Family Inequality weekly link roundup

Maybe you’re trying not to spend so much time on Twitter (or don’t use it), but why miss the things I share during the week? Here are some highlights:

Discrimination against Queer Women in the U.S. Workforce: A Résumé Audit Study, by Emma Mishel

Preregistration Challenge at the Center for Open Science

The Great Chocolate-Milk Concussion Scandal: How the University of Maryland got embroiled in a junk-science saga, Jesse Singal

Black Women Don’t Reap the Same Health Benefits from Delaying Motherhood as Whites (Elissa Straus in Slate covers my new paper)

A drone protester heads to jail, while Oregon protesters literally use heavy machinery to destroy Federal property

Nancy Folbre‘s tribute to the late Barbara Bergmann

Andrew Perrin reviews Aldon Morris on DuBois

Jay Livingston on Ted Cruz and “New York values”

How to bridge that stubborn pay gap, in NYTimes Upshot

The common-law marriage myth, in the Economist 

3 Lingering Questions From the Alice Goffman Controversy, by Jesse Singal

Dynamics of perceived social network support for same-sex versus mixed-sex relationships, by Diane Holmberg and Karen Blair

In D.C., Nearly Half Of Homeless Youth Identify As LGBTQ, Survey Finds, by Armando Trull

Hard Work and Marriage Aren’t the Magic Cure-Alls for Poverty Jeb Bush Is Hoping For, by Ally Boghun at RH Reality Check

  

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Thought leader for a day: Families in uncertain times

I have contributed to the Canvas8 2016 Expert Outlook report. I am not sure what this is, but it has to do with experts, and the future, and being a thought leader. Thirty-nine experts in 13 areas contributed their thoughts. My area was Home, and my Thought #29 was Uncertain Times.

uncertaintimes

The Home section is here, the slideshow version is here, and the full report in PDF is here.

The text of my thought came from a very interesting phone conversation I had with editor Jo Allison, who then wrote it up very nicely. Here is the text she produced from our call (I added some links for supplemental reading or factual support). I wasn’t sure where to start, but I was pretty sure any conversation about the future should start with plastics.

Philip N. Cohen is a sociologist and demographer at the University of Maryland. He’s also the author of The Family: Diversity, Inequality and Social Change.

There’s an increase in family plasticity. In the US especially, there’s a big increase in re-marriage, marriage later in life after people already have children, with one or both partners having children from a previous relationship. Cohabitation has been increasing for a few decades, with couples living together after one and both of them have been married or divorced, or have children with somebody else. These things create a dynamic where the rules are unclear and people have to negotiate their own family boundaries and relationships.

We’ve also seen a lot of people having children and getting married later in life. But it’s not just that people do them at later ages, it’s that the ages at which people do these things are spreading out. Everybody used to get married at 22, but now it’s spread out – some people get married at 22, while some get married at 52.

The major life markers – completing education, having children, living together, marrying – as the periods of time get elongated, these things are more interwoven, instead of sequenced rigidly. Where there used to be firm expectations for how you ordered your life in terms of these events, now the order of those things is more flexible. All that plays into the same theme of uncertainty and people feeling like there are no rules to tell them exactly how they should do things.

There’s also uncertainty around family obligations. It used to be that adult children supported their older parents; maybe they inherited the family home, but they were in the support role with their elderly parents. Now, the relationship is more complex than that because there are more young adults who have had trouble establishing themselves, their careers and their families, so they’re still dependent on their parents.

We have more choices and we have more freedom in how we organise and live our family lives. Same-sex marriage is the latest formal recognition of that. But it’s been coming with divorce, with remarriage, adoption. The downside is that we’re more at sea when it comes to making those decisions and people really need to justify their decisions with regards to family life. In the US in the 50s, we basically had universal marriage – over 90% of people were married before 25, so you didn’t have to justify why you were doing what you were doing. Now we do.

That’s why we see so much attention on celebrities’ and leaders’ personal lives – because people want to hold them up and say, ‘I’m like that person’. They need anchor points to reference their own decisions. So people might say, ‘I’m thinking of adoption and look, Angelina Jolie did it, I like her.’ Celebrities give us models to chose from. It’s harder to be a conformist but people need something to define their behaviour, positively or negatively.

Parents are increasingly worried about how their kids are going to do in an unequal world. We saw this with the scandal that came out with Baby Einstein. It had a product that seemed to be a no-brainer; ‘wow this is great for infants, they’re going to turn out to be smart if they watch these little videos’. It turns out there was no science behind it. People were so mad, because they just want to do the right thing. From breastfeeding to limiting screen time, parents are worried about how their kids are going to turn out.

