Author Archives: Philip N. Cohen

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.

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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.

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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.

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Survivor bias and the 92% of Southern Black men who support spanking

In today’s New York Times both Michael Eric Dyson and Charles Blow write about spanking. Blow doesn’t mention race and the South, but that’s in the background when we writes:

I understand the reasoning that undergirds much of this thinking about spanking: Better to feel the pain of being punished by someone in the home who loves you than by someone outside the home who doesn’t.

Dyson goes further, and ties the practice back to slave plantations:

Black parents beat their children to keep them from misbehaving in the eyes of whites who had the power to send black youth to their deaths for the slightest offense. Today, many black parents fear that a loose tongue or flash of temper could get their child killed by a trigger-happy cop. They would rather beat their offspring than bury them.

Here are a couple of logical points, and then some data.

First, please note that the rationale some Black parents use doesn’t need to explain all of the practice of beating children, just the difference between Blacks and Whites. Blacks are more likely to support spanking than Whites, but a strong majority of both groups in this country agree spanking is “sometimes necessary.” So not every case of Black parents beating their children is attributable to slavery and racism. Some may be, and the rationale no doubt is in many cases, but that’s not the whole story.

Second, it’s common for people who suffer some disadvantage and survive to attribute their survival to the hardship they suffered. NFL player Adrian Peterson, who beat his 4-year-old son with a stick, said, “I have always believed that the way my parents disciplined me has a great deal to do with the success I have enjoyed as a man.”

If there were 15 boys on a lifeboat, and one survived, he would probably say, “I have always believed that my lifeboat experience has a great deal to do with the success I have enjoyed as a man.” If he were successful in his post-lifeboat life, people might agree with his explanation. In fact, statistics might even show that lifeboat survivors are more successful. Statistically, that’s a survivor bias – the people who should be dragging down the average aren’t alive to weigh in.

A more subtle effect is not just statistical bias but real survival selection — the one lifeboat guy who lives was probably the strongest. So his story seems credible, even though lifeboat populations have very high mortality. In fact, the “Black-White mortality crossover” is a classic puzzle upon which many demographers (including me, though I sadly didn’t get it published) have cut their teeth: At old ages, Blacks have lower mortality rates than Whites (here’s a recent update). That’s partly because to live to old age in Black America you have to be tough (and partly because some old Blacks exaggerate their age, intentionally or unintentionally, which is a cultural expression of the same thing).

Data

Anyway, kudos Harry Enten at 538 for turning to the General Social Survey to show trends in spanking attitudes. He shows that born-again Christians, Blacks, Southerners, and Republicans are all more likely to support spanking. And he did a regression showing those variables all predict spanking agreement when entered together. However, what he doesn’t show is the the interaction most important for today’s news: The support for spanking among Black men raised in the South. (Enten uses the GSS code for where people currently live, when for a question like this I think it’s more appropriate to use the code for where people lived when they were age 16.)

To get a decent sample size (this is down to 211 Southern Black men), I pooled three administrations of the GSS (2008, 2010, 2012), to get this:

spanking race and region.xlsx

Notice the huge gender gaps, which Enten for some reason didn’t consider.  And see that the Southern-at-age-16 people have higher rates of supporting spanking than the currently-Southern. If spanking were a reasonable adaptation to hardship, necessary for children to toughen up and learn to follow orders so they don’t get killed by Whites, why would Black men support it more than Black women?

So 92% of Southern Black men support a “good, hard spanking,” and Charles Barkley was probably right, empirically, when he said spanking was ubiquitous in the South in his childhood. But 75% of non-Southern White men support it, too. So it’s variations on a nearly-universal theme.

And the people who think it helps children because it helped them are not alone among the survivors of difficult childhoods. But that doesn’t mean they’re right.

Clarification: Don’t take the term “survivor” too literally. The lifeboat analogy is just an extreme version of, “15 people experienced harsh beating as a child, and one ended up a successful football player.” People who suffer and succeed often incorrectly attribute their success to their suffering.

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Syllabus supplements for fall family sociology

Last year I posted a list of blog pieces by subject, to help people teaching family courses generate ideas and discussion. Now my book is done and some of that material is in there. If you use the book for your class, we’ll give you all kinds of awesome teaching materials. But if you’re not using it (yet), here’s another list of blog posts to supplement your course. I hope this is useful whether you’re assigning the book or not, and even if you’re teaching something besides a family course.

