February 22, 2015 Leave a comment
I’ve been working on regional governments on and off for several years, and this time I feel like I’ve made some progress. There are a number of reasons for subdividing North America into new regional governments, as I’ve already discussed in Part I and Part II. But the main idea comes from architect and known crazy person Christopher Alexander‘s book A Pattern Language, a book about development and building patterns that goes from the very large to the very small scale. The very first pattern in the book is:
Metropolitan regions will not come to balance until each one is small and autonomous enough to be an independent sphere of culture…
Wherever possible, work toward the evolution of independent regions in the world; each with a population between 2 and 10 million; each with its own natural and geographic boundaries; each with its own economy; each one autonomous and self-governing; each with a seat in a world government, without the intervening power of larger states or countries.
This time I tried to be more official and used a GIS to do my work rather than Google and Wikipedia. In the past I’ve used counties as my basic geographic and population unit, but that was problematic, seeing as Los Angeles County has over 10 million people already. It’s also problematic to go down to the level of cities, towns and places, because then you run into 8 million-strong New York City, and the second you lump in any of its suburbs it puts you over 10 million. This time I went in between and used county subdivisions, which will both divide Los Angeles County up as well as take advantage of the fact that New York City, while being one city, is also five different counties.
I also used information from both the US and Canada. Initially I wanted to do Mexico as well, since there are a number of major cities on the Mexican side of the border that draw people in from the US. However, I figure that the ties between the US and Canada are much stronger and that it would be easier to integrate their populations. Also, the fact that the US and Canada make census data and GIS files fairly easy to obtain while Mexico doesn’t might have something to do with it.
My methodology goes something like this. Let’s say you’ve got Country A with Cities 1, 2, and 3 and a population of 30 million.
City 1 and City 2 are the largest cities in the country, so the country would be divided between these two cities.Region 1’s new population is 18 million and Region 2’s is 12 million. Since Region 1 is the larger of the two and since it is still above 10 million in population, it needs to be divided again. The second largest city in Region 2 is City 3, so new boundaries need to be redrawn between that and the two existing cities.The new Region 3 took 8 million people from Region 1 and 2 million from Region 2, giving all three regions a nice round population of 10 million. At this point we no longer need to subdivide them any further.
Of course, when you do this on real land and using real borders, it doesn’t come out quite as clean. It looks a bit more like this:
The largest metropolitan area in Anglo-America is New York City and the second is Los Angeles, so they became the first two regions. Since they were both over 10 million and New York City was the larger of the two, Chicago was the third region, then Dallas, then Philadelphia, etc.
What is apparent in this exercise is that, since the regions are based on population and not geography, the size of the region correlates to population density. The densest parts of Anglo-America, the northeast seaboard and southern California, have the smallest regions, while the sparsely populated Rocky Mountains and northern Canada have enormous regions. What I haven’t realized in past iterations of this project is that it complicates Alexander’s second pattern, the distribution of towns:
If the population of a region is weighted too far toward small villages, modern civilization can never emerge; but if the population is weighted too far toward big cities, the earth will go to ruin because the population isn’t where it needs to be, to take care of it.
Encourage a birth and death process for towns within the region, which gradually has these effects:
1. The population is evenly distributed in terms of different sizes- example, one town with 1,000,000 people, 10 towns with 100,000 people each, 100 towns with 10,000 people each, and 1000 towns with 1000 people each.
2. These towns are distributed in space in such a way that within each size category the towns are homogeneously distributed all across the region.
This process can be implemented by regional zoning policies, land grants, and incentives which encourage industries to locate according to the dictates of the distribution.
The last part of that section, which describes the spacing of towns, leads to a specific size that a nation of a given population should be. I experimented with a few town distribution models and determined that based on a combination of Alexander’s population and town distribution recommendations, a region should not be less than approximately 30,000 square miles, without being more than approximately 130,000 square miles. Several of the regions I’ve created based on population alone are either too large or too small to meet these criteria.
So to comply with Alexander’s recommendations, the small regions would have to have their population distributed more sparsely and their boundaries enlarged to accommodate that lower density, and the large regions would either have to become smaller and more dense, or have their populations concentrated in certain areas while others are left as uninhabited wastes, as is essentially the case in much of the mountain deserts of the western US and the arctic regions of Canada.
While I see the value of Alexander’s argument for smaller governmental units, I find his arguments for the distribution of towns a bit more dubious, especially when it comes to areas that are too dense for his recommendations. I generally feel that the best way to preserve undeveloped land is not to distribute people evenly across it, but to concentrate them all in one area and leave more of the land untouched. That’s why New Yorkers are some of the greenest people on earth; they leave the countryside alone, and are packed dense enough that they don’t have to use cars and take advantage of the energy savings of dense housing, making their environmental impact considerably lower than someone in a lower density area.
That being said, at some point I would like to take one of the Goldilocks regions I’ve created like San Francisco or Pittsburgh and try to create a distribution of towns like what Alexander recommends, just to see what it would look like. But as far as drawing new regions goes, I’m pretty happy with this version, and I don’t see myself redoing this project again.