After reviewing a paper for JAMA Network Open I was invited to write a comment about it. The paper is here, reporting a large drop in the percentage of mothers who are planning or thinking about having another child in a sample from New York City in mid-2020. After summarizing the results, I wrote this:
Before the COVID-19 pandemic, the US was in a period of declining fertility following the 2008 financial crisis and subsequent recession—a decline that was linked to economic precarity and hardship [2]. Then, in 2020, the total number of US births decreased 3.8%, which was the largest annual decline on a percentage basis since the early 1970s. The decreases were steeper at the end of the year, −6% in November and −8% in December, compared with 2019 [3]. In some large states with public monthly reports (California, Florida, and Ohio), it appears that January and February 2021 had fewer births still, with some recovery in the months that followed [4]. This timing suggests a direct association with the onset of the pandemic and closures that began in the spring of 2020. The evidence presented by Kahn and colleagues [1] supports this interpretation and suggests that when people faced the uncertainty and hardships associated with the pandemic, one common response was to pull back from plans to add children to their families. Future research will examine whether family decision-making in more advantaged families was similarly affected.
The current evidence concerns shifts in pregnancy planning. However, in the US, a substantial portion of births results from unintended or mistimed pregnancies, and these are concentrated among disadvantaged women [5]. The inability to predict, much less control, the trajectory of their lives leads many women to postpone the lifelong commitments implied by intentional births, but also makes unintentional pregnancy more likely. How the pandemic may have affected such births is not yet known. If mobility restrictions, unemployment, illness, care work burdens, and social distancing all reduced social interaction, coupled with increased motivation to prevent pregnancy, we may suspect unintended births will have declined as well.
The impacts of the pandemic within and between families points to the complex interrelationships among family structure, health disparities, and social inequality in the US [6]. The COVID-19 pandemic has been an inequality-exacerbating event on a large scale, widening existing health disparities, especially along the lines of socioeconomic status, race, and ethnicity. Excess mortality among Black and Hispanic populations in 2020, directly and indirectly related to the pandemic, far outstripped that seen among non-Hispanic White populations and contributed to the decrease in overall US life expectancy that exceeded that seen in peer countries [7]. In light of disparate impacts of COVID-19 itself and the social and economic fallout of the pandemic, research should concentrate on widening inequalities in fertility and family well-being, and their relationship to health disparities.
Corresponding Author: Philip N. Cohen, PhD, Maryland Population Research Center, Department of Sociology, University of Maryland, Parren J. Mitchell Art Sociology Building, College Park, MD 20742 (pnc@umd.edu).
Conflict of Interest Disclosures: None reported.
References
Kahn LG, Trasande L, Liu M, Mehta-Lee SS, Brubaker SG, Jacobson MH. Factors associated with changes in pregnancy intention among women who were mothers of young children in New York City following the COVID-19 outbreak. JAMA Netw Open. 2021;4(9):e2124273. doi:10.1001/jamanetworkopen.2021.24273
Seltzer N. Beyond the great recession: labor market polarization and ongoing fertility decline in the United States. Demography. 2019;56(4):1463-1493. doi:10.1007/s13524-019-00790-6
Cohen PN. Baby bust: falling fertility in US counties is associated with COVID-19 prevalence and mobility reductions. SocArXiv, March 17, 2021. doi:10.31235/osf.io/qwxz3
Hartnett CS, Gemmill A. Recent trends in US childbearing intentions. Demography. 2020;57(6):2035-2045. doi:10.1007/s13524-020-00929-w
Thomeer MB, Yahirun J, Colón-López A. How families matter for health inequality during the COVID-19 pandemic. J Fam Theory Rev. 2020;12(4):448-463. doi:10.1111/jftr.12398
Woolf SH, Masters RK, Aron LY. Effect of the covid-19 pandemic in 2020 on life expectancy across populations in the USA and other high income countries: simulations of provisional mortality data. BMJ. 2021;373(n1343):n1343. doi:10.1136/bmj.n1343
Having spent a few months collecting data on birth rates over the last year, and a few months pouring over pandemic data, I took the time to bring the two together and assess the relationship between some basic pandemic indicators and the latest fertility outcomes. The result is a short paper I titled, “Baby Bust: Falling Fertility in US Counties Is Associated with COVID-19 Prevalence and Mobility Reductions,” now available on SocArXiv, with links to the data and Stata code for replication.
Here’s the abstract:
The United States experienced a 3.8 percent decline in births for 2020 compared with 2019, but the rate of decline was much faster at the end of the year (8 percent in December), suggesting dramatic early effects of the COVID-19 pandemic, which began affecting social life in late March 2020. Using birth data from Florida and Ohio counties through February 2021, this analysis examines whether and how much falling birth rates were associated with local pandemic conditions, specifically infection rates and reductions in geographic mobility. Results show that the vast majority of counties experienced declining births, suggestive of a general influence of the pandemic, but also that declines were steeper in places with greater prevalence of COVID-19 infections and more extensive reductions in mobility. The latter result is consistent with more direct influences of the pandemic on family planning or sexual behavior. The idea that social isolation would cause an increase in subsequent births receives no support.
Here’s the main result in graphic form, showing that births fell more in January/February in those counties with more COVID-19 cases, and those with more mobility limitation (as measured by Google), through the end of last May:
However, note also that births fell almost everywhere (87% of the population lives in a fertility-falling county), so it didn’t take a high case count or shutdown to produce the effect.
There will be a lot more research on all this to come, I just wanted to get this out to help establish a few basic findings and motivate more research. I’d love your feedback or suggestions.
I was considering assigning the students in my Family Demography seminar to watch the documentary, One Child Nation: The Truth Behind the Propaganda, so I watched it. The movies uses the tragic family history of one of the directors, Nanfu Wang, to tell the story of the Chinese birth planning policy that began in 1979 and extended through many modifications until 2015. Nothing against watching it, but it’s not good. The one-child policy wasn’t good either, of course, leading to many violations of human rights and a lot of suffering and death.
