Racial and Educational Segregation in the U.S.

Originally posted at Sociological Images.

Where you grow up is consequential. It plays a critical role in shaping who you are likely to become. Where you live affects your future earnings, how much education you’re likely to receive, how long you live, and much more.

Sociologists who study this are interested in the concentrated accumulations of specific types and qualities of capital (economic, cultural, social) found in abundance in certain locations, less in more, and virtually absent in some. And, as inequalities intersect with one another, marginalization tends to pile up. For instance, those areas of the U.S. that are disproportionately Black and Latino are also areas struggling economically (see Dustin A. Cable’s racial dot map of the U.S.). Similarly, those areas of the country with the least upward mobility are also areas with some of the highest proportions of households of people of color. And, perhaps not shockingly (although it should be), schools in these areas receive fewer resources and have lower outcomes for students.

How much education you receive is, in part, a result of where you grow up. Think about it: you’re be more likely to end up with at least a bachelor’s degree if you grow up in an area where almost everyone is at least college educated. It’s not a requirement, but it’s more likely. And, if you do and go on to live in a similar community and have children, your kids will benefit from you carrying on that cycle as well. Of course, this system of advantages works in reverse for communities with lower levels of educational attainment.

Recently, a geography professor, Kyle Walker, mapped educational attainment in the U.S. Inspired by Cable’s map of racial segregation, Walker visualizes educational inequality in the U.S. from a bird’s eye view. And when we compare Walker’s map of educational attainment to Cable’s map of racial segregation, you can see how inequalities tend to accumulate.

Below, I’ve displayed paired images of a selection of U.S. cities using both maps. In each image, the top map illustrates educational attainment and the bottom visualizes race.

  • On Walker’s map of educational attainment (top images in each pair), the colors indicate: less than high schoolhigh schoolsome collegebachelor’s degree, and graduate degree.
  • On Cable’s map of racial segregation (bottom images in each pair), the colors indicate: White, Black, Hispanic, Asian, and Other Race/Native American/Multi-Racial

So, one way of comparing the images below is to look at how the blue areas compare on each map of the same region.  

Below, you can see San Francisco, Berkeley, and San Jose, California in the same frame using Walker’s map of educational attainment (top) over Cable’s racial dot map (bottom).See how people are segregated by educational attainment (top image) and race (bottom image) in Chicago, Illinois:
Los Angeles, California:
New York City:
Detroit, Michigan:
Houston, Texas:
Compare regions of the U.S. examining Walker’s map with Cable’s racial dot map, you can see how racial and educational inequality intersect. While I only visualized cities above for comparison on both maps, if you examine Walker’s map of educational attainment, two broad trends with respect to segregation by educational attainment are easily visible:

  • Urban/rural divide–people with bachelors and graduate degrees tend to be clustered in cities and metropolitan areas.
  • Racial and economic inequalities–within metropolitan areas, you can see educational achievement segregation that both reflects and reinforces racial and economic segregation within the area (this is what you see above).

And, as research has shown, the levels of parents’ educational attainment within an area impacts the educational performances of the children living in that area as well. That’s how social reproduction happens. Sociologists are interested in how inequalities are passed on to subsequent generations. And it is sometimes hard to notice in your daily life because, as you can see above, we’re segregated from one another (by race, education, class, and more). And this segregation is one way interlocking inequalities persist.

Masculinity and Fidelity in Pop Music

Originally posted at the Gender & Society blog.

Two songs that seemed like they were on the radio every time I tuned into a pop station last summer were Omi’s single, “Cheerleader” (originally released in 2015) and Andy Grammar’s song, “Honey, I’m good” (originally released in 2014). They’re both songs written for mass consumption. Between 2014 and 2015, “Cheerleader” topped the charts in over 20 countries around the world. And, while “Honey, I’m Good” had less mass appeal, it similarly found its way onto top hit lists around the world.

