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Urbanists have long looked at cars as the scourge of great places.  Jane Jacobs identified the automobile as the “chief destroyer of American communities.” Cars not only clog our roads and cost billions of dollars in time wasted commuting, they are a terrible killer. They caused more than 40,000 deaths in 2017, including of some 6,000 pedestrians and cyclists.

But in the United States, the car plays a fundamental role in structuring the economy, our daily lives, and the political and social differences that separate us.

Writing from prison in the 1930s, the Italian Marxist Antonio Gramsci dubbed our modern economic system Fordism—invoking the system of automotive production developed by Henry Ford. On the factory floor, Fordism described the powerful synthesis of scientific management and the moving assembly line, which revolutionized industrial production. Applied to the economy, the term captured Ford’s move to higher pay for his workers—the famous $5-a-day wage—that enabled them to buy the cars they produced. At a broader societal level, Fordism catalyzed the shift to a mass suburbanized society.

As Ford himself once put it: “We shall solve the city problem by leaving the city.” The car enabled the American suburban dream, prompting the relocation of the middle class, industry, and business from the city. In doing so, it helped shape the relatively short-lived era of post-World War II prosperity and the rise of a stable, blue-collar middle class, stoking economic demand for the products coming off the country’s assembly lines.

But today, the car plays a central role in worsening America’s social, political, and economic divides.

This can be seen in a simple statistical-correlation analysis by my colleague and frequent collaborator Charlotta Mellander. Mellander ran correlations for the share of workers who drive their cars to work alone, along with three other types of commuting: taking transit to work; walking to work; and biking to work. She compared these to certain key features of our economic and political geography, including income, education, and occupational class; population size and density; and political affiliation and voting.

As usual, I point out that correlation in no way infers causation, but simply points to associations between variables. (All of the correlations reported below are statistically significant.)

She found sharp differences between metropolitan areas where a high share of people drive their cars alone to work and those where greater shares of people take transit, walk, or bike there. These are especially striking in the light of the fact that an overwhelming share of Americans—85 percent of us—drive alone to our jobs. Also, car dependence encompasses both liberals and conservatives: 73 percent of independents, 86 percent of Republicans, and more than three-quarters of Democrats say that they depend on their cars to get to work.

The key is not individuals’ car use, but the way we sort into communities based on our reliance on cars.

For one, the geography of car use tracks with income and wealth: Car-dependent places are considerably less affluent. Metros in which a higher share of people depend on their cars to get to work are poorer, and those where more people use transit or bike or walk to work are considerably more affluent. The share of commuters who drive to work alone is negatively correlated with both wages and income. Conversely, in more affluent metros, a higher proportion of commuters use transit, walk, or bike.

	Drive alone to work	Take transit to work	Walk to work	Bike to work
Income	-.36	.53	.21	.23
Wages	-.49	.62	.22	.27
College Grads	-.53	.50	.50	.52

The geography of automobile dependence is also related to divisions along educational lines. Metros with lower levels of educational attainment (measured as the share of adults who have a college degree) are those where a larger share of commuters drive to work. In more highly educated metros, larger shares of commuters use transit or bike or walk to work.

	Drive alone to work	Transit to work	Walk to work	Bike to work
Knowledge workers/creative class	-.43	.47	.32	.31
Working class	.48	-.33	-.34	-.34
Innovation (patents per capita)	-.27	.36	.32	.37

America’s geography of car dependence also reflects differences in the kinds of work we do. Car dependence is a feature of working-class metros, while metros with higher concentrations of knowledge workers and the creative class have much higher shares of people who use transit or walk or bike to work.

We see the same basic pattern where we look at metros that are knowledge and tech hubs. Driving to work alone is negatively associated with the innovativeness of metros (measured as patents per capita), whereas the share of commuters who use transit or bike or walk to work is positively associated with innovation.

America is an increasingly polarized and politically divided nation, and the car both reflects and reinforces those divisions. Car-dependent places are much more likely to have voted for Trump in 2016. Although the associations are stronger for Trump votes, the same basic pattern holds for Romney votes in 2012. On the flip side, metros that voted for Hillary Clinton in 2016 and Barack Obama in 2012 have much higher shares of commuters who use transit or walk or bike to work.

