Santa’s magic, children’s wisdom, and inequality

Eric Kaplan, channeling Francis Pharcellus Church, writes in favor of Santa Claus in the New York Times. The Church argument, written in 1897 and barely updated here, is that (a) you can’t prove there is no Santa, so agnosticism is the strongest possible objection, and (b) Santa enriches our lives and promotes non-rationalized gift-giving, “so we might as well believe in him.” That’s the substance of it. It’s a very common argument, identical to one employed against atheists in favor of belief in God, but more charming and whimsical when directed at killjoy Santa-deniers.

All harmless fun and existential comfort-food. But we have two problems that the Santa situation may exacerbate. First is science denial. And second is inequality. So, consider this an attempted joyicide.

Science

From Pew Research comes this Christmas news:

In total, 65% of U.S. adults believe that all of these aspects of the Christmas story – the virgin birth, the journey of the magi, the angel’s announcement to the shepherds and the manger story – reflect events that actually happened.

Here are the details:

So the Santa situation is not an isolated question. We’re talking about a population with a very strong tendency to express literal belief in fantastical accounts. This Christmas story is the soft leading edge of a more hardcore Christian fundamentalism. For the past 20 years, the General Social Survey GSS has found that a third of American adults agrees with the statement, “The Bible is the actual word of God and is to be taken literally, word for word,” versus two other options: “The Bible is the inspired word of God but not everything in it should be taken literally, word for word”; and,”The Bible is an ancient book of fables, legends, history, and moral precepts recorded by men.” Those “actual word of God” people are less numerous than the virgin-birth believers, but they’re related.

Using the GSS I analyzed the attitudes of the “actual word of God” people (my Stata data and work files are here). Controlling for their sex, age, race, education, political ideology, and the year of the survey, they are much more likely than the rest of the population to:

• Agree that “We trust too much in science and not enough in religious faith”
• Oppose marriage rights for homosexuals
• Agree that “people worry too much about human progress harming the environment”
• Agree that “It is much better for everyone involved if the man is the achiever outside the home and the woman takes care of the home and family”

This isn’t the direction I’d like to push our culture. Of course, teaching children to believe in Santa doesn’t necessarily create “actual word of God” fundamentalists. But I expect it’s one risk factor.

Children’s ways of knowing

A little reading led me to this interesting review of the research on young children’s skepticism and credulity, by Woolley and Ghossainy (citations below were mostly referred by them).

It goes back to Margaret Mead’s early work. In the psychological version of sociology’s reading history sideways, Mead in 1932 reported on the notion that young children not only know less, but know differently, than adults, in a way that parallels social evolution. Children were thought to be “more closely related to the thought of the savage than to the thought of the civilized man,” with animism in “primitive” societies being similar to the spontaneous thought of young children. This goes along with the idea of believing in Santa as indicative of a state of innocence.

In pursuit of empirical confirmation of the universality of childhood, Mead investigated the Manus tribe in Melanesia, who were pagans, looking for magical thinking in children: “animistic premise, anthropomorphic interpretation and faulty logic.”

Instead, she found “no evidence of spontaneous animistic thought in the uncontrolled sayings or games” over five months of continuous observation of a few dozen children. And while adults in the community attributed mysterious or random events to spirits and ghosts, children never did:

I found no instance of a child’s personalizing a dog or a fish or a bird, of his personalizing the sun, the moon, the wind or stars. I found no evidence of a child’s attributing chance events, such as the drifting away of a canoe, the loss of an object, an unexplained noise, a sudden gust of wind, a strange deep-sea turtle, a falling seed from a tree, etc., to supernaturalistic causes.

On the other hand, adults blamed spirits for hurricanes hitting the houses of people who behave badly, believed statues can talk, thought lost objects had been stolen by spirits, and said people who are insane are possessed by spirits. The grown men all thought they had personal ghosts looking out for them – with whom they communicated – but the children dismissed the reality of the ghosts that were assigned to them. They didn’t play ghost games.

