public opinion

We seem to have been struggling with science for the past few…well…decades. The CDC just updated what we know about COVID-19 in the air, misinformation about trendy “wellness products” abounds, and then there’s the whole climate crisis.

This is an interesting pattern because many public science advocates put a lot of work into convincing us that knowing more science is the route to a more fulfilling life. Icons like Carl Sagan and Neil deGrasse Tyson, as well as modern secular movements, talk about the sense of profound wonder that comes along with learning about the world. Even GI Joe PSAs told us that knowing was half the battle.

The problem is that we can be too quick to think that knowing more will automatically make us better at addressing social problems. That claim is based on two assumptions: one, that learning things feels good and motivates us to action, and two, that knowing more about a topic makes people more likely to appreciate and respect that topic. Both can be true, but they are not always true.

The first is a little hasty. Sure, learning can feel good, but research on teaching and learning shows that it doesn’t always feel good, and I think we often risk losing students’ interest because they assume that if a topic is a struggle, they are not meant to be studying it.

The second is often wrong, because having more information does not always empower us to make better choices. Research shows us that knowing more about a topic can fuel all kinds of other biases, and partisan identification is increasingly linked with with attitudes toward science.

To see this in action, I took a look at some survey data collected by the Pew Research Center in 2014. The survey had seven questions checking attitudes about science – like whether people kept up with science or felt positively about it – and six questions checking basic knowledge about things like lasers and red blood cells. I totaled up these items into separate scales so that each person has a score for how much they knew and how positively or negatively they thought about science in general. These scales are standardized, so people with average scores are closer to zero. Plotting out these scores shows us a really interesting null finding documented by other research – there isn’t a strong relationship between knowing more and feeling better about science.

The purple lines mark average scores in each scale, and the relationship between science knowledge and science attitudes is fairly flat.

Here, both people who are a full standard deviation above the mean and multiple standard deviations below the mean on their knowledge score still hold pretty average attitudes about science. We might expect an upward sloping line, where more knowledge associates with more positive attitudes, but we don’t see that. Instead, attitudes about science, whether positive or negative, get more diffuse among people who get fewer answers correct. The higher the knowledge, the more tightly attitudes cluster around average.

This is an important point that bears repeating for people who want to change public policy or national debate on any science-based issue. It is helpful to inform people about these serious issues, but shifting their attitudes is not simply a matter of adding more information. To really change minds, we have to do the work to put that information into conversation with other meaning systems, emotions, and moral assumptions.

Evan Stewart is an assistant professor of sociology at University of Massachusetts Boston. You can follow him on Twitter.

One important lesson from political science and sociology is that public opinion often holds steady. This is because it is difficult to get individual people to change their minds. Instead, people tend to keep consistent views as “settled dispositions” over time, and mass opinion changes slowly as new people age into taking surveys and older people age out.

Sometimes public opinion does change quickly, though, and these rapid changes are worth our attention precisely because they are rare. For example, one of the most notable recent changes is the swing toward majority support for same-sex marriage in the United States in just the last decade.

That’s why a new finding is so interesting and so troubling: NORC is reporting a pretty big swing in self-reported happiness since the pandemic broke out using a new 2020 survey conducted in late May. Compared to earlier trends from the General Social Survey, fewer people are reporting they are “very happy,” optimism about the future is down, and feelings of isolation and loneliness are up. The Associated Press has dynamic charts here, and I made an open-access, creative commons version of one visualization using GSS data and NORC’s estimates:

As with any survey trend, we will need more data to get the true shape of the change and see whether it will persist over time. Despite this, one important point here is the consistency before the new 2020 data. Think about all the times aggregated happiness reports didn’t really change: we don’t see major shifts around September 11th, 2001, and there are only small changes around the Gulf War in 1990 or the 2008 financial crisis.

There is something reassuring about such a dramatic drop now, given this past resilience. If you’re feeling bad, you’re not alone. We have to remember that emotions are social. People have a remarkable ability to persist through all kinds of trying times, but that is often because they can connect with others for support. The unprecedented isolation of physical distancing and quarantine has a unique impact on our social relationships and, in turn, it could have a dramatic impact on our collective wellbeing. The first step to fixing this problem is facing it honestly.

Inspired by demographic facts you should know cold, “What’s Trending?” is a post series at Sociological Images featuring quick looks at what’s up, what’s down, and what sociologists have to say about it.

