Gender gaps are everywhere.  When we use the term, most people immediately think of gender wage gaps.  But, because we perceive gender as a kind of omni-salient feature of identity, gender gaps are measured everywhere.  Gender gaps refer to discrepancies between men and women in status, opportunities, attitudes, demonstrated abilities, and more. A great deal of research focuses on gender gaps because they are understood to be the products of social, not biological, engineering.  Gender gaps are so pervasive that, each year, the World Economic Forum produces a report on the topic: “The Global Gender Gap Report.”

I first thought about this idea after reading some work by Virginia Rutter on this issue (here and here) and discussing them with her.  When you look for them, gender gaps seem to be almost everywhere.  As gender equality became something understood as having to do with just about every element of the human experience, we’ve been chipping away at all sorts of forms of gender inequality.  And yet, as Virginia Rutter points out, we have yet to see gender convergence on all manner of measures.  Indeed, progress on many measures has slowed, halted, or taken steps in the opposite direction, prompting some to label the gender revolution “stalled.”   And in many cases, the “stall” starts right around 1980.  For instance, Paula England showed that though the percentage of women employed in the U.S. has grown significantly since the 1960s, that progress starts to slow in the 1980s.  Similarly, in the 1970s a great deal of progress was made in desegregating fields of study in college.  But, by the early 1980s, about all the change that has been made had been made already.  Changes in the men’s and women’s median wages have shown an incredibly persistent gender gap.

A set of gender gaps often used to discuss inherent differences between men and women are gaps in athletic performance – particularly in events in which we can achieve some kind of objective measure of athleticism.  In Lisa Wade and Myra Marx Ferree’s Gender: Ideas, Interactions, Institutions, they use the marathon as an example of how much society can engineer and exaggerate gender gaps.  They chart world record times for women and men in the marathon over a century.  I reproduced their chart below using IAAF data (below).


In 1963, an American woman, Merry Lepper, ran a world recording breaking marathon at 3 hours, 37 minutes, and 7 seconds.  That same year, the world record was broken among men at 2 hours, 14 minutes, and 28 seconds.  His time was more than 80 minutes faster than hers!  The gender gap in marathon records was enormous.  A gap still exists today, but the story told by the graph is one of convergence.  And yet, I keep thinking about Virginia Rutter’s focus on the gap itself. I ran the numbers on world record progressions for a whole collection of track and field races for women and men.  Wade and Ferree’s use of the marathon is probably the best example because the convergence is so stark.  But, the stall in progress for every race I charted was the same: incredible progress is made right through about 1980 and then progress stalls and a stubborn gap remains.

Just for fun, I thought about considering other sports to see if gender gaps converged in similar ways. Below is the world record progression for men and women in a distance swimming event – the 1500-meter swim.


The story for the gender gap in the 1500-meter swim is a bit different.  The gender gap was smaller to begin with and was primarily closed in the 1950s and early 60s.  Both men and women continued to clock world record swims between the mid-1950s and 1980 and then progress toward faster times stalled out for both men and women at around that time.

One way to read these two charts is to suggest that technological innovations and improvements in the science of sports training meant that we came closer to achieving, possibly, the pinnacle of human abilities through the 1980s.  At some point, you might imagine, we simply bumped up against what is biologically possible for the human body to accomplish.  The remaining gap between women and men, you might suggest, is natural.  Here’s where I get stuck… What if all these gaps are related to one another?  There’s no biological reason that women’s entry into the labor force should have stalled at basically the same time as progress toward gender integration in college majors, all while women’s incredible gender convergence in all manner of athletic pursuits seemed to suddenly lose steam.  If all of these things are connected, it’s for social, not biological reasons.

Tristan Bridges, PhD is a professor at The College at Brockport, SUNY. He is the co-editor of Exploring Masculinities: Identity, Inequality, Inequality, and Change with C.J. Pascoe and studies gender and sexual identity and inequality. You can follow him on Twitter here. Tristan also blogs regularly at Inequality by (Interior) Design.

Originally posted at Made in America.

Explaining how such an unfit candidate and such a bizarre candidacy succeeded has become a critical concern for journalists and scholars. Through sites like Monkey Cage, Vox, and 538, as well as academic papers, we can watch political scientists in real time try to answer the question, “What the Hell Happened?” (There are already at least two catalogs of answers, here and here, and a couple of college-level Trump syllabi.) Although a substantial answer will not emerge for years, this post is my own morning-after answer to the “WTHH?” question.