Does this mean magical thinking is not inherent to childhood? Mead wrote:

The Manus child is less spontaneously animistic and less traditionally animistic than is the Manus adult [“traditionally” here referring to the adoption of ritual superstitious behavior]. This result is a direct contradiction of findings in our own society, in which the child has been found to be more animistic, in both traditional and spontaneous fashions, than are his elders. When such a reversal is found in two contrasting societies, the explanation must be sought in terms of the culture; a purely psychological explanation is inadequate.

Maybe people have the natural capacity for both animistic and realistic thinking, and societies differ in which trait they nurture and develop through children’s education and socialization. Mead speculated that the pattern she found had to do with the self-sufficiency required of Manus children. A Manus child must…

…make correct physical adjustments to his environment, so that his entire attention is focused upon cause and effect relationships, the neglect of which would result in immediate disaster. … Manus children are taught the properties of fire and water, taught to estimate distance, to allow for illusion when objects are seen under water, to allow for obstacles and judge possible clearage for canoes, etc., at the age of two or three.

Plus, perhaps unlike in industrialized society, their simple technology is understandable to children without the invocation of magic. And she observed that parents didn’t tell the children imaginary stories, myths, and legends.

I should note here that I’m not saying we have to choose between religious fundamentalism and a society without art and literature. The question is about believing things that aren’t true, and can’t be true. I’d like to think we can cultivate imagination without launching people down the path of blind credulity.

Modern credulity

For evidence that culture produces credulity, consider the results of a study that showed most four-year-old children understood that Old Testament stories are not factual. Six-year-olds, however, tended to believe the stories were factual, if their impossible events were attributed to God rather than rewritten in secular terms (e.g., “Matthew and the Green Sea” instead of “Moses and the Red Sea”). Why? Belief in supernatural or superstitious things, contrary to what you might assume, requires a higher level of cognitive sophistication than does disbelief, which is why five-year-olds are more likely to believe in fairies than three-year-olds. These studies suggest children have to be taught to believe in magic. (Adults use persuasion to do that, but teaching with rewards – like presents under a tree or money under a pillow – is of course more effective.)

Richard Dawkins has speculated that religion spreads so easily because humans have an adaptive tendency from childhood to believe adults rather than wait for direct evidence of dangers to accumulate (e.g., “snakes are dangerous”). That is, credulity is adaptive for humans. But Woolley and Ghossainy review mounting evidence for young children’s skepticism as well as credulity. That, along with the obvious survival disadvantages associated with believing everything you’re told, doesn’t support Dawkins’ story.

Children can know things either from direct observation or experience, or from being taught. So they can know dinosaurs are real if they believe books and teachers and museums, even if they can’t observe them living (true reality detection). And they can know that Santa Claus and imaginary friends are not real if they believe either authorities or their own senses (true baloney detection). Similarly, children also have two kinds of reality-assessment errors: false positive and false negative. Believing in Santa Claus is false positive. Refusing to believe in dinosaurs is false negative. In this figure, adapted from Woolley and Ghossainy, true judgment is in green, errors are in red.

We know a lot about kids’ credulity (Santa Claus, tooth fairy, etc.). But, Woolley and Ghossainy write, their skepticism has been neglected:

It is perplexing that a young child could believe that his or her knowledge of the world is complete enough to deny the existence of anything new. It would seem that young children would understand that there are many things that exist in the real world that they have yet to experience. As intuitive as this seems, it appears not to be the case. From this perspective, development regarding beliefs about reality involves, in addition to decreased reliance on knowledge and experience, increased awareness of one’s own knowledge and its limitations for assessing reality status. This realization that one’s own knowledge is limited gradually inspires a waning reliance on it alone for making reality status decisions and a concomitant increase in the use of a wider range of strategies for assessing reality status, including, for example, seeking more information, assessing contextual cues, and evaluating the quality of the new information.

The “realization that one’s own knowledge is limited” is a vital development, ultimately necessary for being able to tell fact from fiction. But, sadly, it need not lead to real understanding – under some conditions, such as, apparently, the USA today, it often leads instead to reliance on misguided or dishonest authorities who compete with science to fill the void beyond what we can directly observe or deduce. Believing in Santa because we can’t disprove his existence is a developmental dead end, a backward-looking reliance on authority for determining truth. But so is failure to believe in germs or vaccines or evolution just because we can’t see them working.

