Tag Archives: media

This word ‘generation,’ I do not think it means what you think it means

The people who make up these things drive me bananas.

NPR launched a new series on “millennials” yesterday, called “New Boom,” with this dramatic declaration: “There are more millennials in America right now than baby boomers — more than 80 million of us.”

The definition NPR gives for this generation is “people born between 1980 and 2000.” And it’s true there are more than 80 million of them. In fact, there are 91 million of them, according to the 2012 American Community Survey data you can get from IPUMS.org.* That’s OK, though, because there are only 76 million Baby Boomers, so the claim checks out.

But what’s a generation?

The Baby Boom was a demographic event. In 1946, after the end of World War II, the crude birth rate — the number of births per 1,000 population — jumped from 20.4 to 24.1, the biggest one-year change recorded in U.S. history. The birth rate didn’t fall back to its previous level until 1965. That’s why the Baby Boom went down in history as 1946 to 1964. Because that’s when it happened.

This figure shows the number of living people by birth year, and the crude birth rate recorded in each year, using the NPR definition of millennials (in red), compared with the baby boom (purple):

mellenials.xlsx

Even with population growth I reckon the people born in the years 1946-1964 might outnumber the self-promoting millennials if not for the weight of mortality pulling down the purple bars. But if the young NPR reporters want to brag about outnumbering a generation that is starting to lose its older members to old age (and who are, after all, their parents), then I guess the shoe fits.

The Baby Boom was not a generation. It was a cohort, “a group of people sharing a common demographic experience” (in this case birth during the same period). That demographic event happens to have lasted 18 years, which is unfortunate because that may have contributed to the tendency to declare “generations” of similar lengths.

The Pew Research people, who do lots of interesting work on social change that uses generational concepts, use these slightly different definitions for four generations: Silent Generation, born 1928-1945; the Baby Boom Generation, born 1946-1964; Generation X, born 1965-1980; Millennial Generation, born 1981 and later (Pew says “no chronological endpoint has been set for this group,” which is awkward because if they’re really still going, the oldest are 33 and they have children that are the same generation as themselves**). Ironic, isn’t it, that Pew constructs “Generation X” as the shortest of the four (some generation, a mere 16 years!) before declaring them “America’s neglected ‘middle child.’

Real generations rarely have starting and ending points on a population level. Populations usually just keeping having births every year in smooth patterns of increase or decrease without discrete edges, so generations overlap. Even in families it gets hard to nail down generations once you start moving horizontally; siblings born many years apart are in the same generation, but the cousins get all confused.

Meaningful cohorts, on the other hand, can be defined all over the place, such as: the people who graduated college during the Great Recession, people who introduced the Internet to their parents, and so on. These are not generations.

In 2010, when crisis was really in the air, I was on the NPR show The State of Things in North Carolina, discussing the Baby Boom (no audio online). After attempting to clarify the difference between a generation and a cohort, I offered this dramatic example of a cohort — people born in 1960 specifically:

So if you were born in 1960, graduated college in 1982, and entered the labor force in the middle of an awful recession, then managed to pull some kind of career together, got married and divorced, by the 90s it was time to be downsized already for the first time, you’re 40 in 2000, and it’s time for the dot-com bubble, you’re out of your job again, and here you are ready for your retirement, finally, you’ve been left in your own 401(k), having to put together your own pension, and of course now that’s in the tank and your house isn’t worth anything. So that insecurity and instability is really imprinted this group. We talk about the 60s, and civil rights and antiwar, and great music and everything, but that’s seeming like a long time ago now for people who are looking at retirement.

I don’t know if anyone actually had that experience, but it seems likely.

Anyway, if people really want to keep using these generation labels, and it seems unlikely to stop now given the marketing payoff from naming rights, than that’s the way it goes. But please don’t ask demographers to define them.

Notes

* This is a little different from the population estimates the Census Bureau produces, which are coded by age rather than year of birth. I use the ACS data because they report year of birth, and because it’s easier. The differences are very small.

** Thanks to Mo Willow for pointing this out.

19 Comments

Filed under In the news

The number one cause of traffic fatalities

Please don’t text while driving.

Note: I have updated this post to reflect a response I received from Matt Richtel.

A data illustration follows the rant.

I don’t yet have a copy of Matt Richtel’s new book, A Deadly Wandering: A Tale of Tragedy and Redemption in the Age of Attention. Based on his Pulitzer-prize winning reporting for the New York Times, however, I’m afraid it’s unlikely to do justice to the complexity of the relationship between mobile phones and motor vehicle accidents. Worse, I fear it distracts attention from the most important cause of traffic fatalities: driving.

A bad sign

The other day Richtel tweeted a link to this old news article that claims texting causes more fatal accidents for teens than alcohol. The article says some researcher estimates “more than 3,000 annual teen deaths from texting,” but there is no reference to a study or any source for the data used to make the estimate. As I previously noted, that’s not plausible.

In fact, only 2,823 teens teens died in motor vehicle accidents in 2012 (only 2,228 of whom were vehicle occupants). So, I get 7.7 teens per day dying in motor vehicle accidents, regardless of the cause. I’m no Pulitzer-prize winning New York Times journalist, but I reckon that makes this giant factoid on Richtel’s website wrong, which doesn’t bode well for the book:

richtelpage

In fact, I suspect the 11-per-day meme comes from Mother Jones (or someone they got it from) doing the math wrong on that Newsday number of 3,000 per year and calling it “nearly a dozen” (3,000 is 8.2 per day). And if you Google around looking for this 11-per day statistic, you find sites like textinganddrivingsafety.com, which, like Richtel does in his website video, attributes the statistic to the “Institute for Highway Safety.” I think they mean the Insurance Institute for Highway Safety, which is the source I used for the 2,823 number above. (The fact that he gets the name wrong suggests he got the statistic second-hand.) IIHS has an extensive page of facts on distracted driving, which doesn’t have any fact like this (they actually express skepticism about inflated claims of cellphone effects).

After I contacted him to complain about that 11-teens-per-day statistic, Richtel pointed out that the page I linked to is run by his publisher, not him, and that he had asked them to “deal with that stat.” I now see that the page includes a footnote that says, “Statistic taken from the Insurance Institute for Highway Safety’s Fatality Facts.” I don’t think that’s true, however, since the “Fatality Facts” page for teenagers still shows 2,228 teens (passengers and drivers) killed in 2012. Richtel added in his email to me:

As I’ve written in previous writings, the cell phone industry also takes your position that fatality rates have fallen. It’s a fair question. Many safety advocates point to air bags, anti-lock brakes and wider roads — billions spent on safety — driving down accident rates (although accidents per miles driven is more complex). These advocates say that accidents would’ve fallen far faster without mobile phones and texting. And they point out that rates have fallen far faster in other countries (deaths per 100,000 drivers) that have tougher laws. In fact, the U.S. rates, they say, have fallen less far than most other countries. Thank you for your thoughtful commentary on this. I think it’s a worthy issue for conversation.

I appreciate his response. Now I’ll read the book before complaining about him any more.

The shocking truth

I generally oppose scare-mongering manipulations of data that take advantage of common ignorance. The people selling mobile-phone panic don’t dwell on the fact that the roads are getting safer and safer, and just let you go on assuming they’re getting more and more dangerous. I reviewed all that here, showing the increase in mobile phone subscriptions relative to the decline in traffic accidents, injuries, and deaths.

That doesn’t mean texting and driving isn’t dangerous. I’m sure it is. Cell phone bans may be a good idea, although the evidence that they save lives is mixed. But the overall situation is surely more complicated than TEXTING-WHILE-DRIVING EPIDEMIC suggests. The whole story doesn’t seem right — how can phones be so dangerous, and growing more and more pervasive, while accidents and injuries fall? At the very least, a powerful part of the explanation is being left out. (I wonder if phones displace other distractions, like eating and putting on makeup; or if some people drive more cautiously while they’re using their phones, to compensate for their distraction; or if distracted phone users were simply the worst drivers already.)

Beyond the general complaint about misleading people and abusing our ignorance, however, the texting scare distracts us (I know, it’s ironic) from the giant problem staring us in the face: our addiction to private vehicles itself costs thousands of lives a year (not including the environmental effects).

To illustrate this, I went through all the trouble of getting data on mobile phone subscriptions by state, to compare with state traffic fatality rates, only to find this: nothing:

cellphones traffic deaths with NEJM.xlsx

What does predict deaths? Driving. This isn’t a joke. Sometimes the obvious answer is obvious because it’s the answer:

cellphones traffic deaths with NEJM.xlsx

If you’re interested, I also put both of these variables in a regression, along with age and sex composition of the states, and the percentage of employed people who drive to work. Only the miles and drive-to-work rates were correlated with vehicle deaths. Mobile phone subscriptions had no effect at all.

Also, pickups?

Failing to find a demographic predictor that accounts for any of the variation after that explained by miles driven, I tried one more thing. I calculated each state’s deviation from the line predicted by miles driven (for example Alaska, where they only drive 6.3 thousand miles per person, is predicted to have 4.5 deaths per 100,000 but they actually have 8.1, putting that state 3.6 points above the line). Taking those numbers and pouring them into the Google correlate tool, I asked what people in those states with higher-than-expected death rates are searching for. And the leading answer is large, American pickup trucks. Among the 100 searches most correlated with this variable, 10 were about Chevy, Dodge, or Ford pickup trucks, like “2008 chevy colorado” (r = .68), shown here:

deaths-searches

I could think of several reasons why places where people are into pickup trucks have more than their predicted share of fatal accidents.

So, to sum up: texting while driving is dangerous and getting more common as driving is getting safer, but driving still kills thousands of Americans every year, making it the umbrella social problem under which texting may be one contributing factor.

I used this analogy before, and the parallel isn’t perfect, but the texting panic reminds me of the 1970s “Crying Indian” ad I used to see when I was watching Saturday morning cartoons. The ad famously pivoted from industrial pollution to littering in the climactic final seconds:

Conclusion: Keep your eye on the ball.

15 Comments

Filed under In the news

To know poverty proportions, know your terms (Fox News edition)

In a recent interview on Fox & Friends, despite preparing, I found myself not prepared for Tucker Carlson to ask me this:

It’s pretty conclusive that kids who grow up with married parents — biological parents — do way better than kids who don’t. So the fact that the percentage of kids growing up in that environment has been dropping, why shouldn’t we call that a tragedy?

After a little back-and-forth, I came out with this pretty inarticulate statement:

I think we want to think about pros and cons and and challenges that people face in all different arrangements. And part of the point of this report is that we can’t put people in one category and try to come up with a solution. Our poverty problem for example: Only a third of people in poverty now are living in single-mother families. So we have a large problem of poverty in married couple families as well.

My inarticulateness would probably have been even worse if I had noticed that the Fox audience at that moment was being treated to a completely wrong statistic in the caption below our talking heads:

foxbadcaption

The report I provided to the Fox staff had actually shown that one-third — not two-thirds — of children under 15 live with unmarried parents.

Anyway, my statement, “Only a third of people in poverty now are living in single-mother families,” is pretty much true. On the other hand, the oft-cited Heritage Foundation statement, “Nearly three out of four poor families with children in America are headed by single parents,” is pretty much true, too. How can that be?

To put it as confusingly as possible, the basic issue is that poverty numbers can be reported for different data universes: individuals, families, family households, individuals in families, and families with children. Some families are sub-families — that is, they are in someone else’s household — and some children (if they live in group quarters, or are ages 16-18 and live on their own as neither married nor parents) don’t live in families.

Here are some poverty numbers for 2013 (from various tables here). The rates are just for your information; it’s the numbers in poverty that I refer to below — you can use them to mix and match your own proportions:

poverty2013

Notice that there are 14 million poor people who don’t live in families at all. Some of them have housemates or cohabiting partners that they are sharing income with, but because they’re not technically families that shared income doesn’t count as shared income.

Because, from the 1st and 3rd rows of the table, 15,606/45,318 = .34, my statement that only a third of poor people live in single-mother families was pretty much true. I say “pretty much” because a few of those female-householder-no-husband families aren’t single mothers of children, but rather single women hosting some other family member in their households (such as an older relative).

And because, from rows 12-14, (3,937+607)/6,482 = .70, the Heritage Foundation’s statement that, “Nearly three out of four poor families with children in America are headed by single parents” is pretty much true, too.

So, who’s right?

Well, if you want to talk about the whole poverty problem, it’s fair to say that only a third of it involves people in single-mother families. Maybe by excluding the single fathers from that I’m guilty of shading the number downward to minimize the problem (and I definitely shouldn’t have implied that the rest of the poor people live in married-couple families). I actually did that because the table I get those numbers from (hstpov2) doesn’t report single-man families.

If you want to talk about the problem of children in poverty, then you should use the second panel, which tells you that 57% of children in poverty live with single mothers (8,339/14,659), or if you include single fathers, 65%. That’s what Heritage should do.

The “nearly three out of four” number is true — if you’re OK with 70% as nearly three out of four — but there’s no reason families is the more logical unit of analysis instead of children.

Marriage tracks poverty

Anyway, I was reminded of all this because Brad Wilcox tweeted a link to this editorial from the Tyler Morning Telegraph. The editorial includes the Heritage statistic, and explains why poverty rates haven’t fallen much in the last few years, while unemployment rates have. Quoting Joe Carter of the Acton Institute:

“The findings align with what many family scholars and economists have been predicting: the decline of marriage leads to an increase in poverty. From 2007 to 2011, the American population increased by 10,360,000 while the number of marriages decreased during that same period by 79,000. Over the last few years we’ve seen the same trend: more people, fewer marriages. … The effect of the decline in marriage, coupled with an increase in single parenthood, is that many more children live in poverty than they would if marriage was more common.”

That’s why the headline for the editorial is, “Marriage statistics track with poverty.” To illustrate marriage tracking poverty, I’ve put the two historical trends on the same graph, using this for marriage and this for poverty:

poverty and marriage 1960-2013

As the chart clearly shows (since 1977 at least), when marriage falls, poverty goes up. Also, when marriage falls, poverty goes down. In math-grammar terms, those two equations reduce to: marriage falls; poverty goes up and down.

Leave a comment

Filed under Uncategorized

Mildly altruistic blog post rooted in the brain

Brain science is super interesting and important, of course. In fact, “the brain” is gaining on “the mind” as a topic of our brain-mind’s fixation (Google ngrams):

brainmind

I take a tiny share of responsibility for this trend, as during one of my journalism careers I wrote a 1995 news article about “brain-based learning” for a newsletter sent to more than 100,000 K-12 educators.

On the plus side, in my old article I devoted considerable attention to the issue of brain plasticity, or how brains change in response to time and experience. That plasticity perspective was conspicuously absent from Michelle Trudeau’s NPR story this morning about the brains of extreme altruists. The story was based on a paywalled PNAS article which reported that a nonrandom group of 19 anonymous kidney donors had bigger right amygdalas, and heightened emotional response to pictures of faces, than a nonrandom group of 20 controls. The authors conclude that “these findings suggest extraordinary altruism [is] supported by neural mechanisms that underlie social and emotional responsiveness.”

Or, maybe the cumulative experiences of adults who turn out to be extraordinary altruists change their brains. (Or even, maybe the experience of giving a kidney itself affects people’s brains.) It appears that amygdala size changes within people over time, and that it is correlated with the size of people’s social networks. So, the causal sequencing here is something to consider.

What if, as they imply, something about the way people are born makes them more or less likely to be an extraordinary altruist versus a psychopath (a group this researcher previously studied). How much of the real-life variation in altruism might such a genetic or anatomical influence account for? If that proportion is low, then this is a fascinating evolutionary question with little social implication — worth studying, but not worth writing about with headlines like, “Good Deeds May Be Rooted In The Brain.”

The PNAS authors conclude:

It should be emphasized, however, that the mechanisms we have identified are unlikely to represent a complete explanation for altruistic kidney donation, given the extreme rarity of this phenomenon, and given the overlapping distributions we observed for the variables we measured. Acts of extraordinary altruism are likely to reflect a combination of the neurocognitive characteristics identified here, along with other individual- or community-level variables.

That seems like a safe bet, given this distribution of amygdala size across the two groups:

altruismbrains

In short, we should consider the possibility, however slight, that altruism also has social causes. Disciplinary culture, I suppose, but I’ve never finished an article with a caution to readers that I may not have completely explained the phenomenon under study.

Leave a comment

Filed under Research reports

Changing Hispanic racial identity, or not

Hector Cordero-Guzman called my attention to a controversy over Hispanics changing their racial identities. Here is a quick rehash and a few comments. (Spoiler: the New York Times ran a bad story.)

At the Population Association of America, Carolyn Liebler, a sociologist at the University of Minnesota, and James Noon, who works on administrative records at the Census Bureau, presented preliminary results from a comparison of individual race/ethnic responses to the 2000 and 2010 Decennial Censuses. After analyzing millions of individual Census responses, they reported in their abstract that 6% of people changed their race or Hispanic origin classification between 2000 and 2010.

