Talking about generations with Jean Twenge

PNC photo / CC / flic.kr/p/2hyVLDx

I was on the WHYY radio program Radio Times, on the topic, “Should we stop labeling generations?” The other guest was Jean Twenge, who is pretty far across the spectrum me on this issue — a generations advocate. We had a good conversation. You can listen here, or on your podcast app. (The whole history is under the generations tag.)


Should we stop labeling generations?

WHYY Radio Times, January 13, 2022

Malcolm Burnley: From WHYY in Philadelphia, it’s Radio Times. I’m Malcolm Burnley … Baby Boomers are competitive, Millennials, open minded and a bit overconfident Gen Z, the people born between 1997 and 2012 are surprisingly religious, lonely, phone addicted and afraid to fly the coop. We hold these things to be true thanks to academics, marketers and the media, who all seem to love coming up with names and character traits for large groups of people born between certain years. But is there any merit to thinking these groups of people actually share common traits because the historical or social forces they live through, or simply by virtue of when they were born? More and more researchers seem to be saying no. Others vehemently disagree and say the act of labeling group identities holds empirical value and helps us make sense of the world. This hour, we’re going to explore the debate with two guests who have thought deeply about this. First, we have Philip Cohen, a professor of sociology at the University of Maryland and the author of a recent article called “Generation Labels Mean Nothing, It’s time to retire them.” Philip Cohen, welcome to Radio Times.

Philip Cohen: Hi. Thanks for having me.

Malcolm Burnley: Thank you so much for being here. And we have Jean Twenge. …a psychologist and author of multiple books on generational differences, including, IGen: why today’s super connected kids are growing up less rebellious, more tolerant, less happy, and completely unprepared for adulthood and what that means for the rest of us. Jean Twenge, welcome.

Jean Twenge: Thank you very much.

Malcolm Burnley: …We’re in this moment where identity politics seem to be everywhere, and we’re often as a society, creating new identities along lines of gender and race. So, Jean, I want to open up with you. What do generational labels add in terms of identity? Why do we still use them to begin with?

Jean Twenge: Well, we use them because they are useful and convenient for understanding each other. So really, generational labels have very little difference with, say, grouping people in terms of age or grouping people in terms of race or ethnicity, both of which also often have arbitrary lines and also group people who have many differences from each other. But with generations, if we have a basic understanding of around the time someone was born, we probably know something about their pop culture references. We can kind of understand their perspective in terms of the events they grew up with. And we can at least have an educated guess about some of the cultural values that they probably absorbed when they were growing up. And of course, that last part is where we always have to be cautious that, yes, there are definitely average differences among people of different generations, but we do not want to be prejudiced or stereotyped, just as we don’t want to do that with gender or race or any other identity that we want to treat people as individuals. So to look at someone and say, oh, you’re Gen Z, or as I call them, IGen, that must mean that you are X, that they have certain qualities. And we want to treat people as individuals and not always say, oh, you must be a typical member of your generation. I don’t want to be necessarily seen as a typical woman. Same kind of idea.

Malcolm Burnley: So, Philip … by way of getting into some of the controversy or disagreement around this same question or maybe slightly different, why do you think we still use these labels?

Philip Cohen: I think they’re used primarily in the realms of marketing and media. Most social scientists don’t use the specific categories of these generations with their names and labels. Those of us who study social change, we know that one of the key ways that social change happens is the experiences that people have when they’re born based on when they’re born. So how old you were when 9/11 happened, or if you are trying to start kindergarten in the middle of the pandemic, or if you are trying to get a job in the spring of 2020 when the pandemic starts — all of these things are sort of a combination of when history hits you at a certain point in your life, and that is very important. So generational change, if you look at it that way, is essential. The problem that I and the other researchers who signed this letter that you mentioned have is with the use of fixed categories and also the names for the categories. …Science is all about categorization, biology is all about species and how to define different species, and that scrutiny has just never been applied to these categories.

So unlike gender or race ethnicity, only about half of people can correctly identify the generation label that has been applied to them, even if you show them a list of the titles. So they may identify with certain aspects of when they grow up. They might know what it was like to have been in college at a certain time, to have been afraid of being drafted in Vietnam, to have their education disrupted by the pandemic, and have something in common with those people who went through that at the same point in their lives. So that may be a key part of their identity and personality, but they’re not really identifying with these categories that marketing and consulting people have laid over them.

Malcolm Burnley: Right. And I want to get into how we — I’m using the collective we — name these generations, but just along the lines of what you were saying. I read this story in The Atlantic … by Joe Pinksker, and he noted some of that data that I believe Philip was talking about or similar data about how people often struggle to identify their own generation. So this says, “the labels have also gotten progressively less meaningful. According to a survey that he says 74% of boomers associate themselves with their generational label, but the share declines with each successive generation. Only 53% of Gen X and 45% of Millennials identify as being part of that” Jean, does that mean that they’re actually less meaningful? Is that somehow discrediting, the fact that people don’t identify as being part of that generation?

Jean Twenge: I’m not convinced that that really matters all that much, that people don’t identify with the particular generation. I’m a Gen Xer myself. We don’t want to be grouped into anything. We don’t want to be labeled with anything that’s sort of part of the generational personality. I think the labels are more useful for analysis and more useful for understanding. And I’m not convinced it really matters that much that people identify with the generation themselves.

Malcolm Burnley: So I want to continue with you. You’ve spent 30 years, I believe, writing books, doing research on generational labels. So you’ve obviously continued to not only believe the merit of this, but seen statistically, quantitatively, and qualitatively the value of this. Could you get into it just a little bit from a scientific or research perspective, like why you think it’s valuable to be able to group people in this way, especially over time?

Jean Twenge: Absolutely. Yeah. I think there’s in some ways, two different questions. We want to make sure that we’re focusing and asking the same question. So one is, do people differ based on when they’re born? And Dr. Cohen and I can both agree that that’s true. I think the vast majority of people agree that that’s true, that people are shaped by the times that they grew up in and the times they come of age. In particular, that generations do differ based on personality traits, behaviors, attitudes, and so on. There are many examples of that. One is, say, especially a few years ago, if you ask people about their attitudes around same sex marriage, you would get a very big difference between Gen Z and the silent generation. And that’s changed over time as well. All generations have changed in their attitudes on that, too. So we know that. We know that there’s differences. But then the question is how do we group people when they do the analysis? Do we use individual birth years? Do we use birth decades? Do we use generations? And those decisions are somewhat arbitrary. Dr. Cohen and I think agree on that, but it seems to be useful to group people into larger groups based on events they experienced or certain differences among generations in terms of mental health or optimism or attitudes. And that makes it easier to understand what’s going on from an analysis point of view … I work with very large surveys of people in many cases that go back decades. And when you’re trying to figure out, okay, how has this changed? How has, let’s say, rates of depression, how have they changed? You have to make that decision about how are you going to group that? Are you going to group it by generation, by years? And it is true that these labels are not as often used in academic papers, but that doesn’t mean that they don’t have some value for discussion. They give us a common ground for discussing people born at certain times that I think is useful.

Malcolm Burnley: Okay. So time in society and culture is naturally progressive — I think we can all agree on that to some degree. So there’s always going to be change. And why do we think generational terms, as Jean was just getting into, as opposed to, say, decades as opposed to four year increments? Why can’t we just think of it maybe along a continuum that doesn’t have to be so segmented? Philip, do you have any thoughts on that?

Philip Cohen: Yes. Well, you’re absolutely right. … Even a year is an arbitrary distinction … instead of a day or a minute or an hour. So at some point you break up time just to look at the progression. But there’s no reason to use these generation categories. They are different lengths. The Baby Boom was longer than Generation X for some reason — for no reason, I should say. One of the concerns I have is that once you fix the category in one study and then lay the category onto another study, you miss key things. The Baby Boom was a real event. It was a huge it was an increase in birth rates. And so that will give a certain commonality to the experience of Baby Boomers. They were part of a large group. However, early Baby Boomers came of age in time for the Vietnam draft. So 40% of them served in the military. Late Baby Boomers were after that. So only about 10% of them served in the military. So on one other dimension, they have a completely different experience. Or if you look at the pandemic today and the group that people call Millennials, some of them are 25 and haven’t finished school or gotten married or had children — they’re at a completely different life stage than those who are 40, who have families and are trying to navigate children in school and that whole set of experiences related to the pandemic. But if you had that category “Millennial” in your head before the pandemic came, you would group those people together and you would miss it would not serve your interest in trying to understand the social change.

Malcolm Burnley: …We were talking about how generations previously were both longer and also maybe had more natural definition. Speaking about Baby Boomers, there was an actual event being World War II and coming home after that, that caused that. But since then, it’s been changing a little bit. Right?

Philip Cohen: Well, the society hasn’t really changed. It’s just the convention has changed. There’s no reason that Gen X and Millennial have shorter than the Baby Boom except the impatience of researchers who are in a hurry to name the next generation. In fact, generations in real life have been getting longer, of course, as people get married and have children later in life. So it really doesn’t make any sense that Millennial s, by some accounts, are only 14 or 15 years long, whereas the Baby Boom was 18 years. There is no reason for it.

Malcolm Burnley: Jean, I want to kick that to you. I know that it used to be considered 30 years was a generation. I believe there’s some biblical origins to that, and now it’s half that, maybe even less. Why that shift? Is it technology that’s driving that? What, in your mind makes generation shorter?

