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:

IJ-sambos

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:

chads

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.

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

20200808-DSC_4900
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

Sources

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


Sources

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

 

 

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.

Results

Click the images to enlarge

white intermarriageblack intermarriage

api intermarriage

hispanic intermarriage

Pandemic Social Problems, with video and partial reading list

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PN Cohen photo / CC-BY / https://flic.kr/p/2jw5juv

With a lecture and reading list, almost ready to start class.

Almost 6 months ago, on March 2, I had an informal COVID-19 debriefing with 50 students in my Social Problems class. Some of what I said came true, and I’m glad (sort of?) none of it was completely wrong (though we didn’t actually hit 100 million worldwide confirmed cases in May). For a reality check I go back to this Twitter thread, where I jotted down what I told them:

Now, as I prepare to teach the course online next week, I have updated my overview lecture, which has grown to 40 minutes.

Beyond some fundamentals, I’m tossing out the traditional Social Problems course outline and just doing the pandemic and related issues this semester, so this is the introductory lecture. I expect to record some more lectures. If I decide they’re not too embarrassing to share I’ll put them on my YouTube channel (which you can apparently subscribe to if you want to be notified of the videos). Feel free to use them for whatever you like, and pass along your feedback.

The course doesn’t start till next week, so I don’t have everything together yet, but I have a lot of readings, some for me and some for the students, which I’m sharing below.

Happy to have more suggestions, too.

Illness

The 1918 Flu pandemic

Race and Ethnic Disparities 

  • Hammonds, Evelynn M., and Susan M. Reverby. 2019. “Toward a Historically Informed Analysis of Racial Health Disparities Since 1619.” American Journal of Public Health 109 (10): 1348–49. https://doi.org/10.2105/AJPH.2019.305262.
  • Hogarth, Rana Asali. 2019. “The Myth of Innate Racial Differences Between White and Black People’s Bodies: Lessons From the 1793 Yellow Fever Epidemic in Philadelphia, Pennsylvania.” American Journal of Public Health 109 (10): 1339–41. https://doi.org/10.2105/AJPH.2019.305245.
  • Egede, Leonard E., and Rebekah J. Walker. 2020. “Structural Racism, Social Risk Factors, and Covid-19 — A Dangerous Convergence for Black Americans.” New England Journal of Medicine. https://doi.org/10.1056/NEJMp2023616.
  • Bobrow, Emily. 2020. “She Was Pregnant With Twins During Covid. Why Did Only One Survive?” New York Times, August 6, 2020, sec. New York. https://www.nytimes.com/2020/08/06/nyregion/childbirth-Covid-Black-mothers.html.
  • COVD race/ethnicity data: https://covidtracking.com/race/dashboard
  • Moore, Jazmyn T., Jessica N. Ricaldi, and Charles E. Rose. 2020. “Disparities in Incidence of COVID-19 Among Underrepresented Racial/Ethnic Groups in Counties Identified as Hotspots During June 5–18, 2020 — 22 States, February–June 2020.” Morbidity and Mortality Weekly Report 69. https://doi.org/10.15585/mmwr.mm6933e1.
  • Kim, Lindsay, Michael Whitaker, and Alissa O’Halloran. 2020. “Hospitalization Rates and Characteristics of Children Aged 18 Years Hospitalized with Laboratory-Confirmed COVID-19 — COVID-NET, 14 States, March 1–July 25, 2020.” Morbidity and Mortality Weekly Report 69. https://doi.org/10.15585/mmwr.mm6932e3.

Families

Economic crisis and inequality

Gender and the lockdown

Government response

Anti-Asian racism

Trusting experts and confirmation bias, videos

 

Inequality, family change, and the pandemic (interview with Joanna Pepin)

Joanna Pepin was kind enough to interview me for her family sociology class (she’s just begun a new job at the University at Buffalo). We talked about why family sociology attracted me as an inequality researcher, what’s changed in modern families, some common misperceptions, what’s new the forthcoming edition of my textbook, and what COVID-19 is likely to mean for people and their families. In 11 minutes.