Before watching the movie, I’m glad I read the review by Susan Greenhalgh, an anthropologist who spent about 25 years studying the one-child policy and related questions (summarized in three books and many articles, here). It’s short and you should read it, but just to summarize a couple of key historical points:
The policy was “the cornerstone of a massively complex and consequential state project to modernize China’s population,” and can’t be understood in the context of birth control alone.
Many people opposed and resisted the policy, but reducing birth rates was a commonly-understood goal, for both gender equality and economic development, and many women were glad the government supported them in that effort. The “vast majority” felt “deep ambivalence” about the policy, weighing individual desires against the perceived need to sacrifice for the common good.
The policy was unevenly applied and enforced (it was especially harsh in the provinces featured in the film), and after 1993 enforcement became less egregious.
Exceptions were added starting in the early 1980s, until by the late 1990s the majority of the population was not subject to a one-child rule.
There are some other specific errors and distortions, including the dramatic, incorrect claim that “the one-child policy [was] written into China’s constitution” in 1982 (as Greenhalgh writes, “the 1982 Constitution says only: “both husbands and wives are duty-bound to practice birth planning”). And the decision to translate all uses of the term “birth planning” as “one-child policy.” That said, the stories of forced abortions, sterilizations, and infanticide are wrenching and ring true.
I have two things to add to Greenhalgh’s review. First, a simple data illustration to show that China, really, is not a “one-child nation.” Using Chinese census data, here is the total number of children (by age 35-39) born to three groups of Chinese women, arranged according to their ages in 1980, about when the one-child policy began.
The shift left shows the decline in number of children born: the mean fell from 3.8 to 2.5 to 1.8 in these data. (Measuring Chinese fertility is complicated, but the census provides a reasonable ballpark.) But the main thing I want to show is that among the last group — those who were beginning their childbearing years when the policy took effect — 61% had two or more children. The idea that China became a “one-child nation” under the policy is false.
Second, the movie takes a hard turn in the middle and focuses on international adoption, and the illegal trafficking of mostly second-born girls to orphanages that sought to place them abroad. This was a very serious problem. But the movie tells the story of the most notorious scandal (for which many people served jail terms) as if it were the common practice, and centers on the savior-like behavior of American activists helping adopted children trace their familial roots. Granting that of course that corruption was terrible, and that the motivations of many (some?) adoptive parents (including me) were good, from China’s point of view it’s not a central story in the history of the one-child policy. As the movie notes, 130,000 Chinese children were adopted abroad during the period, during which time hundreds of millions were born.
Greenhalgh summarizes on this point, calling the film a:
“familiar coercion narrative, complete with villain (the state), victims (rural enforcers and targets), and savior (an American couple offering DNA services to match adopted girls in the U.S. with birth parents in China). The characters (at least the victims and saviors) have some emotional complexity, but they still play the stock roles in an oft-told tale. For American viewers, this narrative is comforting, because it provides a simple, morally clear way to react to troubling developments unfolding in a faraway, little understood land. And by using China (communist, state-controlled childbearing) as a foil for the U.S. (liberal, relative reproductive freedom), the film leaves us feeling smug about the assumed superiority of our own system.”
The many centuries of Chinese patriarchy are a dark part of the human story, and in some ways is unique. For example — relevant to this recent histyory — female infanticide and selling girls has a long history (a history that includes foot binding and other atrocities). The Chinese Communist Party, for all its misdeeds, did not create this problem. Gender inequality in China, including the decline in fertility — which was mostly accomplished before 1979 — has markedly improved since 1949. Greenhalgh concludes: “In China, before the state began managing childbearing, reproductive decisions were made by the patriarchal family. Since the shift to a two-child policy, they have been subject to the strong if indirect control of market forces. One form of control may be preferable to another, but freedom over our bodies is an illusion.”
These are notes for my discussion of Like Family, Narratives of Fictive Kinship, by Margaret K. Nelson. Author Meets Critics session at the Eastern Sociological Society, 21 Feb 2021.
Like A Family is a fascinating, enjoyable read, full of thought-provoking analysis and a lot of rich stories, with detailed scenarios that let the reader consider lots of possibilities, even those not mentioned in the text. It’s “economical prose” that suggests lots of subtext and brings to mind a lot of different questions (some of which are in the wide-ranging footnotes).
It’s about people choosing relationships, and choosing to make them be “like” family, and how that means they are and are not “like” family, and in the process tells us a lot about how people think of families altogether, in terms of bonds and obligations and language and personal history.
In my textbook I use three definitions: the legal family, the personal family, and the family as an institutional arena. This is the personal family, which is people one considers family, on the assumption or understanding they feel the same way.
Why this matters, from a demographer perspective: Most research uses household definitions of family. That’s partly because some things we have to measure, and it’s a way to make sure we only get each person once (without a population registry or universal identification), and correctly attribute births to birth parents. But it comes at a cost – we assume household definitions of family too often.
We need formal, legal categories for things like incest laws and hospital rights, and the categories take on their own power. (Note there are young adult semi-step siblings with semi-together parents living together some of the time or not wondering about the propriety of sexual relationships with each other.) Reality doesn’t just line up with demographic / legal / bureaucratic categories – there is a dance between them. As the Census “relationship” categories proliferate – from 6 in 1960 ago to about 16 today – people both want to create new relationships (which Nelson calls a “creative” move) and make their relationships fit within acceptable categories (like same-sex marriage).
Methods and design
The categories investigated here – sibling-like relationships among adults, temporary adult-adolescent relationships, and informal adoptions – are so very different it’s hard to see what they have in common except some language. The book doesn’t give the formal selection criteria, so it’s hard to know exactly how the boundaries around the sample were drawn.
Nelson uses a very inductive process: “Having identified respondents and created a typology, I could refine both my specific and more general research questions” (p. 11). Not how I think of designing research projects, which just shows the diversity among sociologists.
Over more than one chapter, there is an extended case study of Nicole and her erstwhile guardians Joyce and Don, who she fell in with when her poorer family of origin broke up, essentially. Fascinating story.
