5 minutes on the three-parent family

In the Atlantic article, “The Rise of the Three-Parent Family” I was quoted saying, “the increasing visibility and legalization of three-parent arrangements ‘is one of the signs that our definition of family is opening up.'”

That led to an interview with a different journalist. I recorded my end of the interview, and re-enact it here as a five-minute commentary. Could be suitable for a class discussion.

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New COVID-19 and Health Disparities lecture

I recorded a new version of the lecture I created last spring: COVID-19 and Health Disparities. It defines health disparities, introduces the theory of fundamental causes, and then describes COVID-19 disparities by race/ethnicity and age with reference to education and occupational inequality. For intro sociology students.

Using data from Bureau of Labor Statistics (inspired by this piece from Justin Fox), I showed the percentage of workers working at home according to the median wage in their occupations, illustrating how people in lower-paid occupations aren’t working at home, while professionals and managers are:

And, using age- and race/ethnic-specific mortality rates from CDC, with population denominators from the 2018 ACS (I don’t know why I can’t find the denominators CDC uses), I made this:

The greatest race/ethnic disparities are in the working ages, which suggests they are driven at least partly by occupational inequality.

The lecture 23 minutes, slides with references and links are here.

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Are pandemic effects on birth rates already detectable?

As birth data approaches, maybe we can get beyond analyses like Google searches for pregnancy-related terms to see what’s happening with birth rates.

At this writing we are a few days shy of 35 weeks from February 1st. If I read this right, 10% of US births occur at 36 weeks of gestation or less. But the most recent complete data I see is from August, so it’s early. However, most fertilized human eggs do not come to term, being lost either before (30%) or after (30-40%) implantation. That’s from a paper by Jenna Nobles and Amar Hamoudi, who write:

Evidence suggests that multiple mechanisms may be involved in pregnancy survival, including those that affect placental development and function, fetal oxidative stress, fetal neurological development, and likely many others. These, in turn, are shaped by more distal processes that affect maternal nutrition, maternal exposure to biological and psychosocial stress, maternal exposure to infection, and management of chronic conditions. Pregnancy survival varies with women’s body mass index, consumption of folic acid, and in some studies, reports of stressful life events (citations removed).

The pandemic might reasonably have contributed to a higher rate of pregnancy loss from these factors. And then there are abortions, which people have probably needed more even though they had less access to them (see this report from Guttmacher). So the net effect is unclear.

Setting aside how the pandemic might have affected fertility intentions and planning (I assume this is negative, as reported by Guttmacher), there might already be fewer births, from loss and abortion.

I haven’t looked at every state, but Florida and California report births by month. In Florida, there were 9.5% fewer babies born in August 2020 than in the previous year (they revise these as they go, but the August number has been stable for a little while, so probably won’t increase much). In California there were 9.6% fewer births in August of this year compared with last year. Here are the monthly trends, including the last three years (I included Florida’s September number as of today, but that will certainly rise):

This is going to be tricky because birth rates were already falling in many places. But the average decline in the last three years was 2.9% in California and 0.7% in Florida, so these numbers clearly outpace that naïve expectation. Also, what about spring? Maybe the pandemic was already causing a decline in live births in California in March (from immigrants not coming or staying in Mexico or other countries?), but if the decline in March was unrelated, then it’s not clear how to interpret the drop in August. So it will be complicated. But this is a bona fide blip in the expected direction, so I’m posting it with a question mark.

I assume other people will be way ahead of me on this, though I haven’t seen anything. Feel free to post other analyses in the comments.

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Race and racism in America (video)

In my Social Problems class we’re spending the next few weeks on race, racial inequality, and racial politics. Step one is this lecture on race and racism.

After a tangent on racial identity, idealism and its enemies, I address biology and race, describing the classic racist racial categories in relation to vast human diversity in Africa and the world overall, with discussion of biological evolution and the sources of human variation. Then I turn to the US and discuss social definition and self-definition, race versus ethnicity, definitions of racism and discrimination, and how the Census Bureau measures US race and ethnicity, before summarizing current and projected race/ethnic composition. And I used the new Zoom feature where your PowerPoint slides are the virtual background (which is harder than it looks because your image isn’t mirrored while you speak!).

It’s 35 minutes. The slides are here, CC-BY: osf.io/uafvp. To see all my videos, visit my YouTube channel.

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The COVID-19 economic crisis is increasing every kind of inequality (video)

I recorded a 25-minute lecture on the COVID-19 economic crisis, with emphasis on increasing inequalities, for my Social Problems class. The slides are posted here, CC-BY.

