Category Archives: In the news

That Sunday New York Times Style section trend piece

Just folks trying to survive their divorces.

Just folks trying to survive their divorces.

Does it matter which one?

You know it from the opening paragraphs:

The women are architects, film industry executives, skin care consultants, product managers at tech companies, psychologists. They have worked in finance, publishing and television, though some had scaled back or left the work force when their children were born.

Divorce is what they have in common. Their stories are varied: the breadwinner wife whose husband’s career hadn’t quite taken off and who found comfort in an affair; the husband who never really adapted to parenthood; the wife with Ivy League degrees who stayed home with her child but lost her way in the marriage while the husband thrived in his international career.

Really. Divorce is what they have in common? How hard would it be to include a single mention of how rich and privileged these women are compared to the typical woman getting divorced? Penelope Green’s story never mentions the possibility.

Here is what a five-minute effort would have looked like:

top10divoccs

These 10 occupations account for 25% of all women age 40+ who reported getting divorced in the previous year.

In addition, 34% of those just-divorced, 40+ women are not non-Hispanic Whites (14% Black, 13% Hispanic, 4% Asian/Pacific Islander).

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Goffman dissertation followup

I previously reviewed Alice Goffman’s book On The Run, and wrote a critique of the survey that was part of that project (including a formal comment sent to American Sociological Review). Then I complained that her dissertation was not made public, despite being awarded the American Sociological Association’s dissertation prize. I proposed a rule change for the association, requiring that the winning dissertation be “publicly available through a suitable academic repository by the time of the ASA meeting at which the award is granted.”

Here’s a quick followup.

shelf_of_dissertations_500

I was interested in Goffman’s 2010 dissertation because I thought it might have more information about the survey she conducted than the 2014 book did. When I inquired about the dissertation on June 4 of this year, Princeton’s director of media relations, Martin Mbugua, told me she “was granted an exemption from submitting her dissertation to the University Archives, so we do not have a copy of her dissertation in our collection.”

Jesse Singal at New York magazine reported yesterday that they now have the dissertation, and he’s read it. Not only does it not have more methodological information than the book, Singal reports, it actually has less, as the methodological appendix that’s in the book is not in the dissertation. In a saved-you-a-trip-to-Princeton email to me, Singal says the dissertation’s description of her survey is “basically identical” to what is in ASR. That speaks to my critique of her survey, which seems unaffected by the release of the dissertation. (I’m not in charge of dissertations at Princeton, so I’m not critiquing the dissertation anyway.)

With regard to the open-science-inspired rule change for ASA dissertation awards, Singal’s article just reinforces my desire to see the rule adopted. Mbugua told Singal that Princeton now allows up to two two-year embargo periods for PhD students who don’t want their dissertations publicly released. But why embargo it? I think most people do this because they don’t want to undermine their book deals. The need for this may be overstated, but it’s a thing. (Eric Schwartz who acquires sociology books for Columbia University Press, tweeted: “No problem. Book and dissertation are for different audiences.”)

Anyway, Singal quotes Goffman giving a quite different reason:

The dissertation contained very sensitive material about people who were vulnerable to arrest and incarceration. … I wanted to think through the ethical and human subjects issues of making it available beyond the committee members and I wanted some time to go by between the actual events and a public reading. That felt safer for the people who had granted me permission to write about their lives, and for me, than publishing right away.

Apart from the fact that this concern did not prevent Goffman from submitting her book to a reading by an awards committee — “beyond the [dissertation] committee members” — I do not find this very credible, and I don’t like that rationale. If it was wrong to release it in 2010 because it would endanger her subjects, then it was wrong to publish a book in 2014 with the same — actually, more — incriminating information. In fact, as we now know, identifying the individuals mentioned in the book was trivial using Google, and of course the police knew who they were anyway. By this rationale, I cannot understand why the dissertation would not be given to the library until 14 months after the book was published — or until three months after the commercial paperback edition was published. Oh, wait.

Look, if people want to embargo their dissertations for financial gain, and their elite private universities allow it, then so be it. But that doesn’t have to be ASA’s problem. We can add one small piece to that calculation: giving up the ASA Dissertation Award.

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Colorado leads drop in teen birth rate, 2008-2013

Yesterday I tweeted a figure of teen birth rate changes based on the fertility question in the American Community Survey. It showed Colorado with an above-average drop in teem births from 2008 to 2013, but not the biggest drop in the country. I have a better chart on this below.

The reason for the attention was this story in the New York Times, which reported:

Over the past six years, Colorado has conducted one of the largest experiments with long-acting birth control. If teenagers and poor women were offered free intrauterine devices and implants that prevent pregnancy for years, state officials asked, would those women choose them?

