Ritual as urban design problem

Kavanagh identifies several influences weakening the urban Church as civitas. The many churches developed many different liturgies, resulting in what he calls “liturgical hypertrophy.” These were flattened and standardized, shrunk to centrally-manageable size and legible doctrinal authority, by the English Act of Uniformity of 1549 and the Council of Trent by 1614. At the same time, printed books ushered in the new literary consciousness, eroding the power of community ritual consciousness for European Christians.
 
But ancient religious practices (and their modern elaborations) are still performed in Europe; processions may still be seen winding through the streets of cities and small towns. Except for the occasional Palm Sunday procession, they are all but absent in the United States. The American urban design pattern — increasingly spreading even to small towns — is forbidding to the kind of religious practice that transforms space and time.
 
The American urban design pattern is characterized by, first, an orientation toward the automobile above all else; second, toward consumption as the main activity besides work; and third, toward efficient human storage. Human activities other than consumption and “being stored” – as in day cares, schools, prisons, offices, nursing homes, and “housing units” themselves – are made difficult and uncomfortable by the physical built environment itself. Religious activity and social activity, two main components of human flourishing that transform local environments, are increasingly rare and emptied of transformative power.
 

From a great piece at Front Porch Republic by Sarah Perry, whose work I've appreciated wherever it shows up online.

Many people are excited about all the free time self-driving cars might return to people, but I'm more excited to reclaim all the physical space currently dedicated to parking garages, parking spots on the side of the road, and roads themselves. If you had more self-driving cars in operation at all hours, you'd have fewer idle cars requiring space to park. A road that is four lanes wide, one on each side for parking spaces, one in each direction for traffic, could be reduced to two lanes, or maybe even one if self-driving cars could coordinate with each other when to head which way down a road. Now you'd have two or three extra car widths of road space that could be used to widen sidewalks, add dedicated bike lanes, grow trees or plants, and so on.

It is only when one travels to a city that was designed before automobiles became prevalent that one senses just how much of their surface area American cities have sacrificed to cars. Pedestrians have been trained to stay out of the road, it holds nothing but danger for them, and even when there are few cars around, that road space lays idle for the most part. It's a usage of land that is actively hostile to most people who are walking around the city, instead giving preference to cars, many of which are too large, most of whom only hold one person, and a large percentage of which are just driving around in search of a parking spot because street parking is priced too low and public transportation is under built.

The next time you're out in the city, look at the width of the sidewalk you're walking on and compare it to the width of the road off the side. Then travel to Europe and stroll around a town like Seville or Florence and do the same arithmetic. Or you can just use Google Street View or an online image search for a cheaper, if less charming way to complete the exercise.

A street in Seville. If you add up the sidewalk space, it's almost as wide, if not as wide, as the space dedicated to cars and motorcycles. But this understates the pedestrian-friendliness of Seville because people feel very comfortable walking on the roads in Seville, not just the sidewalks.

Market Street in San Francisco. It is the widest street in San Francisco, but the ratio of street space dedicated to automobiles to sidewalk set aside for pedestrians is similar to that of other streets throughout the city. As a pedestrian, the difference in feel between walking in a European city like Seville to an American city like San Francisco is palpable.

Thou shalt have no other gods before me

It feels ridiculous to post a link found from Kottke (especially one that came via Alexis Madrigal) since I assume everyone has already seen it, but this article on analyzing cities like one would the molecular structure of materials intrigued me. Will this modeling actually yield value? I'm skeptical of any algorithm that puts Los Angeles and Seattle in the same bucket.

The premise is intriguing, but the question of the value of metaphor is even more important.

Are materials and metropolises really comparable? And if so, is the comparison useful as more than a metaphor? The urban planning community, which has its roots in the design world, has historically been wary of science’s attempts to capture the incredible complexity of the urban environment. (In her classic 1961 book “The Death and Life of American Cities,” Jane Jacobs lambasted modern urban planning itself as a “pseudoscience,” in which “years of learning and a plethora of subtle and complicated dogma have arisen on a foundation of nonsense.”)

But it is warming to these efforts. Today scientists are some of the leading investigators of urban design issues. “There have been ideas about cities since Aristotle and Plato,” said Luis Bettencourt, professor of complex systems at the Santa Fe Institute. “But the ways we can measure cities, test ideas, and compare cities across time and place and size has become so much more possible, that we can now test those ideas.” Bettencourt, who was trained as a theoretical physicist, published a paper in Science last summer proposing a new quantitative framework for understanding cities: They are a unique complex system, he argues, with predictable social, spatial, and infrastructure properties.
 

