The fathers behind teen births (or, statistical memes and motivated blind trust)

When makes people trust statistical memes? I don’t know of any research on this, but it looks like the recipe includes a combination of scientific-sounding specificity, good graphics, a source that looks credible, and – of course – a number that supports what people already believe (and want their Facebook friends to believe, too).

If that’s the problem, and assuming the market can’t figure out how to make journalism work, I have no solution except seizing the Internet and putting it under control of the Minister of Sociology, or, barring that, encouraging social scientists to get engaged, help reporters, and make all their good work available publicly, free, and fast.

Today’s cringe:

The blogger TeenMomNYC takes credit for creating this, and the Facebook version has been shared tens of thousands of times. Its popularity led to this story from Attn: “The Truth About Teenage ‘Baby Mamas’ is Quite Revealing.” (If anyone did want to study this issue, this is a neat case study, because she posted 8 “did you know” graphics on Facebook at the same time, and none of the others took off at all – why?)

I don’t know anything about TeenMomNYC, but I share her desire to stop stigmatizing and shaming young mothers. I wish her work were not necessary, but I applaud the effort. That said, I don’t necessarily think shaming young fathers (even if they’re not quite as young) is a solution to that, but that’s not the point. My point is, what is this statistic?

According to the footnote (thanks!), it comes from this 1995 National Academies report, and (except for changing “29” to “29.7”) it represents it accurately. From p. 205:

These data highlight an additional component of the sexual abuse picture— the evidence that an appreciable portion of the sexual relationships and resulting pregnancies of young adolescent girls are with older males, not peers. For example, using 1988 data from the NSFG and The Alan Guttmacher Institute, Glei (1994) has estimated that among girls who were mothers by the age of 15, 39 percent of the fathers were ages 20–29; for girls who had given birth to a child by age 17, the comparable figure was 53 percent. Although there are no data to measure what portion of such relationships include sexual coercion or violence, the significant age difference suggests an unequal power balance between the parties, which in turn could set the stage for less than voluntary sexual activity. As was recently said at a public meeting on teen pregnancy, “can you really call an unsupervised outing between a 13-year-old girl and a 24-year-old man a ‘date’?”

This is an important point, and was good information in 1995, when it cited a 1994 analysis of 1988 data, which asked women ages 15-44 a retrospective question. In other words, this refers to births that took place as early as 1958, or between 28 and 58 years ago. That is historical, and really shouldn’t be used like this today, given how much has changed regarding teen births.

The analysis is of the 1988 National Survey of Family Growth, a survey that was repeated as recently as 2011-2013. Someone who knows how to use NSFG should figure out the current state of the age gap between young mothers and fathers and let TeenMomNYC know.

Even if I didn’t know the true, current statistic, this would give me pause. Births to women before age 15 are extremely rare. The American Community Survey, which asks millions of women whether they have had a birth in the previous year, does not even ask the question of women younger than 15. The ACS reports there were 179,000 births in the previous year among women who were under 20 when interviewed, of which only 6,500 were to women age 15 at the interview. So that’s 3.7% of teen births, and 3 out of every thousand 15-year-old women. In 1958 this was much more common, and the social environment was much different.

Another issue is the age range of the fathers, 20-29, which is very wide when dealing with such young mothers. Look at the next phrase from the 1995 report: “girls who had given birth to a child by age 17, the comparable figure was 53 percent.” Realize that the great majority of girls who had a birth “by age 17” were 17 when they did, and the great majority of those men were probably close to 20. I’m not very positive about 20-year-old men having children with 17-year-old women, but it’s pretty different from 29-versus-13.

I can’t find the original source for this, but this report from the Resource Center for Adolescent Pregnancy Protection attributes this table to the California Center for Health Statistics in 2002, which shows that the father was age 20 or older  for 23% of women who had a birth before age 15. And of those, 93% were 20-24 (rather than 25+).

Anyway, this is a good case of a well-intentioned but under-resourced effort to sway people with true information, picked up by click-bait media and repeated because people think it will help them win arguments, not because they have any real reason to believe it’s true (or not true).

