Mary free fall continues

For the past two years I’ve been tracking the fate of the name Mary as given to girls born in the U.S., spurred by the observation that Mary was no longer in the top 100 names, after an unparalleled run at #1 that lasted for all but six years of recorded history.

It’s a difficult job, but it’s got to be done. (Follow the Mary tag for historical background, examples, and more figures.)

So: 2012 was another rough year, according to data from the Social Security Administration.

There was another 5% drop in the number of Marys born, and as a result Mary fell a record 11 ranks, from 112 to 123. The 2,535 Marys born in 2012 were a mere 0.13% of the 1.9 million girls recorded born. Once upon a time, in 1880, more than 7% of all girls born were named Mary.

Part of the point of the Mary name project is to show the predictability of (much) human behavior, even including rare events, such as naming girls Mary. I have a simple model which predicts that the number of girls named Mary will decline at a rate equal to the average decline over the previous five years — what falls continues to fall. This year, out of 1.9 million girls born and 2,535 named Mary, my model was off by a microscopic 79 girls. The model predicted the number of Marys to within 3.2%.

Take that, indeterminancy, free will, or postmodernism (your pick).

P.S. Despite the continued free fall of Mary, my model missed low, incidentally — or, Mary-naming Americans beat expectations by 3.2%. Since my Mary post on the Atlantic site last December was shared more than 5,000 times, unless proven otherwise we have to assume the 79-girl bump was a Mary-name-blog effect. (File under reflexivity.)

ADDENDUM: MARIA

By request, here is the trend for Maria. It is not the case that Maria is replacing Mary — both are trouble. In fact, with Maria falling steeply in the last decade, she has also dropped out of the top 100 for the first time since 1943!

Speculation: As Marias of Latina origin grow more common, perhaps their increase is not enough to compensate for the resulting perception among non-Latinas that Maria is a Spanish name. (Remember, this is just girls born in the U.S.)

Why Don’t Parents Name Their Daughters Mary Anymore?

Originally published on TheAtlantic.com.

Understanding the rapid decline of what was once America’s most popular name

Each year I mark the continued calamitous decline of Mary as a girls’ name in the United States. Not to be over-dramatic, but in the recorded history of names, nothing this catastrophic has ever happened before. Mary was the most common name given to girls every year from the beginning of record-keeping (at least back to 1800) through 1961 (except for a six-year dip to #2, behind Linda).

And then it happened. In 2011, according to the latest report from the Social Security Administration (SSA), Mary fell three more places, to 112th. In absolute numbers, the number of girls given the name Mary at birth has fallen 94 percent since 1961. Here is the trend:

The modernization theory of name trends, advanced most famously by the sociologist Stanley Lieberson, sees the rise of individualism in modern naming practices. “As the role of the extended family, religious rules, and other institutional pressures declines,” he wrote, “choices are increasingly free to be matters of taste.” Mary—both a traditional American name and a symbol religious Christianity—embodies this trend.

The other day I did a search of newspaper birth announcements for the name “Mary,” and turned up a lot of grandmothers named Mary. Here, from a recent day’s birth announcement page from Rock Hill, South Carolina, are three Marys in the grandparent generation, in three different families announcing the births of Mazie, Ja’Nae, and Asani. I diagrammed the family names:

Other generational sequences in recent announcements also mirror the history of common names: Mary–Jennifer–Madelyn; Mary–Ashley–Emily; Mary–Cora–Elizabeth.

In the tradition of treating statistical trends as horse races, I imagine that there is one person named Mary, who is constantly falling behind: first behind Linda, then Lisa, Jennifer, Ashley, Jessica, and so on, all the way to Isabella and now Sophia.

But that’s not how it happens—it just looks that way because of the amazing regularity in human behavior, which produces an orderly succession of names. Incredibly, out of 1.7 million girls’ names recorded by the SSA in 2011, I was able to predict to within 87 how many would be named Mary. By simply taking the number born in 2010 and subtracting the 5-year average decline, I predicted 2,584 would be born; the actual number was 2,671 (an error of 3.3 percent).