It's a worthwhile question to ask because I've long thought Silicon Valley and the technology world to be dangerously addicted to metaphor. If you look hard enough, almost anything can be found to resemble something else, but that does not mean outcomes in one system can be used to predict outcomes in another.

But pattern recognition is a reflexive habit for venture capitalists and technology prognosticators. When the future is unknown, we look to history as a guide because hindsight is rich in specific outcomes. This can be a dangerous trap when the similarity in patterns occur at the surface but result from differing underlying dynamics.

Modeling is one form of metaphor, and it can also be dangerous (recall the first chapter of Kieslowski's masterpiece The Decalogue, based on the first of the Ten Commandments: "I am the Lord thy God; thou shalt have no other gods before me."). However, the increased digitization and measurement of the world has made it possible to model many more natural phenomenon.

Look at the recent success of people with finance backgrounds moving over into the sports franchise ownership and management. Jonah Keri examined one such successful crossover in The Extra 2%: How Wall Street Strategies Took a Major League Baseball Team from Worst to First, but most teams not run entirely by finance alumni still employ quantitative analysts to pore over data and model out player and franchise performance, not to mention attendance and revenue. With advanced camera systems and statistical tracking come more data with which to build models of individual and team performance at greater resolution. Sports previously thought to be too complex to model (mostly team sports like basketball, football, soccer, and hockey, which lack the volume of discrete individual confrontations that baseball offers) are being understood at a deeper level using technology like the SportVU camera systems, and even baseball is being understood at a finer level by its own implementation of 3D camera tracking and systems like PitchFX.

When is there enough data to use a model for prediction? I thought of this when reading about the analysis of cities as molecular structures, and it recalled the legendary city of Magnasanti, the so-called perfect city.

If you haven't heard of Magnasanti, it's likely because it's not a real world city but a virtual city built in the game SimCity a few years ago by a young architecture student named Vincent Ocasla.

This video provides an overview of Magnasanti, as does this interview with Ocasla.

Godfrey Reggio’s Koyaanisqatsi seems to have been a big inspiration.
It very much was--I first watched it in 2006. The film presented the world in a way I never really looked at before and that captivated me. Moments like these compel me to physically express progressions in my thought, I have just happened to do that through the form of creating these cities in SimCity 3000. I could probably have done something similar--depicting the awesome regimentation and brutality of our society--with a series of paintings on a canvas, or through hideous architectural models. But it wouldn’t be the same as doing it in the game, because I wanted to magnify the unbelievably sick ambitions of egotistical political dictators, ruling elites and downright insane architects, urban planners, and social engineers.

I’ve a quote from one of your Facebook status updates here: “The economic slave never realizes he is kept in a cage going round and round basically nowhere with millions of others.” Do you feel that sums up the lives of the citizens of Magnasanti? (And you might want to set your Facebook to private by the way.)
Precisely that. Technically, no one is leaving or coming into the city. Population growth is stagnant. Sims don’t need to travel long distances, because their workplace is just within walking distance. In fact they do not even need to leave their own block. Wherever they go it’s like going to the same place.

Heavy.
There are a lot of other problems in the city hidden under the illusion of order and greatness--suffocating air pollution, high unemployment, no fire stations, schools, or hospitals, a regimented lifestyle--this is the price that these sims pay for living in the city with the highest population. It’s a sick and twisted goal to strive towards. The ironic thing about it is the sims in Magnasanti tolerate it. They don’t rebel, or cause revolutions and social chaos. No one considers challenging the system by physical means since a hyper-efficient police state keeps them in line. They have all been successfully dumbed down, sickened with poor health, enslaved and mind-controlled just enough to keep this system going for thousands of years. 50,000 years to be exact. They are all imprisoned in space and time.
 

If you look at how Ocasla achieved the perfect city in SimCity (I have not played the game in years but “perfect” in this case is measured by in-game metrics such as citizen happiness, crime rates, the number of abandoned buildings, etc), Ocasla came up with a symmetrical layout based on the Buddhist Wheel of Life and Death. The symmetry means everyone has the same amenities within a short distance of their residence, so there's no need to travel a lot for those because everyone has their version nearby. There are no roads, only subways, and there are lots of police stations, one of the things that gives Magnasanti its totalitarian feel.