Jean Twenge: Yeah, I’m glad you asked. I think we have moved from a system of generations, meaning parents and children and their children, to a concept of social generations. And I think there actually is a very good reason why the Millennial generation is shorter and why the Gen X generation is shorter than boomers and shorter than the silent generation. And that’s technology. So events are important. The pandemic, World War II, Vietnam War, they do shape generations. That is the classic view of generations is to see them in terms of how old were you when you experienced a certain event. But in recent times, there have been other influences which have been just as strong or stronger. First among those is the speed of technological change. When I speak of technology, I’m meaning writ large, also includes changes in medical care, in all kinds of technology that influences our day to day lives, everything from airplanes to washing machines to television. I’m not just thinking of smartphones and technological changes sped up. So smartphones are a great example. They went from introduction to half of people in the US owning one in five and a half years. That is the fastest adoption of any technology in human history. So that speed of change, change in the culture, change in technology has sped up. So I think that’s why you can make an argument for why recent generations should be shorter.

Malcolm Burnley: Philip, at the beginning, you started the article I mentioned in the Washington Post referring to the Williams sisters, the champion tennis players, and how Venus and Serena are technically by the definition, in two different generations, despite hardly having a gap. We have a comment on Facebook from Diane that speaks to that. She says, “My husband’s, born in 1958, me, 1959. That statement, ‘OK, Boomer,’ isn’t allowed to be spoken in our house because it sounds like, okay, stupid. We aren’t stupid.” That speaks to something that I’ve heard from a number of people that they feel like often these terms are used in a weaponized way. Is that consistent with what you find, Philip, or are there also, I guess, other, more virtuous ways to use it?

Philip Cohen: No, I think that certainly is a risk. And I would not suggest that everybody who’s using these terms is committing some sort of age discrimination, but I do think they become very convenient handles for that kind of stereotyping and discrimination. So a lot of the use of the term popularly amounts to essentially old people or kids these days. And there’s a sense in which we never expected Millennials to grow up. And it’s really weird that they did because the stereotypes about them were about young people. So it’s an awkward process. And it certainly is the case that change is accelerating in terms of technology. And I absolutely don’t want to diminish that at all. But when you say the Williams sisters are technically in different generations, I just want to be clear that I wouldn’t say “technically,” I would say conventionally by a standard that doesn’t make sense. I use that example because it shows you that if you went into trying to understand something like that family or that experience with a fixed category, you would be undermining your own analysis. Before you start, there are things about did you grow up in a world in which the Williams sisters existed as international star Black female athletes? That’s a different world than existed before. Or in terms of politics, if you think about what was the first election you voted in, or technology, did you have a smartphone when you started high school? These are key ways that world events shape people’s lives. And my problem is just with trying to wrap categories on them before we have even studied them. And I think the person who said, “OK, boomer” can’t be spoken in our household is really onto something, because the easy use of categories really contributes to that kind of stereotyping.

Malcolm Burnley: Yeah. One thing I’ve been wondering, which speaks to what Philip was saying and I want to get your input on this, Jean, is that my understanding is the history of naming generations really dates back only a couple hundred years and has really accelerated in the 20th century, late 20th century. But one thing that seems to change with this convention of naming generations early in their lives — or in their formative years, before we fully know what that generation is going to accomplish or maybe fully know how those traits are going to change or not. So why is there this obsession or emphasis to define a generation, I guess in their formative years as opposed to in their adult years?

Jean Twenge: I think it’s really simply to try to understand the upcoming generation. So it’s kind of a funny little way that it works that older generations are always very often really interested in understanding the younger generation. The younger generation is not interested in understanding the older generation. I don’t know why that is. And I think it comes mostly from a good place of, say, teachers and college faculty members want to understand their students. How are my students different from the students I had five years ago or ten years ago or twenty years ago? Managers want to understand how are my young employees different? How do they see the world differently than when I first started my career? So I think it comes from that idea of wanting to understand. I think that example is a great one of we didn’t expect the Millennials to grow up. That’s actually why we really need generational labels to understand people, for people to say at the beginning of the pandemic, people are complaining about all the Millennials going on Spring break. I love the comments for Millennials online. They would say “we are too old” with a period after every word. We’re at home with our kids — because then it helps us understand to say, no, that’s not the generation that you’re talking about, that’s Gen Z or IGen who is in college now. And that helps shift our understanding that people in their 20s are now born at a different time.

Malcolm Burnley: We got a comment from Katherine that I can definitely relate to. Full disclosure, I’m a Millennial. I should have probably said that at the beginning. So Katherine’s comment is “I’m a Millennial. We were supposed to be more confident and entitled, but also anxious and depressed, social justice oriented, but also selfish, overachievers in school, but also unprepared for the real world. Now I see the same thing written about Gen Z. Is each generation actually more unhappy and unprepared or entitled than the one before? Or is it just a continuation of older generations’ handwringing?” Jean, would you like to take a crack at that one?

Jean Twenge: Sure. So in some cases, we do have linear changes, meaning each generation is more, say, self confident or individualistic or depressed than the one before. That’s been a very common path. That was a very common pattern, especially from, say, Silent Generation to Boomers to Gen Xers to Millennials. And as time goes on, we get a better understanding of these things because a lot of that changed with Gen Z. A lot of those trends started to turn around. Optimism and self confidence was going up for four generations, and then it just fell with IGen. Mental health is a much more complex picture where depression was going up and it kind of leveled off with Millennials, but still at a historically relatively high rate. And then it’s just skyrocketed with Gen Z. So there are different patterns for some of the different traits. But I do think one big caution is necessary that I’ve often heard this said, well, people said that about the previous generation. That doesn’t make it wrong. A lot of changes have gone in the same direction for quite a long time. Other times, then they’ll turn around. It just depends on which traits or behavior or attitude we’re speaking of.

Malcolm Burnley: For example, I think you noted in your research, if I had this right, that individualism has long been on the rise generation to generation, but narcissism is one that seems to be reversing course or at least lessening with this current generation Gen Z. Could you make sure I have that right first of all and explain if that’s true, that narcissism is one, or the idea of generations being selfish may actually not be carrying on?

Jean Twenge: Yeah, that seems to be the case. So we were able to look at scores on the most common measure of narcissistic personality traits, which, by the way, is not the same as the clinical disorder. This is just variation among normal people in how self focused they are, how great they think they are. Those items like, I think I am a special person – if I ruled the world, it would be a better place. And scores on that measure, we’re steadily increasing among college students between early eighties, which would have been, say, late Boomers, early Gen Xers all the way through to about 2008. And then with the Great Recession, it turned around. And even as the economy improved, those scores did not go up, possibly because of some of the influences around social media and smartphones, always in exact science to say exactly why the changes happened. But, yeah, that was a change that turned around. Those scores started to fall around 2008 among college students, and they fell all the way back to close to the level of where they were in the early 80s. So that’s a trend that went one direction, and then you had a complete reversal.

Malcolm Burnley: So, Philip, we obviously don’t have different DNA between generations. It’s not like we are fundamentally different creatures. Right. But as we’ve been talking about, there are multiple theories of change about generations changing, I guess, based on external events or stimuli or maybe simply their values are different — being born in a certain environment. So I guess there’s certain theories either that they’re exerting their influence or maybe they’re being influenced by events that are happening to them. Is there a big debate, I guess, among sociologists about that? Does it feel like there’s more of a consensus on one or the other, and how do generational labels fit into that?

Philip Cohen: Well, the short answer is: they don’t. But you’re right about the question of the different kinds of forces at work. If you think about the sort of the very simple math of time, we can break down the events or the things that shape people into the categories of age, how old you are, and that’s sort of biological. So are you of childbearing age? Are you postmenopausal? Are you older young? There’s the period that you’re living in. So are you alive at the moment that something happens, like a war or recession? And then there’s the cohort that you’re born into the time you were born. So age and period and cohort, and each of those things can have independent effects on people. So some things affect everybody at once. That’s what we call a period effect, like climate change. Some things affect people based on age, like those biological things I mentioned. And some things are at the intersection, are cohorts – so, being a certain age when something happens. And in terms of social analysis, it’s very tricky to parse those things out. And one of the reasons is there’s different kinds of change happening at the same time. So, for example, I’m a sociologist. My cohort I was in graduate school in the 90s when certain fads were in fashion for the kind of research that we did — that may be totally different from somebody who is an actor or an athlete or a truck driver. If you play in the NBA, if you came up during the time when high school players were allowed to go straight to the NBA, that changed the whole league. So that changed your career in a way that didn’t affect me as a sociologist at all. I was much more affected by the personal computing revolution. But those are both cohort effects. That is, how old were you at a certain time? But they’re not universal across society.

Malcolm Burnley: It’s funny you bring a basketball. I had a question about that. I’m a huge basketball fan, and I often think about maybe this corollary to sports where generations are talked about a lot, and that’s true of music, and I think a lot of different fields. Right. But we think of generations differently, maybe with respect to age versus, say, in basketball. Right. When a generation of when a player played or there was a certain rule. And so it’s tricky and confusing. I think our use of generation is often very different, right?

Philip Cohen: We talk about generations of the iPhone or generations of the Internet. And like Jean said, human generations aren’t about reproduction anymore, the way they were thought about once, sort of in the biological sense. But the key thing there is that time moves at different speeds in different arenas in a way. So iPhone generations are shorter than professional athlete generations.

Malcolm Burnley: So we have a comment. Joan said, “I don’t remember being called a Baby Boomer as a generation until we established our identity during the Vietnam War. But we were not homogenous. Some of us protested the war, some of us joined. Our music was distinct in many ways. I think our behavior characteristics were what led the media to look for the label for us.” She continues, one thing that she brings up I think it’s important to note here is how all generations are obviously not monoliths, but different class, race, sex differences, all sorts of other identities can inform how we either conform or don’t conform to these generational labels. Is that right, Jean?