The book focuses on white, (mostly) straight middle class people. This is somewhat frustrating. The rationale is that they are understudied. So that’s useful, but it would be more challenging – I guess a challenge for subsequent research – to more actively analyze their White straight middle classness as part of the research.
Compared to what
A lot of insights in the book come from people comparing their fictive kin relationships to their other family or friend relationships. This raises a methodological issue: These are people with active fictive kin relationships, so it’s a tricky sample from which to draw for understanding non-fictive relationships – it’s select. It would be nice in an ideal world to have a bigger sample without restriction and ask people about all their relationships and then compare fictive and non-fictive. Understandable not to have that, but needs to be wrestled with (by people doing future research).
Nelson establishes that the sibling-like relationships are neither like friendships nor like family, a third category. But that’s just for these people. Maybe people without fictive kin like this have family or friend relationships that look just like this in terms of reciprocity, obligation, closeness, etc. (Applies especially to the adult-sibling-like relationships.)
Modern contingency
Great insight with regard to adult “like-sibling” relationships: It’s not just that they are not as close as “family,” it’s that they are not “like family” in the sense of “baggage,” they don’t have that “tarnished reality” – and in that sense they are like the way family relationships are moving, more volitional and individualized and contingent.
Does this research show that family relationships generally in a post-traditional era are fluid and ambiguous and subject to negotiation and choice? It’s hard to know how to read this without comparison families. But here’s a thought. John, who co-parents a teenage child named Ricky, says, “To me family means somebody is part of your life that you are committed to. You don’t have to like everything about them, but whatever they need, you’re willing to give them, and if you need something, you’re willing to ask them, and you’re willing to accept if they can or can’t give it to you” (p. 130). It’s an ideal. Is it a widespread ideal? What if non-fictive family members don’t meet that ideal? The implication may be they aren’t your family anymore. Which could be why we are seeing so many people rupturing their family of origin relationships, especially young adults breaking up with their parents.
It reminds me of what happened with marriage half a century ago, where people set a high standard, and defined relationships that didn’t meet it as “not a marriage.” Or when people say abusive families aren’t really families. Conservatives hate this, because it means you can “just” walk away from bad relationships. There are pros and cons to this view.
Nelson writes at the end of the chapter on informal parents, “The possibility is always there that either party will, at some point in the near or distant future, make a different choice. That is both the simple delight and the heartrending anxiety of these relationships” (p. 133). We can’t know, however, how unique such feelings are to these relationships – I suspect not that much. This sounds so much like Anthony Giddens and the “pure” relationships of late modernity.
This contingency comes up a few times, and I always have the same question. Nelson writes in the conclusion, “Those relationships feel lighter, more buoyant, more simply based in deep-seated affection than do those they experience with their ‘real’ kin.” But that tells us how these people feel about real kin, not how everyone does. It raises a question for future research. Maybe outside this population lots of people feel the same way about their “real” kin (ask the growing number of parents who have been “unfriended” by their adult children).
I definitely recommend this book, to read, teach, and use to think about future research.
Note: In the discussion Nelson replied that most people have active fictive-kin relationships, so this sample is not so select in that respect.
With the help of the designer Brigid Barrett, I have a new website at philipncohen.com, and a redesigned blog to match (which you’re looking at now). We decided on the tagline, “Sociologist / Demographer” for the homepage photo. It’s true I am those two things, but I also like how they modify each other, a type of sociologist and a type of demographer. First some reflections, then a little data.
Having “sociologist” attached to your name is not going to signal scientific rigor to the public in the way that other discipline labels might (like, I think, “demographer”). A lot of sociologists, as shown by their behavior, are fine with that. Your individual behavior as a researcher can shape the impression you make, but it will not change the way the discipline is seen. Until the discipline — especially our associations but also our departments — adopts (and communicates) scientific practices, that’s how it will be. As an association, ASA has shown little interest in this, and seems unlikely to soon.
A substantial portion of sociologists rejects the norms of science. Others are afraid that adopting them will make their work “less than” within the discipline’s hierarchy. For those of us concerned about this, the practices of science are crucial: openness, transparency, reproducibility. We need to find ways at the sub-discipline level to adopt and communicate these values and build trust in our work. Building that trust may require getting certain publics to see beyond the word “sociologist,” rather than just see value in it. They will see our open practices, our shared data and code, our ability to admit mistakes, embrace uncertainty, and entertain alternative explanations.
There are other sources of trust. For example, taking positions on social issues or politics is also a way of building trust with like-minded audiences. These are important for some sociologists, and truly valuable, but they’re different from science. Maybe unreasonably, I want both. I want some people to give my work a hearing because I take antiracist or feminist positions in my public work, for example. And also because I practice science in my research, with the vulnerability and accountability that implies. Some people would say my public political pronouncements undermine not just my science, but the reputation of the discipline as a whole. I can’t prove they’re wrong. But I think the roles of citizen and scholar are ultimately compatible. Having a home in a discipline that embraced science and better communicated its value would help. A scientific brand, seal of approval, badges, etc., would help prevent my outspokenness from undermining my scientific reputation.
One reply I got, confirming my perception, was, “this pretence of natural science needs to be resisted not indulged.” Another wrote: “As a sociologist and an ethnographer ‘reproducibility’ will always be a very weak and mostly inapplicable criterion for my research. I’m not here to perform ‘science’ so the public will accept my work, I’m here to seek truth.” Lots of interesting responses. Several people shared this old review essay arguing sociology should be more like biology than like physics, in terms of epistemology. The phrase “runaway solipsism” was used.
I intended my tweets to focus on the open “science practices” which which I have been centrally concerned, centered on scholarly communication: openness, transparency, replicability. That is, I am less interested in the epistemological questions of what is meaning and truth, and solipsism, and more concerned with basic questions like, “How do we know researchers are doing good research, or even telling the truth?” And, “How can we improve our work so that it’s more conducive to advancing research overall?”