I hope it helps.

 

July data show 2.7 million extra young adults living at home

Updating this post with July data

Catherine Rampell tweeted a link to a Zillow analysis showing 2.2 million adults ages 18-25 moving in with their parents or grandparents in March and April. Zillow’s Treh Manhertz estimates these move-homers would cost the rental market the better part of a billion dollars, or 1.4% of total rent if they stay home for a year.

We now have the data through July from the Current Population Survey data to work with, so I extended this forward, and did it differently. CPS is the large, monthly survey that the Census Bureau conducts for the Bureau of Labor Statistics each month, principally to track labor market trends. It also includes basic demographics and living arrangement information. Here is what I came up with.*

Among people ages 18-29, there is a large spike of living in the home of a parent or grandparent (of themselves or their spouse), which I’ll call “living at home” for short. This is apparent in a figure that compares 2020 with the previous 5 years (click figures to enlarge):

six year trends

From February to April, the percentage of young adults living at home jumped from 43% to 48%, and then up to 49.4% in June and 48.7% in July. Clearly, this is anomalous. (I ran it back to 2008 just to make sure there were no similar jumps around the time of the last recession; in earlier years the rates were lower and there were no similar spikes.) This is a very large disturbance in the Force of Family Demography.

To get a better sense of the magnitude of this event, I modeled it by age, sex, and race/ethnicity. Here are the estimated share of adults living at home by age and sex. For this I use just July of each year, and compare 2020 with the pooled set of 2017-2019. This controls for race/ethnicity.

men and women

The biggest increase is among 21-year-olds, and women under 22 generally. These may be people coming home from college, losing their jobs or apartments, canceling their weddings, or coming home to help.

I ran the same models but broke out race/ethnicity instead (not separately for gender White, Black, and Latino, as the samples get small).

white black latino

This shows that the 2020 bounce is greatest for Black young adults (below age 26) and the levels are lowest for Latinos (remember that many Latinos are immigrants whose parents and grandparents don’t live in the US).

To show the total race/ethnic and gender pattern, here are the predicted levels of living at home, controlling for age:

raceth-gender

The biggest 2020 bounce is among Black men who have the highest overall levels, 59%, and White women having the lowest at 45%.

In conclusion, millions of young adults are living with their parents and grandparents who would not be if 2020 were like previous years. The effect is most pronounced among Black young adults. Future research will have to determine which of the many possible disruptions to their lives is driving this event.

For scale, there are 51 million (non-institutionalized) adults ages 18-29 in the country. If 2020 was like the previous three years, I would expect there to be 22.2 million of them living with their parents. Instead there are 24.9 million living at home, an increase of 2.7 million from the expected number (numbers updated for July 2020). That is a lot of rent not being spent, but even with that cost savings I don’t think this is good news.


* The IPUMS codebook, Stata code, spreadsheet, and figures are in an Open Science Framework project under CC0 license here: osf.io/2xrhc.

My green screen teaching setup explained

a picture of my makeshift home office with green screen.Janine Barchas, a professor of English who sells advice on “curating your material environment and adjusting the visible setting of your at-home office” for $250 per chat, managed to place a (paywalled) article in the Chronicle of Higher Education, which I haven’t read. But I did see people complaining on twitter about her advice that you “should curate your zoom backdrop.” Including this funny spoof from Andrew Ishak:

There was other followup advice, like this:

If you are white and male enough to own an expensive, new, and highly performing computer, you can opt for a virtual background. Several colleagues poignantly use photos of their now-vacant classrooms or offices. But not everyone has an up-to-date computer. Even for those who do, hours of flickering like a TV weather announcer in front of a greenscreen projection of the Grand Canyon or of your college campus can prove distracting, too. You might consider selling some of your Apple stock to purchase a top of the line machine, but only if you make sure to mention its purchase at the start of every meeting. After all, what use is having expensive things if you can’t constantly bring them up to others?

(I don’t know who wrote that, but it was shared here.)