Jean Twenge: Absolutely. I mean, people are complex. We have many different identities. And when we think about who we are when we were born or our generation is just one part of that. I think the thing that is remarkable, though, is how consistent many generational differences are across different demographic groups. So, for example, with Gen Z or IGen, we have really enormous mental health crisis in this generation. Rates of depression began to rise among teens and young adults around 2012. They’ve now doubled the percentage who are depressed in that age group, and that shows up across race and ethnicity. It shows up among both boys and girls, men and women, and it shows up across different areas of the country. It’s pretty consistent in some cases. Some of the changes are a little bigger for girls and women, but it has affected many of these groups. So even though there are many different influences on people, it’s really pretty amazing how many of those generational differences show up, no matter where you’re living or what your social class is or what your race or ethnicity is or what your gender is.

Malcolm Burnley: I want to play a short clip from Richard Linklater’s 1993 film Dazed and Confused, which is often considered somewhat of a generational look of youth culture in the late 19s 70s. We’re going to play that right now.

A: I’m just going to get drunk, maybe get laid.

B: I’m serious, man. We should be up for anything.

C: I know we are.

B: But what?

A: I mean, God, don’t you ever feel like everything we do and everything we’ve been taught is just to service the future?

B: Yeah, I know. It’s like it’s all preparation, right?

A: But what are we preparing ourselves for?

B: Death, life of the party?

C: It’s true.

A: But that’s valid because if we’re all going to die anyway, shouldn’t we be enjoying ourselves now? I’d like to quit thinking of the present. Like right now is some minor, insignificant preamble to something else.

B: Exactly. And that’s what everybody in this car needs. It’s some good old worthwhile visceral experience.

Malcolm Burnley: So I’m wondering, we talked about how pop culture can sometimes both reflect and potentially influence generations, too. I guess, Philip, our cultural touchstone, say, like Dazed and Confused, do they produce certain character traits of generations? Do they reflect them? Where do those fit in, I guess, to this conversation?

Philip Cohen: Well, one of the amazing features of modern society and generational change, I think I would say, is that we have what we would call reflexivity in these discussions. So we’re having this discussion, Jean and I sort of our Ivory tower academics, but anybody can listen. Or if people make a movie about it, the generational terms suggested in a movie might be the ones that stick. So it’s absolutely the case that the discussion about these things, whether it’s in the cultural arena or in the media or in research, feeds back on itself in a way that is very unpredictable. That’s part of the fun of it. And it certainly gives us, if I would say one positive thing about the generation labels is that it gives people a common language. The downside of that is all the stereotyping and astrology type stuff. But on the positive side, it sort of is a conduit for that kind of reflection. And so I think that kind of interaction between arenas, that dynamic is really great.

Malcolm Burnley: So I have to say, full disclosure, the more I looked into and research this topic and research for this conversation that we’re having, the more I felt somewhat nihilistic, I would say about generations, about age. We were saying generations might be arbitrary, but then if you look at it, decades are arbitrary, and then in some respects, multiple years or presidential tenure is arbitrary. So I’m wondering, Jean, can you pull me back? I mean, can you kind of reinstall some sense of confidence in me? I feel like I was kind of unplugged from The Matrix, if you will, to quote a movie that’s very defined by Millennial s, that none of these things matter. And I know that you feel like they very much do. So I’m just wondering, so why should we care about this?

Jean Twenge: Well, I think, again, we have to make sure we’re asking the same question that does it really matter what the name is of each generation or exactly where the cut off is? Probably not. They’re useful, really, and they give us a common ground. But are we influenced by being born in one time versus another? Absolutely. If you compare your life and what you have experienced to your parents, to your grandparents and to your great grandparents, you can immediately see why there are definitely differences and how important those differences are. Plus, to make it a little bit lighter, that clip from Days and Confused shows just how much fun it is for people to reflect back on their generation’s experience with high school, for the generations that follow, to try to understand what those experiences were like and to understand in terms of their own experience. Days and Confused is an interesting movie because it was set in 1976, so it’s about boomers in high school, but it came out in 1994 when the young people were Gen Xers. So it’s a movie that was popular with Gen Xers, even though it was about boomers. And I think the kind of clip like those three people talking in the car show why it’s a movie that has a GenX sensibility, even though it was about boomers. And it allows us to have fun with those things in the culture and all of the differences we experience, having grown up at different times and understanding ourselves, understanding our children and understanding our parents better. That’s why it’s important. That’s why it’s fun.

Malcolm Burnley: Philip, do you have a thought there?

Philip Cohen: Yeah, I do. I think that’s a great point. I wrote a little reflective essay when I turned 50, and turning 50 was pretty boring. But what was interesting was looking back at what it meant to be 14 and 1981. That’s a much more interesting fact about myself. And of course, I bring a contemporary perspective to looking at that moment, but being 50 years old is kind of boring. But when I think about how I got here, when I think about what it meant to be in junior high school, when Thriller came out, the Michael Jackson album, that’s a defining moment. And the subsequent technological change, the fact that one person that I really looked up to in the 80s carried around a large briefcase full of Grateful Dead cassettes that were rare and hard to come by, and he had to have the humidity checked before he walked into a room. And now I can listen to the Grateful Dead channel on satellite radio in my minivan all day. That’s in one lifetime. So that is fascinating and interesting, and I think I appreciate that in a way that somebody who didn’t live through the 80s can’t.

Jean Twenge: …I think there’s a very interesting thought there, which is that this is the essence of generations and why they’re interesting, that it’s not just that cultures change. It’s not just that events happen. It’s that those events have effects on people. And they’re not just superficial effects, like I lost my job during the pandemic or I got married later. Those are things that change people’s life courses but also change what’s going on in their heads. That if you were born save after 1980, that you have never known a world that put duty before self as an absolute value, that you were probably always told you can be anything you want to be and you’re special. It changes the whole way that you look at yourself and at culture and your life, and it influences how you make decisions and how you operate in relationships, that it’s not just the changes and events and what’s going on outside that. It also is all of those abstract things about how we think and how we feel and how we relate to each other, that those changes as well.

Malcolm Burnley: I’m also wondering about the idea. I couldn’t help but think about the Greatest Generation and how potentially these generational labels either set up individuals for failure or maybe to not live up to expectations. Or conversely, I’ve often heard people say, “I’m a self hating Millennial.” I don’t actually like my generation. And it’s such a strong stance either for or against. I mean, Philip, are these generational labels problematic in that sense, too, that there’s either a burden or expectation that comes with them?

Philip Cohen: Yes. First of all, let me just say that what Jean said is fascinating, and I think that’s totally right. I do think the self-hating Millennial is an interesting thing. What they’re really rejecting is the ways that the category and label is used. “I don’t like the person that is described when people stereotype Millennials,” and that’s pretty reasonable. Or that’s different from saying I don’t like people my age, which is quite a different thing. That might be narcissism, it might be depression, or it could be a social alienation… That goes back to what I was trying to get out before with this idea of reflexivity, is people are thinking about what the categories mean to them, and that’s the dynamic in this, the way we process historical social change now is through this very analytical frame of “I am this, I belong to this group. I know that other people think certain things about this group, and my identity is in the interaction between those two things.” So that’s just the beauty of social change, both the good and the bad.

Malcolm Burnley: I don’t mean to focus on Millennials so much, but as Jean, as you laid out at the beginning, it seems like Millennials often draw the ire of so many different generations. Jia Tolentino in the New Yorker just had this incredible description of Millennials that I wanted to just read. She says, “A composite image emerged of a twitchy, phone addicted pest who eats away at beloved American institutions the way the bol weevils feed on crops.” Describing Millennials. Simply put, why do people have such an issue with Millennials?

Jean Twenge: Well, I think people have an issue with generational change overall. So I’m a Gen Xer. We were called slackers almost immediately. People said we had herky jerky brains, that we were dumb and violent and stupid. This just happens. There are these negative stereotypes that get put often on younger people, and some of them have a basis in truth, and some of them do not. So with Millennials, there is definitely some proof around to say Millennials … are … much more self confident than boomers were at the same age, which actually kind of goes against some generational stereotyping there. And it is absolutely true that Millennials took longer and are taking longer to hit adult milestones, like settling into a career or marrying or having children. That’s just because of the way society has changed. We take longer to grow up now, and it just shows up among Millennials, and it’s a symbol of the way that things have changed. So I think that has a lot to do with it, that you’re seeing the manifestation of the way that things have changed. And that can be scary, especially for older people. You think about how things have changed around you. Some of those things are good, some are bad, some are neutral, but it can change, can be frightening. And I think that is probably why each generation gets subjected to some of that treatment.

Malcolm Burnley: Philip, we didn’t spend too much time talking about the letter that you and 150 other researchers and professors wrote was sent to the Pew Research Center we mentioned at the beginning instructing or asking if they would drop these cultural generational labels. And Pew’s response was that they were considering it. Where do you think things go from here? Do you think it seems like there’s a lot of energy around criticizing generational labels? Where do you think we go from here?

Philip Cohen: Well, I don’t think it’s sustainable. In that letter, I sort of seized on the moment of hitting something that we were calling Generation Z to say maybe this is a good moment to put the brakes on this. We can lay this tradition to rest and not try to come up with a creative, original name that defines the characteristics of a generation that hasn’t really come of age yet and start applying something more arbitrary like decades or years, and just get back to analyzing the question before we determine the answer. We’re all interested in social change. We know that social change happens unpredictably. It seems to be accelerating, especially in the technology realm. We should not be putting new names on forthcoming groups that haven’t yet expressed themselves or experienced even their young adulthood yet. So I think in the research community, there’s a pretty good consensus that the downside is greater than the upside, on using generation labels. On the other hand, the click economy and the people who are writing popular articles you can’t beat them. How many times do you see the headline for an article add something about generations when there’s nothing about generations in the article — it’s because headline writers have different incentives than people who write the articles. They need clicks and the public loves generation labels and arguing about them. So it may be a lost cause, but I think at least it will be helpful if we’re increasingly skeptical and maybe we’ll get off this train.