Whether or not sociology is science, we should have transparency, accountability, and a sharing culture in our work. This makes our work better, and also maybe increases our legitimacy in public.
Where is ASA?
To that end, as an elected member of the American Sociological Association Committee on Publications, two years ago I proposed that the association adopt the Transparency and Openness Promotion Guidelines from the Center for Open Science, and to start using their Open Science Badges, which recognize authors who provide open data, open materials, or use preregistration for their studies. It didn’t go over well. Some people are very concerned that rewarding openness with little badges in the table of contents, which presumably would go mostly to quantitative researchers, would be seen as penalizing qualitative researchers who can’t share their data, thus creating a hierarchy in the discipline.
So at the January 2019 meeting the committee killed that proposal so an “ad hoc committee could be established to evaluate the broader issues related to open data for ASA journals.” Eight months later, after an ad hoc committee report, the publications committee voted to “form an ad hoc committee [a different one this time] to create a statement regarding conditions for sharing data and research materials in a context of ethical and inclusive production of knowledge,” and to, “review the question about sharing data currently asked of all authors submitting manuscripts to incorporate some of the key points of the Committee on Publications discussion.” The following January (2020), the main committee was informed that the ad hoc committee had been formed, but hadn’t had time to do its work. Eight months later, the new ad hoc committee proposed a policy: ask authors who publish in ASA journals to declare whether their data and research materials are publicly available, and if not why not, with the answers to be appended in a footnote to each article. The minutes aren’t published yet, but I seem to remember us approving the proposal (minutes should appear in the spring, 2021). So, after two years, all articles are going to report whether or not materials are available. Someday. Not bad, for ASA!
To see how we’re doing in the meantime, and inspired by the Twitter exchange, I flipped through the last four issues of American Sociological Review, the flagship journal of the association, to assess the status of data and materials sharing. That is, 24 articles published in 2020. The papers and what I found are listed in the table below.
There were six qualitative papers and three mixed qualitative/quantitative papers. None of these provided access to research materials such as analysis code, interview guides, survey instruments, or transcripts — or provided an explanation for why these materials were not available. Among the 15 quantitative papers, four provided links to replication packages, with the code required to replicate the analyses in the papers. Some of these used publicly available data, or included the data in the package, while the others would require additional steps to gain access to the data. The other 11 provided neither data nor code or other materials.
That’s just from flipping through the papers, searching for “data,” “code,” “available,” reading the acknowledgments and footnotes, and so on. So I may have missed something. (One issue, which maybe the new policy will improve, is that there is no standard place on the website or in the paper for such information to be conveyed.) Many of the papers include a link on the ASR website to “Supplemental Material,” but in all cases this was just a PDF with extra results or description of methods, and did not include computer code or data. The four papers that had replication packages all linked to external sites, such as Github or Dataverse, which are great but are not within the journal’s control, so the journal can’t ensure they are correct, or that they are maintained over time. Still, those are great.
I’m not singling out papers (which, by the way, seem excellent and very interesting — good journal!), just pointing out the pattern. Let’s just say that any of these authors could have provided at least some research materials in support of the paper, if they had been personally, normatively, or formally compelled to do so.
Why does that matter?
First, providing things like interview guides, coding schemes, or statistical code, is helpful to the next researcher who comes along. It makes the article more useful in the cumulative research enterprise. Second, it helps readers identify possible errors or alternative ways of doing the analysis, which would be useful both to the original authors and to subsequent researchers who want to take up the baton or do similar work. Third, research materials can help people determine if maybe, just maybe, and very rarely, the author is actually just bullshitting. I mean literally, what do we have besides your word as a researcher that anything you’re saying is true? Fourth, the existence of such materials, and the authors’ willingness to provide them, signals to all readers a higher level of accountability, a willingness to be questioned — as well as a commitment to the collective effort of the research community as a whole. And, because it’s such an important journal, that signal might boost the reputation for reliability and trustworthiness of the field overall.
There are vast resources, and voluminous debates, about what should be shared in the research process, by whom, for whom, and when — and I’m not going to litigate it all here. But there is a growing recognition in (almost) all quarters that simply providing the “final” text of a “publication” is no longer the state of the art in scholarly communication, outside of some very literary genres of scholarship. Sociology is really very far behind other social science disciplines on this. And, partly because of our disciplinary proximity to the scholars who raise objections like those I mentioned above, even those of us who do the kind of work where openness is most normative (like the papers below that included replication packages), can’t move forward with disciplinary policies to improve the situation. ASR is paradigmatic: several communities share this flagship journal, the policies of which are serving some more than others.
What policies should ASA and its journals adopt to be less behind? Here are a few: Adopt TOP badges, like the American Psychological Association has; have their journals actually check the replication code to see that it produces the claimed results, like the American Economic Association does; publish registered reports (peer review before results known), like all experimental sciences are doing; post peer review reports, like Nature journals, PLOS, and many others do. Just a few ideas.
Change is hard. Even if we could agree on the direction of change. Brian Nosek, director of the Center for Open Science (COS), likes to share this pyramid, which illustrates their “strategy for culture and behavior change” toward transparency and reproducibility. The technology has improved so that the lowest two levels of the pyramid are pretty well taken care of. For example, you can easily put research materials on COS’s Open Science Framework (with versioning, linking to various cloud services, and collaboration tools), post your preprint on SocArXiv (which I direct), and share them with the world in a few moments, for free. Other services are similar. The next levels are harder, and that’s where we in sociology are currently stuck.
Faber, Jacob W. 2020. “We Built This: Consequences of New Deal Era Intervention in America’s Racial Geography.” American Sociological Review 85 (5): 739–75.
Quant
Census+
No
No
Brown, Hana E. 2020. “Who Is an Indian Child? Institutional Context, Tribal Sovereignty, and Race-Making in Fragmented States.” American Sociological Review 85 (5): 776–805.
Qual
Archival
No
No
Daminger, Allison. 2020. “De-Gendered Processes, Gendered Outcomes: How Egalitarian Couples Make Sense of Non-Egalitarian Household Practices.” American Sociological Review 85 (5): 806–29.