We have to learn how to inhabit the green boxes without giving up our love for things imaginary, and that seems impossible without education in both science and art.

Rationalizing gifts

What is the essence of Santa, anyway? In Kaplan’s NYT essay it’s all about non-rationalized giving — for the sake of giving. The latest craze in Santa culture, however, says otherwise: Elf on the Shelf. According to Google Trends, interest in this concept has increased 100-fold since 2008. In case you’ve missed it, the idea is to put a cute little elf somewhere on a shelf in the house. You tell your kids it’s watching them, and that every night it goes back to the North Pole to report to Santa on their nice/naughty ratio. While the kids are sleeping, you move it to another shelf in house, and the kids delight in finding it again each morning.

Foucault is not amused. Consider the Elf on a Shelf aftermarket accessories, like these handy warning labels, which threaten children with “no toys” if they aren’t on their “best behavior” from now on:

So is this non-rationalize gift giving? Quite the opposite. In fact, rather than cultivating a whimsical love of magic, this is closer to a dystopian fantasy in which the conjured enforcers of arbitrary moral codes leap out of their fictional realm to impose harsh consequences in the real life of innocent children.

Inequality

What does all this mean for inequality? My developmental question is, what is the relationship between belief in Santa and social class awareness over the early life course? In other words, how long after kids realize there is class inequality do they go on believing in Santa? Where do these curves cross?

Beyond worrying about how Santa rewards or punishes them individually, if children are to believe that Christmas gifts are doled out according to moral merit, than what are they to make of the obvious fact that rich kids get more than poor kids? Rich or poor, the message seems the same: children deserve what they get. Of course, I’m not the first to think of this:

Conclusion

I can’t demonstrate that believing in Santa causes children to believe that economic inequality is justified by character differences between social classes. Or that Santa belief undermines future openness to science and logic. But those are hypotheses.

Between the anti-science epidemic and the pervasive assumption that poor people deserve what they get, this whole Santa enterprise seems risky. Would it be so bad, so destructive to the wonder that is childhood, if instead of attributing gifts to supernatural beings we instead told children that we just buy them gifts because we love them unconditionally and want them — and all other children — to be happy?

First look: 2013 divorce rates show big drop

The 2013 American Community Survey (ACS) is out, and with it the numbers we need to update the divorce rate trend.*

These are the estimates based on the giant sample: In 2013 there were 63,951,934 married men, and  63,619,135 married women. In 2013, 1,071,278 men and 1,197,095 women reported getting divorced in the 12 months prior to their interview. That means the refined divorce rates — divorces per 1,000 married people — were 16.8 for men and 18.8 for women. Wow! Look at the trend now:

That’s a very big drop, almost as big as the 2009 drop. What does this mean? It’s too early to say without more investigation, but consider it in light of my analysis of the recession period. Starting with the 2008 data, it looked to me like there was a big drop at the start of the recession — which we figure is related to the costs of divorce (legal fees, real estate, other transition costs) — and then a rebound as the postponed divorces start to materialize.

I didn’t just guess that based on the trends. I used the variables associated with divorce in 2008 (age at marriage, marital duration, education, race/ethnicity, etc.) to predict divorces in the later years, and found that the prediction was higher than the observed number of divorces, suggesting a deficit of realized divorces.

That interpretation might still be true (which is good, because the paper was published less than a year ago). But the ACS marital events (e.g. ,divorce) data only go back to 2008, so it’s difficult to evaluate the 2009 drop in historical perspective. Now we have to wonder: What if 2009 was really closer to the “normal” rate of divorce decline, and really the recession just gave us the 2010-2012 increase, and no drop? I’m not ready to conclude that, of course. My analysis still makes sense. And there is previous research (cited in the paper) that shows declines in divorce during recessions. But 2013 is going to have to be explained somehow.