Malcolm Burnley: Well, I think we’re going to have to leave it there. Philip Cohen, thanks so much for joining us on radio Times.

Philip Cohen: Thank you. It was a great conversation.

Malcolm Burnley: His article in the Washington Post is titled, “Generational labels mean nothing. It’s time to retire them.” And Jean Twenge, thanks for joining the conversation.

Jean Twenge: Thank you very much. Great conversation.

Malcolm Burnley: Absolutely really enjoyed it. We’ll have to have you back on to maybe continue this. That’s Jean Twenge, author of numerous books including IGen, an upcoming book on generational labels. That’s it for today’s edition of Radio Times. … Diana Martinez is the engineer for today’s edition of Radio Times. The show is produced by Debbie Builder and Paige Murray Bessler. I’m Malcolm Burnley.

2021 content creation report

Detail from Wombo art from the prompt “hard work labor grind muscle sweat”, plus phone selfie.

Our bunny and I spent a lot of time in the home office again this year. One of us spent their time shredding up cardboard, eating green leaves, and pooping in a box — and the other one just sat around. Somehow, content was created.

The way I run my career these days, a good part of my work doesn’t figure in the accounting measures of productivity employed by my employer. Of course, I teach my classes. I am the director of our graduate program. I advise awesome students. I attend meetings (including of UMD PACT at the Libraries, where we work to promote open scholarship at the university), and I’m even chair of the Appointment, Tenure, and Promotions committee of our college. But, apart from the occasional “published” paper, conference presentation, or book, the rest of the content created is just out there.

So, with apologies to our Faculty Activities Reporting System (“Telling Y[Our] Story”, Faculty Success [formerly Digital Measures] by Watermark) if there is some overlap, here’s my content creation report for 2021.

Papers

Scholarly Communication

  • Altman, Micah, and Philip N. Cohen. Forthcoming. “The Scholarly Knowledge Ecosystem: Challenges and Opportunities for the Field of Information.” https://osf.io/preprints/socarxiv/ctdb9/. …We draw upon major reports from a cross-section of disciplines related to large scale scientific information ecosystems to characterize the most significant research challenges, and promising potential approaches. We explore two themes that emerge across research areas: the need to align research approaches and methods with core ethical principles; and the promise of approaches that are transdisciplinary and cross-sectoral.
  • Altman, Micah, and Philip N. Cohen. Preprint. “Openness and Diversity in Journal Editorial Boards.” https://osf.io/preprints/socarxiv/4nq97/. This study aims to measure diversity in scholarly journals’ editorial board structure and characterize patterns of editorial diversity across types of journals. To accomplish these aims, we integrate multiple sources of data at the journal and editor level to assemble a novel database describing the composition of editors and editorial boards for more than six thousand journals internationally, characterized by discipline, commercial publishing model, and research transparency. … Editorial leadership is more homogenous than editorial boards, and diversity across both boards and leadership varies substantially across disciplines. Open-access journals’ boards exhibit less gender diversity and more international diversity than their closed-access counterparts.

Pandemic studies

  • Cohen, Philip N. 2021. “Disrupted Family Plans and Exacerbated Inequalities Associated with COVID-19 Pandemic.” https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2784123. Commentary: 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.
  • Cohen, Philip N. Preprint. “Baby Bust: Falling Fertility in US Counties Is Associated with COVID-19 Prevalence and Mobility Reductions.” https://osf.io/preprints/socarxiv/qwxz3/. 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.
  • Cohen, Philip N. Preprint. “Pandemic-related decline in injuries related to women wearing high-heeled shoes: Analysis of U.S. data for 2016-2020.” https://www.medrxiv.org/content/10.1101/2021.12.26.21268426v1. Background. Wearing high-heeled shoes is associated with injury risk. During the COVID-19 pandemic, changes in work and social behavior may have reduced women’s use of such footwear. Methods. This study assessed the trend in high-heel related injuries among U.S. women, using 2016-2020 data from the U.S. Consumer Product Safety Commission’s National Electronic Injury Surveillance System (NEISS). Results. In 2020 there were an estimated 6,290 high-heel related emergency department visits involving women ages 15-69, down from 16,000 per year in 2016-2019. The 2020 decline began after the start of the COVID-19 shutdowns on March 15. There was no significant change in the percentage of fractures or hospital admissions. Conclusions. The COVID-19 pandemic was associated with a decline in reported injuries related to high-heeled shoes among US women. If this resulted from fewer women wearing such shoes, and such habits influence future behavior, the result may be fewer injuries in the future.
  • Cohen, Philip N. Preprint. “Injuries related to respiratory masks in the US.” https://osf.io/preprints/socarxiv/f3wbn/. Protective facemasks are important for preventing the spread of COVID-19, and almost all Americans have worn them at least some of the time during the pandemic. There are reasonable concerns about some ill effects of mask-wearing, especially for people who wear masks for extended periods, and for the risk of falling as a result of visual obstruction. But there are also unsupported fears and objections stemming from misinformation and fueled by political disputes. The study analyzed the Consumer Product Safety Commission’s National Electronic Injury Surveillance System (NEISS) for 2020, finding an estimated 5122 reported injuries in the population. The most common type of incidents involved facial injuries, rashes, falls, and those that might be considered anxiety-related. Wearing protective face masks is extremely safe, especially in comparison with other common household products, and in light of their protective benefits with regard to prevent the spread of COVID-19.
  • Cohen, Philip N. Preprint. “Host, Parasite, and Failure at the Colony Level: COVID-19 and the US Information Ecosystem.” https://osf.io/preprints/socarxiv/4hgam/. This review uses host-parasite interactions in nonhuman species to frame the poor US response to the SARS-CoV-2 pandemic. The US defenses against SARS-CoV-2 were weakened by malformations in the information ecosystem that disrupted the dissemination of information while spreading misinformation and disinformation. Distortions arising from political corruption, and magnified by social media platforms, were especially consequential. I conclude that this failure may ultimately result in a social evolution that weakens US global dominance. On the other hand, if the crisis contributes to innovation and reform in the information ecosystem, that may contribute to a more egalitarian and democratic system for the production and dissemination of knowledge.

Families and households

  • Cohen, Philip N. 2021. “The rise of one-person households.” https://journals.sagepub.com/doi/full/10.1177/23780231211062315. In this visualization, I show the trend in the proportion of households that comprise only one person in 75 countries, representing 73 percent of the world’s population, using national data collected between 1960 and 2019. Europe and the United States have the highest solo living rates, along with two African countries (South Africa and Botswana, both severely affected by the HIV/AIDS epidemic), Israel, Jamaica, and Puerto Rico. In all, 53 of the 75 countries exhibit increases in one-person households, including all European countries.
  • Caudillo, Mónica L., Andrés Villarreal, & Philip N. Cohen. Preprint. “The Opioid Epidemic and Children’s Living Arrangements in the United States, 2000-2018.https://doi.org/10.31235/osf.io/he4pb. Using the 5 percent sample of the 2000 Census, 2005-2018 American Community Survey (ACS) data and restricted Vital Statistics we assess the effect of the opioid epidemic at the local level on the rates of children living under different types of family arrangements. Local fixed-effects models show that a greater intensity of the opioid epidemic, as measured by a higher opioid-overdose death rate, is associated with a lower rate of children living with two married parents, and a higher rate of children living with two cohabiting parents, with only a father, and with adults other than their parents. The opioid epidemic appears to increase the rates of children living in family structures that tend to be less stable, which has potential long term implications for the wellbeing of future generations.
  • Cohen, Philip N. 2021. “Hard times and falling fertility in the United States.” https://osf.io/preprints/socarxiv/pjf3n/. Recent reports have suggested that falling fertility in the US since the 2008 recession is being driven by women with advantaged status in the labor market taking advantage of career opportunities. This paper takes issue with that conclusion. Fertility decline was widespread after the 2008 recession, but most concentrated among younger women. Although women with above average education have long had lower birth rates, the analysis shows that birth rates fell most for women in states with higher than average unemployment rates, especially among those with below average education. This is consistent with evidence that birth rates are falling, and births delayed, by economic insecurity and hardship.

Op-Ed

Citizen Scholar

My new book, Citizen Scholar, is under contract with Columbia University Press. As I write, I’m posting essays and excerpts on this blog.

Media work

If my list is up to date, I was quoted in print or featured on TV, radio, podcasts, or whatever, about 34 times. Videos I could capture are on this YouTube playlist.

Video

On my YouTube video channel I have class lectures, how-to, media appearances, and academic talks. The most popular one this year was an instructional video titled, “What is Life Expectancy?

This blog

Of course, there’s still this blog. As I write less on here and more in other venues — especially short papers on SocArXiv — reader clicks have fallen 50% since the peak in 2015, to about 200,000 in 2021. Still there were some popular ones this year:

SocArXiv

This one isn’t really content creation, but curation or facilitation. SocArXiv, the research paper archive I’m director of, was made part of the University of Maryland Libraries this year, much to my delight. We also took in more than 2,600 new papers, a 17% increase from last year.

TikTok

Just checking to see if you’re still reading. Yes, it’s here. I guess if you read this far you might like it. Happy new year!

Why I’m leaving the American Sociological Association

Photo by Markus Meier flic.kr/p/Qyv1HN.

I have come to the difficult decision not to renew my membership in the American Sociological Association (ASA). I tried to change the organization for the better over a period of years, including service in elected office, but I failed. Although the association does some good things, for me the good/bad balance has tipped sufficiently that I need to withdraw.

ASA is too expensive. As membership tumbles, a survey showed the biggest problem was the expense of membership and the annual meeting, and they did nothing substantive about it. Association operations are top heavy, bloated, and wastefully inefficient.