All that said, I spend hours and hours in online video meetings, and I’m preparing to teach for hours and hours on Zoom. I want to feel like I’m doing a good job, and also maybe enjoy my job a little. I don’t want to decorate my living space to show students and colleagues in the background, I want a nice green screen setup to put me somewhere else. With under $300 and 4 x 6 feet of space, I found this was possible.

So, without telling anyone what they should do, or even implying that they should do something, this is a 4-minute explanation of how I got to be satisfied, on the very relative scale of our current “situation,” with my Zoom self for teaching. If it’s helpful, great. If you get pleasure from mocking me for it, you’re welcome.

Good luck this semester!

Families, inequality, and sociology in pandemic times (video)

This fall I will be recording video lectures for students in my undergrad class. I’m thinking about the technical aspects, but also the voice and posture. Sitting at my desk at home is quite different from my lecture hall (I usually get a few thousand steps during an hour class). We’ll have to see how it goes.

In June I had a chance to do a one-hour consulting with a “major corporation” to talk about what’s happening in the world, which I recorded and rewrote into this post. I just did another one on the subject of modern families and inequality. This one was like an interview, where I answered questions. I transcribed some of my answers, and then edited that text, figuring it might give me a nice blend of formal and conversational voice, which might work in a video.

After recording the video, I went back and added in some graphics using Photoshop as my video editor (did you know we can get Photoshop as part of our university site license?). A much quicker and easier way, which I assume I’ll be reduced to in the fall, is just to record the lecture live using Zoom or some other PowerPoint screen recorder. Anyway, here is the result, in 12 minutes.

Note: The video includes an update to data from this post on weddings in Florida, and this report on the impact of the epidemic on reproductive health experiences, from Laura Lindberg and colleagues at Guttmacher.

Why there are 3.1 million extra young adults living at home

Answer: The COVID-19 pandemic.

UPDATE: A new post updates this analysis for July 2020

Catherine Rampell tweeted a link to a Zillow analysis showing 2.2 million adults ages 18-25 moving in with their parents or grandparents in March and April. Zillow’s Treh Manhertz estimates these move-homers would cost the rental market the better part of a billion dollars, or 1.4% of total rent if they stay home for a year.

We now have the June Current Population Survey data to work with, so I extended this forward, and did it differently. CPS is the large, monthly survey that the Census Bureau conducts for the Bureau of Labor Statistics each month, principally to track labor market trends. It also includes basic demographics and living arrangement information. Here is what I came up with.*

Among people ages 18-29, there is a large spike of living in the home of a parent or grandparent (of themselves or their spouse), which I’ll call “living at home” for short. This is apparent in a figure that compares 2020 with the previous 5 years (click figures to enlarge):

six year trends

From February to April, the percentage of young adults living at home jumped from 43% to 48%, and then up to 49% in June. Clearly, this is anomalous. (I ran it back to 2008 just to make sure there were no similar jumps around the time of the last recession; in earlier years the rates were lower and there were no similar spikes.) This is a very large disturbance in the Force of Family Demography.

To get a better sense of the magnitude of this event, I modeled it by age, sex, and race/ethnicity. Here are the estimated share of adults living at home by age and sex. For this I use just June of each year, and compare 2020 with the pooled set of 2017-2019. This controls for race/ethnicity.

men and women

The biggest increase is among 21-year-old men and 20-year-old women, and women under 22 generally. These may be people coming home from college, losing their jobs or apartments, canceling their weddings, or coming home to help.

I ran the same models but broke out race/ethnicity instead (for just White, Black, and Latino, as the samples get small).

white black latino

This shows that the 2020 bounce is greatest for Black young adults (below age 24) and the levels are lowest for Latinos (remember that many Latinos are immigrants whose parents and grandparents don’t live in the US).

To show the total race/ethnic and gender pattern, here are the predicted levels of living at home, controlling for age:

raceth-gender

The biggest 2020 bounce is among Black men and women, with Black men having the highest overall levels, 58%, and White women having the lowest at 44%.