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Early pandemic demographic indicators

A couple new ones and a couple updates.


The pandemic could be affecting the number of abortions, miscarriages, or infant deaths, but unless those effects are large it should be too early to see effects on the total birth rate, given that we’re only about 7 months into it here. So for possible birth indicators I did a little Google search analysis using the public Google Trends data.

I found three searches that were pretty well correlated in the weekly series: “am I pregnant”, “pregnancy test,” and “morning sickness”, which all should have something to do with the frequency of new pregnancies. I ran Google Trends back five years, created an index from these searches (alpha = .68) , smoothed it a little, and this is what I got:

There was already a big drop in 2019 from the previous three years (reasonable, based on recent trends), and then 2020 started out with a further drop. But then it spiked downward in March before rebounding back to its lower level. So, maybe that implies birth rates will keep falling but not off the charts compared with recent trends.

I also checked “missed period,” which was not well correlated with the others, and got this:

Again, 2019 was already showing some decline, and 2020 started out lower than that, and now searches for “missed period” are running lower than last year, but not more in the middle of the year than they were in the beginning. So, inconclusive for pandemic effect.


Here’s a new take on the Google trends for weddings. I took the averages of searches for “wedding invitations”, “wedding shower”, “bridal shower”, “wedding shower”, and “wedding dresses” (alpha=.94). With a little smoothing, here is 2020 compared with the average of the four previous years (unlike pregnancy searches, this one didn’t show a marked decline in 2019 compared with previous years).

March and April showed catastrophic declines in searches for wedding topics, and the rebound so far has been weak. However, weddings aren’t the same as marriages. Maybe people who had to cancel their weddings still got married down at whatever the pandemic equivalent of the courthouse is. So here’s the same analysis just for the search term “marriage license.” This shows a steep but not as catastrophic drop-off in March and April, and a stronger rebound. So maybe the decline in drop in marriages won’t be as big as the drop in weddings.

Actual marriages

I previously showed the steep decline in recorded marriages in Florida. Here’s an update.

Florida lists recorded marriages by county and month, one month behind (see Table 17). They update as they go, so as of today August marriages are probably still not all recorded. The comparison with previous years shows a collapse in March and April, and then some rebounding. August is preliminary and will come up some.

Marriages in Florida normally peak between March and May. Of course it’s too early to say how many of these were just being postponed. The cumulative trend shows that through July Florida is down 24,000 marriages, or 27%, compared with last year.

Divorce ideation

When the going gets tough, the afflicted want to get divorced, but maybe they can’t. It’s expensive and time consuming and maybe people think it will upset the children even more. (I’ve written about divorce and recessions here and here). So my initial assumption going into the pandemic was that there would be a stall in divorces even though the intent to divorce would rise, followed by a rebound when people get a chance to act on their wishes.

Here I use Google search trends for four searches: “divorce lawyer”, “divorce attorney”, “get a divorce”, and “how to divorce”. The alpha for this index is .69 (when I just use the attorney and lawyer, the alpha is .86, but the result looks the same, so I’m showing the wider index). The results show a drop in divorce ideation in March into April, followed by a rebound to a level a little above the previous year average. Note this pandemic-spring drop is a lot less pronounced than the wedding and marriage collapses above.

Actual divorces

Divorces take time, of course. Like births, I wouldn’t expect to see definitive results right away. In fact, it’s hard to know how long divorces are in process before they show up as recorded. However, in my favorite real-time demography state, Florida, they have been recording divorces every month, and have a look at this:

It’s a giant plunge in recorded divorces, almost 60% in April, followed by a weaker rebound. Again, the records are not yet complete, especially for August, so we’ll see. But comparing these patterns, it might be that there was a short suspension in divorce ideation as people were distracted by the crisis, followed by a rebound which hasn’t yet translated into divorce filings. Googling about divorce seems cheap and easy (and faster) compared with pulling it off, but this might mean there is growing pent up demand for divorce, which is bad (and may imply greater risks of conflict and violence).

Young adults living “at home”

I previous wrote about young adults living with their parents and grandparents using the June and then July Current Population Survey data made available by IPUMS.org. Subsequently, the Pew Research Center did something very similar using the data through July (with additional breakdowns and historical context). Pew used living with parents, apparently including those in households where the parents are not the householders. I prefer my definition — young adults living in the home of parents (also, or grandparents) — which fits better with the popular concept of living “at home.” So if your parents come to live with you, that’s different.