They did in a big way, and the results were startling. The birthrate among teenagers across the state plunged by 40 percent from 2009 to 2013, while their rate of abortions fell by 42 percent, according to the Colorado Department of Public Health and Environment.

Since the article didn’t provide data for comparisons, and I knew teen births were declining all over, I wanted to see if Colorado’s experiment was really such a standout. The figure was republished by German Lopez at Vox.com in a post on the Colorado program. Although the figure showed Colorado with a big drop, it still cast doubt on the program because it showed four states and DC with bigger drops.

I’m retracting that figure today, because I realized — and I should have known this — that we have teen birth rates by state and year from the vital records data reported by the National Center for Health Statistics. In these reports we can see that Colorado did, in fact, have the largest decline in teen births from 2008 and 2013 (their program started in 2009). Here’s the new figure:

teenbirthratechangestates

The story isn’t that different between NCHS and ACS data, but Colorado is trying to raise money to continue the program, and it sure is nice for them to have this comparison. It’s great to have data right away — and share it — and it’s also great, even greater, to have better data. The vital records data is more complete and reliable, since it is not based on a sample, and teen births are rare enough now that sampling variation matters, even in a big sample like the ACS. So I regret that I published the earlier figure.

That said…

The teen birth rate is declining all over the country, even in places with terrible policies, so the Colorado program — valuable as it may be — is swimming with the tide.

The reason teen births are declining all over is because the teen birth rate is a myth — what’s really happening is women in the U.S. are having their children later, for economic and social reasons that go way beyond what’s happening with teens per se. I have written about this a few times:

See also:

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To tell the truth (right-wing front edition)

lyingcross

The mission of the Institute for Family Studies is “strengthening marriage and family life, and advancing the well-being of children, through research and public education.” As of this morning, this includes not a single use of the words “gay,” “lesbian,” or “same-sex” anywhere on their website, according to Google. They routinely post links to articles and research “of note,” that might interest readers who believe in their mission. So, why never mention the gay?

Or — dramatic pause — is that really their whole mission? The IFS website lists seven “senior fellows.” Don’t tell the others, but W. Bradford Wilcox is the only one getting paid $50,000 per year (in 2013). Their 2013 fundraising included $50,000 from the Bradley Foundation, which also supported Wilcox’s effort to fund the Regnerus study; and $20,000 from the Vine and Branches foundation, which lists the purpose of the donation as “religious” (the foundation’s eligibility criteria include, “Christian organizations that overtly express their faith through programming”).

So, do you really believe this?

As a nonpartisan, nonsectarian, and not-for-profit institute committed to the study of family life, IFS works with scholars, writers, and supporters without regard to academic discipline, party, or ideology.

The only thing that bothers me about this, besides the values, is the blatant, routine dishonesty. Why do respectable people just tolerate that?

Not to get into minutiae, but also, would it kill him to have any women among the nine officers of his shadowy, bogus non-profit foundation?

Note: I first wrote about IFS here, but only some of that info is still accurate.

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The scientific racism in Roof’s statement (can we get Wade and Murray on the record?)

Get it? Scientific racism.

Get it? Scientific racism.

The 2,400-word statement posted by Dylann Roof before he carried out the Charleston massacre — murdering nine Black people in an A.M.E. Church prayer meeting — is a clear statement of his terrorist political intentions (it’s described here, and archived here).

It also includes some very banal scientific racism which could, in slightly fancier language, have been written by Nicholas Wade or Charles Murray. Roof wrote:

Anyone who thinks that White and black people look as different as we do on the outside, but are somehow magically the same on the inside, is delusional. How could our faces, skin, hair, and body structure all be different, but our brains be exactly the same? This is the nonsense we are led to believe. Negroes have lower Iqs, lower impulse control, and higher testosterone levels in generals. These three things alone are a recipe for violent behavior. If a scientist publishes a paper on the differences between the races in Western Europe or Americans, he can expect to lose his job.

With regard to Roof’s first two sentences, you might compare them with Wade’s (all quotes found in my article):

It is reasonable to assume that if traits like skin color have evolved in a population, the same may be true of its social behavior, and hence the very different kinds of society seen in the various races and in the world’s great civilizations differ not just because of their received culture—in other words, in what is learned from birth—but also because of variations in the social behavior of their members, carried down in their genes.