If this is the ideal city in SimCity I have severe doubts as to the sophistication of the game's simulation. It looks one roadless suburb with the same strip mall in the center of each, all with the same exact stores: Chipotle, Starbucks, a Best Buy, maybe a Home Depot. The same suburbs that are seeing ghettoization and an outflow of residents into urban centers. Where is the art museum, the local sports stadium? How do you replicate restaurants from star chefs?

Despite all that, I could see China trying to build a Magnasanti prototype in their countryside.

Cities are superlinear, companies are not

But unlike animals, cities do not slow down as they get bigger. They speed up with size! The bigger the city, the faster people walk and the faster they innovate. All the productivity-related numbers increase with size---wages, patents, colleges, crimes, AIDS cases---and their ratio is superlinear. It's 1.15/1. With each increase in size, cities get a value-added of 15 percent. Agglomerating people, evidently, increases their efficiency and productivity.

Does that go on forever? Cities create problems as they grow, but they create solutions to those problems even faster, so their growth and potential lifespan is in theory unbounded.

...

Are corporations more like animals or more like cities? They want to be like cities, with ever increasing productivity as they grow and potentially unbounded lifespans. Unfortunately, West et al.'s research on 22,000 companies shows that as they increase in size from 100 to 1,000,000 employees, their net income and assets (and 23 other metrics) per person increase only at a 4/5 ratio. Like animals and cities they do grow more efficient with size, but unlike cities, their innovation cannot keep pace as their systems gradually decay, requiring ever more costly repair until a fluctuation sinks them. Like animals, companies are sublinear and doomed to die.
 

From a Stewart Brand summary of research by Geoffrey West.

From a long conversation with West at Edge:

Let me tell you the interpretation. Again, this is still speculative.

The great thing about cities, the thing that is amazing about cities is that as they grow, so to speak, their dimensionality increases. That is, the space of opportunity, the space of functions, the space of jobs just continually increases. And the data shows that. If you look at job categories, it continually increases. I'll use the word "dimensionality."  It opens up. And in fact, one of the great things about cities is that it supports crazy people. You walk down Fifth Avenue, you see crazy people, and there are always crazy people. Well, that's good. It is tolerant of extraordinary diversity.

This is in complete contrast to companies, with the exception of companies maybe at the beginning (think of the image of the Google boys in the back garage, with ideas of the search engine no doubt promoting all kinds of crazy ideas and having maybe even crazy people around them).

Well, Google is a bit of an exception because it still tolerates some of that. But most companies start out probably with some of that buzz. But the data indicates that at about 50 employees to a hundred, that buzz starts to stop. And a company that was more multi dimensional, more evolved becomes one-dimensional. It closes down.

Indeed, if you go to General Motors or you go to American Airlines or you go to Goldman Sachs, you don't see crazy people. Crazy people are fired. Well, to speak of crazy people is taking the extreme. But maverick people are often fired.

It's not surprising to learn that when manufacturing companies are on a down turn, they decrease research and development, and in fact in some cases, do actually get rid of it, thinking "oh, we can get that back, in two years we'll be back on track."

Well, this kind of thinking kills them. This is part of the killing, and this is part of the change from super linear to sublinear, namely companies allow themselves to be dominated by bureaucracy and administration over creativity and innovation, and unfortunately, it's necessary. You cannot run a company without administrative. Someone has got to take care of the taxes and the bills and the cleaning the floors and the maintenance of the building and all the rest of that stuff. You need it. And the question is, “can you do it without it dominating the company?” The data suggests that you can't.
 

Lastly, from an article about West and his research in the NYTimes.

The mathematical equations that West and his colleagues devised were inspired by the earlier findings of Max Kleiber. In the early 1930s, when Kleiber was a biologist working in the animal-husbandry department at the University of California, Davis, he noticed that the sprawlingly diverse animal kingdom could be characterized by a simple mathematical relationship, in which the metabolic rate of a creature is equal to its mass taken to the three-fourths power. This ubiquitous principle had some significant implications, because it showed that larger species need less energy per pound of flesh than smaller ones. For instance, while an elephant is 10,000 times the size of a guinea pig, it needs only 1,000 times as much energy. Other scientists soon found more than 70 such related laws, defined by what are known as “sublinear” equations. It doesn’t matter what the animal looks like or where it lives or how it evolved — the math almost always works.