I have an idea. I’ll just hop over to the government’s official divorce statistics page to compare these ACS numbers with the actual number of divorces recorded. Wait, what?

Hm. Well, OK, there’s no “detailed data” from the vital statistics system anymore. But surely there is at least a simple count available? I’ll just click on “National marriage and divorce rate trends,” to get those. Um…

So these numbers only go through 2011, and they exclude 6 states, which together account for 20% of all US divorces. Here’s a good data exercise: find another rich country that doesn’t have a count of its own marriages and divorces.

As I have pointed out in increasingly alarmed tones (in this post and earlier), the ACS marital events and marital history questions have been slated for removal by the budget powers that be.** Because if there’s one thing we don’t want to spend money on, it’s information. Why bother? We can just do a Google search or use Big Data to count up #imfinallydivorced hashtags. Yes, I just made that up. But the way things are going we may soon be begging Facebook and Google to tell us what’s going on. As Vonnegut might say, “Good luck, America!”

Notes

* The public use files are up on the IPUMS.org site, and the online analysis tool is available for quick analysis, but for this I used the numbers from the full survey, available on the Census Bureau’s American FactFinder, tables 1YR_B12503 and 1YR_B12001. I realize it’s odd that the rates for men and women here differ (by more than would be possible even if lots of women are divorcing other women). This is a survey question, not a count of legal divorces.

**The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

Top 25 cities for Millennial divorce (save the American Community Survey marital history and events questions edition)

First some news, then the urgent story behind the news.

All marriages and divorces are local. Whether and when people marry is dependent on who they meet and the conditions under which their relationships develop — social, economic, and even political. And divorce depends on local factors as well, such as the likelihood or feasibility of meeting alternative partners, the costs and consequences of divorce, and the norms and laws regulating divorce. (The same is true for forming and ending non-marital relationships, but those are harder to measure and their dynamics are different).

The Millennial Divorce Capital

So, I know the question you’re dying to have answered is: Where do Millennials get divorced? This question is so compelling that I’ve suspended my normal objection to arbitrary generational definitions, and let Mellennials be defined as anyone born in 1980 or later — so this is the divorce rate among people roughly ages 15 to 31 in the 2009-2011 American Community Survey.

Measuring divorce is complicated, because you’ve got a lot of choices. Here are two simple ways: The number of divorces among Millennials occurring in the previous year per 1,000 Millennials in the population (the crude Millennial divorce rate), and the number of those divorces per 100 married Millennials (the refined Millennial divorce rate). Think of the crude rate as the chance of meeting a Millennial who just got divorced walking down the street, and the refined rate as the chance that one of your married friends just got divorced. I’ve ranked them by the refined rate for this table, which we can use to crown Portland, Oregon the Millennial Divorce Capital of the United States (it’s #1 on both measures).

This is just the 25 largest Millennial population centers, for which we have the most reliable estimates of divorce rates. Nationally, 6.2 out of every 1,000 living Millennials reported getting divorced in the previous 12 months.

It’s complicated

The differences in the two rates I show can be very important. For example, if I expanded the list to the top 50, you would see that the city in which you are most likely to bump into a divorced Millennial at random (spilling your non-caffeinated beverage) is Salt Lake City, where an astonishing 9.7 out of every 1,000 Millennials got divorced in the past year. That’s not because they love divorce, however, it’s because they love marriage. An amazing 34% of Salt Lake City Millennials in 2009-2011 had already been married, compared to just 23% in Divorce Capital Portland.

On the other hand, it’s not just that more married people means more people available for divorce. It’s also the case that early marriage increases the risk of divorce. And more than that, places where early marriage is common have higher rates, even for people who get married at older ages. In this figure I show an adjusted divorce rate (technically, the predicted chance of divorcing in year 5 given marrying at age 23) by the average age at first marriage in each metro area: Divorce is less common in the late-marriage cities*:

(Note that, to produce this figure, you need a survey that asks millions of people how many times they’ve been married, the year they most recently got married, and whether they got divorced in the past year. You don’t just type this into a Google search box.)

But wait, I’m afraid it’s more complicated than that. And here I’m moving toward the urgent story behind the news.

