Category Archives: In the news

Pregnancy discrimination and the gender gap, involuntary job choice edition

From Rachel Swarns at the New York Times comes the story of a woman, Angelica Valencia, fired from her $8.70-an-hour produce packing job because her doctor said she couldn’t work overtime because she was three months into a risky pregnancy. There actually is a new law on her side, but her employer somehow didn’t get around to notifying her of her right to reasonable accommodation.

Before reading my comment on this, why not check out this new video from the chapter on gender in my book. The video accompanies a much more compelling version of this graphic, showing the gender composition of some occupations, calculated from the American Community Survey:

figures 4-6.xlsx

Count that gender gap

OK, Back to Angelica Valencia. I’m not an expert on pregnancy discrimination, but I want to use this to comment on how we look at the gender gap in pay. The Census Bureau reports on the gender gap this way:

In 2013, the median earnings of women who worked full time, year-round ($39,157) was 78 percent of that for men working full time, year-round ($50,033).

Critics complain that this doesn’t account for occupational choice, time out of the labor force, and so on. As Ruth Davis Konigsberg sneeringly put it in Time:

Women don’t make 77 cents to a man’s dollar. They make more like 93 cents, as long as they don’t major in art history.

And Hanna Rosin helpfully explained:

Women congregate in different professions than men do, and the largely male professions tend to be higher-paying.

So what does the story of Angelica Valencia pregnancy tell us (besides the pitfalls of majoring in art history)? Valencia may end up winning some back pay in a lawsuit. But let’s assume someone just like her didn’t, and ended up instead in a lower-paying job that doesn’t like overtime, such as at McDonald’s. If we insist on statistically controlling for occupation, hours, job tenure, and time out of the labor force in order to see the real wage gap, people like Valencia may not show up as underpaid women — if they’re paid the same as men in the same jobs, holding constant hours, job tenure, and time out of the labor force. So the very thing that makes Valencia earn less — being fired for getting pregnant — disappears from the wage gap analysis. Instead, the data shows that women take more time off work, work fewer hours, change jobs more often, and “choose” less lucrative occupation.

Sure, a lot of women chose to get pregnant (and a lot of men choose to become fathers). But getting fired and ending up in a lower paid job as a result is not part of that choice (and it doesn’t happen to fathers). The overall difference in pay between men and women, which reflects a complicated mix of factors, is a good indicator of inequality.

For background on the motherhood penalty in wage, you might start here or here (including the sources citing these).

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Life expectancy update, disparity edition

The good news is that U.S. life expectancy is at a record high, 78.8 as of 2012.

What about life disparity — the inequality in life expectancy? With the economic crisis and rise in income inequality, it would be great to know. However, the National Center for Health Statistics hasn’t released detailed life tables with data more recent than 2008, so I can’t yet update the data for the analysis I did last year, so here it is reposted instead:

Life Expectancy, Life Disparity

Reposted from July 23, 2013

In 2008 the life expectancy at birth in the U.S. was 78.1. That means that if a group children born in 2008 lived every year of their lives exposed to the risks of death observed in 2008, their average lifespan would be 78.1 years. But those who made it to age 60 would live an average of 22.7 more years, for a total of 82.7. And those who live to age 99 would live an average of 2.4 more years, for an average of 101.4.

So “life expectancy” as commonly used is not a prediction of how long today’s babies will live — since we hope the future is better than living 2008 over and over — and it’s not a prediction of how long your elderly loved ones will live.

Life disparity

Life expectancy — for any age — is a measure of central tendency: the average number of years of life remaining. And so there is a dispersion around that mean. That dispersion is inequality. A very nice article in the open-access journal BMJ Open, by James Vaupel, Zhen Zhang and Alyson A van Raalte, describes the measure of life disparity. It’s complicated, but a neat tool.

Life disparity is the average number of years people are expected to live when they die. For example, in the U.S. in 2008 an infant who died on the first day of life died 78.1 years early. And a 78-year-old who died, counterintuitively, died 10 years early (since the life expectancy at 78 is 10). To understand what this measure means, consider that if everyone died at exactly 78.1 years of age, life expectancy would be unchanged but life disparity would be 0. On the other hand, the greatest life disparity would occur if all early occurred at age 0.

