rural/urban

The built environment reflects our social world. From urban streets that encourage neighborly relationships, to “hostile design” and policing practices that keep people out of public spaces, the physical structure of a space carries with it a whole set of assumptions about how people should interact in that space.

But social structure isn’t always just imposed on us by architects and city planners. It also invites the opportunity for improvisation and innovation to create new norms. A great example of this is the emergence of “desire paths“—the people-made paths that defy, or improve on, the work of urban design.

Desire paths were the bulk of my commute for years without even realizing it. When you walk a lot, you start to see how much our neighborhoods aren’t built for this most basic kind of travel. It is fun to spot these paths along the way, because they show little pockets of collective action where people have found a better way to get from point A to B. Authors like to highlight how some universities, for example, even wait for desire paths to emerge and then pave them to fit students’ commuting routes.

That said, it is also important to pay attention to the limits that urban design, like all kinds of social structures, continues to impose in our communities. Research shows that walkability may only be weakly related to the social health of a neighborhood, since community cohesion takes more work than just putting people in the same space. Walkable neighborhoods also attract more drivers as people commute in to walk around to shops and restaurants. My alma mater, Michigan State University, paved a ton of desire paths in student neighborhoods across campus. It was great, but if you needed to get to the other side of campus for class in a pinch, there was still the matter of that big stadium complex in the way. Sometimes social improvement still takes a bit more conscious effort.

Evan Stewart is an assistant professor of sociology at University of Massachusetts Boston. You can follow his work at his website, or on BlueSky.

Flashback Friday.

The percent of carless households in any given city correlates very well with the percent of homes built before 1940. So what happened in the 40s?

According to Left for LeDroit, it was suburbs:

The suburban housing model was — and, for the most part, still is — based on several main principles, most significantly, the uniformity of housing sizes (usually large) and the separation of residential and commercial uses. Both larger lots and the separation of uses create longer distances between any two points, requiring a greater effort to go between home, work, and the grocery store.

These longer distances between daily destinations made walking impractical and the lower population densities made public transit financially unsustainable. The only solution was the private automobile, which, coincidentally, benefited from massive government subsidies in the form of highway building and a subsidized oil infrastructure and industry.

Neighborhoods designed after World War II are designed for cars, not pedestrians; the opposite is true for neighborhoods designed before 1940. Whether or not one owns a car, and how far one drives if they do, then, is dependent on the type of city, not personal characteristics like environmental friendliness.  Ezra Klein puts it nicely:

In practice, this doesn’t feel like a decision imposed by the cold realities of infrastructure. We get attached to our cars. We get attached to our bikes. We name our subway systems. We brag about our short walks to work. People attach stories to their lives. But at the end of the day, they orient their lives around pretty practical judgments about how best to live. If you need a car to get where you’re going, you’re likely to own one. If you rarely use your car, have to move it a couple of times a week to avoid street cleaning, can barely find parking and have trouble avoiding tickets, you’re going to think hard about giving it up. It’s not about good or bad or red or blue. It’s about infrastructure.

Word.

Neither Ezra nor Left for LeDroit, however, point out that every city, whether it was built for pedestrians or cars, is full of people without cars. In the case of car-dependent cities, this is mostly people who can’t afford to buy or own a car. And these people, in these cities, are royally screwed. Los Angeles, for example, is the most expensive place in the U.S. to own a car and residents are highly car-dependent; lower income people who can’t afford a car must spend extraordinary amounts of time using our mediocre public transportation system, such that carlessness contributes significantly to unemployment.

Originally posted in 2010.

Lisa Wade, PhD is an Associate Professor at Tulane University. She is the author of American Hookup, a book about college sexual culture; a textbook about gender; and a forthcoming introductory text: Terrible Magnificent Sociology. You can follow her on Twitter and Instagram.

Will Davies, a politics professor and economic sociologist at Goldsmiths, University of London, summarized his thoughts on Brexit for the Political Economy and Research Centre, arguing that the split wasn’t one of left and right, young and old, racist or not racist, but center and the periphery. You can read it in full there, or scroll down for my summary.