ASA lacks the capacity for change. As is common with academic associations, the academic leadership is transient while the staff stay. The staff are working in the associations industry, the membership are working in the academia industry, and their interests conflict. The association won’t make structural changes because they simply take too long to happen — when members try to make changes the staff don’t like, they just stall it out.

ASA is inequitable. The greatest source of income for the association is publications, which is mostly subscriptions to journals paid by academic libraries, which are being bled dry by profit-making publishers that ASA organizes academic labor to subsidize with free content and editorial services. This is a wealth transfer from poorer, teaching-intensive libraries to richer, research-intensive libraries. ASA could publish its journals at much lower cost, and make them open access, but the association wants the money. People say open access will cost cash-strapped authors more, and claim this model is good for scholars at less prestigious universities, but they’re wrong. Publication in ASA journals is overwhelmingly dominated by elite institutions, and they should be paying for it. Instead, ASA has more than doubled subscription fees in the last 8 years.

Image
PNC figure.

ASA opposes open access. The association has had many years to consider alternative publishing models, and it simply never has. The leadership signed a new 7-year contract with the for-profit publisher Sage in 2018, with no substantive discussion with the membership and no advance notification. The Sage paywall and subscriptions from broke academic libraries are the association’s lifeblood. To pacify open access advocates, Sage gave ASA Socius, the open access journal, which is great — even though it’s subsidized by the association’s immoral business model, I like it and publish in it (and I will continue to, even though I will have to pay more when my membership expires). This is part of a broad strategy by legacy publishers to undermine fundamental change in the industry.

In 2019 the association leadership and staff signed a letter to the White House voicing opposition to the open distribution of federally-funded science reports. I organized a petition against it. More than 200 people signed, including many members. The Publications Committee managed to pass a resolution stating our opposition to the letter and urging the ASA Council to take up the issue — which the Council ignored.

ASA opposes open science. A number of members of the Publications Committee spent several years trying to get the association’s journals to adopt several versions of a simple policy to notify readers of whether published work includes access to research materials, such as data, questionnaires, and statistical code (detailed here). After two subcommittees eventually produced an extremely moderate policy, the Council rejected it. Last I checked, only 1-in-6 articles in American Sociological Review meet minimal standards of research transparency.

ASA leadership and staff block change. Back to that petition. The effort to get member voices heard on the issue of the ASA letter to the White House, involved a truly ridiculous and insulting struggle against the staff in the Publications Committee — in which, among other shenanigans, the staff invented a rule that would prohibit me from participating in the discussion of my own proposal. They have perfected the art of bureaucratic stagnation, which includes various strategies to pacify the academic leadership by allowing minor reforms that don’t touch the association’s basic workings. And Sage throws the leadership a nice party at the conference.


ASA does some good things. It publishes good research. It offers mechanisms for community and collaboration. In recent years it has, through member elections, elevated the visibility and prestige of women and scholars of color. The leadership sometimes makes good, important public statements. For myself, these things are no longer enough. I devote a lot of my time to running SocArXiv (for which I am not “paid”), which publishes any sociologist’s research for free. I do trainings and give talks to help sociologists communicate about their work, to develop community and collaboration. In my public work, mostly on social media, I try to elevate the visibility and prestige of women and scholars of color. If ASA makes good statements, I’ll share them, too.

It’s not personal, it’s just not worth the effort anymore. I’ve come to the conclusion ASA is going to have to hit bottom before it has a chance to turn itself around. I hope that people declining to fund its dysfunction with their membership dues — while taking our efforts to develop and promote sociology outside the association — may be a useful part of that process.


Read all posts about ASA at the tag.

Inequality heatmaps: marriage and working from home

To a kid with a hammer, everything looks like a nail. So I used the same kind of figure for two different datasets. Materials at the end.

Marriage

Regardless of how you think about the causal relationship between marriage and men’s economic wellbeing, it’s an important fact that marriage in the US has become more economically polarized, with the social class gap in marriage prevalence widening.

Recently, Scott Galloway wrote a bad blog post about marriage and men, which included this truly terrible and misleading figure, which pours bad data analysis of the General Social Survey (see here) into a manipulated-axis clustermuck, which doesn’t even manage to show much of a correlation:

Anyway, Galloway also recycled a figure from bad 2012 blog post from the Hamilton Project. Bad work, but the trend is real, so I updated it and made a different kind of figure, using a heatmap with geom_tile in R, inspired by Kieran Healy’s Baby Boom heatmap. And I added women, separately.

Using the Current Population Survey (CPS) Annual Social and Economic Supplement (downloaded from IPUMS.org), I broke men and women down into 10 income deciles in each year from 1980 to 2021, and calculated the percentage of each cell that was married (and not separated) at the time of the survey. This is men:

This shows that rich men are much more likely to be married than poor men, and the gap has grown even as marriage rates have fallen across the board. The figure for women is more complicated, and is a good way to remind yourself that the causal story here is not as simple as some people make it sound.

In 1980, women with higher incomes (their own incomes) were the least likely to be married (not get married, be married). The most likely to be married were women with just a little income. Now, women with the highest incomes are more likely to be married than all but the bottom 20 percent. The biggest drop has been among women with low incomes. (Remember, these are cross-sections, so it’s not necessarily reflecting change over time in these women’s lives.) This is an inequality story, as high income women are more likely to be married (with spouses who have incomes as well), and low income women are more likely to be single (without spouses). Cohabitation, which is not included here takes some of the edge off this, but not that much.

Working from home

Starting in May 2020, some forward-thinking people at the Bureau of Labor Statistics added a question to the monthly CPS:

At any time in the LAST 4 WEEKS, did (you/name) telework or work at home for pay BECAUSE OF THE CORONAVIRUS PANDEMIC? (Enter No if person worked entirely from home before the Coronavirus pandemic)

At the time, the great majority of workers in some occupations — especially teaching — were working from home, as their workplaces were shut down by epidemic mitigation policies. Others, such as cooks and waiters, were either unemployed or working in dangerous conditions. Since that first survey in May (through August), the pattern has changed a lot, and there is much less teleworking. But some occupations are still staying home at pretty high rates, including college teachers, programmers, lawyers, and management analysts.

There is a sharp distinction between high- and low-telework occupations. It’s not quite a map of status and income, but it’s not not that, either. As in all things, apparently, the pandemic has been a seismic inequality event. Everything has changed, but very differently for different groups of people. More and different inequalities.

Here is the heatmap, which I originally shared on Twitter.

Materials

I can’t share the CPS data I got from IPUMS, but you can get it yourself with a free account. I shared the Stata code I used to manipulate the data, and the R code I used to make the figures, on the Open Science Framework, here: https://osf.io/2k86a/. My R skills are very limited so I just use it to make the figures, but if you are at a functioning beginning level the code might help.

Sociologists: Don’t embargo your dissertation

Your work is important. Don’t hide it. (PNC video)

This post is about the practice of putting your dissertation under an embargo, which means your university library, and probably its agent, ProQuest, don’t let people read it for a certain amount of time, sometimes only a few months, sometimes many years. At my school, the University of Maryland, the graduate school is implementing a new policy that allows two-year embargoes without special permission (down from six years), and longer embargoes only with permission of the advisor and the dean.

Are you in this to advance knowledge? If so, don’t embargo your dissertation. By definition, a dissertation is a contribution to knowledge. By definition, keeping people from reading it stops that from occurring.

Many PhD graduates embargo their dissertations because it feels like the safer thing to do, because they’re vaguely worried about sharing their work, either because it’s so good someone will steal it, or it’s so bad it will embarrass them — or, weirdly, both. Many people don’t seriously think about it, don’t read up on the question, don’t discuss it with knowledgeable mentors (which your PhD advisor is very likely not, at least when it comes to this question). Lots of good people make this mistake, and that’s a shame. I’m writing this post so that, if you see it before you face this choice, there’s a chance my nagging voice will get stuck in your head.

Some graduate students think they’re being exploited and someone is going to make money off their work. Probably not. (You may have been exploited as a graduate student, and you might have good reasons for disliking your university, but this isn’t about making your university happy.) Maybe your dissertation will lead to an important book that lots of people will read — that is wonderful, and I hope it does. Of course, that’s a very small minority of dissertations, even among really good ones that make important contributions to knowledge. That’s just not in the cards in the vast majority of cases. But unless you already have a contract and a publisher telling you that without an embargo the deal is off — a situation that is vanishingly rare if it occurs at all, at least in sociology — making your dissertation publicly available will not hurt (and will probably help) your chances of accomplishing that goal. And if you’re going to publish articles based on your dissertation, no reputable journal will turn them away because they have overlapping content with your dissertation.

Some graduate students are afraid they will get “scooped” or their ideas will be “stolen.” This is profoundly misguided. You are doing the work so that people will read it. People are going to do what they do. You might be taking a small risk to your personal interest by making your work public, but consider it against the benefit of people reading it (which is, after all, the reason you should have written it). This is your finished work. It’s done. By definition it can’t be scooped. It can be plagiarized, like anything else. Would it be awkward or disappointing if someone published something similar that made similar contributions? Maybe. Will that substantially harm your career or personal interests? Very unlikely.* If you had a good idea, it will probably lead to more. Your ideas and your efforts in the dissertation are on the record now. Be proud of them, take credit for them, encourage people to engage with them, and hope that they will be inspired to do work that follows your lead. If your dissertation is good, it’s worth the risk — because you want people to read it. If your dissertation is bad, there is no risk anyway.

Will making your dissertation public hurt your chances of publishing a book? Almost certainly not. As an editor at Harvard University Press wrote:

“Generally speaking, when we at HUP take on a young scholar’s first book, whether in history or other disciplines, we expect that the final product will be so broadened, deepened, reconsidered, and restructured that the availability of the dissertation is irrelevant.”