People move around. Divorce may occur in a split second, but what demographers call “relationship dissolution” unfolds over time. People move after they divorce, they divorce after they move, and they may even get divorced in places other than where they live. The ACS data I’m using here help sort this out. This divorce incidence measure is based on a survey question, not a legal record. As with all the other questions on the survey (age, race, income, education, etc.), we more or less have to trust the answers people give (some implausible answers are edited out by the Census Bureau). If we really want to understand how and where divorce (or marriage) happens, we need to be creative and careful, and use the best data. And this is the best data.

Here’s a simple illustration. This figure shows the percentage of two groups of Millennials in each state who arrived in the past year: Those who are married, and those who just got divorced. For example, in Oregon, home of the Millennial Divorce Capital, 17% of the divorced Millennials lived in a different state last year. So either moving to Oregon led to their divorce, or their divorce led to an interstate migration. In contrast, only 7% of Oregon’s married Millennial population just got there (click to enlarge):

The red line is the diagonal, so states above the line — most states — have more divorced arrivals than married arrivals (I excluded a few states with few cases in the data). There are, naturally, a lot of fascinating ways you might approach these questions. Which brings me to the urgent news.

Save the American Community Survey marital events and history data

I know from experience that some of you are thinking things like, “Break it down by race!”, “What about gay couples?”, and “What about hypergamy?” If you want those answers, get out your wallets. This information doesn’t just happen, it’s garnered through a massive federal data collection, without which our ability to know ourselves and our society would be severely compromised. And that’s what might be about to happen.

The data I just showed came from the American Community Survey (ACS), the large Census Bureau survey that replaced the “long form” of the decennial census in the 2000s. (The data are wonderfully prepared and distributed by the good people at IPUMS.org.) Unlike a simple national random survey — which is a major undertaking in itself — the ACS uses a sophisticated rotating geographic design that samples from all around the country to gather the information we need for all levels of geographic detail – down to the neighborhood.

Filling out this survey, in 3.5 million households, is estimated to take about 2.3 million hours of the American people’s time and cost a fortune. Now the federal government is reviewing the different parts of the survey looking for unnecessary parts, and they have identified 7 questions that could be cut, including the ones I’ve been using here: marital events (did you get married, divorce, or widowed in the last year), marital history (how many times have you been married, when did you get married most recently), and a couple others. So I’m trying to convince you to submit a public comment urging them not to make the cuts.

Why do we need this?

Believe it or not, there is no national count of marriages and divorces. That’s right, your government cannot tell you how many legal marriages and divorces there are. They used to collect this from every state, but now they don’t. States collect this information, but it’s not standardized, and it’s not collected together. And, even if it were, we wouldn’t be able to analyze it with all the detail I’ve used here — using marriage duration, age at marriage, and other important factors. So, even at the national level, this is all we have.

However, just for national marriage and divorce statistics, we wouldn’t need the ACS. We could use a smaller survey, like the Current Population Survey or others. If they wanted to work out one of those alternatives before canceling these questions, that would be OK for national statistics.

However, for smaller populations — state and local populations, minority groups, gay and lesbian couples — there is no alternative. If we lose these questions on the ACS, we lose the ability to do all that. Unfortunately, there is no legal or legislative mandate to collect this information down to the local level, which is why it’s on the chopping block. It’s just super interesting and important, not legally required. So we need to communicate that up the chain of command and hope they listen.

To help motivate and inform you toward that end, here’s a list of what we would not know about divorce without the ACS marital events and history questions, and then the information for contacting the federal government with your comment. These are just from my blog, I haven’t done an exhaustive search. The point is not that I’ve done so much, but that there is so much of vital importance that we can learn from this data.