	Drive alone to work	Public transit to work	Walk to work	Bike to work
Clinton	-.48	.48	.34	.36
Trump	.54	-.50	-.40	-.43
Obama	-.38	.44	.35	.30
Romney	.40	-.44	-.36	-.32
Density	-.53	.62	.30	.28

Of course, voting patterns differ based on the size and density of places as well as their educational and class composition. It is well-known that Trump took the presidency by winning smaller and medium-sized places and rural areas, whereas Hillary Clinton took America’s largest, densest, and most productive areas. Car dependence is negatively associated with the size and density of metros. People in larger, denser urban areas are more likely to commute to work by transit or bike or walk (although the correlation between population and biking to work is statistically insignificant).

All of this raises the question: How exactly does this geography of car dependence work to divide us?

The detailed historical research by Stanford political scientist Clayton Nall offers some clues. Nall’s work shows how road infrastructure that has promoted car use—and in particular America’s massive investment in the federal interstate highway system—played a profound role.

The car and car-dominated infrastructure propelled suburbanization and white flight. They split our society into white, affluent suburbs and poor black and minority cities. The car shaped the rise of what Richard Nixon identified as a “silent majority” of suburban whites back in the late 1960s, and is a precursor to the suburban and rural backlash that lifted Donald Trump to victory in 2016.

Nall has written that “Democrats and Republicans have adopted increasingly different positions on spatial policy issues such as transit and highways. Transportation infrastructure has been a necessary condition of large-scale suburban growth and partisan change, facilitating migration into rural areas that were previously unoccupied and inaccessible to metropolitan commuters and workers.” In other words, the car and the infrastructure that enables it had a huge influence on the disparities that vex us today.

The car’s politically divisive role extends beyond America. It has helped shape the politics of my adopted hometown of Toronto. Indeed, dependence on the car was a key factor in whether or not someone voted for the city’s late, dysfunctional mayor Rob Ford.  Ford singled out so-called “urban elites” for waging a “war on the car,” and promised supporters he would remove bike lanes to give more room on roads to drivers. According to detailed research by political scientist Zack Taylor, commuting to work by car and living in the suburbs (inside the city limits) were among the strongest factors in electoral support for Rob Ford.

I’m not trying to blame the car for everything that’s wrong in America. But it is increasingly clear that in addition to wasted time and productivity, reduced quality of life, and even fatalities, the automobile takes another toll. It may be that cars are not only the chief destroyer of our communities, but are tearing at the nation’s political and social fabric.

Many of the techniques that enabled this evolution to take place were not learned in northern California. For me, Smart City concepts originated in muddy holes, sandstorms and military classrooms around the world. Functional Smart City use cases originated in the cabs of Public Works trucks and at water treatment plants and were articulated by City employees with decades of civil service experience, not a coding background. Truly smart evolutions grow out of solving real problems for real people based on real experiences.

In Munich, the future of public transit might be up in the air. This month, the city is discussing a plan to create a new 4.5-kilometer gondola link in the northern part of the city, linking two districts on the internal beltway that are currently poorly connected for everyone except drivers.

Supported by the mayor, the regional transit minister, and even the opposition parties in the city’s assembly, it’s a plan that has a strong likelihood of being built.

It’s still perhaps a little unexpected: Munich is a flat city with a good public transit network. Gondolas have a mixed reputation, having both transformed mobility in some very hilly cities while failing to be more than gimmicky white elephants in others. So would Munich’s embrace of the gondola be a good or a bad thing? And why would the city even need one in the first place?

The fact is that even the better public transit systems have their limitations. Munich’s subway (U Bahn), Suburban rail (S Bahn), and tram networks offer good coverage of the area, but they all focus primarily on getting people in and out of the city center. This is fine for commuters, but can pose an inconvenience for people in outlying districts who simply want to travel between two adjacent neighborhoods. Bus routes compensate for this, but their speed and efficiency is dependent on road traffic.

The gondola poses a solution to a small local issue that could, if effective, be rolled out at other sites in the city. The proposed link would connect two subway stations (at Oberwiesenfeld and Studentenstadt) that sit 4.5 kilometers apart on a major road. Despite being close to each other, it’s time-consuming to travel between them, requiring a five-stop subway trip toward the city center, a transfer, and a five-stop trip back out in a different direction.