On the second point — IQ, impulse control, and testosterone in Blacks — Roof is also in line with Wade. Wade inflates the weak case that the (rare) MAO-A “warrior gene” makes Blacks more violent than Whites, genetically. And then on the question of violence and impulse control, Wade explains that Africa remains poor because it is genetically stuck in tribalism (read: poor impulse control) despite the awesome helpfulness of the colonial powers on that continent (“Tribal behavior is more deeply ingrained than mere cultural prescriptions. Its longevity and stability point strongly to a genetic basis”). And also violent, as the higher-than-average homicide rate in Africa represents “a difference that does not prove but surely allows room for a genetic contribution to greater violence in the less developed world.”

On the claim of a forced silence about these (supposed) truths among the scientific community, Murray and Wade also are in agreement with Roof. This is a major theme for Wade. Instead of “expect to lose his job,” Murray says a scientist who focuses on the genetics of racial difference will face “professional isolation and stigma.” The point is the same. 

Given the closeness of his statements to their ideas, I think it would be helpful for Wade and Murray to explain how Roof is or is not accurate, and then explicitly denounce Roof’s associated actions. Of course Wade and Murray would never countenance racial murder of the kind perpetrated by Roof, and I would never put them in the same category — except insofar as their ideas are in fact similar. I would hate for Roof’s white supremacist friends to read the silence from Wade and Murray as endorsement of his view of racial genetics and its use as a rationale for violence.

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Stop me before I fake again

In light of the news on social science fraud, I thought it was a good time to report on an experiment I did. I realize my results are startling, and I welcome the bright light of scrutiny that such findings might now attract.

The following information is fake.

An employee training program in a major city promises basic job skills and as well as job search assistance for people with a high school degree and no further education, ages 23-52 in 2012. Due to an unusual staffing practice, new applications were for a period in 2012 allocated at random to one of two caseworkers. One provided the basic services promised but nothing extra. The other embellished his services with extensive coaching on such “soft skills” as “mainstream” speech patterns, appropriate dress for the workplace, and a hard work ethic, among other elements. The program surveyed the participants in 2014 to see what their earnings were in the previous 12 months. The data provided to me does not include any information on response rates, or any information about those who did not respond. And it only includes participants who were employed at least part-time in 2014. Fortunately, the program also recorded which staff member each participant was assigned to.

Since this provides such an excellent opportunity for studying the effects of soft skills training, I think it’s worth publishing despite these obvious weaknesses. To help with the data collection and analysis, I got a grant from Big Neoliberal, a non-partisan foundation.

The data includes 1040 participants, 500 of whom had the bare-bones service and 540 of whom had the soft-skills add-on, which I refer to as the “treatment.” These are the descriptive statistics:

fake-descriptives

As you can see, the treatment group had higher earnings in 2014. The difference in logged annual earnings between the two groups is significant at p

fake-ols-results

As you can see in Model 1, the Black workers in 2014 earned significantly less than the White workers. This gap of .15 logged earnings points, or about 15%, is consistent with previous research on the race wage gap among high school graduates. Model 2 shows that the treatment training apparently was effective, raising earnings about 11%. However, The interactions in Model 3 confirm that the benefits of the treatment were concentrated among the Black workers. The non-Black workers did not receive a significant benefit, and the treatment effect among Black workers basically wiped out the race gap.

The effects are illustrated, with predicted probabilities, in this figure:

fake-marginsplot

Soft skills are awesome.

I have put the data file, in Stata format, here.

Discussion

What would you do if you saw this in a paper or at a conference? Would you suspect it was fake? Why or why not?

I confess I never seriously thought of faking a research study before. In my day coming up in sociology, people didn’t share code and datasets much (it was never compulsory). I always figured if someone was faking they were just changing the numbers on their tables to look better. I assumed this happens to some unknown, and unknowable, extent.

So when I heard about the Lacour & Green scandal, I thought whoever did it was tremendously clever. But when I looked into it more, I thought it was not such rocket science. So I gave it a try.

Details

I downloaded a sample of adults 25-54 from the 2014 ACS via IPUMS, with annual earnings, education, age, sex, race and Hispanic origin. I set the sample parameters to meet the conditions above, and then I applied the treatment, like this:

First, I randomly selected the treatment group:

gen temp = runiform()
gen treatment=0
replace treatment = 1 if temp >= .5
drop temp

Then I generated the basic effect, and the Black interaction effect:

gen effect = rnormal(.08,.05)
gen beffect = rnormal(.15,.05)

Starting with the logged wage variable, lnwage, I added the basic effect to all the treated subjects:

replace newlnwage = lnwage+effect if treatment==1

Then added the Black interaction effect to the treated Black subjects, and subtracted it from the non-treated ones.

replace newlnwage = newlnwage+beffect if (treatment==1 & black==1)
replace newlnwage = newlnwage-beffect if (treatment==0 & black==1)

This isn’t ideal, but when I just added the effect I didn’t have a significant Black deficit in the baseline model, so that seemed fishy.