This is organized according to my table of contents. Please let me know what works and what doesn’t, and offer your additional suggestions in the comments.

1. Introduction

  • What current demographic facts do you need to know? These 22 demographic data points are a good place to start. What else is necessary knowledge just to get through the day without being grossly misled or misinformed?
  • High marks for Census: Describes the cultural shift at the Census Bureau that followed from Obama’s election and the decision to start counting gay and lesbian married couples. Also, a nice video they made explaining how a small error in a large population (mis-marking the sex box) can dramatically distort the number of a small population within it (same-sex couples).
  • Millennial, save thyself: Are millennials in trouble because their ties to marriage, work, and religion are weak? It’s “kids these days” all over again. With some simple data analysis and trends.

2. History

3. Race, ethnicity, and immigration

  • Black is not a color: Black and White are social, not biological, classifications. So why do we treat the words as if they were just colors?
  • Immigrant health paradox update: What can we learn from the surprisingly low infant morality rates of immigrants? Maybe healthier people migrate, but after a generation (or less) in the U.S., their advantage appears to erode.
  • The world that Sabta made: My grandmother lived from 1913 to 2009, and came to the U.S. from Poland in 1921, the youngest passenger on the S.S. Ryndam. Hers is one of the great stories of the century, leaving a mark that goes well beyond her 50+ great-grandchildren.

4. Social class

5. Gender

6. Sexuality

7. Love and romantic relationships

  • Is dating still dead? The death of dating is now 50 years old, and its been eulogized so many times that its feelings are starting to get hurt.
  • Online dating: efficiency, inequality, and anxiety: I’m skeptical about efficiency, and concerned about inequality, as more dating moves online. Some of the numbers I use in this post are already dated, but this could be good for a debate about dating rules and preferences.
  • Is the price of sex too damn low? To hear some researchers tell it in a recent YouTube video, women in general — and feminism in particular — have ruined not only sex, but society itself. The theory is wrong. Also, they’re insanely sexist.

8. Marriage and cohabitation

9. Families and children

10. Divorce, remarriage, and blended families

11. Work and families

12. Family violence and abuse

13. The future of the family

  • Tripping on tipping points: Minority births are now the majority. Is this a tipping point, a milestone, or a watershed? On the importance of accurately representing trends.
  • Dependency futures: An NPR story (linked here) on retirement prompts a look at how US demographic trends may be moving toward a future with more old-age dependency.
  • Marriage is declining globally: Can you say that? Yes, you can say that. But will it continue? We should be careful with predictions, but lots of demographic evidence suggests it will.

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Adjectives for children’s chronic conditions

In the Google ngrams database of American English, I got relative frequencies of the terms x+children, where x is a chronic malady of some sort. I tried a lot of different ones, and only included ones that topped the list at least once in the past 100 years. The most common (as suggested in the comments below) is “handicapped children,” which dominates all others from 1920 to 1995. After that, this is what I came up with, ordered by the period in which they were #1:

  • 1910s: sickly children
  • 1920s: neurotic children
  • 1930s-1950s: maladjusted children
  • 1965-1975: psychotic children
  • Mid-1970s, briefly: hyperactive children
  • Late 1970s-2000s: disabled children

After the mid-1990s, however, “children with disabilities” becomes more common than any of them. I couldn’t find anything in the old days that was as popular as disabled or hyperactive would later become. Does this imply more concern or negative attention to children?

Here is the figure. The frequency of each term is shown in relation to the total uses of “children” (click to enlarge):

childrens-chronic-terms

If you think I missed anything, to play with it yourself, or to see how I did it, here’s the link.

Another question about the same terms: are they individualized (x-child) or grouped (x-children)? Summing all the terms with child, shown as a percentage of all the terms with children (leaving out “with disabilities”), produces this figure (smoothed to a 10-year curve):

childrens-chronic-terms-individual

Individualization peaked from 1920 to 1940, when the combined individual terms outnumbered the plural terms, before sliding till 1990. Now we may be in an individualizing rebound. (Here is the link to that search if you’re interested in the coding).

I get a kick out of language history like this. But I draw no conclusions without further study. Here are some related posts:

 

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Diversity is the new normal

I have new briefing paper out today with the Council on Contemporary Families, titled “Family Diversity is the New Normal for America’s Children.” I’ll post news links soon. In the meantime:

I’m happy to provide high quality graphics.

Let me know what you think!

Reports and commentary:

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