Qual
Interviews
No
No
Mazrekaj, Deni, Kristof De Witte, and Sofie Cabus. 2020. “School Outcomes of Children Raised by Same-Sex Parents: Evidence from Administrative Panel Data.” American Sociological Review 85 (5): 830–56.
Quant
Administrative
No
Upon request
Info on how to obtain data provided.
Becker, Sascha O., Yuan Hsiao, Steven Pfaff, and Jared Rubin. 2020. “Multiplex Network Ties and the Spatial Diffusion of Radical Innovations: Martin Luther’s Leadership in the Early Reformation.” American Sociological Review 85 (5): 857–94.
Quant
Network
No
No
Says data is in the ASR online supplement but it’s not.
Smith, Chris M. 2020. “Exogenous Shocks, the Criminal Elite, and Increasing Gender Inequality in Chicago Organized Crime.” American Sociological Review 85 (5): 895–923.
Quant
Network
No
No
Code described.
Storer, Adam, Daniel Schneider, and Kristen Harknett. 2020. “What Explains Racial/Ethnic Inequality in Job Quality in the Service Sector?” American Sociological Review 85 (4): 537–72.
Quant
Survey
No
No
Ranganathan, Aruna, and Alan Benson. 2020. “A Numbers Game: Quantification of Work, Auto-Gamification, and Worker Productivity.” American Sociological Review 85 (4): 573–609.
Mixed
Mixed
No
No
Fong, Kelley. 2020. “Getting Eyes in the Home: Child Protective Services Investigations and State Surveillance of Family Life.” American Sociological Review 85 (4): 610–38.
Qual
Mixed
No
No
Musick, Kelly, Megan Doherty Bea, and Pilar Gonalons-Pons. 2020. “His and Her Earnings Following Parenthood in the United States, Germany, and the United Kingdom.” American Sociological Review 85 (4): 639–74.
Quant
Survey
Yes
Yes
Offsite replication package.
Burdick-Will, Julia, Jeffrey A. Grigg, Kiara Millay Nerenberg, and Faith Connolly. 2020. “Socially-Structured Mobility Networks and School Segregation Dynamics: The Role of Emergent Consideration Sets.” American Sociological Review 85 (4): 675–708.
Quant
Administrative
No
No
Schaefer, David R., and Derek A. Kreager. 2020. “New on the Block: Analyzing Network Selection Trajectories in a Prison Treatment Program.” American Sociological Review 85 (4): 709–37.
Quant
Network
No
No
Choi, Seongsoo, Inkwan Chung, and Richard Breen. 2020. “How Marriage Matters for the Intergenerational Mobility of Family Income: Heterogeneity by Gender, Life Course, and Birth Cohort.” American Sociological Review 85 (3): 353–80.
Quant
Survey
No
No
Hook, Jennifer L., and Eunjeong Paek. 2020. “National Family Policies and Mothers’ Employment: How Earnings Inequality Shapes Policy Effects across and within Countries , National Family Policies and Mothers’ Employment: How Earnings Inequality Shapes Policy Effects across and within Countries.” American Sociological Review 85 (3): 381–416.
Quant
Survey+
Yes
Yes
Offsite replication package.
Doering, Laura B., and Kristen McNeill. 2020. “Elaborating on the Abstract: Group Meaning-Making in a Colombian Microsavings Program.” American Sociological Review 85 (3): 417–50.
Mixed
Survey+
No
No
Decoteau, Claire Laurier, and Meghan Daniel. 2020. “Scientific Hegemony and the Field of Autism.” American Sociological Review 85 (3): 451–76.
Qual
Archival
No
No
“Information on the coding schema is available upon request.”
Kiley, Kevin, and Stephen Vaisey. 2020. “Measuring Stability and Change in Personal Culture Using Panel Data.” American Sociological Review 85 (3): 477–506.
Quant
Survey
Yes
Yes
Offsite replication package.
DellaPosta, Daniel. 2020. “Pluralistic Collapse: The ‘Oil Spill’ Model of Mass Opinion Polarization.” American Sociological Review 85 (3): 507–36.
Quant
Survey
Yes
Yes
Offsite replication package.
Simmons, Michaela Christy. 2020. “Becoming Wards of the State: Race, Crime, and Childhood in the Struggle for Foster Care Integration, 1920s to 1960s.” American Sociological Review 85 (2): 199–222.
Qual
Archival
No
No
Calarco, Jessica McCrory. 2020. “Avoiding Us versus Them: How Schools’ Dependence on Privileged ‘Helicopter’ Parents Influences Enforcement of Rules.” American Sociological Review 85 (2): 223–46.
Qual
Ethnography w/ survey
No
No
Brewer, Alexandra, Melissa Osborne, Anna S. Mueller, Daniel M. O’Connor, Arjun Dayal, and Vineet M. Arora. 2020. “Who Gets the Benefit of the Doubt? Performance Evaluations, Medical Errors, and the Production of Gender Inequality in Emergency Medical Education.” American Sociological Review 85 (2): 247–70.
Mixed
Administrative
No
No
Kristal, Tali, Yinon Cohen, and Edo Navot. 2020. “Workplace Compensation Practices and the Rise in Benefit Inequality , Workplace Compensation Practices and the Rise in Benefit Inequality.” American Sociological Review 85 (2): 271–97.
Quant
Administrative
No
No
Abascal, Maria. 2020. “Contraction as a Response to Group Threat: Demographic Decline and Whites’ Classification of People Who Are Ambiguously White.” American Sociological Review 85 (2): 298–322.
Quant
Survey experiment
No
No
Preanalysis plan registered. Data embargoed.
Friedman, Sam, and Aaron Reeves. 2020. “From Aristocratic to Ordinary: Shifting Modes of Elite Distinction.” American Sociological Review 85 (2): 323–50.
