Author Archives: Philip N. Cohen

Data snapshot: Married before

Among newlyweds in the United States, 30% have been married before. Here’s the breakdown by state (click to enlarge):



Here’s a list of states and DC, from highest to lowest percent married before:


And here is the Google search most highly correlated with this pattern: Kerrelyn Sparks (correlation = .83):


The top 100 correlated searches is shot through with romance and fantasy novels: Lynsay Sands, romance series, Sherrilyn Kenyon, vampire book, fever series, Jeaniene Frost.

Coming soon: Crouching Tiger, Forbidden Vampire (and your next marriage?):



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9 uses of “the ways in which” that should be replaced by “how”

Searching through sociology for the ways in which is literally like shooting ducks in a barrel (easy).

Shooting Ducks in a Barrel

For this post I made sure to include some giants in the field, and major journals, to underscore the ways in which this problem is not limited to the over-wrought fringe.

The “how” rule is not universally applicable. In some cases “the ways” would be a better replacement. But in these 9 examples “how” is enough.

Reproducing Stories: Strategic Narratives of Teen Pregnancy and Motherhood

Within this narrative, there is no space for negotiating or even acknowledging the ways in which poverty, racism, and sexism affect the lives of young mothers.

Social Network Analysis: An Introduction

… her research showed the importance of ties across kin groups and households and the ways in which the strength of membership within families varied…

The New Institutionalism in Organizational Analysis

Whereas economists and political scientists offer functional explanations of the ways in which institutions represent efficient solutions to problems of governance, sociologists reject functional explanations and focus instead on the ways in which institutions complicate and constitute the paths by which solutions are sought.

The Transformation of Intimacy: Sexuality, Love, and Eroticism in Modern Societies

She found major differences between the ways in which the boys discussed sex (they did not often speak of love) in the course of her lengthy interviews with them and the responses of the girls.

Practicing Intersectionality in Sociological Research: A Critical Analysis of Inclusions, Interactions, and Institutions in the Study of Inequalities

A good example of this can be found in Hays’s (2003) discussion of the ways in which college students are prone to the drug use and sexual activity that are so strongly condemned among poor teens.

The Division of Labor in Society (Introduction)

The new introduction to this edition takes a different tack, focusing on the ways in which this work is of present-day sociological interest.

Video Game Culture, Contentious Masculinities, and Reproducing Racialized Social Class Divisions in Middle School*

Recent feminist theorizing on relations between gender and technology emphasizes the ways in which the two mutually shape each other.

Pattern Variables Revisited: A Response to Robert Dubin

The Editor’s invitation to comment on his paper has given me the opportunity to work out an overdue clarification of the ways in which Model II builds on and goes beyond, rather than replaces, Model I.

Gastronationalism: Food Traditions and Authenticity Politics in the European Union

I use Brubaker’s (1996:10) broad definition of nationalism — a set of idioms, practices, and possibilities available in cultural and political life, delimited by social or physical boundaries — to consider the ways in which a nation’s people are defined, or self-define, as a distinct group.

*This was one of eight pieces in the Summer 2014 issue of Signs that came up in my search. For a previous criticism of the writing in Signs, see this post.


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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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How (and how much) academics talk about inequality, in one chart

Reader advisory: When I say “in one chart,” I never really mean it.

Updated with new chart at the end.

Because someone asked, here is the article count from Web of Science (an academic journal database with emphasis on science), showing the frequency of articles (of all types) according to the inequality-related phrases in their titles. This is obviously not an exhaustive list of work on these subjects, but I did want to show all combinations of race, class, and gender (click to enlarge).

strat terms.xlsx

  • “Social inequality” now completely dominates, but it once was second to “social stratification.”
  • The most common of the three-word combinations is “race, class, and gender.”
  • “Gender, race, and class” has almost always been second.
  • “Gender, class, and race” made a run in the late 1990s, but has since faded.

I’ve written a little more about language and intersectional concerns here.


Don Tomaskovic-Devey sent along this figure, which shows newspaper articles using inequality related terms. The dotted line shows articles with rich, wealthy, top 1%, top one %, while the solid line shows income inequality. He suggests the dotted line may reflect an Occupy Wall Street effect, while the solid line shows the Thomas Piketty framing process:




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Video series debut: The Story Behind the Numbers

The wonderful animators at Kiss Me I’m Polish, who did the design and graphics for my book The Family, are producing short videos based on an infographic series in the text called The Story Behind the Numbers. These are less than 2 minutes long and use just a few numbers, intended to spur reflection and discussion in conjunction with the details in the book, with narration by me.

The first one is available now. From chapter 7, “Love and Romantic Relationships,” we have a one-minute animation called, “Race and ethnicity divides college students’ dating lives.” In the book I took numbers from Elizabeth Aura McClintock’s 2010 paper in Journal of Marriage and Family and reported on the relative frequency of within-race/ethnicity dating among students at Stanford University. It’s fascinating to me how strong the matching is in such an elite setting, where you might expect gradations of social status to matter less.

The graphic in the book represents the whole table of matches relative to the proportion of each group in the dating pool.

As the rest of series comes out I will link them from the Teaching page.


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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:


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* 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):


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.


* 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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