Evan Stewart is an assistant professor of sociology at University of Massachusetts Boston. You can follow him on Twitter.

Based on analyses of General Social Survey data, a well-designed and respected source of data about American life, members of the Millennial generation are acquiring about the same number of sexual partners as the Baby Boomers. This data suggests that the big generational leap was between the Boomers and the generation before them, not the Boomers and everyone that came after. And rising behavioral permissiveness definitely didn’t start with the Millennials. Sexually speaking, Millennials look a lot like their parents at the same age and are perhaps even less sexually active then Generation X.

Is it true?

It doesn’t seem like it should be true. In terms of attitudes, American society is much more sexually permissive than it was for Boomers, and Millennials are especially more permissive. Boomers had to personally take America through the sexual revolution at a time when sexual permissiveness was still radical, while Generation X had to contend with a previously unknown fatal sexually transmitted pandemic. In comparison, the Millennials have it so easy. Why aren’t they having sex with more people?

A new study using data from the National Survey of Family Growth (NSFG) (hat tip Paula England) contrasts with previous studies and reports an increase. It finds that nine out of ten Millennial women had non-marital sex by the time they were 25 years old, compared to eight out of ten Baby Boomers. And, among those, Millennials reported two additional total sexual partners (6.5 vs. 4.6).

Nonmarital Sex by Age 25, Paul Hemez

Are Millennials acquiring more sexual partners after all?

I’m not sure. The NSFG report used “early” Millennials (only ones born between 1981 and 1990). In a not-yet-released book, the psychologist Jean Twenge uses another survey — the Youth Risk Behavior Surveillance System — to argue that the next generation (born between 1995 and 2002), which she calls the “iGen,” are even less likely to be sexually active than Millennial. According to her analysis, 37% of 9th graders in 1995 (born in 1981, arguably the first Millennial year) had lost their virginity, compared to 34% in 2005, and 24% in 2015.

Percentage of high school students who have ever had sex, by grade. Youth Risk Behavior Surveillance System, 1991-2015.

iGen, Jean Twenge

If Twenge is right, then we’re seeing a decline in the rate of sexual initiation and possibly partner acquisition that starts somewhere near the transition between Gen X and Millennial, proceeds apace throughout the Millennial years, and is continuing — Twenge argues accelerating — among the iGens. So, if the new NSFG report finds an increase in sexual partners between the Millennials and the Boomers, it might be because they sampled on “early” Millennials, those closer to Gen Xers, on the top side of the decline.

Honestly, I don’t know. It’s interesting though. And it’s curious why the big changes in sexually permissive attitudes haven’t translated into equally sexually permissive behaviors. Or, have actually accompanied a decrease in sexual behavior. It depends a lot on how you chop up the data, too. Generations, after all, all artificial categories. And variables like “nonmarital sex by age 25” are specific and may get us different findings than other measures. Sociological questions have lots of moving parts and it looks as if we’re still figuring this one out.Lisa Wade, PhD is a Visiting Scholar at Tulane University. She is the author of American Hookup, a book about college sexual culture; a textbook about gender; and a forthcoming Introduction to Sociology text. You can follow her on Twitter, Facebook, and Instagram.

“Fake news” has emerged as a substantial problem for democracy. The circulation of false narratives, lies, and conspiracy theories on self-described “alternative news” sites undercuts the knowledge voters rely on to make political decisions. Sometimes the spread of this misinformation is deliberate, spread by hate groups, foreign governments, or individuals bent on harming the US.

A new study offers information as to the content, connectedness, and use of these websites. Information scholar Kate Starbird performed a network analysis of twitter users responding to mass shootings. These users denied the mainstream narrative about the shooting (arguing, for example, that the real story was being hidden from the public or that the shooting never happened at all). Since most of the fake news sites cross-promote conspiracy theories across the board, focusing on this one type of story was sufficient for mapping the networks. Here is some of what she found:

  • The sites do not share a political point of view. They are dominated by the far right, but they also include the far left, hate groups, nationalists, and Russian propaganda sites. They did strongly overlap in being anti-globalist, anti-science, and anti-mainstream media.

  • Fake news sites are highly repetitive, spreading the same conspiracies and lies, often re-posting identical content on multiple sites.
  • Users, then, aren’t necessarily being careless or undisciplined in their information gathering. They often tweet overlapping content from several different fake news sites, suggesting that they are obeying a hallmark of media literacy: seeking out multiple sources. You can see the dense network created by this use of multiple data sources in the upper left.