In “The Coming Divorce Decline” I showed the U.S. divorce rate falling from 2008 to 2017, and predicted that, because the married population was being stocked with increasingly non-divorce-prone marriages, the rate would continue to fall. After the first draft (based on 2016 data), divorce fell in 2017, providing the first support for my prediction before the paper was even “published” (accepted for Socius). Now the 2018 data is out, and divorce has become less common still.
Here’s a quick update.
Based on the number of divorces reported in the survey each year, by sex, and the number of married people, I calculate the refined divorce rate, or the number of divorces per 1,000 married people. That fell another 3% for both women and men in 2018, to 15.9 and 14.3 respectively (the rates differ because these are self reports and women report more).
When I run the model from the paper again on the new data (on women only), I can show the drop in the adjusted odds of divorce, updating Figure 1 of the paper (the 2018 change in an unadjusted model is significant at p=.06; adjusted is p=.14, the adjusted change from 2016 is significant at p=.002).
For other takes on the latest data, see this report on the marriage-divorce ratio from Valerie Schweizer, and this on geographic variation from Colette Allred, both at the National Center for Family and Marriage Research.
The data and code for the paper are available here. This update uses the same code with one new year of data.
If you like my new Stata figure scheme (modified from Gray Kimbrough’s Uncluttered) you’re welcome to it: here.
Slides from my presentation this fall at the European Divorce Conference are here.
I wrote a short working paper on U.S. mortality trends for the last decade. You can go straight to the paper on SocArXiv, or the code and output, if you want the full version.
The issue is that premature mortality has been rising for Whites, partly because of the opioid epidemic and also from suicide and alcohol, and also from other causes related to stress and hardship. (See, e.g., Case and Deaton, and Geronimus.) And a recent NCHS report showed that mortality nationally declined much more for married people since 2010.
So I got the Mortality Multiple Cause Files from the National Center for Health Statistics, for two years: 2007 and 2017. These are a complete set of death certificates, which include race/ethnicity, marital status, and education. I linked these to the American Community Survey, to create age-specific mortality rates by age, sex, marital status, and education, for non-Hispanic Whites, Hispanics, and Blacks, in the ages 25-74 (old enough to finished with college, but too young to die).
The basic result is that virtually all of the growth in premature death is among Whites, and further among non-married Whites. (Whites still dies less than Blacks, and more than Hispanics, at each age and marital status.)
Here is the figure of age-specific mortality rates, by race/ethnicity, sex, and marital status for 2007 and 2017. At the bottom of each column I calculated “marriage mortality ratios,” which are how much more likely single people are to die than married people. Note these death rates are deaths per 10,000, but they’re on a log scale so you can see changes where rates are very low.
In the figure you can see how much the marriage mortality ratio jumped up, for Whites only. Now, at the most extreme, single White men age 35-39 are more than 4-times more likely to die than married White men (that’s in the bottom left).
Then I zoom into Whites specifically, and do the same thing for four levels of education:
In the lowest education group of Whites (the far left), mortality rates for married and single people increased similarly, so the marriage mortality ratio didn’t increase. However, for the other education levels, death rates increased for single people more than married people, so the ratio increased (across the bottom). Even among White college graduates, there were increases in mortality for single people. I did not expect that.
My bottom line is that marriage is taking an ever-more prominent place in the social status hierarchy, and now we can add growing mortality inequality, at least among Whites, to that pattern.
You can really do a lot with the common public misperception that divorce is always going up. Brad Wilcox has been taking advantage of that since at least 2009, when he selectively trumpeted a decline in divorce (a Christmas gift to marriage) as if it was not part of an ongoing trend.
I have reported that the divorce rate in the U.S. (divorces per married woman) fell 21 percent from 2008 to 2017. And yet yesterday, Faithwire’s Will Maule wrote, “With divorce rates rocketing across the country, it can be easy to lose a bit of hope in the God-ordained bond of marriage.”
Anyway, now there is hope, because, as right-wing podcaster Lee Habeeb wrote in Newsweek, THE INCREDIBLE SUCCESS STORY BEHIND ONE COUNTY’S PLUMMETING DIVORCE RATE SHOULD INSPIRE US ALL. In fact, we may be on the bring of Reversing Social Disintegration, according to Seth Kaplan, writing in National Affairs. That’s because of the Culture of Freedom Initiative of the Philanthropy Roundtable (a right-wing funding aggregator run by people like Art Pope, Betsy Devos, the Bradley Foundation, the Hoover Institution, etc.), which has now been spun off as Cummunio, a marriage ministry that uses marriage programs to support Christian churches. Writes Kaplan:
The program, which has recently become an independent nonprofit organization called Communio, used the latest marketing techniques to “microtarget” outreach, engaged local churches to maximize its reach and influence, and deployed skills training to better prepare individuals and couples for the challenges they might face. COFI highlights how employing systems thinking and leveraging the latest in technology and data sciences can lead to significant progress in addressing our urgent marriage crisis.
The program claims 50,000 people attended four-hour “marriage and faith strengthening programs,” and further made 20 million Internet impressions “targeting those who fit a predictive model for divorce.” So, have they increased marriage and reduced divorce? I don’t know, and neither do they, but they say they do.
Funny aside, the results website today says “Communio at work: Divorce drops 24% in Jacksonville,” but a few days ago the same web page said 28%. That’s probably because Duval County (which is what they’re referring to) just saw a SHOCKING 6% INCREASE IN DIVORCE (my phrase) in 2018 — the 10th largest divorce rate increase in all 40 counties in Florida for which data are available (see below). But anyway, that’s getting ahead of the story.
Gimme the report
The 28% result came from this report by Brad Wilcox and Spencer James, although they don’t link to it. That’s what I’ll focus on here. The report describes the many hours of ministrations, and the 20 million Internet impressions, and then gets to the heart of the matter:
We answer this question by looking at divorce and marriage trends in Duval County and three comparable counties in Florida: Hillsborough, Orange, and Escambia. Our initial data analysis suggests that the COFI effort with Live the Life and a range of religious and civic partners has had an exceptional impact on marital stability in Duval County. Since 2016, the county has witnessed a remarkable decline in divorce: from 2015 to 2017, the divorce rate fell 28 percent. As family scholars, we have rarely seen changes of this size in family trends over such a short period of time. Although it is possible that some other factor besides COFI’s intervention also helped, we think this is unlikely. In our professional opinion, given the available evidence, the efforts undertaken by COFI in Jacksonville appear to have had a marked effect on the divorce rate in Duval County.