——————————–

Many of the strongest advocates for Leave, many have noted, were actually among the beneficiaries of the UK’s relationship with the EU. Small towns and rural areas receive quite a bit of financial support. Those regions that voted for Leave in the greatest numbers, then, will also suffer some of the worst consequences of the Leave. What motivated to them to vote for a change that will in all likelihood make their lives worse?

Davies argues that the economic support they received from their relationship with the EU was paired with a culturally invisibility or active denigration by those in the center. Those in the periphery lived in a “shadow welfare state” alongside “a political culture which heaped scorn on dependency.”

Davies uses philosopher Nancy Fraser’s complementary ideas of recognition and redistribution: people need economic security (redistribution), but they need dignity, too (recognition). Malrecognition can be so psychically painful that even those who knew they would suffer economically may have been motivated to vote Leave. “Knowing that your business, farm, family or region is dependent on the beneficence of wealthy liberals,” writes Davies, “is unlikely to be a recipe for satisfaction.”

It was in this context that the political campaign for Leave penned the slogan: “Take back control.” In sociology we call this framing, a way of directing people to think about a situation not just as a problem, but a particular kind of problem. “Take back control” invokes the indignity of oppression. Davies explains:

It worked on every level between the macroeconomic and the psychoanalytic. Think of what it means on an individual level to rediscover control. To be a person without control (for instance to suffer incontinence or a facial tick) is to be the butt of cruel jokes, to be potentially embarrassed in public. It potentially reduces one’s independence. What was so clever about the language of the Leave campaign was that it spoke directly to this feeling of inadequacy and embarrassment, then promised to eradicate it. The promise had nothing to do with economics or policy, but everything to do with the psychological allure of autonomy and self-respect.

Consider the cover of the Daily Mail praising the decision and calling politicians “out-of-touch” and the EU “elite” and “contemptuous”:

From this point of view, Davies thinks that the reward wasn’t the Leave, but the vote itself, a veritable middle finger to the UK center and the EU “eurocrats.” They know their lives won’t get better after a Brexit, but they don’t see their lives getting any better under any circumstances, so they’ll take the opportunity to pop a symbolic middle finger. That’s all they think they have.

And that’s where Davies thinks the victory  of the Leave vote parallels strongly with Donald Trump’s rise in the US:

Amongst people who have utterly given up on the future, political movements don’t need to promise any desirable and realistic change. If anything, they are more comforting and trustworthy if predicated on the notion that the future is beyond rescue, for that chimes more closely with people’s private experiences.

Some people believe that voting for Trump might in fact make things worse, but the pleasure of doing so — of popping a middle finger to the Republican party and political elites more generally — would be satisfaction enough. In this sense, they may be quite a lot like the Leavers. For the disenfranchised, a vote against pragmatism and solidarity may be the only satisfaction that this election, or others, is likely to get them.

Lisa Wade, PhD is an Associate Professor at Tulane University. She is the author of American Hookup, a book about college sexual culture; a textbook about gender; and a forthcoming introductory text: Terrible Magnificent Sociology. You can follow her on Twitter and Instagram.

Rumors are circulating that the Bureau of Land Management (BLM) has plans to euthanize 44,000 wild horses. The rumor is partly true. An advisory board has authorized the BLM to do so; they have yet to make a decision as to whether they will. Even the possibility of such a widespread cull, though, has understandably sparked outrage. Yet the reality of the American mustang is not as simple as the love and admiration for these animals suggests.

Mustangs are powerful symbols of the American West. The modern mustang is the descendant of various breeds of horses worked by everyone from Spanish conquistadors to pioneers in wagon trains into the Western US. Some inevitably escaped over time and formed herds of feral horses. Wild herds in the east were generally either driven west or recaptured over time as the frontier moved ever westward (the wild ponies of Assateague Island off the coast of Virginia being a famous exception). Over time, they became inextricably entwined with perceptions of the West as still wild and free, not yet fully domesticated. The image of a herd of beautiful horses against a gorgeous but austere Western landscape is a striking one, perhaps something like this:

So how do we get from that to these mustangs penned up in a pasture running after a feed truck in Oklahoma (a screenshot from the video below):

It’s a complicated story involving conflicts surrounding federal land management, public attitudes toward mustangs, and unintended consequences of public policies.