The gondola could knit these two districts tidily together. Sailing over the road, the wires would be far cheaper to install than the terrestrial rails of a train or tram, but still ferry up to 4,000 passengers an hour. Land-wise, the gondola would only take up the space that’s necessary to support its towers. Indeed, the road it would follow already has space for these in the median. To make it a fully functioning link, it’s vital that each terminus connects swiftly to the subway, but broadly the idea seems sensible.

Similar projects elsewhere in Europe—where urban gondolas are still in their infancy—suggest grounds for cautious optimism. France in particular has embraced the mode with enthusiasm, with five gondola projects currently under construction and due for opening before 2021. The gondola that the French city of Brest opened across its river in November 2016, for example, celebrated its millionth passenger last month—not bad for a metro area of only 300,000 people. Initially resisted by some residents for fear it would provide unwelcome views into people’s houses, Brest resolved the issue ingeniously by installing windows that misted temporarily when the cars neared people’s homes. London’s Emirates Air Line nonetheless remains a cautionary tale of what to avoid. Constructed at the time of the Olympics, it was promoted as both a transit link and tourist attraction. Due to a poorly chosen, out-of-the-way location, it hasn’t functioned well as either.

There have been some preposterous suggestions in the German media that Munich’s proposed gondola might possibly be a tourist attraction as well. The route offers little to look at, but proponents are sensibly focusing on its role as a transit fix, rather than a sightseeing adventure.

There’s still a sense that this plan is a too-piecemeal response to outer Munich’s limited connections. Even if the city creates similar gondolas in other underserved areas, the transformative effect of these all joined together would still be far less than that of a full orbital subway or segregated streetcar line circuiting the city. The fact that Munich isn’t considering such solutions reflects the considerable financial burden they would pose, but also suggests a certain narrowness of ambition. There’s also the argument that by avoiding the roads entirely, the gondola link offers little incentive for Munich to reduce the polluting traffic on its major roads. But is the proposed link feasible and likely to attract passengers? Probably, yes.

Join us for a webinar on July 17th, 2018 at 2PM Eastern to dive into the details of our new report, Yes! In My Backyard: A Home Composting Guide for Local Government. The report advocates for home composting programs as one of the best opportunities to reduce food waste, especially as they can be implemented relatively quickly, and in areas lacking curbside organics collection or facilities to compost. Eleven programs were profiled, demonstrating that there is no one right way to implement a home composting program.… Read More

Minnesota’s nation-leading community solar program hit a record 379 megawatts of operational capacity in July 2018. Two charts show the progress of the program since August 2015 and the share of subscribers by customer class.… Read More

In June, the city of Fairlawn and the Medina County Fiber Network in Ohio recently announced that they would soon begin working together, which expand FairlawnGig, the city’s municipal network. The collaboration will boost connectivity in the region for residents and provide more options for businesses in Akron and surrounding communities.… Read More

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Orient yourself: A smarter “smart city”

Perhaps you’ve heard that the future of cities lies on the internet. Buildings, streetlights, roads, and sewers will be blanketed with wifi-connected sensors, tuned to gather vital signs of the urban environment and our movements within it. At least that’s according to many a “smart city” product pitch from the likes of Alphabet, IBM, Cisco, and others.

The uneasy part is what happens with the information, collected by gunshot scanners, traffic detectors, even public wifi kiosks. It’s not that governments necessarily intend to do anything nefarious with people’s data. But “smart cities” are usually designed from the top-down with predetermined objectives, be it surveillance, prediction, science, or profit.

Carlo Ratti, an Italian architect, urban designer, engineer, and theorist, sees that heavily internet-ed future differently. I spent an afternoon with Ratti in May at the Senseable City Lab, his research consortium at MIT—you can read my profile of him here. He develops urban data-gathering projects where sensors interact with people and the environment in a more open-ended feedback loop, rather than in pursuit of particular outcomes. Take his exploratory sewage probes that somewhat inadvertently uncovered a new way to track opioid abuse. “It wasn’t supposed to solve anything. It was more like, what we can discover?” Ratti told me. Or take the GPS trackers tagged to bits of garbage that revealed the surprisingly broad pathways of American waste. Above, a map of a local trash route in Seattle.