A couple things about these very strong causal claims. First, they say nothing about how the “comparable counties” were selected. Florida seems to have 68 counties, 40 of which the Census gave me population counts for. Why not use them all? (You’ll understand why I ask when they get to the N=4 regression.) Second, how about that “exceptional impact,” the “remarkable decline” “rarely seen” in their experience as family scholars? Note there is no evidence in the report of the program doing anything, just the three year trend. And while it is a big decline, it’s one I would call “occasionally seen.” (It helps to know that divorce is generally going down — something the report never mentions.)
To put the decline in perspective, first a quick national look. In 2009 there was a big drop in divorce, accelerating the ongoing decline, presumably related to the recession (analyzed here). It was so big that nine states had crude divorce rate declines of 20% or more in that one year alone. Here is what 2008-2009 looked like:
So, a drop in divorce on this scale is not that rare in recent times. This is important background Wilcox is (comfortably) counting on his audience not knowing. So what about Florida?
Wilcox and James start with this figure, which shows the number of divorces per 1000 population in Duval County (Jacksonville), and the three other counties:
Again, there is no reason given for selecting these three counties. To test the comparison, which evidently shows a faster decline in Duval, they perform two regression models. (To their credit, James shared their data with me when I requested it — although it’s all publicly available this was helpful to make sure I was doing it the same way they did.) First, I believe they ran a regression with an N of 4, the dependent variable being the 2014-2017 decline in divorce rate, and the independent variable being a dummy for Duval. I share the complete dataset for this model here:
div_chg
duval
1.
-1.116101
1
2.
-0.2544951
0
3.
-0.3307687
0
4.
-0.5048307
0
I don’t know exactly what they did with the second model, which must somehow how have a larger sample than 4 because it has 8 variables. Maybe 16 county-years? Anyway, doesn’t much matter. Here is their table:
How to evaluate a faster decline among a general trend toward lower divorce rates? If you really wanted to know if the program worked, you would have to study the program, people who were in the program and people who weren’t and so on. (See this writeup of previous marriage promotion disasters, studied correctly, for a good example.) But I’m quite confident that this conclusion is ridiculous and irresponsible: “In our professional opinion, given the available evidence, the efforts undertaken by COFI in Jacksonville appear to have had a marked effect on the divorce rate in Duval County.” No one should take such a claim seriously except as a reflection on the judgment or motivations of its author.
Because the “comparison counties” was bugging me, I got the divorce counts from Florida’s Vital Statistics office (available here), and combined them with Census data on county populations (table S0101 on census.data.gov). Since 2018 has now come out, I’m showing the change in each county’s crude divorce rate from 2015, before Communio, through 2018.
You can see that Duval has had a bigger drop in divorce than most Florida counties — 32 of which saw divorce rates fall in this period. Of the counties that had bigger declines, Monroe and Santa Rosa are quite small, but Lake County is mid-sized (population 350,000), and bigger than Escambia, which is one of the comparison counties. How different their report could have been with different comparison cases! This is why it’s a good idea to publicly specify your research design before you collect your data, so people don’t suspect you of data shenanigans like goosing your comparison cases.
What about that 2018 rebound? Wilcox and James stopped in 2017. With the 2018 data we can look further. Eighteen counties had increased divorce rates in 2018, and Duval’s was large at 6%. Two of the comparison cases (Hillsborough and Escambria) had decreases in divorce, as did the state’s largest county, Miami-Dade (down 5%).
To summarize, Duval County had a larger than average decline in divorce rates in 2014-2017, compared with the rest of Florida, but then had a larger-than-average increase in 2018. That’s it.
Marriage
Obviously, Communio wants to see more marriage, too, but here not even Wilcox can turn the marriage frown upside down.
Why no boom in marriage, with all those Internet hits and church sessions? They reason:
This may be because the COFI effort did not do much to directly promote marriage per se (it focused on strengthening existing marriages and relationships), or it may be because the effort ended up encouraging Jacksonville residents considering marriage to proceed more carefully. One other possibility may also help explain the distinctive pattern for Duval County. Hurricane Irma struck Jacksonville in September of 2017; this weather event may have encouraged couples to postpone or relocate their weddings.
OK, got it — so they totally could have increased marriage if they had wanted to. Except for the hurricane. I can’t believe I did this, but I did wonder about the hurricane hypothesis. Here are the number of marriages per month in Duval County, from 13 months before Hurrican Irma (September 2017), to 13 months after, with Septembers highlighted.
There were fewer marriages in September 2017 than 2016, 51 fewer, but September is a slow month anyway. And they almost made up for it with a jump in December, which could be hurricane-related postponements. But then the following September was no better, so this hypothesis doesn’t look good. (Sheesh, how much did they get paid to do this report? I’m not holding back any of the analysis here.)
Aside: Kristen & Jessica had a beautiful wedding in Jacksonville just a few days after Hurricane Irma. Jessica recalled, “Hurricane Irma hit the week before our wedding, which damaged our venue pretty badly. As it was outdoors on the water, there were trees down all over the place and flooding… We were very lucky that everything was cleaned up so fast. The weather the day of the wedding turned out to be perfect!” I just had to share this picture, for the Communio scrapbook:
Photo by Jazi Davis in JaxMagBride.
So, to recap: Christian philanthropists and intrepid social scientists have pretty much reversed social disintegration and the media is just desperate to keep you from finding out about it.
Also, Brad Wilcox lies, cheats, and steals. And the people who believe in him, and hire him to carry their social science water, don’t care.
Marital Name Change Survey first results and open data release.