Somehow, out of the millions of individual decisions parents make, they produce steady trends like this. (If you’re as amazed as I am, consider a career in sociology! If not, please bear with me.)

So what does the Mary trend mean? First, it’s the growing cultural value of individuality, which leads to increasing diversity. People value names that are uncommon. When Mary last held the number-one spot, in 1961, there were 47,655 girls given that name. Now, out of about the same number of total births, the number-one name (Sophia) was given only 21,695 times. Conformity to tradition has been replaced by conformity to individuality. Being number one for so long ruined Mary for this era.

Second, America’s Christian family standard-bearers are not standing up for Mary anymore. It’s not just that there may be fewer devout Christians, it’s that even they don’t want to sacrifice individuality for a (sorry, it’s not my opinion) boring name like Mary. In 2011 there were more than twice as many Nevaehs (“Heaven” spelled backwards) born as there were Marys. (If there is anything more specific going on within Christianity, please fill me in.)

I’m not here to give advice to people who want to bring back the “traditional family.” But if I were I would recommend putting your names where your tradition is—and producing some more Marys.

There are precedents for bringing names back. My simple linear prediction method fails once in a while, when a name’s trend turns around. The greatest example is probably Emma. Emma was at number three when the SSA records begin, in 1880. She fell almost down to #500 by the 1970s. But after a decade of uncertainty she began a fantastic run, finally reaching number one in 2008.

I don’t know (yet) what makes a name turn around like that. Why Emma and not Mildred or Bertha, both former top-10s who fell into oblivion? But if any name has a chance for a similar resurgence, it might be Mary, at least as long as Christianity keeps hanging around.

Guns dividing America (Google edition)

Whenever I get a good indicator broken down by state, I head over to Google Correlate to see how it connects to America’s search behavior. Often what I find is a gun connection. This is very big in searches related to the election, so I’ll start with that before giving a couple other examples.

Odds of Romney winning

Taking yesterday’s New York Times 538 forecast chance of Mitt Romney winning each state, I entered the numbers into the search correlation machine. As you can see from the map on the left, these are very polarized numbers, with 42 of the states being above 90% or below 10%. Of the 100 Google searches whose relative frequency is most correlated with this pattern across states, 31 are about guns. Here is the search most correlated (.82) with Romney’s odds of winning: “marlin 30-30,” which is a classic rifle (available at Walmart):

Unintentional deaths

News the other day was about the lives lost to unintentional injuries for people under age 20 — the most common causes of death in that age range. About half of this is from motor vehicle accidents, with most of the rest distributed between drowning, suffocating, fires, falls, and poisoning. The CDC put out a report that included a state breakdown, reported in terms of “years of potential life lost” per 100,000 population. That is just the number of deaths times the number of years between the age at which the death occurred and age 75 (so a death at age 1 is 74 years lost, a death at age 19 is 56).

The big inequalities here are in gender and geography. Males are about 1.8-times more likely to die from this stuff. And the most dangerous state (Mississippi) has more than 4-times the losses of the safest (Massachusetts). There are race differences as well — with American Indians having high rates — but the Black/White difference is not that large (Latino ethnicity wasn’t identified).

How are these rates of lost life correlated with search behavior? Guns. Among the 100 searches that most closely follow the pattern of deaths, 62 were about guns, starting with number 1: “shotgun for sale,” with a correlation of .93.

There were also 14 searches about cars and trucks on the list (mostly Ford F150s and Chevy trucks), four about wedding dresses and rings (“discount wedding dresses”) and three about Fox News.

Divorce

I did this twice with divorce rates. Using the 2008-2009 divorce rates per 1,000 married women, I found a good gun correlation with gun searches, with “colt .45 automatic” scoring a .86:

There were 27 more gun-related searches on that 08-09 divorce-correlation list. I updated that for the new 2011 rates, and again came up with a list of gun-related searches (and other military or survivalist stuff). Here is the Norinco SKS and 2011 divorce rates, correlation .84:

Someone who knows more than me could probably read more into the searches for different kinds of guns and gun-related stuff — for example, the difference between sniper accessories, shotguns and handguns. These different gun results show variations in their geographic patterns.