Wild horses fall under the purview of the BLM because most live on public range (particularly in Nevada, California, and Idaho, as well as Washington, Wyoming, and other Western states). Mustangs have no natural predators in the West; mountain lions, bears, and wolves kill some horses each year, but their numbers simply aren’t large enough to be a systematic form of population control for wild horse herds, especially given that horses aren’t necessarily their first choice for a meal. So wild horse herds can grow fairly rapidly. Currently the BLM estimates there are about 67,000 wild horses and burros on public land in the West, 40,000 more than the BLM thinks the land can reasonably sustain.

Of course, managing wild horses is one small part of the BLM’s mission. The agency is tasked with balancing various uses of federal lands, including everything from resource extraction (such as mining and logging), recreational uses for the public, grazing range for cattle ranchers, wildlife habitat conservation, preservation of archaeological and historical sites, providing water for irrigation as well as residential use, and many, many more. And many of these uses conflict to some degree. Setting priorities among various potential uses of BLM land has, over time, become a very contentious process, as different groups battle, often through the courts, to have their preferred use of BLM land prioritized over others.

The important point here is that managing wild horse numbers is part, but only a small part, of the BLM’s job. They decide on the carrying capacity of rangeland — that is, how many wild horses it can sustainably handle — by taking into account competing uses, like how many cattle will be allowed on the same land, its use as wildlife habitat, possible logging or mining activities, and so on. And much of the time the BLM concludes that, given their balance of intended uses, there are too many horses.

So what does the BLM do when they’ve decided there are too many horses?

For many years, the BLM simply allowed them to be killed; private citizens had a more or less free pass to kill them. There wasn’t a lot of oversight regarding how many could be killed or the treatment of the horses during the process. Starting in the late 1950s, the BLM began to get negative press, and a movement to protect wild horses emerged. It culminated in the Wild Free-Roaming Horses and Burros Act, passed in 1971. The law didn’t ban killing wild horses, but it provided some protection for them and required the BLM to ensure humane treatment, guarantee the presence of wild horses on public lands, and encourage other methods of disposing of excess horses.

One such method is making such horses (and burros) available to the general public for adoption. The BLM holds periodic adoption events. However, currently the demand for these animals isn’t nearly large enough to absorb the supply. For instance, in 2010, 9,715 wild horses were removed from public lands, while 2,742 were adopted.

So, there aren’t enough people to adopt them and killing them has become increasingly unpopular. Controlling herd populations through some form of birth control hasn’t been widely implemented and has led to lawsuits. What to do?

One solution was for the federal government to pay private citizens to care for mustangs removed from public lands. Today there are 46,000 wild horses penned up on private lands, fed by feed trucks. Something for which the American taxpayer pays $49 million dollars a year. Holding wild horses has become a business. Here’s a news segment about one of these wild horse operations:

The ranch in video is owned by the Drummond family, a name that might ring a bell if you’re familiar with the incredibly popular website The Pioneer Woman, by Ree Drummond. They are just one of several ranching families in north central Oklahoma that have received contracts to care for wild horses.

In addition to the sheer cost involved, paying private citizens to hold wild horses brings a whole new set of controversies, as well as unintended consequences for the region. Federal payments for the wild horse and burro maintenance program are public information. A quick look at the federal contracts database shows that in just the first three financial quarters of 2009, for example, the Drummonds (a large, multi-generational ranching family) received over $1.6 million. Overall, two-thirds of the BLM budget for managing wild horses goes to paying for holding animals that have been removed from public lands, either in short-term situations before adoptions or in long-term contracts like the ones in Oklahoma.