And they quoted an assistant editor who went further: making your dissertation available improves your chances of getting a book contract:

“I’m always looking out for exciting new scholarship that might make for a good book, whether in formally published journal articles and conference programs, or in the conversation on Twitter and in the history blogosphere, or in conversations with scholars I meet. And so, to whatever extent open access to a dissertation increases the odds of its ideas being read and discussed more widely, I tend to think it increases the odds of my hearing about them.”

Or, as the editorial director at Columbia University Press, Eric Schwartz wrote in a tweet about sharing dissertations: “No problem. Book and dissertation are for different audiences.”

Of course there may be exceptions. If you have an editor on the hook who insists on an embargo, consider the pros and cons. If you have only a vague hope of publishing it down the road, don’t bother.

Do you want to win awards so everyone is talking about your dissertation? Don’t embargo it. Thanks to a 2015 change in policy at the American Sociological Association:

“To be eligible for the ASA Dissertation Award, nominees’ dissertations must be publicly available in Dissertation Abstracts International or a comparable outlet. Dissertations that are not available in this fashion will not be considered for the award.”

There are real, important principles at stake. Hate on your universities all you want, but some of their lofty rhetoric is true and good — and we should be holding them to it, not scoffing at it. Many universities, like the University of California system, have policies based on such high-minded statements as this:

“The University of California is committed to disseminating research and scholarship conducted at the University as widely as possible…. The University affirms the long-standing tradition that theses and dissertations, which represent significant contributions to the advancement of knowledge and the scholarly record, should be shared with scholars in all disciplines and the general public.”

Embargoing the work for years absolutely violates the spirit of such a principled policy, even if they do allow an embargo. Making your work accessible years later is clearly depriving the public of “significant contributions to the advancement of knowledge and the scholarly record” for the most important period in the life of the work — the years right after it’s done.

Here’s the statement from the University of Chicago:

“The public sharing of original dissertation research is a principle to which the University is deeply committed, and dissertations should be made available to the scholarly community at the University of Chicago and elsewhere in a timely manner. If dissertation authors are concerned that making their research publicly available might endanger research subjects or themselves, jeopardize a pending patent, complicate publication of a revised dissertation, or otherwise be unadvisable, they may, in consultation with faculty in their field (and as appropriate, research collaborators), restrict access to their dissertation for a limited period of time.”

Some people might skim through this policy and say, “Oh, cool, they allow an embargo,” and just check the box requesting it. But that’s making a powerful statement against the important principle articulated in this policy. If you don’t have a really good reason to embargo your dissertation — and you almost certainly don’t — the public interest demands that you make it public. Take the value of your work seriously. Not it’s commercial value, it’s actual value — which is to people who want to read it.

There is also an important accountability principle at stake. Should PhDs be awarded in secret, with no accountability beyond the committee room walls, until years later? For those of us on the faculty, how are we to evaluate programs and their candidates if we can’t scrutinize their most important works? How can we claim to be reputable programs if we shroud our work behind embargoes. Without at least this bottom-line transparency, there can be little accountability.

I write this post out of a certain sense of shame. I’m the director of graduate studies in our department, and I haven’t made it a priority to talk to students about this, because I didn’t know it was happening. When I looked at the dissertations from our department, which are archived in the Digital Repository at the University of Maryland (or, if they are embargoed, merely listed), I saw that among the last 19 dissertations, 12 were currently embargoed. The seven that were made public have been downloaded 1,200 times.

If you want to embargo your dissertation, or if someone is telling you that you should, the burden is on you (or them) to prove that the real benefits of the embargo — not just for you, but for the contribution to knowledge that your work represents — are greater than the harm of denying readers access to your research. The default must be to share our dissertations, with rare exceptions only when real (not imagined or rumored) circumstances demand that the public interest in access to knowledge be sacrificed.


* My dissertation, completed in 1999, although excellent, was not especially original. My major contributions were updating research on a longstanding theory to (a) use more recent data, (b) include women, and (c) use hierarchical linear models. My dissertation was titled, “Black Population Size and the Structure of United States Labor Market Inequality.” In 1997, as I was hard at work, and had a chapter under review at Social Forces (which I had already presented at two conferences), an article appeared (in Social Forces!) titled, “Black Population Concentration and Black-White Inequality: Expanding the Consideration of Place and Space Effects.” The authors used (a) the new data I was using, they (b) included women, and their (c) models were fancier than mine. I was crushed. And then, with my advisor’s help, I got over it. My article (with a citation to theirs added) got published the next year anyway, titled, “Black Concentration Effects on Black-White and Gender Inequality: Multilevel Analysis for U.S. Metropolitan Areas.” People read both articles. And then I went on to do a bunch more work in that area, with great collaborators, building up a body of research that drew from my dissertation but went much further in terms of theory, methods, and data. My article got cited plenty, partly because it was part of a group of articles that traveled together. I was “scooped,” but they didn’t get their ideas from sneaking a look at my brilliant work in progress, they were logical next steps in a 40-year trajectory of research on an established set of questions. Their publication strengthened the field in which I was working. (In fact, if they had stolen my ideas their paper would have been worse for them, and less damaging to me.)

Comment on pandemic family plans

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.

Published: September 15, 2021. doi:10.1001/jamanetworkopen.2021.24399

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Cohen PN. JAMA Network Open.

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

  1. 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
  2. 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
  3. National Center for Health Statistics. Provisional estimates for selected maternal and infant outcomes by month, 2018-2020. Accessed July 1, 2021. https://www.cdc.gov/nchs/covid19/technical-notes-outcomes.htm
  4. 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
  5. Hartnett  CS, Gemmill  A.  Recent trends in US childbearing intentions.   Demography. 2020;57(6):2035-2045. doi:10.1007/s13524-020-00929-w
  6. 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
  7. 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

Chasing Life podcast on making babies, or not

CNN’s Dr. Sanjay Gupta has a podcast called Chasing Life about coming out of the pandemic. Associate producer Grace Walker interviewed me for an episode titled, “Let’s Talk About Making Babies (Or Deciding Not To).” In it reporter Chloe Melas starts with the story of a Black couple (two women, one of them trans) seeking to have children. At about minute 21, she turns to the fertility decline in the US. The transcript of that part is below. This episode would be good for teaching.


Chloe Melas: But we can’t forget – not everyone wants to have children. And that’s OK. According to the CDC, the number of births in the United States fell by 4% last year – the largest annual decline since 1973. Given the global pandemic, for demographers like Philip Cohen of the University of Maryland, this isn’t too surprising.

Philip Cohen: What we’ve learned in the last century or so is that when there are crises birth rates go down. It’s partly deliberate, that is, people decide to hold off on having children, or decide against having children, because they’re unsure about the future, they’re unsure they’ll be able to care for them, they think they might lose their job, they think their mother might lose her job – all the things that go into the calculations of when and whether to have children.

CM: 2020 is not an outlier. Cohen says birthrates have been on a downward trend for quite a while.

PNC: We were sort of focusing on issues like work-family balance, childcare, healthcare, housing, the expenses of raising children, and the difficulty of raising children, which had been putting pressure on people to reduce their number of children. That’s the main reason. At the same time, when people have more opportunities to do other things in their lives, they’re also inclined to have fewer children, or delay having children. So especially for women, when opportunities improve, the number of children they have tends to go down, because on average they’re more likely to choose something else.

CM: Hispanic women in particular are seeing some of the largest declines. From 2007 to 2017 birth rates fell by 31%. Experts attribute this drop to more Hispanic women joining the workforce, and waiting longer to start families than previous generations. Overall, the data doesn’t lie. Fewer people are having kids. That could lead to smaller kindergarten classrooms, as well as larger demands on Social Security, given the aging population. But Cohen and others think there could be positives, too. For example, fewer people means less of an environmental impact on the planet. So it’s really a glass half empty, glass half full kind of situation. The point is, I think this pandemic has really made many of us reflect on what we want our future to look like, including our future families. Some have been inspired to freeze their eggs, some to seek out help for infertility, and some have decided against having kids while others have been inspired to do so.

Now in the Washington Post: The generation labels mean nothing. It’s time to retire them

The Washington Post has published my Opinion piece on generation labels, “The generation labels mean nothing. It’s time we retired them.” They even commissioned art, which moves!

by Tara Jacoby, for The Washington Post

This follows the series of posts on this blog, going back a few years, you can read under the generations tag.

You can read or sign the open letter to the Pew Research Center here.

Hard times and falling fertility in the United States

The text and figures of this short paper are below, and it’s also available as a PDF on SocArXiv, in more citable form. The Stata code and other materials are up as well, here. It’s pretty drafty — very happy to hear any feedback.

Preamble: When Sabrina Tavernise, Claire Cain Miller, Quoctrung Bui and Robert Gebeloff wrote their excellent New York Times piece, Why American Women Everywhere Are Delaying Motherhood, they elevated one important aspect of the wider conversation about falling fertility rates — the good news that women with improving economic opportunities often delay or forego having children because that’s what they’d rather do.

But it’s tricky to analyze this. Consider one woman they quote, who said, “I can’t get pregnant, I can’t get pregnant… I have to have a career and a job. If I don’t, it’s like everything my parents did goes in vain.” Or another, who is waiting to have children till she finishes a dental hygienist degree, who said, “I’m trying to go higher. I grew up around dysfunctional things. I feel like if I succeed, my children won’t have to.” If people can’t afford decent childcare (yet), or won’t have a job that pays enough to afford the parenting they want to provide until they finish a degree — so they delay parenthood while investing in their careers — are they not having a baby because there are promising opportunities, or because of economic insecurity? These are edge cases, I guess, but it seems like they extend to a lot of people right now. That’s what motivated me to do this analysis.