I make three arguments: First, Trump’s electoral college victory was a fluke, a small accident with vast implications, but from a social science perspective not very interesting. Second, the deeper task is to understand who were the distinctive supporters for Trump, in particular to sort out whether their support was rooted mostly in economic or in cultural grievances; the evidence suggests cultural. Third, party polarization converted Trump’s small and unusual personal base of support into 46 percent of the popular vote.

Explaining November 8, 2016

Why did Donald Trump, an historically flawed candidate even to many of those who voted for him, win? With a small margin in three states (about 100,000 votes strategically located), many explanations are all true:

* Statistical fluke: Trump won 2.1 percentage points less of the popular vote than did Clinton, easily the largest negative margin of an incoming president in 140 years. (Bush was only 0.5 points behind Gore in 2000.) Given those numbers, Trump’s electoral college win was like getting two or three snake-eye dice rolls in a row. Similarly, political scientists’ structural models–which assume “generic” Democratic and Republican candidates and predict outcomes based on party incumbency and economic indicators–forecast a close Republican victory. “In 2012, the ‘fundamentals’ predicted a close election and the Democrats won narrowly,” wrote Larry Bartels. “In 2016, the ‘fundamentals’ predicted a close election and the Republicans won narrowly. That’s how coin tosses go.” But, of course, Donald Trump is far from a generic Republican. That’s what energizes the search for a special explanation.

* FBI Director Comey’s email announcement in the closing days of the election appeared to sway the undecided enough to easily make the 100,000 vote difference.

* Russian hacks plus Wikileaks.

* The Clinton campaign. Had she visited the Rust Belt more, embraced Black Lives Matter less (or more), or used a slogan that pointed to economics instead of diversity… who knows? Pundits have been mud-wrestling over whether her campaign was too much about identity politics or whether all politics is identity politics. Anyway, surely some tweak here would have made a difference.

* Facebook and Fakenews.

* The weather. It was seasonably mild with only light rain in the upper Midwest on November 8. Storms or snow would probably have depressed rural turnout enough to make Clinton president.

* The Founding Fathers. They meant the electoral college to quiet vox populi (and so it worked in John Q. Adams’s minus 10 point defeat of Andrew Jackson in 1824).

* Add almost anything you can imagine that could have moved less than one percent of the PA/MI/WI votes or of the national vote.

* Oh, and could Bernie would have won? Nah, no way, no how. [1]

Small causes can have enormous consequences: the precise flight of a bullet on November 22, 1963; missed intelligence notes about the suspicious student pilots before the 9/11 attacks; and so on. Donald Trump’s victory could become extremely consequential, second only to Lincoln’s in 1860, argues journalist James Fallows, [2] but the margin that created the victory was very small, effectively an accident. From an historical and social science point of view, there is nothing much interesting in Trump’s electoral college margin.

Trump’s Legions

More interesting is Trump’s energizing and mobilizing so many previously passive voters, notably during the primaries. What was that about?

One popular answer is that Trump’s base is composed of people, particularly members of the white working class (WWC), who are suffering economic dislocation. Because their suffering has not been addressed, they rallied to a jobs champion.

Another answer is that Trump’s core is composed of people, largely but not only WWC, with strong cultural resentments. While often suffering economically and voicing economic complaints, they are mainly distinguished by holding a connected set of racial, gender, anti-immigrant, and class resentments–resentments against those who presumably undermined America’s past “greatness,” resentments which tend to go together with tendencies toward authoritarianism (see this earlier post).

The empirical evidence so far best supports the second account. Indicators of cultural resentment better account for Trump support than do indicators of economic hardship or economic anxiety. [3]

In-depth, in-person reports have appeared that flesh out these resentments in ways that survey questions only roughly capture. They describe feelings of being pushed out of the way by those who are undeserving, by those who are not really Americans; feelings of being neglected and condescended to by over-educated coastal elites; feelings of seeing the America they nostalgically remember falling away. [4]

trump-supportersDefenders of the economic explanation would point to the economic strains and grievances of the WWC. Those difficulties and complaints are true–but they are not new. Less-educated workers have been left behind for decades now; the flat-lining of their incomes started in the 1970s, with a bit of a break in the late 1990s. Moreover, the economy has been in an upswing in the last few years; the unemployment rate was about 8 percent when Obama was re-elected in 2012, but about half of that when Trump was elected. Economic conditions do not explain 2016.