This is very lucrative. Because prices are guaranteed in advance, holding wild horses isn’t as risky as raising cattle. And, if a horse dies, the BLM just gives the rancher a new one. But this income-generating opportunity isn’t available to everyone; generally only the very largest landowners get a chance. From the BLM’s perspective, it’s more efficient to contract with one operation to take 2,000 horses than to contract with 20 separate people to take 100 each. So almost all small and mid-size operations are shut out of the contracts. This has led to an inflow of federal money to operations that were already quite prosperous by local standards. These landowners then have a significant advantage when it comes to trying to buy or lease pastures that become available in the area; other ranchers have almost no chance of competing with the price they can pay. The result is more concentration of land ownership as small and medium-sized ranchers, or those hoping to start up a ranch from scratch, are priced out of the market. In other words, the wild horse holding program contributes to the wealth of the 1%, while everyone else’s economic opportunities are harmed.

This is why the BLM is considering a cull. Not because they love the idea of killing off mustangs, but because they’re caught between a dozen rocks and hard places, trying to figure out how to best manage a very complicated problem, with no resolution in sight.

Revised and updated; originally posted in 2011. Cross-posted at Scientopia and expanded for Contexts.

Gwen Sharp, PhD is a professor of sociology and the Associate Dean of liberal arts and sciences at Nevada State College. 

Cross-posted at Cyborgology.

Fake news among the alt-right has been central in post-election public discourse, like with Donald Trump’s dubiously sourced tweet about the “millions of illegal voters” supposedly driving Clinton’s substantial lead in the popular vote. Less attention, however, has been paid to the way “real” news is, to use the sociologist Nathan Jurgenson’s term, based in “factiness,” described as “the feel and aesthetic of ‘facts,’ often at the expense of missing the truth.”  Mainstream news gets cast as objective in part because journalists, stack of papers and obligatory pen studiously in hand, point to statistics that back up their reports. Such reliance on “data” can mask the way that humans are involved in turning things into numbers and numbers into stories. So here I present a cautionary tale.

It is a common truism that white male voters without college degrees disproportionately supported Trump in the 2016 election. Indeed, the notion that men with high school as their highest level of education were more likely to vote for Trump is an empirically supported fact. This data point spread widely throughout the campaign season, and bore out in the post-election analyses. But also in the post-election analyses — over which researchers poured in response to the statistically surprising result — another data point emerged that could have, but didn’t, change the narrative around this demographic voting bloc.

The data point that emerged was that white American men without college degrees have remained economically depressed since the 2008 recession and subsequent recovery. Although the U.S. economy has been steadily improving, the economic reality for this particular segment of the population has not. This is what Michael Moore talked about experientially (but not statistically), claiming that he knows the people who live in the rust belt, and they are struggling. He was right, the data show that they are struggling. Highlighting the economic reality for people without college degrees in the U.S. tells a very different story than highlighting the fact that they don’t have college degrees. The former renders an image of a voting contingent who, in the face of personal economic hardship that contrasts with national economic gain, are frustrated and eager to try something — anything — new. The latter renders an image of ignorance.

Data about education levels of voters is transformed by its coupling with economic trajectories. What’s been strange, is that although this coupling was discovered, it never really penetrated the larger “what happened” narrative. This is particularly strange given the meticulous and sometimes frantic search for explanation and the media’s public introspective quests to understand how so many got it all so wrong.

The transformative effect of the economic data point and its failure to effectively transform the story underlines two related things: data are not self-evident and narrative currents are hard to change.

The data weren’t wrong — people without college degrees were more likely to vote for Trump — but they were incomplete and in their partialness, quite misleading. That’s not a data problem, it’s a people problem. Data are not silent, but they are inarticulate. Data make noise, but people have to weave that noise into a story. The weaving process begins with survey construction, and culminates in analyses and reports. Far from an objective process, turning data into narrative entails nuanced decisions about the relevance of, and relationship between, quantifiable items captured through human-created measures. The data story is thus always value-laden and teeming with explicit and implicit assumptions.

Framing a contingent of Trump supporters through the exclusive metric of education without examining the interaction, mediating, and moderating effects of economic gains, was an intellectual decision bore out through statistical analyses. That is, pollsters, strategists, and commentators treated “lack of education” as the variable with key explanatory power. Other characteristics or experiences of those with low levels of education could/should/would be irrelevant.