Hard times and falling fertility in the United States

by Philip N. Cohen

Abstract

Recent reports have suggested that falling fertility in the US since the 2008 recession is being driven by women with advantaged status in the labor market taking advantage of career opportunities. This paper takes issue with that conclusion. Although high incomes are associated with lower fertility in general, both in the cross section and over time (within and between countries), economic crises also lead to lower fertility. I offer a new descriptive analysis using data from the American Community Survey for 2000-2019. In the U.S. case, the fertility decline was widespread after the 2008 recession, but most concentrated among younger women. Although women with above average education have long had lower birth rates, the analysis shows that birth rates fell most for women in states with higher than average unemployment rates, especially among those with below average education. This is consistent with evidence that birth rates are falling, and births delayed, by economic insecurity and hardship.

Introduction

A New York Times article by Sabrina Tavernise et al. was titled, “Why American Women Everywhere Are Delaying Motherhood” (Tavernise et al. 2021). Although it did not provide a simple answer to the question, it did offer this: “As more women of all social classes have prioritized education and career, delaying childbearing has become a broad pattern among American women almost everywhere.” And it included a figure showing birth rates falling faster in counties with faster job growth. Reading that article, the writer Jill Filipovic concluded, “the women who are driving this downturn [in fertility] are those who have the most advantage and the greatest range of choices, and whose prospects look brightest” (Filipovic 2021). This paper takes issue with that conclusion.

Clearly, one driver of delayed childbearing is the desire to maximize career opportunities, but there is also the weight of uncertainty and insecurity, especially regarding the costs of parenting. Filipovic (2021) also wrote, “Children? In this economy?” These two tendencies appear to generate opposing economic effects: A strong economy gives mothers more rewarding opportunities that childrearing threatens (reducing fertility), while also providing greater economic security to make parenting more affordable and desirable (increasing fertility). These two pathways for economic influence on fertility trends are not easily separable in research – or necessarily exclusive in personal experience. In what follows I will briefly situate falling US fertility in the wider historical and global context, and then offer a descriptive analysis of the US trend in births from 2000 to 2019, focusing on relative education and state unemployment rates.

Review and context

Historically, economic growth and development have been key determinants of fertility decline (Herzer, Strulik, and Vollmer 2012; Myrskylä, Kohler, and Billari 2009), although by no means the only ones, and with coupling that is sometimes loose and variable (Bongaarts 2017). In the broadest terms, both historically and in the present, higher average incomes at the societal level are strongly associated with lower fertility rates; and this relationship recurs within the United States as well, as shown in the cross section in Figure 1.

Figure 1. Total fertility rate by GDP per capita: Countries and U.S. states, 2019. Note: Markers are scaled by population. US states linear fit weighted by population. Source: World Bank, US Census Bureau, National Center for Health Statistics, Bureau of Economic Analysis.

A lower standard of living is associated with higher birth rates. However, economic crises cause declines in fertility (Currie and Schwandt 2014), and this was especially true around the 2008 recession in the U.S. (Comolli 2017; Schneider 2015) and other high-income countries (Gaddy 2021). The crisis interrupted what had been a mild recovery from falling total fertility rates in high-income countries, leading to a decline from 1.74 in 2008 to 1.57 by 2019 (Figure 2).

Figure 2. Total fertility rate in the 10 largest high-income countries: 1990-2019. Note: Countries with at least $30,000 GDP per capita at PPP. Source: World Bank.

Figure 2 shows that the pattern of a peak around 2008 followed by a lasting decline is widespread (with the notable exceptions of Germany and Japan, whose TFRs were already very low), although the post-crisis decline was much steeper in the U.S. than in most other high income countries. Figure 3 puts the post-crisis TFR decline in global context, showing the change in TFR between the highest point in 2007-2009 and the lowest point in 2017-2019 for each country, by GDP per capita. (For example, the U.S. had a TFR peak of 2.12 in 2007, and its lowest point in 2017-2019 was 1.71 in 2019, so its score is -.41.) Fertility decline is positively associated with per capita income, as low-income countries continued the TFR declines they were experiencing before the crisis. However, among the high-income countries the relationship reversed (the inflection point in Panel A is $36,600, not shown). Thus, the sharp drop in fertility in the U.S. after the 2008 economic crisis is indicative of a larger pattern of post-crisis fertility trends. Globally, fertility is higher but falling in lower-income countries; fertility is lower in high-income counties, but fell further during the recent period of economic hardship or uncertainty. As a result of falling at both low and high ends of the economic scale, therefore, global TFR declined from 2.57 in 2007 to 2.40 in 2019 (by these World Bank data).

Figure 3. Difference in total fertility rate between the highest point in 2007-2009 and the lowest point in 2017-2019, by GDP per capita. Note: Markers scaled by population; largest countries labeled. Source: World Bank.

The mechanisms for these relationships – higher standard of living and rising unemployment both lead to lower fertility – defy simple characterization. The social scale (individual to global) may condition the relationship; there may be different effects of relative versus absolute economic wellbeing (long term and short term); development effects may be nonlinear (Myrskylä, Kohler, and Billari 2009); and the individual or cultural perception of these social facts is important as well (Brauner-Otto and Geist 2018). Note also that, as fertility rates fall with development, the question of having no children versus fewer has emerged as a more important distinction, which further complicates the interpretation of TFR trends (Hartnett and Gemmill 2020).

U.S. recessions

In the case of recent U.S. recessions, the negative impact on fertility was largest for young women. After the 2001 recession, birth rates only fell for women under age 25. In the wake of the more severe 2008 economic crisis, birth rates fell for all ages of women up to age 40 (above which rates continued to increase every year until 2020) although the drop was still steepest below age 25 (Cohen 2018). For the youngest women, births have continued to fall every year since, while those over age 35 saw some rebound from 2012 to 2019 (Figure 4). Clearly, during this period many women postponed births from their teens or twenties into their thirties and forties. The extent to which they will end up with lower fertility on a cohort basis depends on how late they continue (or begin) bearing children (Beaujouan 2020).

Figure 4. Annual change in U.S. births per 1,000 women, by age: 2001-2020. Source: National Center for Health Statistics.

Contrary to the suggestion that fertility decline is chiefly the result of improving opportunities for women, the pattern of delaying births is consistent with evidence that structural changes in the economy, the decline in goods-producing industries and the rise of less secure and predictable service industry jobs, are largely responsible for the lack of a fertility rebound after the 2008 recession, especially for Black and Hispanic women (Seltzer 2019). Lower education is also associated with greater uncertainty about having children among young people (Brauner-Otto and Geist 2018). For women in more precarious circumstances, especially those who are not married, these influences may be observed in the effect of unemployment rates on birth rates at the state level (Schneider and Hastings 2015). The available evidence supports the conclusion that the 2008 recession produced a large drop in fertility that did not recover before 2020 at least in part because the economic uncertainty it amplified has not receded – making it both a short-term and long-term event.

Birth rates recovered some for older women, however – over 30 or so – which is consistent with fertility delay. But this delay does not necessarily favor the opportunity cost versus economic constraint explanations. On one hand are people with higher levels of education (anticipated or realized) who plan to wait until their education is complete. On the other hand are those with less education who are most economically insecure, whose delays reflect navigating the challenges of relationship instability, housing, health care, childcare and other costs with lesser earning potential. This latter group may end up delaying either until they attain more security or until they face the prospect of running out of childbearing years. Both groups are deliberately delaying births partly for economic reasons, but the higher-education group is much more likely to have planned births while the latter have higher rates of unintended or mistimed births (Hayford and Guzzo 2016).

The opportunity cost of women’s childbearing, in classical models, is simply the earnings lost from time spent childrearing – the product of the hours of employment lost and the expected hourly wage (Cramer 1979). Although rising income potential for women has surely contributed to the long-run decline of fertility rates, in the U.S. that mechanism has not been determinative. Women experienced large increases in earnings for decades during which fertility rates did not fall. As the total fertility rate rose from its low point in 1976 (1.74) to the post-Baby Boom peak in 2007 (2.12) – defying the trend in many other high-income countries – the average weekly earnings of full-time working women ages 18-44 rose by 16% in constant dollars (Figure 5).

Figure 5. Median weekly earnings of full-time employed women ages 18-44, and total fertility rate. Source: Current Population Survey Annual Social and Economic Survey, and Human Fertility Database.

Clearly, other factors beyond lost earnings calculations are at work. However, there is no simple way to distinguish those who make direct cost comparisons, where investments in time and money take away from other needs and opportunities, from those who delay out of concern over future economic security, which weighs on people at all income levels and generates reluctance to make lifelong commitments (Pugh 2015). But the implications of these two effects are opposing. For people who don’t want to lose opportunities, a strong economy with abundant jobs implies lower fertility. For people who are afraid to commit to childrearing because of insecurity about their economic fortunes, a weak economy should decrease fertility. The experience of the post-2008 period provides strong evidence for the greater weight of the latter mechanism.

US births, 2000-2019

If opportunity costs were the primary consideration for women, one might expect an inverse relationship between job market growth and fertility rates: more jobs, fewer babies; fewer jobs, more babies. This is the pattern reported by Tavernise et al. (2021), who found that birthrates after the 2008 crisis fell more in counties with “growing labor markets” – which they attribute to the combination of improving opportunities for women and the high costs of childcare. However, their analysis did not attend to chronological ordering. They identified counties as having strong job growth if they were in the top quintile of counties for labor market percent change for the period 2007 to 2019, and compared them with counties in the bottom quintile of counties on the same measure with regard to birth rates (author correspondence). Thus, their analysis used a 2007-2019 summary measure to predict birth rates for each year from 1990 to 2019, making the results difficult to interpret.