West’s insight was that these strange patterns are caused by our internal infrastructure — the plumbing that makes life possible. By translating these biological designs into mathematics, West and his co-authors were able to explain the existence of Kleiber’s scaling laws. “I can’t tell you how satisfying this was,” West says. “Sometimes, I look out at nature and I think, Everything here is obeying my conjecture. It’s a wonderfully narcissistic feeling.”
 

The pace of technology has already shifted some of the old company scaling constraints in the past two decades. When I first joined Amazon, one of the first analyses I performed was a study of the fastest growing companies in history. Perhaps it was Jeff, perhaps it was Joy (our brilliant CFO at the time), but someone had in their mind that we could be the fastest growing company in history as measured by revenue. Back in 1997, no search engine gave good results for the question "what is the fastest growing company in history."

Some clear candidates emerged, like Wal-Mart and Sam's Club or Costco. I looked at technology giants like IBM and Microsoft. Two things were clear: most every company had some low revenue childhood years when they were finding their footing before they achieved the exponential growth they became famous for. Second, and this was most interesting to us, many companies seemed to suffer some distress right around $1B in revenue.

This was very curious, and a deeper examination revealed that many companies went through some growing pains right around that milestone because smaller company processes, systems, and personnel that worked fine until that point broke down at that volume of business. This was a classic scaling problem, and around $1B or just before it, many companies hit that wall, like the fabled 20 mile wall in a marathon.

Being as competitive as we were, we quickly turned our gaze inward to see which of our own systems and processes might break down as we approached our first billion in revenue (by early 1998 it was already clear to us that we were going to hit that in 1999).

Among other things, it led us to the year of GOHIO. Reminiscent of how, in David Foster Wallace's Infinite Jest, each year in the future had a corporate sponsor, each year at Amazon we had a theme that tied our key company goals into a memorable saying or rubric. One year it was Get Big Fast Baby because we were trying to achieve scale ahead of our competitors. GOHIO stood for Getting Our House In Order.

In finance, we made projections for all aspects of our business at $1B+ in revenue: orders, customer service contacts, shipments out of our distribution centers, website traffic, everything. In the year of GOHIO, the job of each division was to examine their processes, systems, and people and ensure they could support those volumes. If they couldn't, they had to get them ready to do so within that year.

Just a decade later, the $1B scaling wall seems like a distant memory. Coincidentally, Amazon has helped to tear down that barrier with Amazon Web Services (AWS) which makes it much easier for technology companies to scale their costs and infrastructure linearly with customer and revenue growth. GroupOn came along and vaulted to $1B in revenue faster than any company in history.

[Yes, I realize Groupon revenue is built off of what consumers pay for a deal and that Groupon only keeps a portion of that, but no company takes home 100% of its revenue. I also realize Groupon has since run into issues, but those are not ones of scaling as much as inherent business model problems.]

Companies like Instagram and WhatsApp now routinely can scale to hundreds of millions of users with hardly a hiccup and with many fewer employees than companies in the past. Unlike biological constraints like the circulation of blood, oxygen, or nutrients, technology has pushed some of the business scaling constraints out.

Now we look to companies like Google, Amazon, and Facebook, companies that seem to want to compete in a multitude of businesses, to study what the new scaling constraints might be. Technology has not removed all of them: government regulation, bureaucracy or other forms of coordination costs, and employee churn or hiring problems remain some of the common scaling constraints that put the brakes on growth.

Detroit's urban decay as seen on Google Street View

A Tumblr dedicated to showing the decay of Detroit over just a short period of time, from 2009 to 2013, through a series of Google Street View photos of the same address. 

James Griffioen refers to houses that have been reclaimed by nature as feral houses.

I love Google Street View's Time Machine capability, though this is a more poignant view through its eyes. We only have a handful of years with which to look back now, but future generations will have such a precise visual and textual record of so much that it may change their understanding of human history. Think about how much of history we're taught today feels just like narrative. Think of how differently we conceive of historical figures whom we can see in video and photos as compared to those who we only see in paintings.

There's a version of Wall-E to be made in which the robot is replaced by a self-driving Google Maps Street View car,  still cruising up and down streets of abandoned streets documenting the slow decay of civilization, humanity having long since fled to outer space.

[via Web Urbanist]

The cost of commuting

There is a clear connection between social deficit and the shape of cities. A Swedish study found that people who endure more than a 45-minute commute were 40% more likely to divorce. People who live in monofunctional, car‑dependent neighbourhoods outside urban centres are much less trusting of other people than people who live in walkable neighbourhoods where housing is mixed with shops, services and places to work.