Such dismissal created a major problem with regard to Democratic strategy. To situate a voting bloc as “uneducated” is to dismiss that voting bloc. How does one campaign to those voting in ignorance? In contrast, to situate a voting bloc as connected through an economic plight not only validates their position, but also gives a clear policy platform on which to speak.

But okay, after the election, analysts briefly shed light on the way that economics and education operated together to predict candidate preference. Why has this gotten so little attention? Why is education — rather than economics or the economic-education combination — still the predominant story?

The predominance of education remains because narrative currents are strong. Even when tied to newly emergent data, established stories are resistant to change. Narratives are embedded with social frameworks, and changing the story entails changing the view of reality. A key tenet of sociology is that people tend towards stability. Once they understand and engage the world in a particular way, they do social and psychological gymnastics to continue understanding and engaging the world in that way. To reframe (some) Trump voters as part of an economic interest group that has been recently underserved, is an upheaval of previous logics. Moreover, disrupting existing logics in this way forces those who practice those logics to, perhaps, reframe themselves, and do so in a way that is not entirely flattering or identity affirming. To switch from a frame of ignorance to a frame of economics is to acknowledge not only that the first frame was distorted, but also, to acknowledge that getting it wrong necessarily entailed ignoring the economic inequality that progressives take pride in caring so much about. Switching from ignorance to economics entails both a change in logic and also, a threat to sense of self.

Data are rich material from which stories are formed, and they are not objective. Tracing data is a process of deconstructing the stories that make up our truths — how those stories take shape, evolve, and solidify into fact. The “truth” about Trump voters is of course complex and highly variable. The perpetually missed nuances tell as much of a story as those on which predominant narratives hang.

Jenny L. Davis, PhD, is in the department of sociology at James Madison University. She studies social psychology, experimental research methods, and new and social media. She is also a contributing author and editor at Cyborgology.  You can follow her at @Jenny_L_Davis.

Originally posted at Orgtheory.

Iowa in 2008, Iowa in 2016

So there are a thousand reasons Trump won the election, right? There’s race, there’s class, there’s gender. There’s Clinton as a candidate, and Trump as a candidate, the changing media environment, the changing economic environment, and the nature of the primary fields. It’s not either-or, it’s all of the above.

But Josh Pacewicz’s new book, Partisans and Partners: The Politics of the Post-Keynesian Society, implies a really interesting explanation for the swing voters in the Rust Belt—the folks who went Obama in 2008, and maybe 2012, but Trump in 2016. These voters may make up a relatively small fraction of the total, but they were key to this election.

Pacewicz’s book, which just came out this month, doesn’t mention Trump, and presumably went to press long before Trump was even the presumptive Republican nominee. And the dynamics Pacewicz identifies didn’t predict a specific outcome. (In fact, Josh guest-blogged at orgtheory in August, but focused on explaining party polarization, and did not venture to predict a winner.)

But Partisans and Partners nevertheless does a really good job of explaining what just happened. Its argument is complex, and doesn’t imply a lot of obvious leverage points for decreasing political polarization or the desire for “disruptive” candidates. But I think it’s an important explanation nonetheless.

The book is based on ethnographic and interview data collected over a period of several years in two Rust-Belt Iowa cities of similar size, one traditionally Republican, and the other traditionally Democratic. Both of these cities saw a transformation in their politics in the 1980s. Until the 1970s, urban politics were organized around a partisan divide closely associated with local business elites, on the Republican side, and union leaders, on the Democratic side. Politics was highly oppositional, and the party that won local elections got to distribute a lot of spoils. But it was not polarized in the sense it is today—while there were fundamental differences between the parties, particularly on economic issues, positions on social issues were less rigidly defined.