So I really hope someone with the resources, skills, and training to answer this question will produce the real numbers regarding father’s age for teen births, and post them, with accompanying non-technical language, along with their code, on the Open Science Framework (or other open-access repository).

Fixing the media and its economy is a tall order, but academics can do better if we put our energy into this work, reward it, and restructure our own system so that good information gets out better, faster and more reliably.

Related posts:

• No Black women are not the “most educated” group in the US
• International Women’s Day breathes new life into the 1% meme

Black women really do have high college enrollment rates (at age 25+)

The other day I reported on the completely incorrect meme that Black women are the “most educated group” in the U.S. That was a simple misreading of a percentage term on an old table of degree attainment, which was picked up by dozens of news-repeater websites. Too many writers/copiers and editors/selectors don’t know how to read or interpret social statistics, so this kind of thing happens when the story is just too good to pass up.

I ignored another part of those stories, which was the claim that Black women have the highest college enrollment rates, too. This is more complicated, and the repeated misrepresentation is more understandable.

Asha Parker in Salon wrote:

By both race and gender there is a higher percentage of black women (9.7 percent) enrolled in college than any other group including Asian women (8.7 percent), white women (7.1 percent) and white men (6.1 percent), according to the 2011 U.S. Census Bureau.

You know the rewrite journalists are playing telephone when they all cite the same out-of-date statistics. (That Census report comes out every year — here’s the 2014 version; pro-tip: with government reports, try changing the year in the URL as a shortcut to the latest version.)

But is that true? Sort of. Here I have to blame the Census Bureau a little, because on that table they do show those numbers, but what they don’t say is that 9.7% (in the case of Black women) is the percentage of all Black “women” age 3 or older who are attending college. On that same table you can see that about 2% of Black “women” are attending nursery school or kindergarten; more relevant, probably, is the attendance rate for those ages 3-4, which is 59%.

So it’s sort of true. Particularly odd on that table is the low overall college attendance rate of Asian women, who are far and away the most likely to go to college at the “traditional” college ages of 18-24. That’s because they are disproportionately over age 25 (partly because many have immigrated as adults). But, if you just limit the population to those ages 18-54, Black women still have the highest enrollment rates: 15.5%, compared with 14.6% for Asians, 12.6% for Hispanics, and 12.4% for Whites. Asians are just the most likely to be over 25 and not attending college, most of them having graduated college already.

This does not diminish the importance of high enrollment rates for Black women, which are real — after age 25; the pattern is interesting and important. Here it is:

Under age 25, Black women are the least likely to be in college, over 25 they’re the most likely. This really may say something about Black women’s resilience and determination, but it is not a feel-good story of barriers overcome and opportunity achieved. And, despite her presence in the videos and stories illustrating this meme, it is not the story of Michelle Obama, who had a law degree from Harvard at age 24.

This is part of a pattern in which family events are arrayed differently across the life course for different race/ethnic groups, and the White standard is often mistaken as universal. I have noted this before with regard to marriage (with more Black women marrying at later ages) and infant mortality (which Black women facing the lowest risk of infant death when they have children young). It’s worth looking at more systematically.

ADDENDUM 6/29/2016: Cumulative projected years of higher education

If you take the proportion of women enrolled in each age group, multiply it by the years if the age group (so, for example, 18-19 is two years), and sum up those products, you can get a projected total years in college (including graduate school) for each group of women. It looks like this:

Note this makes the unreasonable assumption that everyone who says they are enrolled in college in an October survey attends college for a full year. So, for example, Asian women are projected to spend 6.2 years in college on average between ages 18 and 54. What’s interesting here is that Black women are projected to spend more years in higher education than White women (5.5 versus 4.9). But we know they are much less likely than White women to end up with a bachelor’s degree (currently 23% versus 33%). This has to be some combination of Black women not spending full years in college, not going to school full time, or not completing bachelor’s degrees after however many years in school. Attendance may be an indicator of resilience or determination, but it’s not as good an indicator of success.