There are often gorgeous mapping components to Ratti’s work, rooted as it tends to be in cities. Above, behold a visualization of Boston’s “Green View Index,” part of his lab’s “Treepedia” project, which gathered satellite imagery to determine the quality of canopy coverage in cities around the world. The idea was to help people get smarter about the living, breathing infrastructure around them, and possibly pique their interest in protecting it. A positive feedback loop, indeed.

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Compass points: Inside the 100-mile zone

With the help of ESRI, CityLab’s Tanvi Misra recently mapped the U.S. Customs and Border Protection’s “100-mile-zone,” a wide belt of American soil where CBP agents are allowed to detain, search, and seize individuals, including on the basis of race.

The zone happens to contain a whopping two-thirds of the U.S. population. But after Tanvi published the story, she got a lot of questions asking why all of Michigan was in there, too. After all, a portion of the state lies far beyond the 100-mile line from the U.S.-Canada border, as the crow flies.

In other words, when the government decides where to patrol “the border,” how does it decide where it is? Turns out, it makes up the answer. Exclusively for MapLab, Tanvi writes an update:

This issue came up in a lawsuit filed by the American Civil Liberties Union (ACLU) in 2016. In the complaint, the plaintiffs cited a map obtained from the CBP showing that the agency considered a “reasonable distance” of 100 nautical miles to extend from the shore OF THE? Great Lakes. They marked it as the “functional equivalent” of the actual U.S.-Canadian border in this region—whatever that means. The agency declined to directly answer my question regarding this interpretation.

CBP’s reading of the international boundary has also come up in the case of a lawsuit in New Hampshire, where, according to a statement the agency provided to a local news outlet, 100 nautical miles starts at “12 nautical miles offshore from the mean low-tide.” By that measure, all of New Hampshire falls in the zone.

The big takeaway? Tanvi tells me that the “reasonable distance” from the border varies a lot from region to region, depending on the CBP’s discretion.

Looking for more of Tanvi’s maps of U.S. immigration policy? Peer into where migrant kids separated from their parents at the border might have wound up, and which U.S. cities are helping detain immigrants.

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Mappy links

Up and up: what a city’s “vertical agglomeration” says about its economy. ♦ Paris, c’est trop chaud: A map of heatwave hideaways in the French capital. ♦ ICYI: Apple Maps says it’s ready to be taken seriously. ♦ Beware the State of Solemnization: Fanciful maps of emotional terrain, circa the 17^th century. ♦ Heart maps, but seriously: Advances in medical imaging reveal maps of the beating organ. ♦ Hot diggity: A tubular map projection by a conceptual artist, good for the grill. ♦ Hard not to balk: Montenegro, one NATO ally Trump might not help in a crisis, has its moment on the map.

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Cheers,

Laura

Raise the banners and strike up the band, because the “War on Poverty” is won. Mission accomplished! And that means it’s time to hack down the safety net that saved the nation’s poor.

That was the head-turning takeaway from a report last week from the White House Council of Economic Advisors that declared the War on Poverty “largely over and a success.” The report diverged sharply from what even other Republicans say about poverty, to say nothing of economists. (“Do these people ever visit the real world?” Paul Krugman asked.)

But while the language marked a rhetorical reversal of the usual conservative efforts to undo Johnson-era programs designed to aid low-income Americans—which hinge on the conceit that federal aid is wasteful, not that it nailed it—the intent is largely the same. This was an argument for work requirements in welfare, one of the Trump administration’s top domestic priorities.

The Trump administration’s declaration might also come as a surprise to the millions of American children (still) living in what looks and feels a lot like poverty. Kids are major beneficiaries of most safety-net programs for food, housing, and healthcare. Some 44 percent of the people who receive food stamps through the Supplemental Nutrition Assistance Program are children, for example. Cutting spending on poverty means cutting spending on kids—a downward trend that is already happening.

…While poverty has been decreasing, especially once using the most accurate measure which is based on consumption (including government benefits) pic.twitter.com/gTvj2nZ9OU

— CEA (@WhiteHouseCEA) July 12, 2018

Declaring an end to the war on poverty allows federal agencies to pivot to other goals, namely “self-sufficiency,” which is a watchword for setting strict work requirements for aid. Congress has yet to pass draconian cuts to aid, but spending on children is already declining, even as overall federal spending continues to rise since the Great Recession. A new report from the Urban Institute finds that by 2020, the federal government will spend more on interest payments on its debt than it pays to provide support for children.