Anyway, here’s the update through August, which shows the percentage of young adults living at home falling back some from the June peak. I will be very interested to follow this through the fall.

Stata code for the living at home analysis is available here: https://osf.io/2xrhc/.

The pandemic and its attendant economic crisis is having massive effects on many aspects of family life. These early indicators are just possible targets of future analysis. There is a lot of other related work going on, which I’ve not taken the time to link to here. Please feel free to recommend other work in the comments.

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Measuring inequality, and what the Gini index does (video)

I produced a short video on measuring inequality, focusing on the construction of the Gini index, the trend in US family inequality, and an example of using it to measure world inequality. It’s 15 minutes, intended for intro-level sociology students.

I like teaching this not because so many of my students end up calculating and analyzing Gini indexes, but because it’s a readily interpretable example of the value of condensing a lot of numbers down to one useful one — which opens up the possibility of the kind of analysis we want to do (Going up? Going down? What about France? etc.). It also helps introduce the idea that social students of inequality are systematic and scientific, and fun for people who like math, too.

The video is below, or you can watch it (along with my other videos) on YouTube. The slides are available here, including one I left out of the video, briefly discussing Corrado Gini and his bad (fascist, eugenicist) politics. Comments welcome.

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Sambo’s Restaurant: Rise and fall, with Ithaca and Santa Barbara

The sociologist David Pilgrim, in an essay on the “The Picaninny Caricature” for the Jim Crow Museum of Racist Memorabilia at Ferris State University, tells the story of the Little Black Sambo:

Arguably, the most controversial picaninny image is the one created by Helen Bannerman. … She spent thirty years of her life in India. … In 1898 there “came into her head, evolved by the moving of a train,” the entertaining story of a little black boy, beautifully clothed, who outwits a succession of tigers, and not only saves his own life but gets a stack of tiger-striped pancakes. The story eventually became Little Black Sambo. The book appeared in England in 1899 and was an immediate success.

At the time, the book was not the most racist thing out there:

Stereotypical anti-black traits — for example, laziness, stupidity, and immorality — were absent from the book. Little Black Sambo, the character, was bright and resourceful unlike most portrayals of black children. Nevertheless, the book does have anti-black overtones … The illustrations were racially offensive, and so was the name Sambo. At the time that the book was originally published Sambo was an established anti-black epithet, a generic degrading reference. It symbolized the lazy, grinning, docile, childlike, good-for-little servant.

I learned from Pilgrim that Julius Lester co-authored an Afrocentric retelling of the story in 1996, Sam and the Tigers. Pilgrim quotes Lester:

When I read Little Black Sambo as a child, I had no choice but to identify with him because I am black and so was he. Even as I sit here and write the feelings of shame, embarrassment and hurt come back. And there was a bit of confusion because I liked the story and I especially liked all those pancakes, but the illustrations exaggerated the racial features society had made it clear to me represented my racial inferiority — the black, black skin, the eyes shining white, the red protruding lips. I did not feel good about myself as a black child looking at those pictures.

These are the covers of Lester’s book and a 1934 version.

Ithaca, 1979

I didn’t know any of this at age 12, in 1979, when Sambo’s Restaurant opened up in Ithaca, NY, my hometown. The chain of restaurants was started in 1957 by Sam Battistone Sr. and Newell Bohnett (get it, Sam-Bo’s). Despite a growing clamor to change its racist name (the interiors of the restaurants were also decorated with images from the story), Wikipedia says there were more than 1,100 outlets by that time. Here’s their 1980 TV commercial, featuring a White child with his divorce-era single dad, saving money because of inflation:

In Ithaca, anyway, there was a boycott movement. Maybe someone still has their orange “Boycott Sambo’s” bumper sticker; I can’t find mine. We canceled that shit, and the company declared bankruptcy in 1981.

Here’s a story from the Ithaca Journal, November 26, 1979:


A couple things are amazing about this, to me. First, the reporter Fred Gaskins (who is Black). Right around that time, must have been seventh grade, I spent some time (a day?) shadowing him under an apprenticeship-mentoring program called The Learning Web (still there!), because I wanted to be a writer. (News reporting was my first job after food service, in 1985.)*

Anyway, the other interesting thing in this article is Newstell Marable, the company’s Black regional community relations manager, who is running down the protesters and talking up the company’s hiring record. “The name is not demeaning to me as a black man,” he’s quoted as saying, noting that 12% of the local restaurant’s 50 employees were Black, while Ithaca was only 5% Black.