• The refined divorce rate in 2012 was 19 per 1,000 married people.
• The overall projected divorce rate for couples marrying in 2012 is about 50%. This requires using marriage, divorce, and widowhood incidence to calculate competing risks. You need all the ACS questions for that.
• We lost about 150,000 divorces during and after the recession. Then divorce rebounded to catch up to its (declining) trend. That’s the result of my analysis published in Population Research and Policy Review, which relied on a model using all the ACS individual data in all 50 states.
• People with disabilities are much more likely to get divorced than people without. The magnitude of the difference depends on the type of disability.
• Divorce rates in first marriages are more than three-times as high for Black women as for Asian women in the U.S.
• The 2008-09 refined divorce rate by state was correlated with Google searches for “colt 45 automatic” at .86 (on a scale of -1 to 1).
• The 2011 crude divorce rate by state was correlated with Google searches for “vasectomy reversal” at .79.
• The changing pattern of same-sex marriage across states and local areas. We don’t know this yet, but we should, and we’ll want to, and the ACS is the only way we’ll be able to.

Speak up

The information about the planned cuts to the American Community Survey is here: https://www.federalregister.gov/articles/2014/10/31/2014-25912/proposed-information-collection-comment-request-the-american-community-survey-content-review-results:

Direct all written comments to Jennifer Jessup, Departmental Paperwork Clearance Officer, Department of Commerce, Room 6616, 14th and Constitution Avenue NW., Washington, DC 20230 (or via the Internet at jjessup@doc.gov).

Comments will be accepted until December 30.

* Here’s the mixed-effect multilevel regression testing the relationship between average age at marriage (meanagemarr) and odds of divorcing, controlling for age at marriage and duration of marriage, for 262,269 married people in 283 metro areas:

If you want to see serious research into the effects of age at marriage, local age at marriage, and religion, on divorce, this paper by Glass and Levchak is the right place to start.

Repeated misinterpretation is not causation

The other day I criticized Brad Wilcox and Bob Lerman for claiming that increasing marriage would reduce inequality. In that post I passed up the chance to reinforce a lesson about misleading claims regarding selection and unobserved factors by members of the right-wing family social science community.

Which comes first, social advantages or marriage?
Photo by Jonathan Tellier from Flickr Creative Commons.

Passages like the following have become standard for Wilcox when he makes overblown claims regarding the benefits of marriage. Here is the latest:

Notwithstanding this report’s extensive data analysis, we do not claim that the associations we find among family structure while growing up, marriage as an adult, and economic outcomes are definitively causal. … Even after netting out the effects of many observed differences among individuals, both marriage and economic well-being may be the result of some third factor, such as unobserved differences in personality or character … Moreover, most of the evidence in this report is descriptive and does not derive from a causal model. For all these reasons, this report cannot definitively assert that adolescent family structure and adult marital status have a causal impact on individual and family economic well-being. …  Nevertheless, the evidence is widespread and consistent enough to suggest strong, causal positive roles for being raised in an intact family and for current marriage on a range of important economic outcomes for the average American.

So this is the criteria for evaluating whether selection and omitted variables are a problem — whether the “evidence is widespread and consistent enough”? No. The volume of evidence is irrelevant; what matters is what it means. If people with various kinds of advantages and privileges are more likely to get and stay married, then research that fails to take that into account will always show married people doing better than people who aren’t married. The evidence will be “widespread and consistent,” and that does not mean it means marriage is the cause of their advantages.

I think that repeating this over and over, having been corrected on it many times, qualifies as demagoguery, or the practice of a demagogue, as the OED defines it:

…a political agitator who appeals to the passions and prejudices of the mob in order to obtain power or further his own interests; an unprincipled or factious popular orator.

It’s appealing to passions and prejudices, and taking advantage of the credulity of the friendly media — and abusing their status as professional researchers, in Wilcox’s case with academic tenure — in the service of their own ideological and material interests.

I made this argument in a previous post, which demonstrated widespread and consistent evidence for an assertion that is probably not true because of obvious selection bias: Cars improve child health. There is no end to the ways you can demonstrate this pattern (and I controlled for income, to show how far that gets you), but the ubiquity of the evidence does not correspond with the veracity of the claim that the relationship is causal.