Life disparity and life expectancy usually go together. That’s because reducing early deaths has the biggest effect on both measures. Here is the cool figure from that paper:

The association between life disparity in a specific year and life expectancy in that year for males in 40 countries and regions, 1840–2009. The black triangle represents the USA in 2007; the USA had a male life expectancy 3.78 years lower than the international record in 2007 and a life disparity 2.8 years greater. The brown points denote years after 1950, the orange points 1900–1949 and the yellow points 1840–1900. The light blue triangles represent countries with the lowest life disparity but with a life expectancy below the international record in the specific year; the dark blue triangles indicate the life expectancy leaders in a given year, with life disparities greater than the most egalitarian country in that year. The black point at (0,0) marks countries with the lowest life disparity and the highest life expectancy. During the 170 years from 1840 to 2009, 89 holders of record life expectancy also enjoyed the lowest life disparity.

The association between life disparity in a specific year and life expectancy in that year for males in 40 countries and regions, 1840–2009. The black triangle represents the USA in 2007; the USA had a male life expectancy 3.78 years lower than the international record in 2007 and a life disparity 2.8 years greater. The brown points denote years after 1950, the orange points 1900–1949 and the yellow points 1840–1900. The light blue triangles represent countries with the lowest life disparity but with a life expectancy below the international record in the specific year; the dark blue triangles indicate the life expectancy leaders in a given year, with life disparities greater than the most egalitarian country in that year. The black point at (0,0) marks countries with the lowest life disparity and the highest life expectancy. During the 170 years from 1840 to 2009, 89 holders of record life expectancy also enjoyed the lowest life disparity.

Countries at the bottom left (0,0) have both the world’s highest life expectancy and the lowest life disparity in the world for that year, which occurred 89 times over 170 years. Countries below the diagonal have relatively low life disparity given their life expectancy; those above the diagonal (like the U.S.) have higher-than-expected life disparity for their level of life expectancy. In our case that reflects the fact that we do a pretty good job keeping old people alive, but let too many young people die.

U.S. improvement

The good news is that life expectancy is increasing in the U.S. (and most other places), and that the inequality between Blacks and Whites is getting smaller, as reported by the National Center for Health Statistics. That is, the Black-White inequality in average expectation of life at birth has shrunk.

The mixed news is that life disparity is much higher for Blacks than Whites — but that gap is falling as well. Here are those numbers for 1998 and 2008 (I did the life disparity calculations from this and this, and will happily share the spreadsheet). Click to enlarge:

expectancydisparity

So Black deaths are more dispersed than White deaths: 14 and 13 for males and females, compared with 12 and 11. For comparison, the Swedish female life disparity is 9. What does a higher disparity mean? Generally, a larger share of early deaths. That’s why the race gap in life expectancy at birth is greater than the race gap in life expectancy at older ages — average 65-year-old Whites and Blacks have more similar life expectancies than do infants.

Why is life disparity more interesting than life expectancy alone, and how does this help explain Black-White inequality in the U.S.? For one thing, high life disparity indicates either relatively unhealthy or dangerous living conditions at younger ages. So it’s partly a measure of the quality of life. Vaupel et al. add:

Reducing early-life disparities helps people plan their less-uncertain lifetimes. A higher likelihood of surviving to old age makes savings more worthwhile, raises the value of individual and public investments in education and training, and increases the prevalence of long-term relationships. Hence, healthy longevity is a prime driver of a country’s wealth and well-being. While some degree of income inequality might create incentives to work harder, premature deaths bring little benefit and impose major costs. Moreover, equity in the capability to maintain good health is central to any larger concept of societal justice.

I think what they say about differences between countries would apply to differences between groups within a society as well.

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

The people who make up these things drive me bananas.

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

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

But what’s a generation?

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

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

mellenials.xlsx

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

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

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

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

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

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

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

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

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

Notes

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

** Thanks to Mo Willow for pointing this out.

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The persistence of gender differences, Catholic furor edition

The Pope’s convention of male moral pontificators is convening to discuss family matters. One of the most important questions, as Ross Douthat has described at great length, is how to strike the right balance between laxity and rigorism on the question of divorce, to maximize Church membership by keeping divorced people (and their children) on the rolls while sending the minimum of those members to hell for adultery after they remarry.

catholic-laxity-game

(This is a great project for a sociologist interested in simulations.)