Anyway, I can’t think of what else besides search data tells us so much about so many people’s behavior — not their stated interests, their reported behavior, their tax forms, or their consumption patterns. And yet I can’t really put my finger on what it does tell us. It’s a million miles wide and not that deep, but it’s endlessly fascinating. If someone can figure out how to explain the value of what this all shows, I’m all ears.

Where did we go wrong, or did we? (love and sex edition)

For ever – or at least for 70 years - make love was many times more common than have sex, at least in the Google Ngrams database of millions of books in American English. And, then — well, you can guess what happened then:

The results are the same with “making” and “having” (you can play with the search here).

Why? What happened? Could it be “the culture”? Zooming in on the period since 1950, preliminary evidence is mixed:

I’m open to hypotheses.

 

 

A lot of juggling metaphors in the air

But what are people juggling?

[Updated with a look at phrase origins at the end.]

Judging by the prevalence of terms in the Google Ngrams database of books, since 1970 people have begun juggling their families, their work-and-family, their responsibilities, and even their children themselves.

Maybe all the metaphorical juggling has contributed to the rise of real-life juggling, although based on the distribution of juggling conventions this is a bigger deal in Europe than the U.S. In American English, “juggling balls” is thriving, but since the mid-1980s its growth can’t keep up with “juggling work.”

And, judging by who’s juggling in a Google image search for “juggling work,” the clip-artists of today, at least, think it’s women who are driving the trend about 2-to-1:

Origins update:

The Oxford English Dictionary doesn’t have a clear dating of this kind of use for juggling before 1985, “They have to know how to do many things—from juggling the futures market to overhauling a tractor or curing viral scours.”

The first instance of “juggling work” I get in the Lexis database is from the New York Times, Sep. 23, 1980:

She conceded that juggling her work and family is not always easy. ”You feel split all the time,” said Mrs. Massie, taking a cigarette. ”Sometimes the family responsibility collides with the need to be alone, and with the selfishness that is necessary for any creative effort.”

The American Sociological Review has a reference to “juggling work assignments” in a 1956 book review on industrial practices, which isn’t quite the sense of juggling tasks within a single life. By 1983 Frontiers: A Journal of Women Studies has this:

The impossible pressures of juggling work and family responsibilities have led some Soviet women to reject the ideology of emancipation altogether.

And by then we’re off and juggling.

Tangled up in Disney’s dimorphism

Sitting through Disney’s Tangled again, I saw new layers of gender in there. They’ve moved beyond the old-fashioned problem of passive princesses and active princes, so Rapunzel has plenty of action sequences. And it’s not all about falling in love (at least at first). Fine.

But how about sexual dimorphism? In bathroom icons the tendency to differentiate male and female bodies is obvious. In anthropomorphized animal stories its a convenient fiction. But in social science it’s a hazardous concept that reduces social processes to an imagined biological essence.

In Tangled, the hero and heroine are apparently the more human characters, whose love story unfolds amidst a cast of exaggerated cartoons, including many giant ghoulish men (the billed cast includes the voices of 12 men and three women).

Making the main characters more normally-human looking (normal in the statistical sense) is a nice way of encouraging children to imagine themselves surrounded by a magical wonderland, which has a long tradition in children’s literature: from Alice in Wonderland to Where the Wild Things Are.

That’s what I was thinking. But then they went in for the lovey-dovey closeup toward the end, and I had to pause the video:

Their total relative size is pretty normal, with him a few inches taller. But look at their eyes: Hers are at least twice as big. And look at their hands and arms: his are more than twice as wide. Look closer at their hands:

Now she is a tiny child and he is a gentle giant. In fact, his wrist appears to be almost as wide as her waist (although it is a little closer to the viewer).

In short, what looks like normal humanity – anchoring fantasy in a cocoon of reality – contains its own fantastical exaggeration.