Nor are complaints about economic insecurity new. For example, the percentage of WWC respondents to the General Social Survey who said that they were dissatisfied with their financial situations has varied around 25 percent (+/- 5 points) over the last 30 years. The percentage dissatisfied did hit a high in the early years of the Great Recession (34 percent in 2010), but it dropped afterwards (to 31% in 2012 when Obama was re-elected and 29% in 2014). Economic discontent has been trending down, not up. [5] That only one-fifth of Trump voters supported raising the minimum wage to $15 further undercuts the primacy of economic motives.

To be sure, journalists can find and record the angry voices of economic distress; they do so virtually every election year. (Remember the painful stories about the foreclosure crisis and about lay-offs during the Great Recession?). There was little distinctive about either the economic distress or the economic anxiety of 2016 to explain Trump.

Some have noted, however, what appear to be a significant number of voters who supported Obama in 2008 or in 2012 and seemed to have switched to Trump in 2016 (e.g., here). Do these data not undermine a cultural, specifically a racial, explanation for Trump? No. In 2008, Obama received an unusual number of WWC votes because of the financial collapse, the Iraq fiasco, and Bush’s consequent unpopularity. These immediate factors overrode race for many in the WWC. But WWC votes for Obama dropped in 2012 despite his being the incumbent. Then, last November, the WWC vote for a Democratic candidate reverted back to its pre-Great Recession levels. [6] Put another way, Clinton’s support from the WWC was not especially low, Obama’s was unusually high for temporary reasons.

What was special about 2016 was the candidate: Donald Trump explicitly and loudly voiced the cultural resentments and authoritarian impulses of many in the WWC (and some in the middle class, too) that had been there for years but had had no full-throated champion–not Romney, not McCain, not the Bushes, probably not even Reagan–since perhaps Richard Nixon. What changed was not the terrain for a politics of resentment but the arrival of an unusual tiller of that soil, someone who brought out just enough of these voters to win his party’s nomination and to boost turnout in particular places for the general election. As one analyst wrote, “Trump repeatedly went where prior Republican presidential candidates were unwilling to go: making explicit appeals to racial resentment, religious intolerance, and white identity.”

But this is still less than half the story.

Party Polarization

To really how understand how Trump could get 46 percent of the vote, it takes more than identifying the distinctive sorts of people whom Trump attracted, because they are not that numerous. Trump won only a minority of the primary votes and faced intense opposition within his party. In the end, however, almost all Republicans came home to him–even evangelicals, to whose moral standards Trump is a living insult. The polarization of American politics in recent years was critical. Party ended up mattering more to college-educated, women, and suburban Republicans than whatever distaste they had for Trump the man.

Consider how historically new this development is. In 1964, the Republican nominee, Barry Goldwater, was considered to be at the far right end of the political spectrum. About 20 to 25% of Republicans crossed over and voted for Democrat Lyndon Johnson. (This crossover was mirrored by Democrats in the 1972 election. [7]) In 2016, by contrast, fewer than 10% of Republicans abandoned Trump–a far more problematic candidate than Goldwater–so much has America become polarized by party in the last couple of decades. [8]


Readings of the 2016 election as the product of a profound shift in American society or politics are overblown. In particular, notions that the WWC’s fortunes or views shifted so substantially in recent years as to account for Trump seem wrong.

What about the argument that the Trump phenomenon is part of a general rise across the western world of xenophobia? I don’t see much evidence outside of the Trump case itself for that in the United States. Long-term data suggest a decline–too slowly, for sure–rather than an increase in such attitudes.[9] And let’s not forget: Hillary Clinton won the popular vote.

The best explanation of why Trump got 46% of the ballots: Advantages for the out party in a third-term election + Trump’s unusual cultural appeal to a minority but still notable number of Americans + historically high party polarization. That Trump actually won the electoral college as well is pretty much an accident, albeit a hugely consequential one.