They’re different genres of music. But they both fall under the increasingly meaningless category of “pop.”  And, because they both gained popularity around the same time, it was possible to hear them back to back on radio stations across the U.S.  Both songs are about the same issue: each are ballads sung by men celebrating themselves for being faithful in their heterosexual relationships.  Below is Omi’s “Cheerleader.” Here is the chorus:

“All these other girls are tempting / But I’m empty when you’re gone / And they say / Do you need me? / Do you think I’m pretty? / Do I make you feel like cheating? / And I’m like no, not really cause / Oh I think that I found myself a cheerleader / She is always right there when I need her / Oh I think that I found myself a cheerleader / She is always right there when I need her”

In Omi’s song, he situates himself as uninterested in cheating because he’s found a woman who believes in him more than he does. And this, he suggests, is worth his fidelity. Though, he does admit to being tempted, which also works to situate him as laudable because he “has options.”

Andy Grammar’s song is a different genre. And like Omi’s song, it’s catchy (though, apparently less catchy if pop charts are a good measure). Grammar’s video is dramatically different as well. It’s full of couples lip syncing his song while claiming amounts of time they’ve been faithful to one another. Again, and for comparison, below is the chorus:

“Nah nah, honey I’m good / I could have another but I probably should not / I’ve got somebody at home, and if I stay I might not leave alone / No, honey I’m good, I could have another but I probably should not / I’ve gotta bid you adieu and to another I will stay true”

Unlike Omi’s song, Grammar’s single is a song about a man at a bar without his significant other. He’s turning down drinks from a woman (or women), claiming that he doesn’t trust himself to be faithful if he gives into the drink. Instead, he opts to leave the bar to ensure he doesn’t give in to this temptation.

Both songs are written in the same spirit. They’re songs that appear to be about women, but are actually anthems about what amazing men these guys are because… well, because they don’t cheat, but could.

I was struck by the common message, a message at least partially to blame for why we all heard them so much. And the message is that, for men in heterosexual relationships, resisting the temptation to be unfaithful is hard work. And this message helps to highlight key ingredients of contemporary hegemonic masculinities: heterosexuality and promiscuity. Both men are identifying as heterosexual throughout each song. But, you might think, they’re not identifying as promiscuous. So, how are they supporting this cultural ideal if they appear to be challenging it? The answer to that is all in the delivery.

Amy C. Wilkins studied the ways that a group of college Christian men navigated what she terms the “masculinity dilemma” of demonstrating themselves to be heterosexual and heterosexually active when they were in a group committed to abstinence. Wilkins discovered that they navigated this dilemma by enacting what she refers to as “collective processes of temptation” whereby they crafted a discourse about just how masculine they were by resisting the temptation to be heterosexually active. They ritualistically discussed the problem of heterosexual temptation. And, in so doing, Wilkins argues that the men she studied, “perform their heterosexuality collectively, aligning themselves with conventional assumptions about masculinity through the ritual invocation of temptation” (here: 353). It’s hard to craft an identity based on not doing something. But if you’re going to, Wilkins argues that temptation is key.

Similarly, Sarah Diefendorf found that young evangelical Christian men navigate their gender identities alongside pledges of sexual abstinence until marriage. Men in Diefendorf’s study used one another as “accountability partners” to make sure they didn’t cheat on their pledges if they were in relationships, but even with things like pornography or masturbation. As Diefendorf writes, “These confessions… enable these men to demonstrate a connection with hegemonic masculinity through claims of desire for future heterosexual practices” (here: 658-659). In C.J. Pascoe’s study of high school boys navigating tenuous gender and sexual identities, she refers to this process more generally as “compulsive heterosexuality.”

Both songs are meant to situate the two singers as great men, men to be admired. But, being able to listen to this message and “get it” means that you can take for granted the premise on which the songs are based—in this case, that men are hard-wired to be sexual scoundrels and that heterosexual women should count themselves lucky if they are fortunate enough to have landed a man committed to not living up to his wiring. Without understanding men as having a natural and apparently insatiable sexual wanderlust, these songs don’t make sense.