During the 1980s, something changed. Pacewicz calls that something “neoliberal reforms”; I might argue that those are just one piece of a bigger economic transformation that was happening. But either way, the political environment shifted. Regulatory changes encouraged corporate mergers and buyouts. This put control of local industry in distant cities and hollowed out both business elites and union power. The federal government shifted from simply handing cities pots of money that the party in power could control, to requiring cities to compete for funds, putting together applications that would compete with those of other cities. This environmental change facilitated the decline of the old “partisans”—the business and labor elites—and the rise of a new group of local power brokers—the “partners”.

The partners were more technocratic and pragmatic. They did not have strong party allegiances, nor did they see politics as being fundamentally about competition between the incompatible interests of business and labor. Instead, they focused on building temporary alliances among diverse groups with often-conflicting interests. Think business-labor roundtables, public-private partnerships, and the like. This is what was needed to attract industry from other places (look how smooth our labor relations are!) and to compete for federal grants and incentives (cities with obviously oppositional politics tended to lose out). The end of politics. Sounds great, right?

The problem was that these dynamics also hollowed out local parties. The old partisans had lost power. Partners didn’t want to be active in party politics. This left parties to activists, who over time came to represent increasingly extreme positions—a new wave of partisans.

What did this mean for the average voter? Pacewicz shows how older voters still conceptualized the two parties as fundamentally reflecting a business/labor divide. But most younger voters came to understand politics as representing a divide between partners—people working together, setting aside differences, for the benefit of the community—and partisans—people representing the interests of particular groups.

Partners didn’t like politics. They didn’t really think it should exist. They disliked political polarization, thought that people were pretty similar underneath their surface differences, and that conflict was generally avoidable. They distrusted politics, their party affiliation tended to be provisional, and they often responded only to negative ads around hot-button issues.

The new partisans, on the other hand, were alienated from contemporary life. They thought things were going to hell in a handbasket. They were looking for change, and saw outsider candidates as appealing—candidates who promised to shake up the system. Many had a strong preference for Democrats or Republicans. But while for traditional voters party affiliation was rooted in a sense of positive commitment, for the new partisans, it was based on disaffection with the alternative. And a key group of “partisans” was politically uncommitted (a contradiction in terms?)—disaffected and angry and wanting politics to solve their problems, but not aligned with a party.

The 2008 election illustrates how these types respond to candidates. In the primaries, partners liked Obama, responding well to his post-partisan image. He was less favored by Democrats and traditional voters and partisans. By fall, though, traditional (Democratic) voters and (Democratic) partisans tended to get on board, while partners waffled as Obama came to seem more partisan.

The most erratic group was the uncommitted partisans. These people wanted somebody—anybody—to shake things up, to change the system. And they wanted somebody to represent them—the outsider. They tended to lean toward GOP candidates (one illustrative voter was a big Palin fan), but many also simply remained disaffected and stayed home.

This is the group, it seems to me, that is key to understanding the 2016 election. Democrats gonna Democrat, and Republicans gonna Republican. In the end, most people really aren’t swing voters. But the unaffiliated partisans are the type of voters who would have found some appeal in both Bernie and Trump: someone claiming to represent the everyman, and someone willing to shake up the status quo.

In the end, these folks are unlikely to be motivated to vote for a Clinton or a Romney. It’s just more of the same. But they can be energized by populism, and by the outsider. These are the people who will vote for Trump just as a big old middle finger to the system. Partisans and Partners isn’t specifically trying to explain Trump’s win, in Iowa or anywhere else. But it does as good a job as anything I’ve read at pointing in the direction we should be looking.

Elizabeth Popp Berman, PhD is an associate professor of sociology at the University at Albany, SUNY, and the author of the award-winning book Creating the Market University: How Academic Science Became an Economic Engine. 

FBI director, James Comey, didn’t call it the “Ferguson Effect.” Instead, he called the recent rise in homicide rates a “viral video effect” – a more accurately descriptive term for the same idea: that murder rates increased because the police were withdrawing from proactive policing. The full sequence goes something like this:  Police kill unarmed Black person. Video goes viral. Groups like Black Lives Matter organize protests. Politicians fail to defend the police. Police decrease their presence in high-crime areas. More people in those areas commit murder.