That’s it. I spent about 20 minutes trying different parameters for the fake effects, trying to get them to seem reasonable. The whole thing took about an hour (not counting the write-up).

I put the complete fake files here: code, data.

Would I get caught for this? What are we going to do about this?

BUSTED UPDATE:

In the comments, ssgrad notices that if you exponentiate (unlog) the incomes, you get a funny list — some are binned at whole numbers, as you would expect from a survey of incomes, and some are random-looking and go out to multiple decimal places. For example, one person reports an even $25,000, and another supposedly reports $25251.37. This wouldn’t show up in the descriptive statistics, but is kind of obvious in a list. Here is a list of people with incomes between $20000 and $26000, broken down by race and treatment status. I rounded to whole numbers because even without the decimal points you can see that the only people who report normal incomes are non-Blacks in the non-treatment group. Busted!

fake-busted-tableSo, that only took a day — with a crowd-sourced team of thousands of social scientists poring over the replication file. Faith in the system restored?

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Cohabitation in the marriage trend

The other day I complained about the low value added from a commercial marriage soothsayer. Making predictions about marriage in the short run isn’t very important (because short-run change is modest), and in the long run is much more complicated than the simple models I used. One very important complication that we in the United States are ill-prepared to deal with is cohabitation, raised in a comment yesterday by Gosta Esping-Andersen.

After a scare last fall over funding for the marital events and marital history questions in the Census Bureau’s American Community Survey (ACS), the government decided to keep the questions (I wrote about it here, here, and here). With these questions, we know a lot about the timing of marriage and divorce, in addition to births, from the biggest annual survey we have. However, we don’t know much about cohabitation. We know if people are cohabiting as “unmarried partners,” but only if they are doing so in a home owned or rented by one of the partners. And we don’t know how long they’ve been living together, or if someone used to cohabit but no longer does (cohab breakups aren’t recorded like divorces).

This isn’t so bad in the U.S., compared to some other countries where cohabitation tends to me more serious and long-lasting, but it still is a significant blind spot in our demographic data system. For example, according to an analysis of data from the National Survey of Family Growth (much smaller and less frequent than the ACS), by the Nation Center for Family and Marriage Research, the majority of unmarried women having births (57%) are in cohabiting relationships, which amounts to a quarter of all births. The proportion of single new-mothers living with someone is higher among Whites and Hispanics (two-thirds) than among Blacks (one-third).

Ultimately, the reason we care whether parents are married, or cohabiting, is because we want to know who’s going to take care of the children, and pay for them, and what their developmental environment will be. Marital status or living arrangements are a rough way to measure these things.

Marriage trends

Anyway, what role does cohabitation play in the decline in marriage? If people were just redefining their commitments, choosing cohabitation instead of marriage, that would mean something different than if they were just spending more of their lives truly single.

Frustratingly, the best annual data on cohabitation now comes from the Census Bureau’s Current Population Survey (CPS), rather than the ACS, which means it’s not paired with the marital events and history questions. In the CPS, since 2007 (a change I discussed here), we know if someone is cohabiting even if the couple is living in someone else’s household (such as a parent or roommate). So here’s a look at where cohabitation fits in to the marriage trends for young adults, from 2007 to 2014 (for these trends, I counted people as married only if they were not separated, and I counted people as cohabiting if they said they were living with a boyfriend or girlfriend even if they were married but separated):

Microsoft PowerPoint - marcohab-07-14.pptx

The figure shows that, even with the increase in cohabitation for 25-34-year-olds, singleness is still increasing. This is especially true for those in the peak marriage age of 25-29, for whom marriage has decreased 9% while cohabitation has increased only 4%. Strikingly, it also shows that cohabitation now is more common among 20-24-year-olds than marriage; I don’t remember noticing that before.*

So, at least in these broad strokes, cohabitation doesn’t account statistically for recent declines in marriage. But it is important: if you just focus on marriages, you miss the trend toward higher rates of cohabitation among unmarried people.

* UPDATE

Here are some figures showing the relative prevalence of cohabitation versus marriage, by sex, age, and year, using the same data and definitions as above. Restricting the data to those who are married or cohabiting, these figures show the percentage cohabiting, so over 50% means more people are cohabiting than are married (spouse present). Green is more cohabitation, red is less. Moving down the figures is time, and to the right is age, so older people are more likely to be married, and cohabitation increased from 2007 to 2014. By 2014, cohabiting was more common for men up to age 25, for women up to age 23. Because the samples are relatively small the estimates bounce around, so I smoothed the figures by averaging adjacent cells.

marcohab-07-14.xlsx

marcohab-07-14.xlsx

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