There’s big controversy over the gendering of toys, too. It was interesting that Target said it wasn’t going to have separate aisles for boys and girls. I think that’s very healthy. Children have an inclination to rock the boat, but as soon as it appears that they’re going to be penalised, it can be harsh. So it’s a very positive thing when they have more choices and variety. Particularly for boys. That’s why it’s been harder for men to become secretaries, even as women’s roles have changed. Because men have higher status, the penalties for gender non-conformity are more harsh, especially for adolescent boys.

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Trump facts (demography and demagoguery)

The other day I listed some must-know basic demographic facts. If Chuck Todd on Meet the Press had practiced them he could have caught this from Donald Trump (if he wanted to). Trump said this (transcript here) on Sunday:

But listen, Chuck, you have 60, 70, 80 million people out there that want to work that aren’t getting jobs.

First clue to a big lie is he scaled it up by 33% in 0.5 seconds. Second clue is it’s ridiculous.

How far can you get to debunking this with just our basic demography lesson? The U.S. population is 323 million, and 23% are children under 18. So that leaves 249 million. Remember that 48 million (15% of the population) is age 65 or older. Round numbers, that leaves 200 million. If kids and seniors don’t want jobs, that means 40% of working-age adults want jobs but can’t get them (80 million out of 200 million). So, off the top of your head, either things are literally worse than ever, or that’s wrong.

To get a better estimate of the answer will take five minutes at IPUMS.org’s Current Population Survey online data tool. Here’s the query you need, showing who has a job, and who of those who don’t wants a job (it’s not complicated — the Bureau of Labor Statistics asks them). The people who meet Trump’s criteria highlighted, all 16 million of them.

trumpno

About 10.4 million are unemployed — that is, no job and actively seeking one — so they are NIU (not in universe) for the “do you want a job” question, but by definition they want a job. Another 5.6 million are out of the labor force (no job, not looking), and when asked say they would rather have a job. So that’s 16 million.*

Of course an interviewer can’t fact check everything on the fly. But a big claim, off by a factor of 5-to-1, should give a good journalist pause.**

You know who’s really hurting?

Lots of people are really hurting. But come on.

I wrote earlier about the mingling of racism and masculinism in Trump’s rhetoric. I hate that the racism is an issue that people bring up sometimes but then shelve when they talk about other issues. That’s no way to understand America. One way they do this is talking in race-neutral terms about how people support Trump because they’re economically insecure. OK, but you just have to add, “and White” for that to make sense.

Here is the exchange from the final segment of Meet the Press. Chuck Todd asks Washington Post reporter Robert Costa, “What’s fueling Trump?” He gives him a lead in about stagnating wages, and then they have this exchange:

ROBERT COSTA

I was flipping through my notebook the other day, and I found that the most enthusiastic Trump supporters are white males who lack a college education between the ages of 35 and 55.

CHUCK TODD:

They’re getting it. This economy is killing them.

ROBERT COSTA:

And Trump talks about scarred landscapes across the Rust Belt. He talks about factories being taken down. I mean, that is connecting with these voters. And they’re not ideological. They like Trump because he seems to have answers.

This economy is killing who, now? White men, 35-55, with no college degree. This economy is tough for them. Almost as tough — but not really — as it is for Black men, age 35-55, with no college degree. Here are their employment rates for the last decade:

trumpvotersemp

By this theory of the Trump voter, shouldn’t it be Black men who are lining up for Trump?***

* Note This is just non-institutionalized people. (In the unlikely event Trump is counting prisoners, you could add another 2 million, since they’d probably rather be out and employed.)

** John Hipple at the Bureau of Labor Statistics just wrote a short piece on why people don’t have jobs, such as retirement, disability, attending school, and so on, but he didn’t include this handy “do you want a job” question, which gets right to Trumps point.

*** This reminds me of Brad Wilcox’s description of the “classic working class or lower middle-class American,” which he clarified meant people in the lower-middle part of the income distribution who are “both white and Hispanic.”

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

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

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:

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. 

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Maternal age and infant mortality paper forthcoming

Update: The paper is now published here. 