Both Omi and Grammar need the discourse of temptation to frame themselves as noble. If we want to challenge men to not cheat, we should be challenge the idea that they’re working against biologically deterministic inclinations to do so. I’m not sure it would make a top 20 hit, but neither would it recuperate forms of gendered inequality through the guise of dismantling them.

________________

*Thanks to Sarah Diefendorf for her edits and smart feedback on this post.

Visualizing Gender Inequality in a Feminist Bookstore

Originally posted at Sociological Images.

It’s International Women’s Day–a day to celebrate the social, cultural, economic, and political achievements of women. It’s a day we often take stock of gender inequality, look at how far we’ve come and where we still need to go. This is a day people in my corner of the world share posts about the gender wage gap, statistics surrounding the enduring reality of violence against women, information about women’s access to health care, and more. It’s a day that sociologists have the tools to make lots of charts.

In my feed, sociologist Jane Ward shared a post about a feminist bookstore in Cleveland, Ohio that chose to celebrate Women’s History Month in a unique way: they flipped all of the books written by men in the fiction room of the store around on the shelf. The room will be left that way for for two weeks – through March 14, 2017. Take a look at the result!

The Fiction Room – Loganberry Books, Cleveland Ohio

It’s a powerful piece of feminist installation art. And it’s sociological. While a sociologist might have produced a content analysis of the room (or genre) and produced a proportion of books written by women, this feels different. They’ve entitled the exhibit “Illustrating the Fiction Gender Gap” and explain the project with this simple sentence: “We’ve silenced male authors, leaving works of women in view.”

They could have simply counted the books and produced figures made available to the public. That’s what most sociologists I know would have done. But something critical would have been missing when compared with the illustration of the gender gap they produced here. Think about it this way: in 2015, the Census calculated that the poverty rate was 13.5% in the U.S. (that was a drop from the year prior). In actual numbers, there were 43.1 million people in poverty in the U.S. that year. Just to think about the size of that group, that’s a number that is basically the same as the total combined state populations of New York, Florida, and Iowa. Can you imagine everyone in all three states being in poverty. That’s the scale of poverty as a social problem in the U.S.

In a similar way, Loganberry Books, produced a really clever piece of feminist installation art to make a reality about literature more visible. It’s different from telling us the proportion of books written by women in the fiction section. In Loganberry, we get to see what that means. If you went in, you could feel it as you looked around. Works by women who be jumping off the shelves, rather than hidden between piles of books by men.

The owner of the bookstore, Harriet Logan, put it this way: “Pictures are loud communicators.  So we are in essence not just highlighting the disparity but bringing more focus to the women’s books now, because they’re the only ones legible on the shelf” (here). In an interview with Cleveland Scene, she further explained: “To give the floor and attention to women, you need to be able to hear them. And if someone else is talking over them, that just doesn’t happen.”

It’s a small way of asking the question, What would this corner of the world look like if women’s accomplishments had not been systematically, structurally, and historically drowned out by men’s?  What does women’s signal sound like here when we get rid of men’s noise? Books by men are still there. They’re not being banned, removed, or even mentioned as “unworthy” in any way. Men’s books are simply being silenced for two weeks to let women’s work shine. What a powerful, feminist, sociologically imaginative statement.

Happy International Women’s Day!

Political Polarization in the U.S. and Social Inequalities

Originally posted at Sociological Images.

Democrats and Republicans are deeply divided. By definition, political parties have differences of opinion. But these divisions have widened. Twenty years ago, your opinions on political issues did not line up the way we have come to expect them. Today, when you find you share an opinion with someone about systemic racism, you’re more likely to have like minds about environmental policies, welfare reform, and how they feel about the poor, gay and lesbian people, immigrants and immigration, and much more. In other words, Democrats and Republicans have become more ideologically consistent in recent history.

A recent Pew Report reported that in 1994, 64% of Republicans were more conservative than the median Democrat on a political values scale. By 2014, 92% of Republicans were more conservative than the median Democrat. Democrats have become more consistently liberal in their political values and Republicans have become more consistently conservative. And this has led to increasing political polarization (see HERE and HERE for smart posts on this process by Lisa Wade and Gwen Sharpe). You can see political polarization happening below.