Baltimore is a good example, as Peter Moskos has strongly argued on his blog Cop in the Hood. But many cities, even those with all the Ferguson elements, have not seen large increases in homicide. New York, for example, the city where I live, had all of the Ferguson-effect elements. Yet the number of murders in New York did not rise, nor did rates of other crimes. Other factors – gang conflict, drugs, and the availability of guns – make a big difference, and these vary among cities. Chicago is not New York. Las Vegas is not Houston. All homicide is local.

There is another flaw with the viral-video theory: It assumes that the crime is a game of cops and robbers (or cops and murderers), where the only important players are the bad guys and the cops. If the cops ease up, the bad guys start pulling the trigger more often. Or as Director Comey put it,

There’s a perception that police are less likely to do the marginal additional policing that suppresses crime — the getting out of your car at 2 in the morning and saying to a group of guys, “Hey, what are you doing here?”

This model of crime leaves out the other people in those high-crime neighborhoods. It sees them as spectators or bystanders or occasionally victims. But those people, the ones who are neither cops nor shooters, can play a crucial role in crime control. In some places, it is the residents of the neighborhood who can get the troublesome kids to move off the corner. But even when residents cannot exert any direct force on the bad guys, they can provide information or in other ways help the police. Or not.

This suggests a different kind of Ferguson Effect. In the standard version, the community vents its anger at the cops, the cops then withdraw, and crime goes up. But the arrows of cause and effect can point in both directions. Those viral videos of police killing unarmed Black people reduce the general level of trust. More important, those killings are often the unusually lethal tip of an iceberg of daily unpleasant interactions between police and civilians. That was certainly the case with the Ferguson police department with its massive use of traffic citations and other fines as a major source of revenue. Little wonder that a possibly justifiable shooting by a cop elicited a huge protest.

It’s not clear exactly how the Full Ferguson works. Criminologist Rich Rosenfeld speculates that where people don’t trust the police, they are more likely to settle scores themselves. That may be true, but I wonder if it accounts for increases in killings between gang members or drug dealers. They weren’t going to call the cops anyway. Nor were people who have been drinking and get into an argument, and someone has a gun.

But maybe where that trust is absent, people don’t do what most of us would do when there’s trouble we cannot handle ourselves  –  dial 911. As in Director Comey’s version, the police are less a presence in those neighborhoods but not because they are afraid of being prosecuted for being too aggressive and not because they are being petulant about what some politician said, but because people there are not calling the cops.

Originally posted at Montclair SocioBlog.

Jay Livingston is the chair of the Sociology Department at Montclair State University. You can follow him at Montclair SocioBlog or on Twitter.

One of the concerns of environmental sociologists is the way that harm is unequally distributed. The way, for example, that poor people and people of color are more likely to live with high levels of lead, near toxic release facilities, with bad air quality, and in the paths of airborne pesticides.

I thought of this research when I saw Time‘s 1-minute illustration of the rise of earthquakes in Oklahoma. To sum, thanks to the particular type of oil drilling done there, the state is now “one of the most seismic places on the planet.” There were 21 earthquakes in 2005. In 2015, there were 5,957. Nine hundred of these were magnitude 3 or higher.

Click here to watch the video.

I am trying to imagine what would happen if an industry caused almost 6,000 extra earthquakes annually (and growing) in or near a city America cared about. I’ve lived in Los Angeles and New York and, I can’t be sure but, I suspect politicians there might be quicker to interfere with business practices. And, if they weren’t, the political power of residents of those cities might force them to.

“But it’s just Oklahoma,” is apparently the refrain. Who cares if the oil companies’ saltwater disposal wells are causing the houses of hillbillies to shake? Apparently Okies don’t have anything — aren’t anybody — worth protecting. At least, not over the rights of corporations.

Lisa Wade, PhD is an Associate Professor at Tulane University. She is the author of American Hookup, a book about college sexual culture; a textbook about gender; and a forthcoming introductory text: Terrible Magnificent Sociology. You can follow her on Twitter and Instagram.