Divorce is a leading issue, but homosexuality looms. In yesterday’s New York Times, Frank Bruni writes about the American Catholic Church leadership’s obsession with homosexuality:

…Catholic officials here have elected to focus on this one issue and on a given group of people: gays and lesbians. Their moralizing is selective, bigoted and very sad. It’s also self-defeating, because it’s souring many American Catholics, a majority of whom approve of same-sex marriage, and because the workers who’ve been exiled were often exemplars of charity, mercy and other virtues as central to Catholicism as any guidelines for sex. But their hearts didn’t matter. It was all about their loins. Will the church ever get away from that?

As Bruni reports, employees at Catholic institutions are still being fired for acknowledging their homosexuality (the starting point, incidentally, of the new movie Love Is Strange, for the couple played by John Lithgow and Alfred Molina).

loveisstrange

Bruni may speak for the majority of American Catholics when he condemns the Church’s witch-hunt. But as the synod approached, a group speaking for the academic right wing of the anti-gay movement within American Christianity beseeched the Holy Father to use the occasion to “express timeless truths about marriage,” which are that cohabitation, divorce, homosexuality, and pornography are wrong.

(Aside: Academics will appreciate the funny requests for money for themselves and their movement in the letter. They want money for “cross-discipline, longitudinal research on the role of pornography and ‘no fault’ divorce in the marriage crisis,” and they want “mandatory courses [for seminarians] covering social science evidence on the benefits of marriage, threats to marriage, and the consequences of divorce and cohabitation to children and society.”)

The letter calls for opening a new front in the war on modern marriage law, using the language of religious freedom to prevent divorce (as they have urged with regard to marriage equality):

Many do not know that religious freedom is routinely violated by divorce judges who ignore or demean the views of a spouse who seeks to save a marriage, keep the children in a religious school, or prevent an abandoning spouse from exposing the children to an unmarried sexual partner.

In other words, they want to argue — in court — that divorced spouses who have new partners are violating the religious freedom of their ex-spouses. (By this logic, I guess, I could argue that them even making this argument violates my religious freedom not to live in a society where someone makes this argument.)

They would like the Pope to:

Support efforts to preserve what is right and just in existing marriage laws, to resist any changes to those laws that would further weaken the institution, and to restore legal provisions that protect marriage as a conjugal union of one man and one woman, entered into with an openness to the gift of children, and lived faithfully and permanently as the foundation of the natural family.

Regnerus himself (follow the Regnerus tag for background) is taking the long view in his new role as movement intellectual. And the logic he uses helps explain Bruni’s puzzle over the Church’s homosexuality obsession. In an interview on a Christian radio station last month, Regnerus said there are a lot of objectionable marriage laws outside the same-sex marriage debate. He went on:

It’s important for us to not sort of just get caught up in the big kahuna around same-sex marriage, and to remember, as we’ve seen with the abortion debate, incremental change, legally, can occur even after all hope seems lost. But there’s also sort of – nobody’s holding us back from creating a marriage culture in, say, the Catholic Church or broader evangelicalism. We hold ourselves back, right? I tend to think the way things are rolling at the moment, it’s not just as if same-sex marriage fell out of the sky, and was on our plate. I mean, it was paved, right? The road to there was paved in part by all sorts of poor laws around opposite-sex marriage, right? And the giving away of what we might call the sort of functional definition of marriage, visions of complementarity, you know? We have bought, hook, line, and sinker, the idea that essentially men and women are interchangeable in our marriages. And it’s hard to get away from that, but I think we’re going to have to. So in some ways we want to fashion a counter-cultural movement regardless of what the states signal.

The way I see the way he sees it, the mission is to protect and restore gender differentiation itself. That agenda, not just old-fashioned patriarchal views, underlies the anti-homosexual obsession, the opposition to marriage equality and single motherhood, and the effort to protect the male religious hierarchy.

Different genders

I object to this agenda personally on moral grounds, naturally. But my scientific opinion is that the concern is misplaced. In some broad ways, of course, gender differences have eroded — for example, as women have gained political rights and access to gainful employment. And on the rare occasions when they choose to, men can even be nurses, teachers, and stay-at-home parents. You might call all that a convergence of gender roles. But gender differentiation is alive and well.

boysactivities

In some respects the gender binary is resurgent after a brief surge of androgyny in popular culture around 1970 (which Jo Paoletti traces in the fascinating forthcoming book, Sex and Unisex). A visit to the Sociological Images Pinterest board on pointlessly gendered products helps reinforce this point — there are even gendered kids’ Bibles:

kidsbibles

Or consider the relative frequency of the phrases “toys for boys” and “toys for girls” in American English as a fraction of references to “toys for children,” from Google ngrams:

toysngrams

In fact, it seems to me that gender difference is proliferating. But it’s not just the binary difference.