The patriarchal norm of bigger, stronger men paired up with smaller, weaker women, is a staple of royalty myth-making – which is its own modern fantasy-within-reality creation. (Diana was actually taller than Charles, at least when she wore heels .)

In this, Tangled is subtler than the old Disney, but it seems no less powerful.

Pink and blue kid(s)

Jo Paoletti got a nice cover write-up from the UMD magazine Terp, for her new book, Pink and Blue: Telling the Boys from the Girls in America. I especially love the cover photo:

The photo(s) is (are) by John T. Consoli, linked without permission. This is a great exercise for noticing how we internalize gender norms. If you thought even for a moment that one of these kids is a boy and the other is a girl, you’re busted as a product of socialization. (I won’t reveal the “true” answer.)

This is much better than my own crude Photoshop version:

I’ve done a series of posts on color and children, which you can find here. That led me to do a survey on color preferences, which got close to 2,000 responses to the question, “What’s your favorite color.” Based on a simple color chart provided, these were the responses:

More than the gender breakdown, I wanted to see if the nurture-versus-nature element of color preference could be teased out in a single survey. So I asked people if they had children, and the gender of their children — figuring that might reflect some “adult socialization.” And that modest result is what I found. From the abstract:

This study asks whether the gendered social environment in adulthood affects parents’ color preferences. The analysis used the gender of children to represent one aspect of the gendered social environment. Because having male versus female children in the U.S. is generally randomly distributed, it provides something of a natural experiment, offering evidence about the social construction of gender in adulthood. The participants were 749 adults with children who responded to an online survey invitation, asking “What’s your favorite color?” Men were more likely to prefer blue, while women were more likely to prefer red, purple, and pink, consistent with long-standing U.S. patterns. The effect of having only sons was to widen the existing gender differences between men and women, increasing the odds that men prefer blue while reducing the odds that women do; and a marginally significant effect showed women having higher odds of preferring pink when they have sons only. The results suggest that, in addition to any genetic, biological or child-socialization effects shaping adults’ tendency to segregate their color preferences by gender, the gender context of adulthood matters as well.

The paper has been provisionally accepted and should be published in a peer-reviewed journal near you soon.

Jo’s excellent blog is here, where you can read about her new project, exploring the rise and fall of unisex clothing for children.

MaddowColbert vs. FoxLimbaugh, Google edition

The Internet’s political echo chambers, red states and blue states, fennel salad and home abortion methods.

The debate goes on about whether online political chatter opens minds more than it closes doors to people with opposing views — with growing concern about how corporate filtering by services like Google and Facebook increasingly serve us what our own behavior tells them we want (and do us the favor of keeping out what we probably don’t like).

As Amy Harmon observed in the NY Times way back in 2004, “The same medium that allows people to peruse a near-infinite number of news sources also lets them pinpoint the ones they want and filter out the rest.” It’s information versus isolation. (The recent poll showing Fox News viewers were the least well-informed on a variety of current news stories was taken as evidence that the network was draining knowledge from its audience, but they probably know less before they decide to watch Fox in the first place.)

Because of the winner-take-all mechanism in our electoral politics, states are described as “red” or “blue” according to how their majorities vote. With regard to family patterns, more nuanced analysis shows that the patterns are not just regional, but also urban/rural/suburban, religious, and so on. But, Google Correlate gives us search data by states, so with the caveat that states contain diverse populations, look at this…

Stereotype, show thyself

Searches for Maddow, Colbert, Limbaugh, and Fox News, by state, with correlations between them shown (on a scale of -1 to 1):

I previously showed that divorce rates are positively correlated with searches for “tea party” and negatively correlated with Obama’s 2008 vote. Not surprisingly, these searches are correlated with political outcomes as well. I combined Maddow+Colbert and Limbaugh+FoxNews, and subtracted one from the other, creating an index that runs from a high of 6.0 in Vermont to a low of -6.0 in Mississippi. This lines up quite well with the 2008 vote:

That’s not the result I’m interested in, but just a little validation for the more squishy cultural stuff that accompanies these media-politics searches. Do they really reflect the search habits of conservative versus liberal voters? I can’t say, but I like looking over the lists and thinking about it.