Details of the analysis apparently are not publicly available, but D’Vera Cohn, a writer at the Pew Research Center, reported on their findings, under the headline, “Millions of Americans changed their racial or ethnic identity from one census to the next.” Is this a lot of change? It’s hard to say without a comparison (and without the analysis details). “Millions” does not really mean “a lot,” but it sounds like it does. If the Census race/ethnic identity questions don’t fit people’s self-concept very well then a certain amount of bouncing around is to be expected.

The focus was on Hispanics, whose place in the racial classification scheme is squishy (including immigrants who came at different ages from countries with different racial schemes and ancestral origins, living in different parts of the country with different racial attitudes, some concentrated in dense communities and some dispersed, some economically marginalized and some much more upwardly mobile, etc.). According to D’vera Cohn, 2.5 million Hispanics were “some other race” in 2000 and “white” in 2010, while 1.3 million were “white” in 2000 and “some other race” in 2010.

I might conclude from that that it’s messy and the categories don’t work very well. But it’s also possible that this reflects fluid identities, and people actually change how they see themselves in a systematic way over time. The PAA abstract says “responses and corresponding identities can change over time,” which leaves open the possibility that the change is in measurement in addition to identity, but the hypothesis they suggest are about identity (hypothesizing that women, young people, and people in the West have more complex or less stable identities).

Identity shift is how New York Times Upshot writer Nate Cohn interpreted the D’Vera Cohn report. Under the headline, “More Hispanics Declaring Themselves White,” he converted that bidirectional flow into “net 1.2 million” changing from “some other race” to “white,” and proceeded to run away with the implications. It’s a good example of using any number greater than zero to confirm something you already believe. For example, he wrote:

The data also call into question whether America is destined to become a so-called minority-majority nation, where whites represent a minority of the nation’s population. Those projections assume that Hispanics aren’t white, but if Hispanics ultimately identify as white Americans, then whites will remain the majority for the foreseeable future.

Hm. The “net” flow from “some other race” to “white” is 1.2 million. That is 3% of the 2000 Hispanic population, or 2% of the 2010 population. So even if it’s truly an identity change, does that save the White majority in the long run?

Anyway, as Cordero-Guzman points out in a detailed discussion, referring to a post by Manuel Pastor, the Census questions changed between 2000 and 2010, with Census adding, in bold, “For this census, Hispanic origins are not races” to the form in 2010. Since many Hispanics write “Hispanic” under “some other race,” this probably discouraged them from choosing “some other race” in 2010.

Cordero-Guzman also points out that the context in which the question is asked (and in which the respondents live) is important. For example, 82% of Puerto Ricans on the island use “white” on the American Community Survey, while in New York City only 45% do. Does their identity — in the sense of how they really think of themselves — change when they are in New York, or do they interpret the question differently because they are answering a question in a different social setting? You can’t quantify that difference, probably, but I wouldn’t assume it’s just an identity change.

In a follow-up post, Nate Cohn acknowledges the wording changes — “an important detail” — but returns to the assimilation-upward mobility story. He should have just acknowledged that he jumped to conclusions in the first post and overreached in the race to produce an important, “data-driven” post. (Nate Cohn may have consulted actual experts, but if he did he didn’t include them in the post. It’s just data, I guess.)

The information economy did it

There is a lesson here in the new information economy. Academic conferences used to be less in the public eye. A preliminary analysis, shared with other researchers, then a Pew writer posts on the results, and the Times splashes them all over, all before a paper is even available. I think the Times story is basically wrong — the data as reported are not independent evidence of “assimilation.” (So, the person with the biggest megaphone was the person who was most wrong — surprise!) But the analysis could well be an important piece of research in a larger literature, and I think it’s good to present preliminary research at conferences. You can’t stop reporters from racing to be wrong, but I do think it would be better to distribute the paper publicly when it’s presented.

4 Comments

Filed under Uncategorized

US teen birth rates remain high, and they’re not falling for the reasons you’ve heard

Everyone is excited by the decline in the teen birth rate in the US. But And here are a few things you should know about it.

This chart shows the birth rates for women ages 15 to 19 in 192 countries, plus the world and the UN-defined rich countries, for 1991 and 2011. Dots below the black line show countries where the teen birth rate fell. The red line shows the overall relationship between 1991 and 2011. Dots below the red line had greater than expected reduction in teen births.

teen births global

Source: My graph United Nations data.