No Black women are not the “most educated” group in the US

I don’t know where this started, but it doesn’t seem to be stopping. The following headlines are all completely factually wrong, and the organizations that published them should correct them right away:

The Root: Black Women Now the Most Educated Group in US

Upworthy: Black women are now America’s most educated group

Salon: Black women are now the most educated group in the United States

Good: Black Women Are Now The Most Educated Group In The U.S.

And then the video, by ATTN:, on Facebook, with 6 million views so far. I won’t embed the video here, but it includes these images, with completely wrong facts:

What’s true is that Black women, in the 2009-2010 academic year, received a higher percentage of degrees within their race/ethnic group than did women in any other major group. So, for example, of all the MA degrees awarded to Black students, Black women got 71% of them. In comparison, White women only got 62% of all White MA degrees. Here is the chart, from the data that everyone linked to (which is not new data, by the way, and has nothing to do with 2015):

For Black women to be the “most educated group,” they would have to have more degrees per person than other groups. In fact, although a greater percentage of Black women have degrees than Black men do, they have less education on average than White women, White men, Asian/Pacific Islander women, and Asian/Pacific Islander men.

Here are the percentages of each group that holds a BA degree or higher (ages 25-54), according to the 2010-2014 American Community Survey, with Black women highlighted:

23% of Black women ages 25-54 have BA degrees or more education, compared with 38% of White women. This does not mean Black women are worse (or that White women are better). It’s just the actual fact. Here are the percentages for PhD degrees:

Just over half of 1% of Black women have PhDs, compared with just over 1% of White women – and almost 3% of Asian/PI women. White women are almost twice as likely to have a PhD and Black women, Asian/PI women are more than 5-times as likely.

Racism is racism, inequality is inequality, facts are facts. Saying this doesn’t make me racist or not racist, and it doesn’t change the situation of Black women, who are absolutely undervalued in America in all kinds of ways (and one of those ways is that they don’t have the same educational opportunities as other groups). There are some facts in these stories that are true, too. And of course, why Black women (and women in general) are getting more degrees than men are is an important question. But please don’t think it’s my responsibility to research and present all this information correctly before it’s appropriate for me to point out the obvious inaccuracy here. You don’t need this meme to do the good you’re trying to do by sharing these stories.

Our current information economy rewards speed and clickability. Journalists who know what they’re doing are more expensive and slower. Making good graphics and funny GIFs is a good skill, but it’s a different skill than interpreting and presenting information. We can each help a little by pausing before we share. And those of us with the skills and training to track these things down should all pitch in and do some debunking once in a while. For academics, there is little extra reward in this (as evidenced by my most recent, sup-par departmental “merit” review), beyond the rewards we already get for our cushy jobs, but it should be part of our mission.

NYT’s Richtel traffic hype soars at historic rate

What if everything you learned about traffic fatalities you got from Matt Richtel at the New York Times?

On April 27, Richtel wrote:

Over the last seven years, most states have banned texting by drivers, and public service campaigns have tried an array of tactics — “It can wait,” among them — to persuade people to put down their phones when they are behind the wheel.

Yet the problem, by just about any measure, appears to be getting worse. Americans confess in surveys that they are still texting while driving, as well as using Facebook and Snapchat and taking selfies. Road fatalities, which had fallen for years, are now rising sharply, up roughly 8 percent in 2015 over the previous year, according to preliminary estimates.

I left the paragraph breaks as they were, so you can see the connection he implied. Sure seems that all that texting is driving up the rate of fatalities, although there is no evidence offed for that. Of course, since you only read Richtel, you don’t know that since 1994, cell phone subscription rates have risen 1200% while traffic fatalities have fallen 13%. (My series on this, with all these facts, is under the texting tag.)

But what about this “now rising sharply” fact? The same fact – an estimated 8% increase in one year, grew from “now rising sharply” on April 27 to “soaring at a rate not seen in 50 years” by May 22.

When I complained to the NYT Science Desk that this was a misleading representation of a traffic fatality rate that is still at historically low levels, someone checked it out and nicely informed me they had “confirmed the article accurately states the fact: preliminary estimates indicate road fatalities are rising at a rate not seen in 50 years.” Complaint denied.

Assuming you share my obsession with this problem of hyping traffic fatalities – and distracting the public with stories of bad drivers instead of paying attention to the real problem, which is rampant car culture itself – then you’ll want to make a distinction between the facts themselves and the NYT representation of them.

Facts

The fact here is actually kind of weird. Instead of using the official traffic fatality rates, which the National Highway Traffic Safety Administration hasn’t released yet for 2015, Richtel here is reporting the preliminary 2015 estimate from a private group, the National Safety Council. The weird thing is that NSC uses a different method, counting people as dead from a traffic incident if they die from any cause within a year of the accident, while NHTSA only counts them as dead from the incident if they die within 30 days. The rule is arbitrary either way, but I prefer to NHTSA method in the absence of a compelling argument. (As any Law & Order fan can tell you, people who die can have that death attributed to something that happened years earlier if the medical examiner owes the detectives a favor.) Not surprisingly, NSC produces estimates that are higher – about 8% higher, about 3,000 deaths more than the roughly 35,000 NHTSA reports. The longer death window seems bad for comparing rates over time, because the population is aging and therefore the death rate will probably rise among people who have had an accident in the previous year just because they’re older on average.

Anyway, since NSC doesn’t report their long-term trend (at least on the free part of their website), I applied their estimate of the “soaring” 2015 change – an 8.2% increase in total deaths – to the NHTSA series (helpfully recorded on this Wikipedia page), to extend the series to 2015. We also now have the Federal Highway Administration’s report on vehicle miles traveled in 2015 (+4% from 2014), so I can use that estimate of total deaths to calculate deaths per mile for 2015, as well as deaths per person (using the average of the Census Bureau’s monthly estimates for the year, which was 321.4 million, +0.8%). By these calculations, Richtel’s soaring 8.2% increase in total deaths becomes a 4% increase in deaths per mile, and a 7.3% increase in deaths per person. Here are the 50-year trends, with recessions shown:

The dramatic increase in deaths for 2015, which is quite large on a relative scale during this time period – in fact, at no time in last 50 years has the number of deaths increase by 8.2% in one year – looks kind of small. But perhaps more important, it seems in line with the cyclical nature of the trend. Death rates fall during recessions and rebound afterwards. In fact, the declines in 2008 and 2009 – which were 9.3% and 9.5% respectively – are also unprecedented during this period, so a larger rebound is not surprising.

Representations

So how should Richtel describe the trend? Keep in mind this is a reporter who is still promoting a book premised on the crisis of distracted driving – the homepage for which, despite notifications to the author and publisher, still repeats the bogus internet meme that 11 teens per day die from texting while driving.

After I complained on Twitter, Richtel tweeted to his followers:

Fatalities soaring at rate not seen in 50 years. (Friends, please ignore white noise) https://t.co/MHjOYEE554. https://t.co/uZM26zvhCa

— matt richtel (@mrichtel) May 23, 2016

So I put the description question to the test of my Twitter readers, offering them a poll. I made two figures, one from the actual death trend (with my 2015 estimate), and one with the same trend in reverse, and asked people (without comment) which one they thought was better described by Richtel’s phrase:

Here are two trends. Based only on the description given, which series do you think fits best? (poll follows) pic.twitter.com/l8ooOIETbv

— Philip N. Cohen (@familyunequal) May 24, 2016

My readers were closely divided, but gave Richtel the edge, 56% to 44%:

Here's the poll: The description given best fits…

— Philip N. Cohen (@familyunequal) May 24, 2016

I don’t think it’s very strong vindication to barely eke out a majority in a poll where people are asked to choose which is right, what you said or the exact opposite of what you said. I would think real reporting would have a higher rate of concordance than that.

Why can’t the texting-panic establishment handle the truth?

Don’t drive distracted, okay? Now for some more updated facts. (Follow the whole series under the texting tag.)

The Diane Rehm show on NPR (Washington station WAMU) did another full episode on the perils of distracted driving. The extremely misleading title of the episode was, “Distracted Driving: What It Will Take To Lower Fatalities.”

The guests were researcher David Strayer; Jeff Larason, director of highway safety for Massachusetts; Joan Claybrook, former administrator of the National Highway Traffic Safety Administration; and Ben Leiberman, the co-founder of Distracted Operators Risk Casualties (DORCs), which is trying to develop the technology (and legislation) to allow police to scan phones at the scene of an accident to determine whether they were being used at the time of the crash.

I am pretty sure that every one of these guests knows that our roads are safer now than they have ever been, and that accident and fatality rates are at historic lows. And yet the entire conversation — without explicitly stating any trend facts — was conducted as if it is self-apparent that the problem is getting worse and worse. Several callers said they see more and more drivers on their phones; someone said one-in-four drivers is using a phone; someone said texting and driving is as dangerous as driving drunk. Maybe more and more people are using their phones while they drive, but that’s not making the roads less safe than they used to be.

Why can’t they handle the truth? Texting and other distractions are dangerous, and people shouldn’t do them — and the roads are getting safer over time. Here are the fatality trends for the last 20 years, from NHTSA:

In the last 20 years, fatalities per mile have fallen 38% and fatalities per person have fallen 34%. That doesn’t make texting and driving okay, okay? But it’s true.

Further, much was made in the conversation about the special risks posed by younger drivers, who are said to be less skilled and more distractable behind the wheel. This also highly misleading. A separate data series, maintained by the Insurance Institute for Highway Safety, has fatal accidents by the age of the driver going back to 1975. This shows that the steepest decline in fatal accidents has been among teenage drivers — a stunning 71% decline in fatal accidents per person in that age group since the peak in 1978. In fact, teen drivers are now involved in fewer fatal accidents per person than 20-34-year-olds:

I can understand that for advocates a story of continuously increasing peril is attractive. That doesn’t justify their refusal to speak facts, but it’s at least predictable. The guests all spoke of the need for more money to be devoted to the problem, more legislation, more awareness — all things that (no offense) pay their personal and professional bills.*

Less forgivable are the journalists who refuse to look seriously at the issue even as they devote inordinate amounts of time to it. This is a serious disservice, because the media-consuming public may want to seriously consider how to allocate resources to address different problems. Call me crazy, but knowing the facts seems important for this process. And in this case it’s not just that the facts are a little out of line with the narrative — they absolutely and dramatically contradict it.

Now for the fact you think I would be reluctant to mention: for the first time in two decades, the rate of property-damage-only accidents has increased for three years in a row. This may be a better measure of accident risk, because the fatality numbers could be partly driven by things like improved medical response time or auto safety devices. Still, property-only accidents per mile are down 21% since 1994 (while mobile phone subscriptions have risen more than 1200%).

That is an interesting turnaround, worth looking into. Unfortunately, I don’t have much confidence in the current crop of experts to offer a credible explanation for it.

* It’s no more surprising than academic professional association staff defending journal paywalls.

Has your marriage lasted 50 years? Congratulations, you’re old

Just kidding: Congratulations, you’re old and have had a long marriage.

The Washington Post magazine has a feature out today called “The secret to a long-lasting marriage.” I don’t have a general comment on it, because I only made it to the third paragraph, and it’s probably worth reading.

But the third paragraph is funny:

They have beaten the odds of death and divorce: Of all current U.S. marriages, only 7 percent have reached the 50-year mark, according to the National Center for Family and Marriage Research at Bowling Green State University.

It is certainly true that making it to the 50-year mark of marriage means you have beaten the odds of death and divorce. But that 7% figure has nothing to do with it, because it includes people who got married yesterday!

Here is the breakdown of when people got married, among people married right now (in the 2014 American Community Survey, which has to be the source for that statistic):

So the statistic is correct: only 7% of currently married people have been married for 50 years or more. Good for them! To bad for all those other people they were born so recently.

It’s all in the denominator. Sure, 50-year marrieds are rare, but compared to what?

With the ACS we can answer a more relevant question, which is this: among living people whose most recent marriage was 50 years ago or more, what is their current marital status? This is a little more encouraging: half are still married.

So let’s restate the original congratulatory message like this:

They have beaten the odds of death and divorce: Of all people who tied the knot 50 or more years ago, and who haven’t yet died, only 50% percent have made it this far without divorcing or becoming widowed, according to the American Community Survey.

Many happy returns.

Why I snarked on a 538 blog post (and I’m sorry)

Gaza. What does inequality have to do with it? (Photo by gloucester2gaza)

The first thing that bugged me about this blog post by Jay Ulfelder at Five Thirty Eight was not the most important thing. The first thing I reacted to was that Ulfelder opened by asking whether “economic inequality causes political turmoil,” and then chastising, “Just because a belief is widely held, however, does not make it true,” before offering only evidence from economics studies. So I tweeted this obnoxious thing:

.@dtchimp If you squint hard enough you may see disciplines other than economics, some of which have studied this question for decades

— Philip N. Cohen (@familyunequal) January 7, 2016

It was obnoxious, and I apologize. That response was part of my routine, defensive, complaining about how complex sociological work is neglected in favor of glib economics (e.g., here, here, here). But I do substantively object to the piece. If I had taken the time to figure out what really bugged me about it I could have sent a more constructive Tweet. Oh well, you never get a second chance to make a first snarky response.

What really bugged me is that the piece reduced this question of world-historic importance to a matter of microdata quality and measurement:

In fact, it’s still hard to establish with confidence whether and how economic inequality shapes political turmoil around the world. That’s largely because of the difficulty in measuring inequality…

Despite the slipperiness of “whether and how,”* Ulfelder’s point is definitely that we are “not there yet” on the question of “the belief that inequality causes political crises.” Still, maybe this is a case of trying to sell a narrow empirical piece as something bigger than it is — in which case it’s also a lesson in how people overreact when you do that.

I have to examine my own motives here, because this is one of those times when someone’s empirical claims threaten something that I don’t routinely subject to empirical testing. If there is an actual article of faith in my sociological worldview — and I would not really use the word faith to describe it, it’s more like a foundational understanding — it’s that inequality causes conflict, which causes social change. Ulfelder notes this is attributed partly to Marx, which is one reason why I and so many other sociologists hold it dear, but it’s also because it’s actually true. But that depends on what you mean by true, and here I think I disagree with Ulfelder, who writes:

With such incomplete and blurry information about the crucial quantities, why are so many of us so sure that economic inequality is a principal cause of political turmoil? Careful observation is one answer. Aristotle and Marx drew inferences about the destabilizing effects of inequality from their deep knowledge of the societies around them.

He never explains why this isn’t good enough, instead wandering into a critique of contemporary activist claims, based in part on an argument that “the seminal economic study” on the question is methodologically flawed (I’m sure it is).

This reducing of the question is too reductionist. I would be very interested to know whether within-country economic inequality, measured at the national level, if accurately measured, could help predict which countries would experience political turmoil, if that could be measured with a single indicator. But that’s not answering the question of whether inequality causes political turmoil — it’s one very narrow slice of that giant historical question, for which we have many sources of data and many affirmative answers.

Use a little of Marx’s “deep knowledge of societies” to consider, for example, the anti-colonial revolutions in many countries after 1945. Do you need to test a within-country economic inequality measure to know that such “turmoil” was one consequence of inequality? Of course, the timing and nature of those revolts is an interesting question to be addressed through research, but is such research asking whether inequality causes conflict?

What about slave revolts? What if someone found that harsher slavery regimes were not more likely to explode in revolt than those in which the slaves had enough food and water — would that tell you that inequality does not “cause” conflict? (Inequality causes conflict; that’s why they’re called slave revolts.)

Even, what about the civil rights movement, women’s movement, gay rights movement, or Black Lives Matter?

Does inequality cause conflict? Yes. Of course the relationship is not necessarily linear or simplistically univariate, which is the subject of lots of great sociology (and probably some minor work in other disciplines). But this is the kind of complex issue that data journalism nowadays loves to turn into yes-or-no, show-me-the-scatterplot short blog posts. I’ve done some of that myself, of course — and if I do it with something that’s a vital part of your analytical worldview, feel free to send me a snarky tweet about it.

* Nothing against this expression in general, it’s just slippery in this case because it might or might not be moving the goalposts from the opening question.