  • One of the main conspiracy stories promulgated by fake news sites is that the real news is fake.
  • Believing this, Twitter users who share links to fake news sites often also share links to traditional news outlets (see the connections in the network to the Washington Post, for example), but they do so primarily as evidence that their false belief was true. When the New York Times reports the mainstream story about the mass shooting, for instance, it is argued to be proof of a cover up. This is consistent with the backfire effect: exposure to facts tends to strengthen belief in misinformation rather than undermine it.

In an interview with the Seattle Times, Starbird expresses distress at her findings. “I used to be a techno-utopian,” she explained, but she is now deeply worried about the “menace of unreality.” Emerging research suggests that believing in one conspiracy theory is a risk factor for believing in another. Individuals drawn to these sites out of a concern with the safety of vaccines, for example, may come out with a belief in a Clinton-backed pedophilia ring, a global order controlled by Jews, and an aversion to the only cure for misinformation: truth. “There really is an information war for your mind,” Starbird concluded. “And we’re losing it.”Lisa Wade, PhD is a Visiting Scholar at Tulane University. She is the author of American Hookup, a book about college sexual culture; a textbook about gender; and a forthcoming Introduction to Sociology text. You can follow her on Twitter, Facebook, and Instagram.

Originally posted at Scatterplot.

There are few things more satisfying than finding another reason that millennials are the worst. They’re narcissistic, coddled, unpatriotic, racist, and nervous about free speech. And now, millennial men want a return to the nostalgic 1950s, with women in the kitchen, whipping up a nice quiche after a hard day on the line.

This is the story presented in Stephanie Coontz’s Friday piece in the New York Times, “Do Millennial Men Want Stay-at-Home Wives,”which reports on evidence from the Council on Contemporary Families (using the General Social Survey) and from sociologists Joanna Pepin and David Cotter (using Monitoring the Future ).

Journalists have gone a bit nuts for this millennial-as-Ward-Cleaver narrative, consistent with what we already know about garbage millennials, and stories from Quartz and Time Magazine have already popped up.

The Times piece includes this damning trend among men ages 18-25:

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See? Millennial men are the WORST.

 

But the GSS just released their 2016 data this week. 89% of men disagree or strongly disagree with the statement “It is much better for everyone involved if the man is the achiever outside the home and the women takes care of the home and family” – the highest rate among either men or women ages 18-25 in the GSS’s 40-year history. It’s also much higher than the rate reported by everyone older than 25, about 71%.

So is the story, “Clinton defeat inspires millennial men to gender equality”? Or more likely, “Garbage millennial men can’t make up their mind about women”?

I suspect it’s another, less sexy story: you can’t say a lot about millennials based on talking to 66 men.

The GSS surveys are pretty small – about 2,000-3,000 per wave – so once you split by sample, and then split by age, and then exclude the older millennials (age 26-34) who don’t show any negative trend in gender equality, you’re left with cells of about 60-100 men ages 18-25 per wave. Standard errors on any given year are 6-8 percent.

So let’s throw some statistics at it. Suppose you want to know whether there is a downward trend in young male disagreement with the women-in-the-kitchen statement. Using all available GSS data, there is a positive, not statistically significant trend in men’s attitudes (more disagreement). Starting in 1988 only, there is very, very small negative, not statistically significant effect.

Only if we pick 1994 as a starting point, as Coontz does, ignoring the dip just a few years prior, do we see a negative less-than half-percentage point drop in disagreement per year, significant at the 10-percent level.

As Columbia statistician Andrew Gelman wisely warns, none of these results account for the many, many paths the researchers could have taken to arrive at these results, which can make overreliance on any of these p-values problematic. For example, if we just looked at millennials the way they’re usually defined, as individuals ages 18-34?

The Pepin and Cotter piece, in fact, presents two additional figures in direct contrast with the garbage millennial theory – in Monitoring the Future, millennial men’s support for women in the public sphere has plateaued, not fallen; and attitudes about women working have continued to improve, not worsen. Their conclusion is, therefore, that they find some evidence of a move away from gender equality – a nuance that’s since been lost in the discussion of their work.

So what does this mean? Standard errors matter, and millennials might not always be as garbage as we think they are.