The chart shows four things:

1. Teen birth rates are falling globally. From 1991 to 2011, the birth rate for women ages 15 to 19 fell from 65 to 46 births per 1,000 women worldwide.

2. US has higher teen birth rates than any other rich country. At 33 per 1,000, the US has more teen births than Pakistan (28), but fewer than India (36). For high income countries, by the UN definition, the rate is 19. The rate for the Euro area is 7.

3. The teen birth rate is falling faster in the US than in the world overall. The world rate fell 29% from 1991 to 2011, while the drop in the US was 44%.

In the US, there are a lot of factors related to falling teen births. But they’re mostly about how it’s happening, not why it’s happening. For example, Vox published a list of factors, as did Pew before them, that are reasonable: the recession, more birth control, more Medicaid money for family planning, cultural pressure, and less sex.

But to understand why this is happening, you have to stop thinking about teenagers as some sort of separate subspecies. They are just young women. Soon they will be in their 20s. The same women! So the short answer for why falling teen birth rates happening is this:

4. Teen birth rates in the US are falling because women are postponing their births generally.

You can see this if you line up teens next to women of other ages. Here are the changes in birth rates for women, by age, from 1989 to 2012.

birthratechangebyage

Source: My graph from National Center for Health Statistics data.

See how the trend for the last decade is parallel for 15-17, 18-19, and 20-24? As those rates fell, birth rates rose for the 30+ community. The younger women are, the fewer births they’re having; the older they are, the more births they’re having. Teenage women are women! They do it for all the reasons it’s happening around the world: some because they are delaying marriage, some to pursue education and careers, some to see the world, and so on.

Here is another way to look at this. Here are the 50 US states, from the 2000-2012 American Community Survey. This shows that states with lower teen birth rates (those are per 100, on the y-axis), have higher birth rates for 25-34 year-old women relative to 20-24 year-old women. I’ll explain:

teenbirthstates

Teen births rates and the ratio of teen birth rates ages 25-34 / 20-24. US states, 2010-2011

Where more women have children ages 25-34 relative to 20-24, there are fewer teen births. So, in Alabama, about 3% of women 15-19 had a baby per year, and in that state the birth rates are about the same for women 25-34 as 20-24. Alabama is an early-birth state. But in New Hampshire, only 1% of teens had a baby, and women 25-34 were almost 2.5-times more likely to have a baby than women 20-24. New Hampshire is a late-birth state. What’s happening with teens reflects what’s happening with older women.

To some significant degree, it’s not about teenagers, it’s about women delaying births.* I would love it if reporting on teen births would always compare them to older women.

*Notice I didn’t just exaggerate and say, “it’s not about teenagers.” I added “to some significant degree.” That’s the difference between a post that is selling you (your clicks) to someone versus a post that’s trying to explain things as clearly as possible.

16 Comments

Filed under In the news

Misogyny and masculinity, less edited

One point of all this work that I do speaking about sociology to people who aren’t academic sociologists — teaching, blogging, writing a textbook, speaking to the news media — is to help our research have a greater social impact. When a public tragedy occurs, such the Santa Barbara mass murder, there is a chance to widen the conversation and include a sociological perspective.

Photo by Robert Vitulano from Flickr Creative Commons

Photo by Robert Vitulano from Flickr Creative Commons

Sometimes I have the chance to do this even when my own research is not what’s most applicable. That’s great, but I try to be careful (and recommend that journalists speak to others as well). I hope I was right in this case. When Jessica Bennett – a journalist who writes incisively about gender and popular culture – asked me (among others) for a reaction, for what became this column, my first thought was about misogyny. I offered here these comments in an email:

There are two ways that misogyny could play into this case. The first possibility is that he simply hated women, a perspective that is highly accessible in US society. This is illustrated in a lot of pornography — rape or humiliation — and advertising, and articulated by a lot of men who objectify women and seek their conquest or abuse in order to express power or impress other men.

The other possibility is he was schizophrenic or otherwise disassociated from social reality. In that case, misogyny is just the vehicle his disordered brain latched onto. Paranoid people choose from the available entities when building up the fantasy of their persecution. The source of their persecution may not be real, but it is also not random. (The CIA may not be after you, but if it didn’t spy on and assassinated some people, schizophrenics wouldn’t be afraid of them.)

If a paranoid delusional young man believes women are persecuting him, he may be crazy but he is also picking up on the hatred and fear directed toward women that he sees around him.