[1] Basically no one, including Trump, said anything bad about Bernie Sanders from the moment it became clear that Sanders would lose the primaries to Clinton. Had he been nominated, that silence would have ended fast and furiously. Moreover as the always astute Kevin Drum pointed out, Sanders is much too far to left to get elected, even way to the left of George McGovern, who got creamed in 1972. Finally, the “Bernie Brothers” who avoided Clinton would have been more than outnumbered by Hillary’s pissed-off sisters if she had been once again displaced by a man.

[2] On the other hand, economist-blogger Tyler Cowen is skeptical: If the doomsayers are right, why aren’t investors dumping equities, shorting the market, or fleeing to safer commodities?

[3] See these sources: 1, 2, 3, 4, 5, 6.

[4] For examples: 1, 2, 34.

[5] My analysis of the GSS through 2014. White working class is defined as whites who have not graduated college.

[6] Again, I used the GSS. In 2000 and 2004, the Democratic candidates, Gore and Kerry, got about 35 percent of the WWC vote, about what Bill Clinton got in his first run in 1992. Obama got substantially more, 48%, in 2008, then somewhat less, 42%, in 2012. Hillary Clinton got, according to a very different sort of survey, the exit polls, 29% of the WWC, but it is hard to compare the two methods. Note that the GSS reports of who people voted for in the previous election tend to skew toward the winners, but the point still stands that Obama’s jump in support from the WWC, especially in 2008, was quite unusual, not Hillary Clinton’s apparent slump in support.

[7] According to Gallup’s last poll before the 1964 election, 20% of Republicans were going to vote for Johnson. According to my analysis of the American National Election Survey, which is retrospective, 26% actually did. In 1972, the Democrats nominated the most left-leaning candidate of postwar era. According to Gallup data, 33% of Democrats crossed over to vote for Nixon. ANES data suggest that about 40 percent did. Whatever the specifics, there was much more cross-over voting 40 to 50 years ago, even under milder provocation.

[8] On the decline of ticket-splitting, see here.

[9] For example, one of the longest-running items in the GSS is the question, “I’d like you to tell me whether you think we’re spending too much money … too little money, or about the right amount … improving the conditions of Blacks.” In the 1970s, 28% of whites said too much; in the 2000s, 19% did. Another question was asked only through 2002: “Do you agree or disagree… (Negroes/blacks/African-Americans) shouldn’t push themselves where they’re not wanted?” In the 1970s, 74% of whites agreed; from 1990 to 2002, 15% did. More striking, in the 1970s, 11% of whites “strongly disagreed”; from 1990 to 2002, 32% did. On immigrants: David Weakliem has graphed responses to a recurrent Gallup Poll question, “Should immigration be kept at its present level, increased or decreased?”. From 1965 to the mid-1990s, the trend was strongly toward “decreased,” but since then the trend has strongly been toward “increased” (although that’s still a minority view).

Claude S. Fischer, PhD is a sociologist at UC Berkeley and is the author of Made in America: A Social History of American Culture and Character. This post originally appeared at his blog, Made in America.

The 2020 Summer Olympics will be held in Japan.  And when the prime minister of Japan, Shinzo Abe, made this public at the 2016 Olympics in Rio de Janeiro, Brazil, he did so in an interesting way.   He was standing atop a giant “warp pipe” dressed as Super Mario.  I’m trying to imagine the U.S. equivalent.  Can you imagine the president of the United States standing atop the golden arches, dressed as Ronald McDonald, telling the world that we’d be hosting some international event?

Prime minister Abe was able to do this because Mario is a cultural icon recognized around the world.  That Italian-American plumber from Brooklyn created in Japan is truly a global citizen. The Economist recently published an essay on how Mario became known around the world.

Mario is a great example of a process sociologists call cultural globalization.  This is a more general social process whereby ideas, meanings, and values are shared on a global level in a way that intensifies social relations.  And Japan’s prime minister knew this.  Shinzo Abe didn’t dress as Mario to simply sell more Nintendo games.  I’m sure it didn’t hurt sales.  In fact, in the past decade alone, Super Mario may account for up to one third of the software sales by Nintendo.  More than 500 million copies of games in which Mario is featured circulate worldwide.  But, Japan selected Mario because he’s an illustration of technological and artistic innovations for which the Japanese economy is internationally known.  And beyond this, Mario is also an identity known around the world because of his simple association with the same human sentiment—joy.  He intensifies our connections to one another.  You can imagine people at the ceremony in Rio de Janeiro laughing along with audience members from different countries who might not speak the same language, but were able to point, smile, and share a moment together during the prime minister’s performance.  A short, pudgy, mustached, working-class, Italian-American character is a small representation of that shared sentiment and pursuit.  This intensification of human connection, however, comes at a cost.