Emily Beam is Assistant Professor of Economics at the University of Vermont. She studies labor and development economics, with a particular focus on employment and education policy, migration, fertility and marriage, and the role of incomplete information and behavioral biases on individual decision-making.

Are some Trump supporters’ political views motivated by race?

One way to find out is to see whether the typical Trump supporter is less likely to support policies when they are subtly influenced to think that they are helping black versus white people. This was the root of a study by political scientists Christopher Federico, Matthew Luttig, and Howard Lavine.

Prior to the election, they asked 746 white respondents to complete an internet survey. Each person was randomly assigned to see one of two pictures at the beginning of the survey: a white man standing next to a foreclosure sign or the exact same photograph featuring a black man. Respondents were also asked whether they supported Trump. (Non-white people were left out of the analysis because there were too few Trump supporters among them to run meaningful comparative statistics.)

The first graph shows that white Trump supporters were eight percentage points more likely to oppose mortgage relief if they had seen a “black cue” (the picture featuring a black man) than a “white cue.” The opposite was true for white Trump opponents.

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When asked if they were “somewhat angry” about the assistance, the same pattern held:

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And likewise when asked if the beneficiaries of mortgage assistance were at least “somewhat to blame” for their situation:

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Findings held when the researchers controlled for possible confounding variables.

These findings aren’t particularly surprising. Others have also found that priming respondents to think of black people tends to make them tougher on crime and advocate for less generous social programs, like in this study on attitudes toward CA’s three-strikes law. What’s new here is the difference between Trump supporters and opponents. For opponents of Trump, priming made them more sympathetic toward mortgage holders; for supporters, priming made them less. This speaks to a real divide among Americans. Some of us feel real hostility toward African Americans. Others definitely do not.Lisa Wade, PhD is a Visiting Scholar at Tulane University. She is the author of American Hookup, a book about college sexual culture; a textbook about gender; and a forthcoming Introduction to Sociology text. You can follow her on Twitter, Facebook, and Instagram.

Originally posted at Orgtheory.

6Iowa 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. 

In a recent poll of registered voters by Pew Research Center, 30% of women, 26% of people of Hispanic descent, and 2% of black people say they’re planning to vote for Donald Trump. In fact, polls consistently find that women and racial minorities favor Hillary Clinton. So, what do we make of the statistics-defying members of those groups who support Trump?

Flickr photo by Johnny Silvercloud; creative commons license.
Flickr photo by Johnny Silvercloud; creative commons license.

For many, this fact is source of cognitive dissonance, that uncomfortable feeling of knowingly holding irreconcilable beliefs. How could women, racial minorities, and especially minorities who are women, support a man who so persistently insults and attacks them? The discomfort of dissonance has led some to look for answers, with a few coming to the conclusion that supporting Trump is equivalent to betrayal — an identity-voiding decision (“You’re not true Mexican“) — and that women and racial minorities who support Trump are “hypocritical” and “ought to be ashamed.”

This sense of cognitive dissonance though, the idea that it’s “strange” for women or racial minorities to support Trump, is based on identity politics. Such politics has its strengths, but it also risks reducing complex social beings into one-dimensional labels, with the assumption that the label is the most important thing about them.  In this case, critics of women and racial minorities for Trump find their support of him to be more incomprehensible than that of others, based on identity alone. Thus, the individual blurs into a monolithic group, where each person is expected to be politically identical to the whole, thereby setting up the case for Trump support to be framed as a betrayal.

In fact, people are complex. They carry many intersecting identities at once, sometimes ones with conflicting politics attached, as well as a suite of other personal characteristics and structural situations. People make political choices that seem to contradict some of their identities not because they’re hypocrites, but because most people are themselves a whole host of contradictions. Reality is never so clear cut and finite as a singular label, nor are humans so easily generalized.

Given these realities, the poll numbers with which I began this post makes some sense. Trump has insulted and degraded women and minorities, and he has made policy promises that threaten them, too. Based on these facts, it should be no surprise that he is losing large swaths of those groups to Clinton. But given the complexity of identity, it should also be no surprise that he isn’t losing all of them. People are complicated, and politics is as well.

Paige Miller is a graduate student at the University of New Orleans working on her MA in Sociology. Her research interests include social psychology, new media, gender, and inequalities. You can find her on Twitter and Instagram.