No matter how you slice it, it is a tragedy that reflects the societal influence of hatred toward women. That is not the whole story of gender relations in our society, but it is definitely present and dangerous.

Then, when Bennett let me know she was interested in focusing the piece on masculinity, I added this (the excerpt she chose is underlined):

One issue is the narrow range of acceptable expressions of masculinity. This is one place where women have more flexibility than men (pants or dress). Especially in adolescence, the question is: If you can’t be good at sports or have sex, what makes you [a] man? Maybe it’s violence.

The alternative many men/boys learn to deal with, of course, is just not being an ideal man. [as mentioned,] most men don’t kill people. Partly that means learning to be ok with not achieving the ideal. So that’s a coping thing many men need to develop, and failure to develop that could be evidence of a problem.

I’m not an expert on masculinity studies. In the quote on masculinity that Bennett used, I was thinking specifically of the chapter by Barbara Risman and Elizabeth Seale, in which they interviewed middle schoolers about gender, concluding:

We find that both boys and girls are still punished for going beyond gender expectations, but boys much more so than girls. For girls, participation in traditionally masculine activities, such as sports and academic competition, is now quite acceptable and even encouraged by both parents and peers. We fi nd, indeed, that girls are more likely to tease each other for being too girly than for being a sports star. Girls still feel pressure, however, to be thin and to dress in feminine ways, to “do gender” in their self-presentation. Boys are quickly teased for doing any behavior that is traditionally considered feminine. Boys who deviate in any way from traditional masculinity are stigmatized as “gay.” Whereas girls can and do participate in a wide range of activities without being teased, boys consistently avoid activities defined as female to avoid peer harassment.

 

The chapter appears in the reader that Risman edited, titled Families as They Really Are (keep an eye out for a new edition!). Someone posted a bootleg copy of the chapter here.

As I read my comments now, I realize there are a lot of other ways to be “a man,” but what I was trying to get at is the concept of hegemonic masculinity, the dominant (in the sense of power) way of being “a man” in a particular cultural context. Of course there other ways to be happy and a man without hanging it on sports, sex, or violence. In reaction to the #YesAllWomen Twitter movement, some people have responded with “real men don’t rape” (which is ironically similar to the old feminist perspective that “rape is violence, not sex”). It attempts to preserve the basic status (men, sex) as good while making the oppressive or violent part deviant, not of the essence. Here is one tweet to that effect, from Michelle Ray:

Feminists seem to have no idea what a man is. Men don’t rape. Sick people who never learned to be men commit violence to solve their issues.

If you say “men don’t rape,” that’s a nice way to try to make it cool to be a man against rape, to resist that image of masculinity. So I like it as an imperative. But as a description of society it’s not true, so there’s that. (A similar move happens in family discourse, sometimes, as when someone says about abuse within families, “real fathers don’t treat their children that way.” Of course, real fathers do good as well as evil — the questions are how and why, and what to do about it.)

Anyway, I would also recommend C. J. Pascoe’s ethnography, Dude, You’re a Fag, in which she discussed sex and masculinity with high school students. Here’s one excerpt:

If a guy wasn’t having sex, “he’s no one. He’s nobody.” Chad explained that some guys tried to look cool by lying about sex, but they “look like a clown, [they get] made fun of.” He assured me, however, that he was not one of those “clowns” force to lie about sex, bragging, “When I was growin’ up I started having sex in the eighth grade.”

And Pascoe concluding:

These practices of compulsive heterosexuality indicate that control over women’s bodies and their sexuality is, sadly, still central to definitions of masculinity, or at least adolescent masculinity. By dominating girls’ bodies boys defended against the fag position, increased their social status, and forged bonds of solidarity with other boys. However, none of this is to say that these boys were unrepentant sexists. Rather, for the most post, these behaviors were social behaviors. Individually boys were much more likely to talk empathetically and respectfully of girls. … Maintaining masculinity, though, demands the interactional repudiation of this sort of empathy in order to stave off the abject fag position.

That insight about interaction is crucial. To go above my pay grade a little (more), I might add that this division between the way one acts in “public” versus “private” is notoriously tricky and frustrating for people with some kinds of mental illness.

That’s just the tip of the masculinity-studies iceberg. Feel free to post other recommended readings in the comments.

7 Comments

Filed under In the news, Me @ work