One of the benefits of the high visibility of the marriage rights movement has been its exposure of gender variance. Far from a convergence around a single gender, as the traditionalist Christians fear — or the elimination of gender — instead I think we have a growing diversity of gender perspectives and identities. The very narrow interpretation of this is that “men and women are interchangeable.” The reality is that no one is.

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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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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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My rejection of the National Marriage Project’s “Before ‘I Do'”

All day today, “The Decisive Marriage” has topped the New York Times most-emailed list. The piece is a Well Blog post, written by Tara Parker-Pope, which reports on a report published by the National Marriage Project and written by Galena Rhoades and Scott Stanley, “Before ‘I Do': What Do Premarital Experiences Have to Do with Marital Quality Among Today’s Young Adults?”

I have frequently criticized the National Marriage Project, run by Bradford Wilcox (posts listed under this tag), and I ignore their work when I can. But this report is getting a lot of attention now and several people have asked my opinion. Since the research in the report has not been subject to peer review, and the Pope piece does not include any expert commentary from non-authors, I figured I’d structure this post like the peer review report I would dash off if I had been asked to review the piece (it’s a little different because I have access to the author and funding information, and I wouldn’t include links or graphics, but this is more or less how it would go if I were asked to review it).

Before “I Do”

This paper reports results from an original data collection which sampled 1,294 people in 2007/08, and then followed an unknown number of them for five years. The present paper reports on the marriage quality of 418 of the individuals who reported marrying over the period (ages 18-40). The authors provide no information on sample attrition or how this was handled in the analysis, or the determinants of marriage within the sample. Although they claim (without evidence) that the sample was “reasonably representative of unmarried adults,” they note it is 65% female, so it’s obviously not representative. More importantly, the analysis sample is only those who married, which is highly select. Neither sexual orientation of the respondents, nor gender composition of the couples described is reported.

The outcome variable in the study is a reasonable measure of “marital quality” based on a four-item reduced-form version of the Dyadic Adjustment Scale (originally developed by Graham Spanier), which includes these items:

  • How often do you discuss or have you considered divorce, separation, or terminating your relationship?
  • In general, how often do you think that things between you and your partner are going well?
  • Do you confide in your mate?
  • Please circle the dot which best describes the degree of happiness, all things considered, of your relationship.

The authors provide no details on the coding of these items, but say the scale ranges from 0 to 21, and their sample included people who scored from 0 to 21. However, the mean was 16.5 and the standard deviation was 3.7, indicating a strong skew toward high scores. Inexplicably, for the presentation of results the authors dichotomize the dependent variable into those they classify as “higher quality,” the 40% of respondents who scored (19-21), versus everyone else (0-18). To defend this decision, the authors offer this non-explanation, which means exactly nothing:

This cut point was selected by inspection of the distribution. While it is somewhat arbitrary, we reasoned that these people are not just doing “above average” in their marriages, but are doing quite well.

The average marriage duration is not reported, but the maximum possible is 5 years, so we are talking about marriage quality very early in these marriages.

The main presentation of findings consists of bar graphs misleadingly labeled “Percent in Higher-Quality Marriages, by…” various independent variables. These are misleading because, according to the notes to these figures, “These percentages are adjusted for race/ethnicity, years of education, personal income, religiousness, and frequency of attendance at religious services.” Here is one:

stanleygraph

The method for arriving at these “adjusted” percentages is not given. This apparently confused Parker-Pope, who reported them as unadjusted percentages, like this:

People who lived with another person before marrying also reported a lower-quality relationship. In that group, 35 percent had higher-quality marriages. Among those who had not lived with another romantic partner before marriage, 42 percent had higher-quality marriages.

The statistical significance of this difference is not reported. However, if this were a simple difference of proportions, the difference would not be statistically significant at conventional levels (with a sample of 418, 39% of whom lived with someone else before, the test for difference of proportions for .42 and .35 yields a z-score of 1.43, p=.15). The full report includes an appendix which says they used multilevel modeling, but the form of the regression is not specified. The regression table provided includes no fit statistics or variance components so the efficacy of the model cannot be evaluated.