Using the ColbertMaddow-FoxNewsLimbaugh index, I asked Google correlate which 100 searches were most common in the states with high index values but least common in those with low values. Then I rescaled it backwards to get the reverse results. So the first list is items searched for in the high-liberal-media states, and the second list is those in the high-conservative-media states. Here are the food-related correlations (all at .88 or higher).

Liberal:

• arugula pasta [I'm not making these up -pnc]
• beets nutrition
• beets urine
• cauliflower pasta
• cheese health
• darjeeling express
• fake meat
• fennel salad
• firm tofu
• gianduja
• kitchen confidential
• muesli
• mushroom risotto
• nicoise
• pasta pesto
• poached chicken
• puree
• risotto
• tea caffeine
• tea wiki
• tea wikipedia
• top chef season 8
• vegan bags
• vegan cupcakes
• vegan dessert
• vegetarian
• vegetarian cooking
• vegetarian food
• vegetarian recipe

The conservative list has no real foods, just things about dieting:

• acai berry diet
• acaitrim
• berry diet
• carbs list
• p90x results
• prescription weight loss
• prescription weight loss pills
• weight loss pills

The lists support other stereotypes, like the liberal-state penchant for searching “french movie,” “chomsky” and “lost in translation,” versus conservative political mean-spiritedness (“obama jokes”), lack of sex education  (“how soon can you tell if you are pregnant”) and reproductive health care (“home abortion methods”) and, finally, marital problems:

• how to make a marriage work
• how to save a marriage
• how to save my marriage
• save a marriage

It’s interesting to think about the central place of food in distinguishing the cultural milieu that includes politics — at least those that include these media. That food list is about 1/3 of the liberal correlation terms. Are food habits and terms codes for political views, or are they both aspects of similar world views? Someone must do research on this.

There are lots of other media terms you could use for this. I tried Hannity as well, but decided it was too fringy — and really thrown off by the huge number in Utah. One search from that list jumped out at me: “how long is the first trimester.”

Anyway, the disclaimer from my Stuff White People Google post applies here as well:

In case you’re prepared to be offended, remember this does not mean this is most of what these groups search for, or most of the searches in these areas. Rather, it’s the things that are searched for in these states that are not searched for in other states. So, people in all groups search for porn and shopping and restaurant reviews and health conditions — but these are the things that differentiate the states.

The complete lists of searches correlated with the liberal and conservative indexes are in this PDF. Feel free to question my interpretations and examples.

Gingrich channels William Julius Wilson?

Illustrations from NY Review of Books, here and here.

Newt Gingrich, in Iowa, December 1, 2011:

Really poor children, in really poor neighborhoods, have no habits of working, and have nobody around them who works. So they literally have no habit of showing up on Monday, they have no habit of staying all day. They have no habit of “I do this and you give me cash,” unless it’s illegal.

William Julius Wilson, The Truly Disadvantaged: The Inner City, the Underclass, and Public Policy (1987):

Inner-city social isolation also generates behavior not conducive to good work histories. The patterns of behavior that are associated with a life of casual work (tardiness and absenteeism) are quite different from those that accompany a life of regular or steady work (e.g., the habit of waking up early in the morning to a ringing alarm clock). In neighborhoods in which nearly every family has at least one person who is steadily employed, the norms and behavior patterns that emanate from a life of regularized employment become part of the community gestalt. (p. 60)

Wilson tried to differentiate between the “culture of poverty” and “social isolation,” but the distinction often has not come through in the popular retelling of his work.

Perhaps coincidentally, Gingrich started on this pitch in a speech at Harvard, where Wilson is in the sociology department.

Profile word cloud reveals familyunequal followers

Family Inequality’s unique community of followers, as revealed by the top 100 words in their Twitter blurbs (minus “sociology”):

Not to be confused with, say, the first 500 followers of Feminist Hulk:

Or Karl Rove: