Scientists and industrialists had to transfer knowledge precisely; gunmakers, shipbuilders, soldiers, and sailors increasingly needed to read written instructions, plans, and maps; letters had to move between Asia and Europe. Nineteenth-century British information technology was crude compared to what we now take for granted (private letters needed three months to get from Guangzhou to London; government dispatches, for some reason, needed four), but it had already advanced far beyond eighteenth-century levels, which, in turn, were well head of the seventeenth century. Information processing is critical to social development, and I use it as my third trait.

Last but sadly not least is the capacity to make war. However well the British extracted energy, organized it, and communicated, it was their ability to turn these three traits toward destruction that settled matters in 1840. I grumbled in
Chapter 1
about Arthur C. Clarke equating evolution with skill at killing in his science-fiction classic
2001: A Space Odyssey
, but an index of social development that did not include military power would be no use at all. As Chairman Mao famously put it, “
Every Communist
must grasp this truth: ‘Political power grows out of the barrel of a gun.’ “Before the 1840s, no society could project military power across the whole planet, and to ask who “ruled” was nonsense. After the 1840s, though, this became perhaps the most important question in the world.

Just as with the UN’s human development index, there is no umpire to say that these traits, rather than some other set, are the ultimate
way to measure social development, and again like the UN index, any change to the traits will change the scores. The good news, though, is that none of the alternative traits I have looked at over the last few years changed the scores much, and none changed the overall pattern at all.
*

If Eddington had been an artist he might have been an Old Master, representing the world at a level of detail painful to behold. But making an index of social development is more like chainsaw art, carving grizzly bears out of tree trunks. This level of roughness and readiness would doubtless have turned Einstein’s hair even whiter, but different problems call for different margins of error. For the chainsaw artist, the only important question is whether the tree trunk looks like a bear; for the comparative historian, it is whether the index shows the overall shape of the history of social development. That, of course, is something historians will have to judge for themselves, comparing the pattern the index reveals with the details of the historical record.

Provoking historians to do this may in fact be the greatest service an index can perform. There is plenty of scope for debate: different traits and different ways of assigning scores might well work better. But putting numbers on the table forces us to focus on where errors might have crept in and how they can be corrected. It may not be astrophysics, but it is a start.

HOW TO MEASURE?

Now it is time to come up with some numbers. It is easy enough to find figures for the state of the world in 2000
CE
(since it is such a nice round number, I use this date as the end point for the index). The United Nations’ various programs publish annual statistical digests that tell us, for instance, that the average American consumes 83.2 million kilocalories of energy per year, compared to 38 million for the average person in Japan; that 79.1 percent of Americans live in cities, as against
66 percent of Japanese; that there are 375 Internet hosts per thousand Americans but only 73 per thousand Japanese; and so on. The International Institute for Strategic Studies’s annual
Military Balance
tells us, so far as it can be known, how many troops and weapons each country has, what their capabilities are, and how much they cost. We are drowning in numbers. They do not add up to an index, though, until we decide how to organize them.

 

Sticking to the simple-as-possible program, I set 1,000 points as the maximum social development score attainable in the year 2000 and divide these points equally between my four traits. When Raoul Naroll published the first modern index of social development in 1956 he also gave equal points to his three traits, if only, as he put it, “
because no
obvious reason appeared for giving one any more weight than another.” That sounds like a counsel of despair, but there is actually a good reason for weighting the traits equally: even if I thought up reasons to weight one trait more heavily than another in calculating social development, there would be no grounds to assume that the same weightings have held good across the fifteen-thousand-plus years under review or have applied equally to East and West.

Having set the maximum possible score for each trait in the year 2000 at 250 points, we come to the trickiest part, deciding how to award points to East and West at each stage of their history. I will not go step-by-step through every calculation involved (I summarize the data and some of the main complexities in the appendix at the end of this book, and I have posted a fuller account online),
*
but it might be useful to take a quick look inside the kitchen, as it were, and explain the procedure a bit more fully. (If you don’t think so, you can of course skip to the next section.)

Urbanism is probably the most straightforward trait, although it certainly has its challenges. The first is definitional: Just what do we mean by urbanism? Some social scientists define urbanism as the proportion of the population living in settlements above a certain size (say, ten thousand people); others, as the distribution of people across several ranks of settlements, from cities down to hamlets; others still, as the average size of community within a country. These are all useful approaches, but are difficult for us to apply across the whole period we are
looking at here because the nature of the evidence keeps changing. I decided to go with a simpler measure: the size of the largest known settlement in East and West at each moment in time.

Focusing on largest city size does not do away with definitional problems, since we still have to decide how to define the boundaries of cities and how to combine different categories of evidence for numbers within them. It does, though, reduce the uncertainties to a minimum. When I played around with the numbers I found that combining largest city size with other criteria, such as the best guesses at the distribution of people between cities and villages or the average size of cities, hugely increased the difficulties of the task but hardly changed the overall scores at all; so, since the more complicated ways of measuring produced roughly the same results but with a whole lot more guesswork, I decided to stick to simple city sizes.

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