Regression says: Adding 100 people to the wedding party 5 times would not equal the effect on marital quality of not being Black.

Regression says: Adding 100 people to the wedding party 5 times would not equal the effect on marital quality of not being Black.

Much is made here (and in the Pope article about these findings) about the wedding-size effect. That is, among married couples, those who reported bigger weddings had higher average marriage quality. The mean wedding size was 117. In the regression model, each additional wedding guest was associated with an increase in marriage quality (on the 0-21 scale) of .005. That is, if this were a real effect, adding 100 wedding guests would increase marital quality by half a point, or less than 1/7 of a standard deviation. For comparison, in the model, the negative effect of being Black (-2.69) is more than 5-times greater than the effect of a 100-guest swing in wedding attendance. (The issue of effect size did not enter into Pope’s description of the results.)

The possibility of nonlinear effects of wedding size or other variables is not discussed.

Are the results plausible?

It is definitely possible that, for example, less complicated relationship histories, or larger weddings, do contribute to marital happiness early in the marriage. The authors speculate, based on psychological research from the 1970s, that the “desire for consistency” means “having more witnesses at a wedding may actually strengthen marital quality.”

Sure. The much bigger issue, however, is two kinds of selection. The first, which they address — very poorly — concerns spurious effects. Thus, the simplest explanation is that (holding income constant) people with larger weddings simply had better relationships to begin with. Or, because personal income (not couple income — and note only one person from each couple was interviewed) is at best a very noisy indicator of resources available to couples, big weddings may simply proxy for wealthier families.

Or, about the finding that living with someone else prior to the current relationship is associated with poorer marriage quality, it may simply be that people who have trouble in relationships are more likely to have both lived with someone else and have poor quality marriages later. Cherlin et al. have reported, for example, that women with a history of sexual abuse are more likely to be in transitory relationships, including serial cohabiting relationships, so a history of abuse could account for some of these results. And so on.

The authors address this philosophically, which is all they can do given their data:

One obvious objection to this study is that it may be capturing what social scientists call “selection effects” rather than a causal relationship between our independent variables and the outcome at hand. That is, this report’s results may reflect the fact that certain types of people are more likely to engage in certain behaviors—such as having a child prior to marriage—that are correlated with experiencing lower odds of marital quality. It could be that these underlying traits or experiences, rather than the behaviors we analyzed, explain the associations reported here. This objection applies to most research that is not based on randomized experiments. We cannot prove causal associations between the personal and couple factors we explore and marital quality.

However, because they have rudimentary demographic controls, and the independent variables chronologically precede the outcome variable, they think they’re on pretty firm ground:

With the help of our research, we hope current and future couples will better understand the factors that appear to contribute to building a healthy, loving marriage in contemporary America.

This is Wilcox’s standard way of nodding to selection before plowing ahead with unjustified conclusions. This is not a reasonable approach, for reasons apparent in today’s New York Times. Tara Parker-Pope does not mention this issue, and her piece will obviously reach many more people than the original report or this post.

They hope people will take their results as relationship advice. In Pope’s piece, Stanley offers exactly the same advice he always gives. If that is to be the case, the best advice by far — based on their models — is to avoid being Black, and to finish high school. Living with both one’s biological parents at age 14 helps, too. In relationship terms, unfortunately, most of the results could just as easily reflect wealth or initial relationship quality rather than relationship decisions, and thus tell us that people who have healthy (and less complicated) relationships before marriage have healthy relationships in the first few years after marriage.

Perhaps more serious, however, for this study design, is the second kind of selection: selection into the sample (by marriage). Anything that affects both the odds of marrying and the quality of marriage is potentially corrupting these results. This is a big, complicated issue, with a whole school of statistical methods attached to it. Unless they attend to that issue this analysis should not be published.

On the funding

The authors state the project was “initially funded” by the National Institute of Child Health and Human Development, but the report also acknowledges support from the William E. Simon Foundation, a very conservative foundation that in 2012 gave hundreds of thousands of dollars to the Witherspoon Institute (which funded the notorious Wilcox/Regnerus research on children of same-sex couples), the Heritage Foundation, the Hoover Institute, the Manhattan Institute, and other conservative and Christian activist organizations. Details on funding are not provided.

The National Marriage Project is well-known for publishing only work that supports their agenda of marriage promotion. Some of what they publish may be true, but based on their track record they cannot be trusted as honest brokers of new research.

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