You might think ideological commitments naturally come in groupings. But there are lots of illogical pairings without natural connections. Why, for instance, should how you feel about school vouchers be related to how you feel about global warming, whether police officers use excessive force against Black Americans, or whether displays of military strength are the best method of ensuring peace?  The four issues are completely separate. But, if your Facebook feed looks anything like mine, knowing someone’s opinion about any one of these issues gives you enough information to feel reasonably confident predicting their opinions about the other three. That’s what ideological consistency looks like.

Consider how this process affects understandings of important systems of social inequality that structure American society. Discrimination is an issue that sociologists have studied in great detail. We know that discrimination exists and plays a fundamental role in the reproduction of all manner of social inequalities. But, people have opinions about various forms of discrimination as well—even if they’re unsupported by research or data. And while you might guess that many Americans’ opinions about one form of discrimination will be predictive of their opinions about other forms, there’s not necessarily a logical reason for that to be true. But it is.

The following chart visualizes the proportions of Americans who say there is “a lot of discrimination” against Black people, gay and lesbian people, immigrants, transgender people, as well as the proportions of Americans who oppose laws requiring transgender people to use bathrooms that correspond to their sex at birth. And you can see how Americans identifying as Democrat and Republican compare.

The majority of Americans understand that social inequalities exist and that discrimination against socially marginalized groups is still a serious problem. By that, I mean that more than half of Americans believe these things to be true. And data support their beliefs. But look at the differences between Democrats’ and Republicans’ opinions about important forms of discrimination in U.S. society. The gap is huge. While just less than 1 in 3 Republicans feels that there is a lot of discrimination against Black people in the U.S., almost 8 in 10 Democrats support that statement. That’s what political polarization looks like. And Pew found that the trend is even more exaggerated among voters.

Republicans and Democrats are not just divided about whether and what to do about forms of social inequality. They’re divided about whether these inequalities exist. And that is an enormous problem.

Why People Are So Averse to Facts

Originally posted at Sociological Images.

Facts about all manner of things have made headlines recently as the Trump administration continues to make statements, reports, and policies at odds with things we know to be true. Whether it’s about the size of his inauguration crowd, patently false and fear-mongering inaccuracies about transgender persons in bathrooms, rates of violent crime in the U.S., or anything else, lately it feels like the facts don’t seem to matter. The inaccuracies and misinformation continue despite the earnest attempts of so many to correct each falsehood after it is made.  It’s exhausting. But why is it happening?

Many of the inaccuracies seem like they ought to be easy enough to challenge as data simply don’t support the statements made. Consider the following charts documenting the violent crime rate and property crime rate in the U.S. over the last quarter century (measured by the Bureau of Justice Statistics). The overall trends are unmistakable: crime in the U.S. has been declining for a quarter of a century.

Now compare the crime rate with public perceptions of the crime rate collected by Gallup (below). While the crime rate is going down, the majority of the American public seems to think that crime has been getting worse every year. If crime is going down, why do so many people seem to feel that there is more crime today than there was a year ago?  It’s simply not true.

There is more than one reason this is happening. But, one reason I think the alternative facts industry has been so effective has to do with a concept social scientists call the “backfire effect.” As a rule, misinformed people do not change their minds once they have been presented with facts that challenge their beliefs. But, beyond simply not changing their minds when they should, research shows that they are likely to become more attached to their mistaken beliefs. The factual information “backfires.” When people don’t agree with you, research suggests that bringing in facts to support your case might actually make them believe you less.  In other words, fighting the ill-informed with facts is like fighting a grease fire with water.  It seems like it should work, but it’s actually going to make things worse.

To study this, Brendan Nyhan and Jason Reifler (2010) conducted a series of experiments. They had groups of participants read newspaper articles that included statements from politicians that supported some widespread piece of misinformation. Some of the participants read articles that included corrective information that immediately followed the inaccurate statement from the political figure, while others did not read articles containing corrective information at all.

Afterward, they were asked a series of questions about the article and their personal opinions about the issue. Nyhan and Reifler found that how people responded to the factual corrections in the articles they read varied systematically by how ideologically committed they already were to the beliefs that such facts supported. Among those who believed the popular misinformation in the first place, more information and actual facts challenging those beliefs did not cause a change of opinion—in fact, it often had the effect of strengthening those ideologically grounded beliefs.

It’s a sociological issue we ought to care about a great deal right now. How are we to correct misinformation if the very act of informing some people causes them to redouble their dedication to believing things that are not true?

Possibly the most exhaustive study of “manspreading” ever conducted

Originally published at Sociological Images.

“Manspreading” is a relatively new term.  According to Google Trends (below), the concept wasn’t really used before the end of 2014.  But the idea it’s describing is not new at all.  The notion that men occupy more space than women is one small piece of what Raewyn Connell refers to as the patriarchal dividend–the collection of accumulated advantages men collectively receive in androcentric patriarchal societies (e.g., wages, respect, authority, safety).  Our bodies are differently disciplined to the systems of inequality in our societies depending upon our status within social hierarchies.  And one seemingly small form of privilege from which many men benefit is the idea that men require (and are allowed) more space.

captureIt’s not uncommon to see advertisements on all manner of public transportation today condemning the practice of occupying “too much” space while other around you “keep to themselves.”  PSA’s like these are aimed at a very specific offender: some guy who’s sitting in a seat with his legs spread wide enough in a kind of V-shaped slump such that he is effectively occupying the seats around him as well.

I recently discovered what has got to be one of the most exhaustive treatments of the practice ever produced.  It’s not the work of a sociologist; it’s the work of a German feminist photographer, Marianne Wex.  In Wex’s treatment of the topic, Let’s Take Back Our Space: Female and Male Body Language as a Result of Patriarchal Structures (1984, translated from the German edition, published in 1979), she examines just shy of 5,000 photographs of men and women exhibiting body language that results from and plays a role in reproducing unequal gender relations.

The collection is organized by an laudable number of features of the various bodily positions.  Interestingly, it was published in precisely the same year that Erving Goffman undertook a similar sociological study of what he referred to as “gender display” in his book, Gender Advertisements–though Goffman’s analysis utilized advertisements as the data under consideration.

Like Goffman, Wex examined the various details that made up bodily postures that seem to exude gender, addressing the ways our bodies are disciplined by society.  Wex paired images according to the position of feet and legs, whether the body was situated to put weight on one or two legs, hand and arm positions, and much much more.  And through this project, Wex also developed an astonishing vocabulary for body positions that she situates as the embodied manifestations of patriarchal social structures.  The whole book organizes this incredible collection of (primarily) photographs she took between 1972 and 1977 by theme.  On every page, men are depicted  above women (as the above image illustrates)–a fact Wex saw as symbolizing the patriarchal structure of the society she sought to catalog so scrupulously.  She even went so far as to examine bodily depiction throughout history as depicted in art to address the ways the patterns she discovered can be understood over time.

If you’re interested, you can watch the Youtube video of the entire book.

Just How Big Was the 2017 Women’s March?

By: Tristan Bridges and Tara Leigh Tober

Originally posted at Sociological Images.

The 2017 Women’s March was a historic event. Social media alone gave many of us the notion that something happened on an incredibly grand scale. But measuring just how “grand” is an inexact science. Women’s Marches were held around the world in protest of Trump on the day following his inauguration. Subsequently, lots of folks have tried to find good ways of counting the crowds. Photos and videos of the crowds at some of the largest marches are truly awe-inspiring. And the media have gotten stirred up attempting to quantify just how big this march really was.

Think about it. The image below is taken of some of the crowds in Los Angeles. The caption Getty Images associates with the image includes the estimate “Hundreds of thousands of protesters…” But, was it 200,000? Or was it more like 900,000? Do you think you could eyeball it and make an educated guess? We’d bet you’d be off by more than you think. Previous research has found, for instance, that march participants and organizers are not always the best source of information for how large a protest was. If you’re there and you’re asked how many people were there, you’re much more likely to exaggerate the number of people who were actually there with you. And that fact has spawned wildly variable estimates for marches around the U.S. and beyond.


More than one set of estimates exist attempting to figure this out. The estimates that have garnered the most media attention (deservedly) are those produced by Jeremy Pressman and Erica Chenoweth. They collected as many estimates as they could for marches all around the world to try to figure out just how large the protest was on a global scale. Pressman & Chenoweth collected a range of estimates, and in their data set they classify them by source as well as providing the lowest and highest estimates for each of the marches for which they were able to collect data. You can see and interact with those estimates visually below in a map produced by Eric Compas (though some updates were made in the data set after Compas produced the map).

By Pressman & Chenoweth’s estimates, the total number of marchers in the U.S. was between 3,266,829 and 5,246,321 participants. When they include marches outside the U.S. as well they found that we can add between 266,532 and 357,071 marchers to that number to understand the scale of the protest on an international scale. That is truly extraordinary. But, the range is still gigantic. The difference between their lowest and highest estimate is around 2.1 million people! Might it be possible to figure out which of these estimates are better estimates of crowd size than others?

Nate Silver at FiveThirtyEight.com tried to figure this out in an interesting way. They only attempted to answer this question for U.S. marches alone. And Silver and a collection of his statistical team produced their own data set of U.S. marches. They collected as many crowd estimates as they could for all of the marches held in the U.S. And there are lots of holes in their data that Pressman and Chenoweth filled. March organizers collect information about crowd size and are eager to claim every individual who can be claimed to have been present. But, local officials estimate crowd sizes as well because it helps to give them a sense of what they will need to prepare for and respond to such crowds. As a part of this, some marches had estimates from march organizers, news sources, official estimates, as well as estimates from non-partisan experts (so-called crowd scientists)–this is especially true of the larger marches. Examining their data, they discovered that for every march in which they had both organizer and official estimates, the organizers’ estimate was 50-70% higher than the officials’ estimates. As Silver wrote: “Or put another way, the estimates produced by organizers probably exaggerated crowd sizes by 40 percent to 100 percent, depending on the city” (here). The estimates Silver produced at FiveThirtyEight are mapped below.

You can interact with the map to see Nate Silver’s team estimate, but also the various estimates on which that estimate is based. And you may note that the low and high estimates are often the same for Silver and for Pressman & Chenoweth (though not always). Additionally, there were a good number of marches in FiveThirtyEight’s data set that lacked any estimates at all. And those marches are not visible on the map above. Just to consider some of what is missing, you might note that there are no marches on the map immediately above in Puerto Rico, though Silver’s data set includes four marches there–all with no estimates.

Interestingly, Silver took a further step of offering a “best guess” based on patterned differences between types of estimates they found for marches for which they had more than a single source of data (more than one estimate). For instance, where there were only organizers’ estimates, they discounted that estimate by 40%, assuming that it was exaggerated. They discounted news estimates by 20% for similar reasons. Sometimes, non-partisan experts relying on photographs and videos provide estimates were available, which were not discounted (similar to official estimates).

It might be possible then, as Pressman & Chenoweth collected many more estimates, to fine-tune Silver’s formula and possibly come up with an even more accurate estimate of crowd sizes at marches around the world based on the source of the estimate. It’s a fascinating puzzle and a really interesting and simple way of considering how to resolve it with a (likely) conservative measure.

By these (likely conservative) estimates, marches in the U.S. alone drew more than 3,000,000 people across hundreds of separate locations across the nation. In the U.S. alone, FiveThirtyEight estimated that 3,234,343 people participated (though, as we said, some marches simply lacked any source of data in the data set they produced). And that number, you might note, is strikingly close to Pressman & Chenoweth’s low estimate for the U.S. (3,266,829). Even by this conservative estimate, this would qualify the 2017 Women’s March as certainly among the largest mass protests in U.S. history. It may very well have been the largest mass protest in American history. And in our book, that’s worth counting.