The working paper I wrote about here has now been accepted for publication in Sociological Science. Although the results haven’t changed substantially, I revised it since the last post, so you should use this copy instead. Here’s the abstract:

Maternal Age and Infant Mortality for White, Black, and Mexican Mothers in the United States

This paper assesses the pattern of infant mortality by maternal age for White, Black, and Mexican mothers, using 2013 Period Linked Birth/Infant Death Public Use File from the Centers for Disease Control. The results are consistent with the “weathering” hypothesis, which suggests that White women benefit from delayed childbearing while for Black women early childbearing is adaptive because of deteriorating health status through the childbearing years. For White women, the risk (adjusted for covariates) of infant death is U-shaped – lowest in the early thirties – while for Black women the risk increases linearly with age. Mexican-origin women show a J-shape, with highest risk at the oldest ages. The results underscore the need for understanding the relationship between maternal age and infant mortality in the context of unequal health unequal health experiences across race/ethnic groups in the U.S.

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Book review: Labor’s Love Lost by Andrew Cherlin

I previously wrote some comments about Andrew Cherlin’s most recent book here, in preparation for a launch event I attended. Here is a full review for submission to Contemporary Sociology.


laborlovelost

Labor’s Love Lost: The Rise and Fall of the Working-Class Family in Americaby Andrew J. Cherlin. New York: Russell Sage Foundation, 2014. 258 paper. ISBN: 9780871540300.

Andrew Cherlin’s latest book is a concise history of U.S. family trends since the late 19th Century. The history builds a well-argued case for policies to improve family stability, to address the problems of children facing “the chaos of postmodern culture and the constraints of the hourglass economy” (p. 195). The book should serve as a staple in the debate over the causes and consequences family change, offering the most reasonable case for the downside of contemporary trends.

Cherlin frames the history around the post-War 1950s-1960s as a period of peak stability and conformity among working-class families, surrounded by periods of greater instability and inequality in the decades before and after. Peak conformity meant the smallest social-class gap in marriage rates between rich and working-class families, compared with the turn of the 20th and 21st centuries, when rich people were much more likely to be married than those in working-class occupations. Cherlin sees the trend in the current period as perilous for children because family instability – concentrated among working-class families – is accompanied by high levels of income inequality and poor support for social mobility from institutions outside the family.

Thus, Cherlin argues, we should consider policies to “lessen the effects of the fall of the working-class family on children” by finding ways to “support stable partnerships without returning to the gender imbalances of the past” (p. 176). He favors policies that would disseminate cultural messages in favor of delaying childbearing, bolster education and training for working-class children and young adults, and raise incomes for those with less than a four-year college degree.

This book should be widely read and taught. It is compellingly written, making a sophisticated set of arguments with original evidence; I recommend it for undergraduate as well as graduate courses. Cherlin’s treatment of the “rise of the working-class family” in the industrial era is well-crafted and original. Especially welcome is the extensive discussion of gender norms and the “masculinity imperative” (p. 30) in the construction of the working-class family ideal. He has a non-superficial view of culture, and incorporates evidence from qualitative research and linguistic trends as well as Census data and economic trends. He also pays considerable attention to Black workers, from their historical emergence from slavery to the effect of declining blue-collar opportunities on their families after the post-War economic peak.

Cherlin’s treatment of the era of peak family conformity addresses the abuse, alcoholism, and women’s alienation that are too-often swept under the rug in accounts that privilege family stability and draw not just from historical nostalgia but “male nostalgia” (p. 92). That includes a revealing and enlightening description of his own family upbringing (he was born to White, working-class parents in 1948), in which his father was happy but his mother – whose abilities were underutilized during her time out of the labor market, and who was prescribed opiates to treat allergies – probably was not. But in the end he had a “happy childhood” (p. 99), and his conclusion about the era returns to the privileging of stability: “All things considered, children received good upbringings in these [1950s] families and experienced stable, two-parent environments while growing up” (p. 100). In the decades that followed, marriage become less common, and less stable, for people with less than a four-year college education, in what Cherlin calls the “fall of the working-class family” (which, as he notes, undermined the very notion of social-class identity for families as opposed to individuals).

Cherlin concludes that the 1950s “was a good era for children,” who “benefited from this familistic culture” (pp. 115-116). But the evidence we have for this is based on the fortunes of a generation which, although born to those families, turned against their norms as adults, riding a wave of prosperity into the women’s movement and abandoning universal early marriage, shotgun weddings, and enforced domesticity. It is ironic that so many people (Cherlin is certainly not alone here) attribute the success of the Baby Boom children to a style of upbringing that they themselves largely rejected at the first opportunity.