A couple of University of Zurich economists, Bruno Frey and Alois Stutzer, compared German commuters' estimation of the time it took them to get to work with their answers to the standard wellbeing question, "How satisfied are you with your life, all things considered?"

Their finding was seemingly straightforward: the longer the drive, the less happy people were. Before you dismiss this as numbingly obvious, keep in mind that they were testing not for drive satisfaction, but for life satisfaction. People were choosing commutes that made their entire lives worse. Stutzer and Frey found that a person with a one-hour commute has to earn 40% more money to be as satisfied with life as someone who walks to the office. On the other hand, for a single person, exchanging a long commute for a short walk to work has the same effect on happiness as finding a new love.

Daniel Gilbert, Harvard psychologist and author of Stumbling On Happiness, explained the commuting paradox this way: "Most good and bad things become less good and bad over time as we adapt to them. However, it is much easier to adapt to things that stay constant than to things that change. So we adapt quickly to the joy of a larger house, because the house is exactly the same size every time. But we find it difficult to adapt to commuting by car, because every day is a slightly new form of misery."

Much more here. The irony of my move from Los Angeles to San Francisco has been an enormous lengthening of my commute, it's the longest of my life, and I feel that pain acutely. LA is legendary for its bad traffic, yet the overall lower cost of living in that region makes it far easier to live closer to where you work which is ultimately what matters the most. The quest to get from the West Side to downtown during rush hour in Los Angeles is actually much less painful and long than having to drive up the 101 to San Francisco from the Peninsula during rush hour.

Most days I take the Caltrain, but again, it's the variability of the service that drives me crazy, to Daniel Gilbert's point. At least once or twice a month, something catastrophic causes train service to just dry up for several hours, leaving you stranded. Often it's because of a suicide, at other times it's a car that gets hit, or a power line that falls, or something else you would think would be a rare black swan event. And then your evening is shot, your dinner date left to make alternative plans, unless you pony up for a $90 to $100 taxi or Uber up to the city, but oh wait, the traffic on the 101 means you won't make it on time anyway.

It's difficult to judge what it's like to live in a city just by visiting as a tourist. It wasn't until I'd lived in NYC for a year that I realized it's a far better city to live in than to visit, contrary to popular wisdom. The same is true of Los Angeles, where most natives know when to avoid certain highways at certain times, spending more time in their neighborhood.

For all the good that cities have brought to the U.S., they fail miserably, with the exception of New York, on the quality of public transportation. At least 30% of my pleasure in visiting cities in Europe is being in an environment that makes me, as a pedestrian, first among citizens. American cities were built up in the age of the automobile, and that metallic beast has taken control of our cities in a way that may not be overturned in our lifetime.

It may be that China is where we see some of the greatest innovation on this urban planning dilemma. For one thing, their hand may be forced by the shockingly high levels of pollution in their largest cities. They also face a huge migration of people from rural to urban areas, probably the largest in human history. Combine that with a form of government that has much more freedom to impose its will in matters great and small and you have the potential for a new type of city to be erected, one that is built around direct human mobility rather than transportation by automobile.

The high cost of housing

In the early- and mid-twentieth century, the Great Migration of African Americans out of the South was a movement of tenant farmers fleeing Jim Crow for a chance at menial factory jobs in places like Cleveland and Detroit. More recently, the great flow in the opposite direction, from Rust Belt to Sun Belt, has seldom been motivated by any utopian political-religious dream; far more often, it’s been the desire to escape difficult economic circumstances.

This feature of American life has served the country’s economy well, if not always its culture. Writers from Henry David Thoreau to Theodore Dreiser to John Cheever may have decried the rootlessness in American life, but at whatever the price in urban anonymity or suburban anomie, the high mobility of American labor meant that a comparatively high share of the nation’s workforce migrated to wherever it could add the most economic value. As the population reduced its concentration in lower-wage areas and increased it in higher-wage areas, the effect was to gradually reduce inequality of income and opportunity, until something like an “American standard of living” emerged in the twentieth century. All told, according to a 2013 paper by Harvard economists Peter Ganong and Daniel Shoag, approximately 30 percent of the drop in hourly wage inequality that occurred in the United States between 1940 and 1980 was the result of the convergence in wage income among the different states during this period.