We may be more connected through Mario, but that connection takes place within a global capitalist economy.  In fact, Wisecrack produced a great short animation using Mario to explain Marxism and the inequalities Marx saw as inherent within capitalist economies.  Cultural globalization has more sinister sides as well, as it also has to do with global cultural hegemony.  Local culture is increasingly swallowed up.  We may very well be more internationally connected.  But the objects and ideas that get disseminated are not disseminated on an equal playing field.  And while the smiles we all share when we connect with Mario and his antics are similar, the political and economic benefits associated with those shared smirks are not equally distributed around the world.  Indeed, the character of Mario is partially so well-known because he happened to be created in a nation with a dominant capitalist economy.  Add to that that the character himself hails from another globally dominant nation–the U.S.  The culture in which he emerged made his a story we’d all be much more likely to hear.

Tristan Bridges, PhD is a professor at The College at Brockport, SUNY. He is the co-editor of Exploring Masculinities: Identity, Inequality, Inequality, and Change with C.J. Pascoe and studies gender and sexual identity and inequality. You can follow him on Twitter here. Tristan also blogs regularly at Inequality by (Interior) Design.

Counting the number of lesbian, gay, bisexual, and transgender people is harder than you might think.  I’ve written before on just how important it is to consider, for instance, precisely how we ask questions about sexuality.  One way scholars have gotten around this is to analytically separate the distinct dimensions of sexuality to consider which dimension they are asking about.  For research on sexuality, this is typically done by considering sexual identities as analytically distinct from sexual desires and sexual behaviors.  We like to imagine that sexual identities, acts, and desires all neatly match up, but the truth of the matter is… they don’t.  At least not for everyone.  And while you might think that gender might lend itself to be more easily assessed on surveys, recent research shows that traditional measures of sex and gender erase our ability to see key ways that gender varies in our society.

Gallup just released a new publication authored by Gary J. Gates.  Gates has written extensively on gender and sexual demography and is responsible for many of the population estimates we have for gender and sexual minorities in the U.S.  This recent publication just examines shifts in the past 5 years (between 2012 and 2016).  And many of them may appear to be small.  But changes like this at the level of a population in a population larger than 300,000,000 people are big shifts, involving huge numbers of actual people.  In this post, I’ve graphed a couple of the findings from the report–mostly because I like to chart changes to visually illustrate findings like this to students.  [*Small note: be aware of the truncated y axes on the graphs.  They’re sometimes used to exaggerate findings.  I’m here truncating the y axes to help illustrate each of the shifts discussed below.]


The report focuses only on one specific measure of membership as LGBT–identity.  And this is significant as past work has shown that this is, considered alongside other measures, perhaps the most conservative measure we have.  Yet, even by that measure, the LGBT population is on the move, increasing in numbers at a rapid pace in a relatively short period of time.  As you can see above, between 2012 and 2016, LGBT identifying persons went from 3.5%-4.1% of the U.S. population, which amounts to an estimated shift from 8.3 million people in 2012 to more than 10 million in 2016.


The report also shows that a great deal of that increase can be accounted for by one particular birth cohort–Millennials.  Perhaps not surprisingly, generations have become progressively more likely to identify as LGBT.  But the gap between Millenials and the rest is big and appears to be growing.  But the shifts are not only about cohort effects.  The report also shows that this demographic shift is gendered, racialized, and has more than a little to do with religion as well.

The gender gap between proportion of the population identifying as LGBT in the U.S. is growing.  The proportion of women identifying as LGBT has jumped almost a full percentage point over this period of time.  And while more men (and a larger share of men) are identifying as LGBT than were in 2012, the rate of increase appears to be much slower.  As Gates notes, “These changes mean that the portion of women among LGBT-identified adults rose slightly from 52% to 55%” (here).