In conclusion, millions of young adults are living with their parents and grandparents who would not be if 2020 were like previous years. The effect is most pronounced among Black young adults. Future research will have to determine which of the many possible disruptions to their lives is driving this event.

For scale, there are 51 million (non-institutionalized) adults ages 18-29 in the country. If 2020 was like the previous three years, I would expect there to be 22.2 million of them living with their parents. Instead there are 25.4 million living at home, an increase of 3.1 million from the expected number (numbers updated for June 2020). That is a lot of rent not being spent, but even with that cost savings I don’t think this is good news.


* The IPUMS codebook, Stata code, spreadsheet, and figures are in an Open Science Framework project under CC0 license here: osf.io/2xrhc.

Framing social class with sample selection

A lot of qualitative sociology makes comparisons across social class categories. Many researchers build class into their research designs by selecting subjects using broad criteria, most often education level, income level, or occupation. Depending on the set of questions at hand, the class selection categories will vary, focusing on, for example, upbringing and socialization, access to resources, or occupational outlook.

In the absence of a substantive review, here are a few arbitrarily selected examplar books from my areas of research:

This post was inspired by the question Caitlyn Collins asked the other day on Twitter:

She followed up by saying, “Social class is nebulous, but precision here matters to make meaningful claims. What do we mean when we say we’re talking to poor, working class, middle class, wealthy folks? I’m looking for specific demographic questions, categories, scales sociologists use as screeners.” The thread generated a lot of good ideas.

Income, education, occupation

Screening people for research can be costly and time consuming, so you want to maximize simplicity as well as clarity. So here’s a way of looking at some common screening variables, and what you might get or lose by relying on them in different combinations. This uses the 2018 American Community Survey, provided by IPUMS.org (Stata data file and code here).

  • I used income, education, and occupation to identify the status of individuals, and generated household class categories by the presence of absence of types of people in each. That means everyone in each household is in the same class category (a choice you might or might not want to make).
  • Income: Total household income divided by an equivalency scale (for cost of living). The scale counts each adult as 1 person, each child under 18 as .70, and then scales that count by ^.70. I divided the resulting distribution into thirds, so households are in the top, middle, or bottom third. Top third is what I called “middle/upper” class, bottom third is “lower class.”
  • Education: I use BA degree to identify households that have (middle/upper) or don’t (lower) a four-year college graduate present. This is 31% of adults.
  • Occupation: I used the 2018 ACS occupation codes, and coded people as middle/upper class if their codes was 10 to 3550, which are management, business, and financial occupations; computer, engineering, and science occupations; education, legal, community service, arts, and media occupations; and healthcare practitioners and technical occupations. It’s pretty close to what we used to call “managerial and professional” occupations. Together, these account for 37% of workers.

So each of these three variables identifies an upper/middle class status of about a third of people.

For lower class status, you can just reverse them. The except is income, which is in three categories. For that, I counted households as lower class if their household income was in the bottom third of the adjusted distribution. In the figures below, that means they’re neither middle/upper class nor lower class if they’re in the middle of the income distribution. This is easily adjusted.

Venn diagrams

You can make Venn diagrams in Stata using the pvenn2 add-on, which I naturally discovered after making these. If  you must know, made these by generating tables in Stata, downloading this free plotter app, entering the values manually, copying the resulting figures into Powerpoint and applying the text there, then printing them to PDF, and extracting the images from PDF using Photoshop. Not recommended workflow.

Here they are. I hope the visuals might help people think about for example, who they might get if they screened on just one of these variables, or how unusual someone is who has a high income or occupation but no BA, and so on. But draw your own conclusions (and feel free to modify the code and follow your own approach). Click to enlarge.

First middle/upper class:

Venn diagram of overlapping class definitions

Then lower class:

Venn diagram of overlapping class definitions.

I said draw your own conclusions, but please don’t draw the conclusion that I think this is the best way to define social class. That’s a whole different question. This is just about simply ways to select people to be research subjects. For other posts on social class, follow this tag, which includes this post about class self identification by income and race/ethnicity.


Data and code: osf.io/w2yvf/