In our own time, though, all of that has changed. Americans are moving far less often than in the past, and when they do migrate it is typically no longer from places with low wages to places with higher wages. Rather, it’s the reverse. That helps explain why, since the 1970s, income inequality has gone up and upward mobility has (depending on who you ask) either stagnated or gone down.

The U.S., a country once remarkable for the flowing movement of its citizens seeking their fortune wherever it beckoned, has now entered a post-migratory phase. The question investigated by this article is why? 

It turns out the most plausible culprit is the high cost of housing. Cities are one of the world's great technologies: good for the environment, increasing the productivity and incomes of all who move into them. Yet restrictive zoning laws in American cities has made it difficult for more people to move into them, amplifying income inequality in the country. 

It's great, of course, if you can afford to live in San Francisco or New York or one of its wealthy surrounding territories. As you'd expect, most folks who live there love their huge houses and giant yards and don't want more development driving down the price of their properties. 

But for society as a whole, the soaring rents in American cities is a disturbing trend. My cost of living more than doubled when I moved from Los Angeles to San Francisco, and it shows no sign of slowing down. I can't imagine what it would have been like for someone moving from a more affordable city or suburb. For now, technology companies in the Bay Area can mitigate the impact on its hiring by just increasing what it pays its employees, but that can't continue ad infinitum. Eventually, companies may have to consider building more affordable housing, almost like dormitories, for young workers fresh out of school, or they should join the chorus of voices pushing the local governments to ease up on zoning restrictions.

Among that chorus of voices, it's unlikely you'll find those who've managed to get a foothold in those neighborhoods. After all, the whole point of moving up the economic ladder is membership in an elite and exclusionary club, isn't it?

Yogi Berra supposedly once said, “Nobody goes to that restaurant anymore. It’s too crowded.” We might similarly observe, “Nobody moves to that state anymore. It offers too much economic opportunity.” It doesn’t make any sense, but that’s life in our present post-migration era. For all his historic foresight, Greeley could never have imagined an outcome so undemocratic and economically perverse.

UPDATE: Found another related article open in one of my browser tabs.:

In a nutshell, San Francisco is expensive for myriad reasons—some positive, like the city’s successful transition from an industrial to a post-industrial economy and its walkability; others negative, like the NIMBYism that leads to fights over high-density development every step of the way:

Unfortunately, it worked: the city was largely “protected” from change. But in so doing, we put out fire with gasoline. Over the past two decades, San Francisco has produced an average of 1,500 new housing units per year. Compare this with Seattle (another 19th century industrial city that now has a tech economy), which has produced about 3,000 units per year over the same time period (and remember it’s starting from a smaller overall population base). While Seattle decided to embrace infill development as a way to save open space at the edge of its region and put more people in neighborhoods where they could walk, San Francisco decided to push regional population growth somewhere else.

Racial diversity in American cities

I killed a good half hour playing with this racial diversity dot map. It visualizes some of the spatial racial distribution of cities that you can only intuit from ground level as a resident. While a city may seem quite integrated and diverse, it isn't until you zoom in that you see that what looks like a diverse blob of people is really a series of segregated neighborhoods. 

One personal hunch, though, is that how diverse a city feels is not just based on how segregated the population is based on their place of residence but how much those populations interact in day to day life, and that is a function of city density and the developmental maturity of the city's public transportation. While New York City looks like Chicago or San Francisco or other big cities in being a collection of segregated neighborhoods, it felt like the most diverse city I've ever lived in because those populations crossed paths on the city streets and subways every day in high numbers. 

Thomas Schelling's Segregation Model, one of the more powerful agent based models I've ever studied, shows how the extreme segregation of American cities might arise from much milder racial preferences. It's a critical model to study, one that is useful to keep in mind when trying to avoid a variant of fundamental attribution error when trying to explain how something that builds over time ended up in a bad state.

This report (PDF) from 2011 studies long term racial segregation trends in America and comes to this conclusion:

The 2010 Census offers new information on changes in residential segregation in metropolitan regions across the country as they continue to become more diverse. We take a long view, assessing trends since 1980. There are two main findings: 1) the slow pace of lowering black-white segregation has continued, but there is now some change in the traditional Ghetto Belt cities of the Northeast and Midwest; and 2) the rapidly growing Hispanic and Asian populations are as segregated today as they were thirty years ago, and their growth is creating more intense ethnic enclaves in many parts of the country.