Marable died at age 84 in 2015, in Pottstown, Pennsylvania. When he died, the Pottstown branch of the NAACP, of which Marable had been president (not clear which years), picked up his Sambo’s story:

Employed as Sambo’s Restaurants, Inc. Regional Marketing Manager for the Eastern Coast, he was their EEOC Officer and Community Relations Manager from 1980 to 1982. Mr. Marable shared racial sensitivity with the management and persuaded them to change the name from Sambo’s, a name with racist overtones, to Seasonal Restaurants.**

Noting his commitment to “public service, fighting poverty, and equal rights through jobs, housing, education, and health,” the chapter biography remembers Marable, a graduate of Alabama A&M and an Army veteran, with these moving words:

He bestowed blessing through a life filled with many rolls of service to others both at home and in the larger community. For countless people of all ages and walks of life, Mr. Marable demonstrated true leadership by serving others with integrity and courage. He mentored from personal experiences; guided with knowledge and insight; advised with wisdom; emphasized with true understanding; chastised with living kindness; battled courageously for justice while seeking truth and showing integrity; and encouraged many with endless patience.

(With his Sambo’s history, would Marable be memorialized as a “civil rights leader” today?)

Santa Barbara, 2020

Anyway, the Sambo’s Restaurant chain went away one way or the other. Except for the “first and last-standing” Sambo’s Restaurant, in Santa Barbara, California, which finally, only after the murder of George Floyd and subsequent protests this summer, changed its name. After a brief stint as [Peace] & Love, the owner (Sam Battistone’s grandson, Chad Stevens) changed the name to Chad’s, because “I knew it was time to change.”

The KEYT news report on the name change, bizarrely, says: “the name, however, had been interpreted as racist, as was the book about Little Black Sambo, an Indian boy, the restaurant had connected with.” And shows these totally not racist images on the wall:


Whatever you want to tell yourself, Chad Stevens. The report quotes local activist Rashelle Monet as “involved in name change.” She wrote on her Instagram account: “I’ll never forget this moment. I could literally feel something inside me awaken.”

The history runs through us.

Next day addendum: On account of doing no lit review, I just found out sociologist Karyn Lacy wrote an essay about Sambo’s last week. I should have linked to it. Feel free to post other relevant things in the comments.

* Here’s a story on the restaurant renaming from 1982. I don’t know if Marable’s role in that decision is documented anywhere.

** Gaskins went on to a long career in journalism, and now works in communications for the city of Hampton, VA.

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Demographic facts your students need to know right now (with COVID-19 addendum)


PN Cohen photo / Flickr CC: https://flic.kr/p/2jw6stF

Here’s the 2020 update of a series I started in 2013. This year, after the basic facts, I’ll add some pandemic facts below.

Is it true that “facts are useless in an emergency“? I guess we’ll find out this year. Knowing basic demographic facts, and how to do arithmetic, lets us ballpark the claims we are exposed to all the time. The idea is to get your radar tuned to identify falsehoods as efficiently as possible, to prevent them spreading and contaminating reality. Although I grew up on “facts are lazy and facts are late,” I actually still believe in this mission, I just shake my head slowly while I ramble on about it (and tell the same stories over and over).

It started a few years ago with the idea that the undergraduate students in my class should know the size of the US population. Not to exaggerate the problem, but too many of them don’t, at least when they reach my sophomore level family sociology class. If you don’t know that fact, how can you interpret statements like, “The U.S. economy lost a record 20.5 million jobs in April“?

Everyone likes a number that appears to support their perspective. But that’s no way to run (or change) a society. The trick is to know the facts before you create or evaluate an argument, and for that you need some foundational demographic knowledge. This list of facts you should know is just a prompt to get started in that direction.

These are demographic facts you need 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 make sense of those things when other people use them. And it’s really a ballpark requirement (when I test the undergraduates, I give them credit if they are within 20% of the US population — that’s anywhere between 264 million and 396 million!).