The gap between different racial groups identifying as LGBT has also shifted with non-Hispanic Whites still among the smallest proportion of those identifying.  As you can see, the shift has been most pronounced among Asian and Hispanic adults in the U.S.  Because White is the largest racial demographic group here, in actual numbers, they still comprise the largest portion of the LGBT community when broken down by race.  But, the transitions over these 5 years are a big deal.  In 2012, 2 of every 3 LGBT adults in the U.S. identified as non-Hispanic White.  By 2016, that proportion dropped to 6 out of every 10. This is big news.  LGBT people (as measured by self-identification) are becoming a more racially diverse group.

They are also diverse in terms of class.  Considering shifts in the proportion of LGBT identifying individuals by income and education tells an interesting story.  As income increases, the proportion of LGBT people decreases.  And you can see that finding by education in 2012 as well–those with less education are more likely to be among those identifying as LGBT (roughly).  But, by 2016, the distinctions between education groups in terms of identifying as LGBT have largely disappeared.  The biggest rise has been among those with a college degree.  That’s big news and could mean that, in future years, the income gap here may decrease as well.

There were also findings in the report to do with religion and religiosity among LGBT identifying people in the U.S.  But I didn’t find those as interesting.  Almost all of the increases in people identifying as LGBT in recent years have been among those who identify as “not religious.”  While those with moderate and high levels of religious commitment haven’t seen any changes in the last five years.  But, among the non-religious, the proportion identifying as LGBT has jumped almost 2 percentage points (from 5.3% in 2012 to 7.0% in 2016).

All of this is big news because it’s a powerful collection of data that illustrate that the gender and sexual demographics of the U.S. are, quite literally, on the move.  We should stand up and pay attention.  And, as Gates notes in the report, “These demographic traits are of interest to a wide range of constituencies.”  Incredible change in an incredibly short period of time.  Let the gender and sexual revolution continue!

Edit (1/17/17): The graph charting shifts by age cohort may exaggerate (or undersell) shifts among Millennials because the data does not exclude Millennials born after 1994.  So, some of those included in the later years here wouldn’t have been included in the earlier years because they weren’t yet 18.  So, it’s more difficult to tell how much of that shift is actually people changing identity for the age cohort as a whole as opposed to change among the youngest Millennials surveyed.

Tristan Bridges, PhD is a professor at The College at Brockport, SUNY. He is the co-editor of Exploring Masculinities: Identity, Inequality, Inequality, and Change with C.J. Pascoe and studies gender and sexual identity and inequality. You can follow him on Twitter here. Tristan also blogs regularly at Inequality by (Interior) Design.

Originally posted at Reports from the Economic Front.

Defenders of capitalism in the United States often choose not to use that term when naming our system, preferring instead the phrase “market system.”  Market system sounds so much better, evoking notions of fair and mutually beneficial trades, equality, and so on.  The use of that term draws attention away from the actual workings of our system.

In brief, capitalism is a system structured by the private ownership of productive assets and driven by the actions of those who seek to maximize the private profits of the owners.  Such an understanding immediately raises questions about how some people and not others come to own productive wealth and the broader social consequences of their pursuit of profit.

Those are important questions because it is increasingly apparent that while capitalism continues to produce substantial benefits for the largest asset owners, those benefits have increasingly been secured through the promotion of policies – globalization, financialization, privatization of state services, tax cuts, attacks on social programs and unions – that have both lowered overall growth and left large numbers of people barely holding the line, if not actually worse off.

The following two figures come from a Washington Post article by Jared Bernstein in which he summarizes the work of Thomas Piketty, Emmanuel Saez and Gabriel Zucman. The first set of bars shows the significant decline in US pre-tax income growth.  In the first period (1946-1980), pre-tax income grew by 95 percent.  In the second (1980-2014), it grew by only 61 percent.


This figure also shows that this slower pre-tax income growth has not been a problem for those at the top of the income distribution.  Those at the top more than compensated for the decline by capturing a far greater share of income growth than in the past.  In fact, those in the bottom 50 percent of the population gained almost nothing over the period 1980 to 2014.

The next figure helps us see that the growth in inequality has been far more damaging to the well-being of the bottom half than the slowdown in overall income growth.  As Bernstein explains:

The bottom [blue] line in the next figure shows actual pretax income for adults in the bottom half of the income scale. The top [red] line asks how these folks would have done if their income had grown at the average rate from the earlier, faster-growth period. The middle [green] line asks how they would have done if they experienced the slower, average growth of the post-1980 period.