Cherlin ably represents the growing chorus of social scientists concerned that poor and working-class parents today are “creating complex and unstable family lives that are not good for children” (p. 5). To his credit, Cherlin’s prescriptions for improving family stability mostly focus on education and the labor market, but the stated goal is the promotion of family stability. Why? For all the research into effects of family instability on children, we know that this factor is not more decisive than its economic precursors; that is, it’s more valuable to have one or more parents with adequate education and income (regardless of their marital status) than it is to have stably married parents, many of whom are time-and resource-poor in our economic and policy environment. This point of contention is important because Cherlin’s case for aiming interventions at family stability – which have, as he acknowledges, no record of success – assumes that the parameters of our stingy and ineffective welfare system are constant.

Cherlin makes a strong case for economic policy to promote employment and wage growth, expanded access to education at all levels, and institutional reforms such as financial regulation and a higher minimum wage. Absent from this discussion, however, is any consideration of our welfare system, including any treatment of family leave policy, child tax credits, guaranteed basic income, or access to health care – all part of the current (albeit lopsided) policy debate. There are a lot of proven policy levers to mitigate the effects of family change. Given this range of options, it is unclear why, even as Cherlin records the abject failure of marriage promotion programs, he nevertheless believes “the message of pregnancy postponement may be worth trying,” in conjunction with efforts to improve the labor market at the low end (p. 183).

In conclusion, Labor’s Love Lost is an important, valuable book, from which many sociologists and their students can learn, and over which many fruitful arguments should emerge.

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Must-know current demographic facts

Here’s an update of a post I wrote two years ago, with some additions.

One reason you, and your students, need to know these things is because they are the building blocks of first-line debunking. We use these facts, plus arithmetic, to ballpark the empirical claims we are exposed to all the time.

This followed my aggressive campaign to teach the undergraduate students in my class the size of the US population (I told you sociology isn’t an easy A). If you don’t know that — and some large portion of them didn’t — how can you interpret statements such as, “On average, 24 people per minute are victims of rape, physical violence, or stalking by an intimate partner in the United States.” In this case the source followed up with, “Over the course of a year, that equals more than 12 million women and men.” But, is that a lot? It’s a lot more in the United States than it would be in China. (Unless you go with, “any rape is too many,” in which case why use a number at all?)

statscartoon

I even updated the cartoon!

Anyway, just the US population isn’t enough. I decided to start a list of current demographic facts you need to know just to get through the day without being grossly misled or misinformed — or, in the case of journalists or teachers or social scientists, not to allow your audience to be grossly misled or misinformed. Not trivia that makes a point or statistics that are shocking, but the non-sensational information you need to know to make sense of those things when other people use them. And it’s really a ballpark requirement (when I tested the undergraduates, I gave them credit if they were within 20% of the US population — that’s anywhere between 258 million and 387 million!).

I only got as far as 25 facts, but they should probably be somewhere in any top-100. And the silent reporters the other day made me realize I can’t let the perfect be the enemy of the good here. I’m open to suggestions for others (or other lists if they’re out there).

They are rounded to reasonable units for easy memorization. All refer to the US unless otherwise noted. Most of the links will take you to the latest data:

Fact Number Source
World Population 7.3 billion 1
US Population 323 million 1
Children under 18 as share of pop. 23% 2
Adults 65+ as share of pop. 15% 2
Unemployment rate 5.0% 3
Unemployment rate range, 1970-2015 4% – 11% 4
Labor force participation rate, age 16+ 63% 4
Labor force participation rate range, 1970-2015 60% – 67% 4
Non-Hispanic Whites as share of pop. 62% 2
Blacks as share of pop. 13% 2
Hispanics as share of pop. 17% 2
Asians as share of pop. 5% 2
American Indians as share of pop. 1% 2
Immigrants as share of pop 13% 2
Adults with BA or higher 29% 2
Median household income $53,000 2
Total poverty rate 15% 8
Child poverty rate 21% 8
Poverty rate age 65+ 10% 8
Most populous country, China 1.4 billion 5
2nd most populous country, India 1.3 billion 5
3rd most populous country, USA 323 million 5
4th most populous country, Indonesia 256 million 5
5th most populous country, Brazil 204 million 5
Male life expectancy at birth 76 6
Female life expectancy at birth 81 6
National life expectancy range 50 – 85 7

Sources:
1. http://www.census.gov/popclock/

2. http://quickfacts.census.gov/qfd/states/00000.html

3. http://www.bls.gov/

4. Google public data: http://bit.ly/UVmeS3

5. https://www.cia.gov/library/publications/the-world-factbook/rankorder/2119rank.html

6. http://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_02.pdf

7. https://www.cia.gov/library/publications/the-world-factbook/rankorder/2102rank.html

8. https://www.census.gov/hhes/www/poverty/about/overview/

Now with handy PDF: Family Inequality Must-Know Demographic Facts

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