Real research addendum

If, unlike Wilcox and Lerman, you want to consider this set of issues seriously, I must say I don’t mean to imply that there is no causal effect of marriage on anything. But real research that rigorously takes selection into account usually finds the remaining (probable) effects of marriage are small, if still theoretically important. With earnings, for example, a substantial part of men’s marriage effect is due to selection — that is, men who are either already earning more or who are headed for higher earnings are more likely to get married. For example, this recent study by Christopher Dougherty finds that men’s earnings start rising on average more than five years before marriage. You could attribute this to the cultural power of marriage if you think it shows men getting their act together and earning more because they want or plan to get married, but there’s no evidence for that over the interpretation that marriage is a windfall that follows from other advantages — such as physical or mental traits or health, or social advantages such as rich networks of job and relationship connections (none of which is measured directly in the kinds of data we have for these purposes). Alexandra Killewald and Margaret Gough report a similar pattern, although it’s not the focus of their paper. Killewald, in another good piece, does a lot of selection checking for the positive effect of married fatherhood on men’s earnings, before coming down on the side of  a causal story. But her effect, although important, is not anywhere near large enough to lift poor people out of poverty or substantially reduce income inequality in the unlikely event that marriage increased among low-income parents. That’s a different discussion. As I argued the other day, even if marriage is good for married people, those who aren’t married are very unlikely to get the same benefit from marrying that we observe among the married population. They’re different people with different (mostly fewer) assets to capitalize on in marriage.

Data snapshot: Married before

Among newlyweds in the United States, 30% have been married before. Here’s the breakdown by state (click to enlarge):

 

Here’s a list of states and DC, from highest to lowest percent married before:

And here is the Google search most highly correlated with this pattern: Kerrelyn Sparks (correlation = .83):

The top 100 correlated searches is shot through with romance and fantasy novels: Lynsay Sands, romance series, Sherrilyn Kenyon, vampire book, fever series, Jeaniene Frost.

Coming soon: Crouching Tiger, Forbidden Vampire (and your next marriage?):

Why you can’t understand the texting and driving problem in one chart, in one chart

The other day I argued that focus on the “texting-white-driving epidemic” diverts attention from the dangers of driving generally. Here’s a different direction.

The contemporary fascination with using data to tell stories runs up against the need to tell stories in the length of a tweet or in one chart, sometimes resulting in data-focused news that uninforms people rather than informing them.

So, I may not be able to tell the whole teen car death story in one chart, but I can show that you can’t reduce the whole teen car death story to a texting epidemic in one chart (source).

The rate at which teen drivers are involved in fatal crashes has fallen 55% in the last 10 years, faster than the rate for all other age groups (which are also falling). This is part of a long term trend, which has accelerated in the last 10 years. Between 2002 and 2008 alone, the number of text messages sent in the US increased from almost none to more than 100 million per month.* According to the Centers for Disease Control and Prevention’s 2011 national Youth Risk Behavior Survey, reported in Pediatrics, 45% of teens say they texted while driving in the past 30 days — compared with only 10% who said they drove when they had been drinking. An astonishing 12% of teens said they text while driving every day.**

Far be it from me to decide what the public pays attention to. However, we should understand that in this era of distraction there is an opportunity cost to focusing on any one thing. For example (source):

Incidentally, there is a possible clue in that Pediatrics article as to why accident rates aren’t rising due to all this texting. The teens who text while driving are much more likely to engage in other risky behaviors: driving drunk, riding with drunk drivers, and not wearing seatbelts. So texting deaths may to some extent be displacing deaths those same teens would have caused in other ways.

Follow this series of posts at the texting tag.

Notes:

*Thank linked paper argues that texting is contributing to the increase in distracted driving deaths, based on cellphone subscription rates and texts sent per month. It’s plausible but not entirely convincing, because I have doubts about the measure of distracted driving deaths (which rely on local police reports, fluctuate wildly, and include lots of labels, including “carelessness”). They don’t analyze the trend in total traffic deaths.

**This fact may be the source of the myth that 11 teens die from texting and driving every day (less than 8 die daily from all motor vehicle accidents), because someone got carried away by lab studies showing texting while driving was as dangerous as drinking and driving and just extrapolated.

 

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:

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:

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:

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.