The difference between the top two lines is the price these bottom-half adults paid because of slower growth. The larger gap between the middle and bottom line shows the price they paid from doing much worse than average, i.e., inequality… That explains about two-thirds of the difference in endpoints. Slower growth hurt these families’ income gains, but inequality hurt them more.


A New York Times analysis of pre-tax income distribution over the period 1974 to 2014 reinforces this conclusion about the importance of inequality.  As we can see in the figure below, the top 1 percent and bottom 50 percent have basically changed places in terms of their relative shares of national income.


The steady ratcheting down in majority well-being is perhaps best captured by studies designed to estimate the probability of children making more money than their parents, an outcome that was the expectation for many decades and that underpinned the notion of “the American dream.”

Such research is quite challenging, as David Leonhardt explains in a New York Times article, “because it requires tracking individual families over time rather than (as most economic statistics do) taking one-time snapshots of the country.”  However, thanks to newly accessible tax records that go back decades, economists have been able to estimate this probability and how it has changed over time.

Leonhardt summarizes the work of one of the most important recent studies, that done by economists associated with the Equality of Opportunity Project. In summary terms, those economists found that a child born into the average American household in 1940 had a 92 percent chance of making more than their parents.  This falls to 79 percent for a child born in 1950, 62 percent for a child born in 1960, 61 percent for a child born in 1970, and only 50 percent for a child born in 1980.

The figure below provides a more detailed look at the declining fortunes of most Americans.   The horizontal access shows the income percentile a child is born into and the vertical access shows the probability of that child earning more than their parents.   The drop-off for children born in 1960 and 1970 compared to the earlier decade is significant and is likely the result of the beginning effects of the changes in capitalist economic dynamics that started gathering force in the late 1970s, for example globalization, privatization, tax cuts, union busting, etc.  The further drop-off for children born in 1980 speaks to the strengthening and consolidation of those dynamics.


The income trends highlighted in the figures above are clear and significant, and they point to the conclusion that unless we radically transform our capitalist system, which will require building a movement capable of challenging and overcoming the power of those who own and direct our economic processes, working people in the United States face the likelihood of an ever-worsening future.

Martin Hart-Landsberg, PhD is a professor emeritus of economics at Lewis and Clark College. You can follow him at Reports from the Economic Front.

If there’s one thing Americans can agree upon, it might be that people shouldn’t be indiscriminately firing guns crowds, no matter how angry they are. The shooting in the Ft. Lauderdale airport is just the latest example. Mass shootings are on the rise and I’m fearful that what we are seeing isn’t just an increase in violence, but the rise of a new habit, a behavior that is widely recognized as a way to express an objection to the way things are.

To register an objection to something about the world, a person or group needs to engage in an action that other people recognize as a form of protest. We know, in other words, what protest looks like. It’s a strike, a rally, a march, a sit-in, a boycott. These are all recognizable ways in which individuals and groups can stake a political claim, whereas other group activities — a picnic, a group bike ride, singing together — are not obviously so. To describe this set of protest-related tools, the sociologist Charles Tilly coined the phrase “repertoire of contention.” Activists have a stock of actions to draw from when they want to make a statement that others will understand.

A culture’s repertoire of contention is in constant evolution. Each tool has to be invented and conceptually linked to the idea of protest before it can play this role. The sit-in, for example, was invented during the early civil rights movement. When African American activists and their allies occupied white-only restaurants, bringing lunch counters to a halt to bring attention to the exclusion of black people, they introduced a new way of registering an objection to the status quo, one that almost anyone would recognize today.

New ways of protesting are being invented every day: the hashtag, the hacktivist, and shutting down freeways are some newer ones. Some become part of the repertoire. Consider the image below by sociologist Michael Biggs, which shows how suicide as a form of protest “caught on”  in the 1960s:


I am afraid that mass murder has become part of the repertoire of contention. This is theoretically tricky – others have fought over what really counts as a social movement action – but it does seem quite clear that mass murder with a gun is a more familiar and more easily conceptualized way of expressing one’s discontent and then it was, say, pre-Columbine. If a person is outraged by some state of affairs, mass killing is a readily available way to express that outrage both technically (thanks to gun regulation) and cognitively (because it is now part of the recognized repertoire).