Over the last three days 3,400 ever-married U.S. residents took my Marital Name Change Survey. I distributed the survey link on this blog, Facebook and Twitter. I don’t know who took it, but based on the education and occupation data a very large share of the respondents were women (88%) with professional degrees (30%) or Phds (27%). It’s not a representative sample, but the results may still be interesting.
Here I’ll give a few topline numbers as of 8:00 this morning, and then link to a public version of the data and materials. These results reflect a little data checking and cleaning and of course are subject to change.
Respondents were asked about their most recent marriage. Half were married in the 2010s, but the sample includes more than 400 married in the 1990s and 200 earlier.
The vast majority (84%) were women married to men; 11% were men married to women and 4% (~140) were in same-gender marriages. Here are some observations about the women married to men. The name-change choices are shown below, with “R change” indicating the respondent changed their name, and “Sp change” indicating their spouse changed. The “Other” field included a write-in, and the vast majority of those were variations on hyphenations or changes to middle names.
Because of the convenience nature of the sample, I don’t put much stock in the overall trend (I’ll try to develop a weighting scheme for this, but even then). However, I think the PhD sample is worth looking at. Here is the trend of women with PhDs (now or at the time of marriage) married to men.
By this reckoning, the feminist-name heyday was in the 1980s, followed by a backslide, and now a rebound of women with PhDs keeping their names. The 2010s trend is like that found in the Google Consumer survey reported by Claire Cain Miller and Derek Willis in NYT Upshot.
Note, these no-change rates are higher than those reported by Gretchen Gooding and Rose Kreider from the 2004 American Community Survey, which showed 33% of married women with PhDs had different surnames than their husbands (regardless of when they got married). I show 53% in the 2000s had different names than their husbands, and 57% in the 2010s. Maybe that’s because I have more social science and humanities PhDs, or just a more woke sample.
These results also show a strong age-at-marriage pattern, with PhD women much more likely to keep their names if they married at older ages. Over age 40, 74% of women with PhDs kept their names, compared with 20% who married under age 25. (Note this is based on education at the time of the survey; I also collected education at the time of marriage, which I discuss below.)
I asked people how important various factors were if people considered changing their names. Among PhD women marrying men who did not change their names, the most important reasons were feminism (52% “very important”), professional considerations (34%), convenience (33%), and maintaining independence within the marriage (24%). Among those who took their husbands’ names, the most important factors were the interests of their children (48%) and showing commitment to the marriage (25%).
A few other observations: PhD women were most likely to keep their names if they had no religion (53%), were Jewish (46%), or other non-Christian religion (43%); protestants (27%), Catholics (29%), and other Christians (21%) were less likely to keep their names. Finally, those who had lived together before marriage were most likely to keep their names (51% for those who lived together for three years or more, compared with 27% for those who did not live together at all).
Data availability
I don’t have time now to analyze this more, but that shouldn’t stop you. Feel free to download the data and documentation here under a CC-BY license (the only requirement is attribution). This includes a Stata data file, and PDFs of the questionnaire and codebook. This will all be revised when I have time.
Open-ended responses
I am not including in the shared files (yet) the open-ended question responses, which include descriptions of “other” name change patterns, as well as a general notes field, which is full of fascinating comments; given the non-random nature of the survey, this may turn out to be its most valuable contribution.
Here are a few.
Reasons:
I changed my name to my spouses because I HATED my father and it was the easiest way to ditch his name. I kept my married name after divorce. I’m currently pregnant (on my own) and plan to change my name again and now I will take the surname of my step-father, who has been my “dad” since I was 5.
“True partnership”
My wife and I had been together 10 years and through several iterations of domestic partnerships prior to marrying. Including before she completed her PhD. I didn’t want to change my name because my name flows really poetically and a change would ruin it (silly but true). She didn’t want to change her name in part because it’s what everyone in her profession know her as. I think we both also feel like our names represent our life histories and although we are a true partnership, that doesn’t negate our family histories or experiences. Which I guess is feminist of us. But we never explicitly discussed feminism as an issue.
This is complicated.
My partner and I both had our own hyphenated names already! We kept our own hyphenated names initially (and our marriage was not legally recognized at the time so there wasn’t a built-in or convenient option to change at that point anyway). When we had kids, we have them a hyphenated name, one of my last names and one of hers. Eventually we both changed to match the kids, so we all share the same hyphenated name now.
I just read this Demography paper by Benjamin G. Gibbs, Joseph Workman, and Douglas B. Downey for my work on the new edition of The Family (don’t hold your breath, but I’m working on it). It seeks to modify the traditional “resource dilution” model of explaining why children with more siblings end up with lower educational attainment, arguing that the effect depends on who else is sharing in the child rearing. Worth a read.
Anyway, since their 2016 paper only used the General Social Survey through 2010, I figured I could make a quick update through 2018. So this is based on their model, but a lot simpler — I didn’t impute missing values, and I didn’t include all the background variables (most notably parents’ education), or get into the religious context, which is the whole point of their analysis.
So, this is my result, showing proportion of people age 25 and older who have a BA or higher, by the number of siblings they have and the decade of their birth. These are average marginal effects from a model that includes race and age, as well as region, family structure (married parents), and religion at age 16.
I find no difference between 0 and 1 sibling, a little lower odds for those with 2 siblings, and then the proportion with a BA or higher drops off. The sibling effect has decreased, at least proportionally — for example, the 3-sibs to 1-sib ratio fell from 1.9-to-1 for those born in the 1910s to 1.4-to-1 for the 1940s to 1960s cohorts and even lower for the 1970s. However, the gaps crept back up in the years after Gibbs’ et al’s analysis ended, back to 1.5-to-1 for the 1990s cohort.
No doubt this is relevant to the decisions people make about how many children to have, discussed in yesterday’s post on fertility trends, and in another Atlantic piece today.
Some people who say getting married is good for kids so you should do it are also more-kids proponents. They should make their priorities clear.
I put the Stata code for this on the Open Science Framework, here.