Children will receive just one cent of every dollar from the projected $1.6 trillion increase in federal spending authorized under the Trump administration, according to the report. And over the next decade, the children’s share of the budget will drop from 9.4 percent to 6.9 percent.

That dip is happening even without factoring in the changes now being proposed by chief White House economic advisor Kevin Hassett* and company—those who argue that poverty’s a thing of the past. If and when work requirements and cuts to aid are implemented, the outlook for kids will only get darker.

“If we spend less on children, we’re investing less in the next generation,” says Julia Isaacs, senior fellow at the Urban Institute. “We want children to be well fed, well housed, and well educated.”

Isaacs, the co-author of the Urban Institute’s report on current and future federal expenditures on children, adds that cutting spending on kids has implications for future growth. “We can think of children as human capital, if we want to be economists. And if we don’t invest in human capital, it may come back to bite us in the long run.”

Medicaid is the largest source of federal expenditures for children: about $90 billion in 2017. Tax provisions make up another big chunk of spending on kids, namely the earned income tax credit ($60 billion in 2017), the child tax credit ($49 billion), and dependent exemptions ($38 billion). Other large categories of federal spending on kids include nutrition, education, and income through various programs. Spending in these discretionary categories is dropping already. Local and state governments—who pay the lion’s share of spending on education—will be left to make up the gap.

Federal spending on children increased sizably between 1960 and 2010, thanks to a mix of demographic and political forces. Over the next decade, though, this trend will reverse as millions of Baby Boomers enter retirement and spending on older adults under Social Security, Medicare, and Medicaid is projected to soar. Interest payments on the rising federal debt will also go up.

These projections don’t take into account the newer policy priorities under the Trump administration, which would shift spending away from children even more dramatically. For example, the House version of the farm bill would cut spending for food aid dramatically and establish strict work requirements for recipients.

“More than three-quarters of the people [who receive SNAP aid] are either kids or people living with kids,” Isaacs says. “If we were to enact the farm bill that cuts SNAP so much, then the numbers would be worse. This decline is happening before we take into account any additional changes.”

If the White House report is any indication, its war on welfare is only just beginning. Getting to a near-zero figure for poverty requires some creative math, namely a cherry-picked “consumption-based” measure for poverty based on families’ spending. This measure is wildly out of step with traditional and official measures for poverty. As researchers from the University of Michigan show, a consumption-based poverty measure indicates that poverty was worse during the early 2000s than during the Great Recession.

Similarly, the report’s call for work requirements assumes that work-able adults who receive aid aren’t working. Organizations such as the Kaiser Family Foundation say otherwise. In the end, children will be hurt by the policies set under these faulty premises.

More than 14 million people under age 17 were living below the federal poverty limit in 2016, according to the U.S. Census Bureau. That number has fallen since 2012, but still represents about 20 percent of all children in the U.S. The share of federal spending for children that reaches low-income families has grown over time— meaning that the war on poverty is achieving results. That doesn’t mean it’s over: Spending cuts on food, housing, and healthcare will hurt children disproportionately. Kids can’t live on alternative facts alone.

*CORRECTION: An earlier version of this story named Gary Cohn as the chair of the Council of Economic Advisors. He left the office in 2017, and left the White House in March. Kevin Hassett now serves as the chief White House economist.

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Benjamin Schneider gives an intro course on inclusionary zoning, walking us through the history of the affordable housing policy and how leaders have used it to address city segregation. This syllabus comes packed with frequently asked questions, a case study, viewpoints, a toolkit, and a reading list—explaining all the acronyms and jargon along the way. Even if you’re already an expert, keep it on hand to share with people you know who could use the lesson: CityLab University presents: Inclusionary Zoning.

• Let us know what you think of our pilot endeavor and what you’d like to study up on next: Drop us a line at hello@citylab.com

—Andrew Small

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What We’re Reading

Heat makes you dumb, in four charts (Washington Post)

I tried to fall asleep at a nap bar (Fast Company)

Rising seas could cause problems for internet infrastructure (NPR)

Senators want to sneak safety exemptions for self-driving cars into law (Streetsblog)

A photography project, by homeless people (The Guardian)

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