This is only a few dozen facts, not exhaustive but they belong on any top-100 list. Feel free to add your facts in the comments (as per policy, first-time commenters are moderated). 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:

Number Source
World Population 7.7 billion 1
U.S. Population 330 million 1
Children under 18 as share of pop. 22% 2
Adults 65+ as share of pop. 17% 2
Official unemployment rate (July 2020) 10% 3
Unemployment rate range, 1970-2018 3.9% – 15% 3
Labor force participation rate, age 16+ 61% 9
Labor force participation rate range, 1970-2017 60% – 67% 9
Non-Hispanic Whites as share of pop. 60% 2
Blacks as share of pop. 13% 2
Hispanics as share of pop. 19% 2
Asians / Pacific Islanders as share of pop. 6% 2
American Indians as share of pop. 1% 2
Immigrants as share of pop 14% 2
Adults age 25+ with BA or higher 32% 2
Median household income $60,300 2
Total poverty rate 12% 8
Child poverty rate 16% 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 327 million 5
4th most populous country, Indonesia 261 million 5
5th most populous country, Brazil 207 million 5
U.S. male life expectancy at birth 76 6
U.S. female life expectancy at birth 81 6
Life expectancy range across countries 51 – 85 7
World total fertility rate 2.4 10
U.S. total fertility rate 1.7 10
Total fertility rate range across countries 1.0 – 6.9 10


1. U.S. Census Bureau Population Clock

2. U.S. Census Bureau quick facts

3. Bureau of Labor Statistics

5. CIA World Factbook

6. National Center for Health Statistics

7. CIA World Factbook

8. U.S. Census Bureau poverty tables

9. Bureau of Labor Statistics

10. World Bank

COVID-19 Addendum: 21 more facts

The pandemic is changing everything. A lot of the numbers above may look different next year. Here are 21 basic pandemic facts to keep in mind — again, the point is to get a sense of scale, to inform your consumption of the daily flow of information (and disinformation). These are changing, too, but they are current as of August 31, 2020.

Global confirmed COVID-19 cases: 25 million

Confirmed US COVID-19 cases: 6 million

Second most COVID-19 cases: Brazil, 3.9 million

Third most COVID-19 cases: India, 3.6 million

Global confirmed COVID-19 deaths: 850,000

Confirmed US COVID-19 deaths: 183,000

Second most COVID-19 deaths: Brazil, 121, 000

Third most COVID-19 deaths: India: 65,000

Percent of U.S. COVID patients who have died: 3%

COVID-19 deaths per 100,000 Americans: 50

COVID-19 deaths per 100,000 non-Hispanic Whites: 43

COVID-19 deaths per 100,000 Blacks: 81

COVID-19 deaths per 100,000 Hispanics: 55

COVID-19 deaths per 100,000 Americans over age 65: 400

Annual deaths in the U.S. (these are for 2017): Total, 2.8 million

Leading cause of death: Heart disease, 650,000

Second leading cause: Cancer: 600,000

Third leading cause: Accidents: 160,000

Deaths from flu and pneumonia, 56,000

Deaths from suicide: 47,000

Deaths from homicide: 20,000


COVID-19 country data: Johns Hopkins University Coronavirus Resource Center

U.S. cause of death data: Centers for Disease Control

U.S. age and race/ethnicity COVID-19 death data: Centers for Disease Control



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Race/ethnic intermarriage trends, 2008-2018

Rising, with gender differences.

Since 2008 the American Community Survey has been asking respondents whether they got married in the previous 12 months. Using the race/ethnicity of spouses (when they are living together), you can estimate the proportion of new marriages that cross racial/ethnic lines.

Defining such “intermarriage” is not as simple as it sounds. Some people have multiple racial or ethnic identities. Some people marry across national-origin lines within panethnic groups (e.g., Mexicans marrying Puerto Ricans). Is a Black+White Dominican marrying a White Mexican, or a Black+White person marrying a Black person, “intermarriage”? In these estimates I drop people who are not Hispanic and specified more than one race, then combine Hispanic origin and race into one, mutually exclusive 5-category variable: White, Black, American Indian, Asian/Pacific Islander, Hispanic (of any race). In other words, intrapanethic marriage (Mexicans marrying Puerto Ricans, or Filipinos marrying Koreans) is not intermarriage. I’m not saying this is the best way; it combines conventional categories with convenience. I combine same-sex and different-sex marriages.

To present the results, I separate men and women (you’ll see why), and estimate predicted probabilities of intermarriage at the mean of controls for age and age-squared, using logistic regression with normalized weights. My Stata code is on the Open Science Framework; help yourself. (I previously did something very similar for states and metro areas.)

The results are in figures, with each race/ethnic group presented on its own scale (check the y-axes). I don’t present American Indians because the samples are small (about half the API sample) and the multirace group is large.


Click the images to enlarge

white intermarriageblack intermarriage

api intermarriage

hispanic intermarriage

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