Dylann Roof wanted to register his discontent with the place of black people in American society, Robert Lewis Dear stormed a Planned Parenthood with a pro-choice message, Elliot Rodgers was angry about women’s freedom to reject him, Omar Matteen killed dozens to express his (internalized) disgust for homosexuality, Gavin Long communicated his sense of rage and helplessness in the face of black death by killing police. At some point each thought, “What can I do to make a difference?” And mass murder came to mind.

In the aftermath of such events, the news media routine contributes to the idea that mass murder is a form of protest by searching for an explanation above and beyond the desire to kill. That explanation often positions the rationale for the murder within the realm of politics, whether we call it terrorism, resistance, or prejudice. This further sends the message that mass murder is political, part of the American repertoire of contention.

The terrifying part is that once protest tools become part of the repertoire, they are diffused across movements and throughout society. It’s no longer just civil rights activists who use the sit-in; any and all activists do. Perhaps that’s why we see such a range of motivations among these mass murderers. It has become an obvious way to express an objection that the discontented can be sure others will understand.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.

Originally posted at Work in Progress.

Why do people sometimes resist remediation of pollution in their own backyards? Conventional academic wisdom suggests that it is because they are afraid of losing their jobs, but my recent research in La Oroya, Peru, questions this dominant framework.

Photo by Pamela Neumann.

Since 1922, La Oroya has been home to three refineries for processing lead, copper, and zinc, and a lead smelter owned until recently by a company called Doe Run Peru. In the late ’90s, several scientific studies demonstrated dangerously high lead levels among the town’s children.

The findings drew extensive attention from the media, but not the kind that some residents appreciated. Tania, a local schoolteacher told me, “In the media there are these ideas that we are nothing but a bunch of slow, sick, contaminated people, but they don’t pay any attention to how some students are very high performing.” Elena, a 45-year old shop owner, agreed, saying: “Of course there are sick children everywhere, slow children, just like in your country [referring to the United States]. But we have children who are doing well, we have professionals, professors.”

School teachers and principals took pride in the achievements of their students, which they felt were ignored in the rush to paint La Oroya as nothing more than a town full of “mongolicos” (a local term for people who have Down’s syndrome or are disabled). In seeking to defend their town’s identity against a barrage of negative media coverage, some residents denied that the contamination was a problem at all. “Look at all the awards we’ve won,” one principal told me, pointing to a row of trophies on the wall. “We couldn’t have done this if the contamination was really a problem.”

In response to the media portrayals, many residents became reluctant to protest against the pervasive lead contamination because doing so affirmed negative stories about their town’s identity. Residents weren’t protective of their jobs, they were protective of their town and of their own reputation as “normal” and “good,” not a place full of “mongolicos.”

These findings suggest that heavy-handed exposes of polluted cities and towns might do harm as well as good. Environmental activists might be better served to find a balance between condemning pollution and uplifting the places and people who are its victims.

Pamela Neumann, PhD is a Post-Doctoral Fellow at the Stone Center for Latin American Studies at Tulane University. A longer version of this post can be found at Work in Progress.

Late last year Covergirl announced a new spokesmodel, a 17-year-old named James Charles. Their Instagram announcement currently boasts over 53,000 likes, though the comments on the post were decidedly mixed. They ranged from “I will never buy another (coverGIRL) because of this” to  “love love love” and “the world is coming to equality and acceptingness.”

In my circles, the overwhelming response was enthusiasm. Charles’ ascendance to Covergirl status was evidence that gender flexibility was going mainstream. And, I suppose it is.

I am always suspicious, though, of corporate motives. Covergirl’s decision to feature Charles does serve to break down the gender binary, but it does other things, too. Most notably, if makeup companies could convince boys and men that their product is as essential for them as it is for girls and women, it would literally double the size of their market.

That this hasn’t happened yet, in fact, is evidence of the triumph of gender ideology over capitalism. Either companies have decided that there’s (almost) no market in men or men have resisted what marketing has been applied. It’s an impressive resistance to what seems like an obvious expansion. There’s just no money in men thinking their faces look just fine as they are; the fact that we’ve allowed them to do so thus far is actually pretty surprising when you think about it.

If Covergirl had its way, though, I have no doubt that it would make every 17-year-old boy in America into a James Charles. Such a change would contribute to breaking down the gender binary, at least as we know it (though no doubt there are more and less feminist ways of doing this). Of course, if it was advantageous to do so, Covergirl would claim that it had something to do with feminism. But, I wouldn’t buy it.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.