In addition to using contemporaneous economic data, whereas Tavernise et al. (2021) used county-level birth rates, in this analysis I use individual characteristics and state-level data. I construct indicators of individual- and state-level relative advantage during the period before and after the 2008 economic crisis, from 2000 to 2019. Individual data are from the 2000-2019 American Community Survey (ACS) via IPUMS (Ruggles et al. 2021). I include in the analysis women ages 15-44, and use the fertility question, which asks whether they had a baby in the previous 12 months. I analyze this as a dichotomous dependent variable, using ordinary least squares regression. Results are graphed as marginal effects at the means, using Stata’s margins command. The sample size is 9,415,960 million women, 605,150 (6.4%) of whom had a baby in the previous year (multiple births are counted only once).

In models with controls, I control for age in five-year bins, race/ethnicity (White, Black, American Indian, Asian/Pacific Islander, Other/multiple-race, and Hispanic), citizenship (U.S.-born, born abroad to American parents, naturalized, and not a citizen), marital status (married, spouse absent, separated, divorced, widowed, and never married), education (less than high school, high school graduate, some college, and BA or higher degree), as well as (in some models) the state unemployment rate (lagged two years), and state fixed effects. State unemployment rates are from Local Area Unemployment Statistics (Bureau of Labor Statistics 2021). ACS person weights are used in all analyses.

For states, I use the unemployment rate in each state for each year, and divide the states at the median, so those with the median or higher unemployment for each year are coded as high unemployment states, and low unemployment otherwise (this variable is lagged two years, because the ACS asks whether each woman has had a birth in the previous 12 months, but does not specify the month of the birth, or the date of the interview). For individuals, the identification of economic advantage is difficult with the cross-sectional data I use here, because incomes are likely to fall in the year of a birth, and education may be determined endogenously with fertility as women age (Hartnett and Gemmill 2020), so income and education cannot simply be used to identify economic status. Instead, I identify women as low education if they have less than the median level of education for women of their age in their state for each year (using single years of age, and 26 categories of educational attainment), and high education otherwise. Thus, individual women in my sample are coded as in a high or low unemployment state relative to the rest of the country each year, and as having high or low education relative other women of their age and state and year. Using the ACS migration variable, I code women into the state they lived in the previous year, which is more likely to identify where they lived when they determined whether to have a baby (which also means I exclude women who were not living in the U.S. in the year before the survey).

Figure 6 shows the unadjusted probability of birth for women in high- and low-unemployment states for the period 2000-2019. This shows the drop in birth rates after 2008, which is steeper for women who live in high-unemployment states, especially before 2017. This is what we would expect from previous research on the 2008 financial crisis: a greater falloff in birth rates where the economy suffered more.

Figure 6. Probability of birth in the previous year: 2000-2019, by state unemployment relative to the national media (marginal effects at the means). Women ages 15-44. Based on state of residence in the previous year; unemployment lagged two years.

Next, I split the sample again by women’s own education relative to the median for those of the same age, year, and state. Those less than that median are coded as low education, those at or higher than the median are coded as high education. Figure 7 shows these results (again, unadjusted for control variables), showing that those with lower education (the top two lines) have higher birth rates throughout the period. After 2008, within both the high- and low-education groups, those in high-unemployment states had longer and steeper declines in birth rates (at least until 2019). The steepest decline is among low-education, high-unemployment women: those facing the greatest economic hardship at both the individual and state level. Finally, Figure 8 repeats the model shown in Figure 7, but with the control variables described above, and with state fixed effects. The pattern is very similar, but the differences associated with state unemployment are attenuated, especially for those with low education.

Figure 7. Probability of birth in the previous year: 2000-2019, by education relative to the age-state median, and state unemployment relative to the national media (marginal effects at the means). Women ages 15-44. Based on state of residence in the previous year; unemployment lagged two years.

Figure 8. Probability of birth in the previous year: 2000-2019, by education relative to the age-state median, and state unemployment relative to the national media, with controls for age, race/ethnicity, citizenship, marital status, and state fixed effects (marginal effects at the means). Women ages 15-44. Based on state of residence in the previous year; unemployment lagged two years.

Discussion

Although birth rates fell for all four groups of women in this analysis after the 2008 recession, these results reflect that paradoxical nature of economic trends and birth rates. Women with higher education (and greater potential earnings) have lower birthrates, consistent with the opportunity cost reasoning described in Tavernise et al. (2021) and elsewhere. However, women in states with higher unemployment rates – especially when they have high relative education – also have lower birthrates, and in these states saw greater declines after the 2008 crisis. This is consistent with the evidence of negative effects of economic uncertainty and stress. And it goes against the suggestion that stronger job markets drive down fertility rates for women with higher earning potential, at least in the post-2008 period. In the long run, perhaps, economic opportunities reduce childbearing by increasing job market opportunities for potential mothers, but in recent years this effect has been swamped by the downward pressure of economic troubles. US birth rates fell further in 2020, apparently driven down by the COVID-19 pandemic, which raised uncertainty – and fear for the future – to new heights (Cohen 2021; Sobotka et al. 2021). We don’t yet know the breakdown of the shifts in fertility for that year, but if the effects were similar to those of the 2008 economic crisis, we would expect to see greater declines among those who were most vulnerable.

References

Beaujouan, Eva. 2020. “Latest-Late Fertility? Decline and Resurgence of Late Parenthood Across the Low-Fertility Countries.” Population and Development Review 46 (2): 219–47. https://doi.org/10.1111/padr.12334.

Bongaarts, John. 2017. “Africa’s Unique Fertility Transition.” Population and Development Review 43 (S1): 39–58. https://doi.org/10.1111/j.1728-4457.2016.00164.x.

Brauner-Otto, Sarah R., and Claudia Geist. 2018. “Uncertainty, Doubts, and Delays: Economic Circumstances and Childbearing Expectations Among Emerging Adults.” Journal of Family and Economic Issues 39 (1): 88–102. https://doi.org/10.1007/s10834-017-9548-1.

Bureau of Labor Statistics. 2021. “States and Selected Areas:  Employment Status of the Civilian Noninstitutional Population, January 1976 to Date, Seasonally Adjusted.” 2021. https://www.bls.gov/web/laus/ststdsadata.txt.

Cohen, Philip N. 2018. Enduring Bonds: Inequality, Marriage, Parenting, and Everything Else That Makes Families Great and Terrible. Oakland, California: University of California Press.

———. 2021. “Baby Bust: Falling Fertility in US Counties Is Associated with COVID-19 Prevalence and Mobility Reductions.” SocArXiv. https://doi.org/10.31235/osf.io/qwxz3.

Comolli, Chiara Ludovica. 2017. “The Fertility Response to the Great Recession in Europe and the United States: Structural Economic Conditions and Perceived Economic Uncertainty.” Demographic Research 36 (51): 1549–1600. https://doi.org/10.4054/DemRes.2017.36.51.

Cramer, James C. 1979. “Employment Trends Ofyoung Mothers and the Opportunity Cost of Babies in the United States.” Demography 16 (2): 177–97. https://doi.org/10.2307/2061137.

Currie, Janet, and Hannes Schwandt. 2014. “Short- and Long-Term Effects of Unemployment on Fertility.” Proceedings of the National Academy of Sciences 111 (41): 14734–39. https://doi.org/10.1073/pnas.1408975111.

Filipovic, Jill. 2021. “Opinion | Women Are Having Fewer Babies Because They Have More Choices.” The New York Times, June 27, 2021, sec. Opinion. https://www.nytimes.com/2021/06/27/opinion/falling-birthrate-women-babies.html.

Gaddy, Hampton Gray. 2021. “A Decade of TFR Declines Suggests No Relationship between Development and Sub-Replacement Fertility Rebounds.” Demographic Research 44 (5): 125–42. https://doi.org/10.4054/DemRes.2021.44.5.

Hartnett, Caroline Sten, and Alison Gemmill. 2020. “Recent Trends in U.S. Childbearing Intentions.” Demography 57 (6): 2035–45. https://doi.org/10.1007/s13524-020-00929-w.

Hayford, Sarah R., and Karen Benjamin Guzzo. 2016. “Fifty Years of Unintended Births: Education Gradients in Unintended Fertility in the US, 1960-2013.” Population and Development Review 42 (2): 313–41.

Herzer, Dierk, Holger Strulik, and Sebastian Vollmer. 2012. “The Long-Run Determinants of Fertility: One Century of Demographic Change 1900–1999.” Journal of Economic Growth 17 (4): 357–85. https://doi.org/10.1007/s10887-012-9085-6.

Myrskylä, Mikko, Hans-Peter Kohler, and Francesco C. Billari. 2009. “Advances in Development Reverse Fertility Declines.” Nature 460 (7256): 741–43. https://doi.org/10.1038/nature08230.

Pugh, Allison J. 2015. The Tumbleweed Society: Working and Caring in an Age of Insecurity. 1 edition. New York, NY: Oxford University Press.

Ruggles, Steven, Sarah Flood, Sophia Foster, Ronald Goeken, Jose Pacas, Megan Schouweiler, and Matthew Sobek. 2021. “IPUMS USA: Version 11.0 [Dataset].” 2021. doi.org/10.18128/D010.V11.0.

Schneider, Daniel. 2015. “The Great Recession, Fertility, and Uncertainty: Evidence From the United States.” Journal of Marriage and Family 77 (5): 1144–56. https://doi.org/10.1111/jomf.12212.

Schneider, Daniel, and Orestes P. Hastings. 2015. “Socioeconomic Variation in the Effect of Economic Conditions on Marriage and Nonmarital Fertility in the United States: Evidence From the Great Recession.” Demography 52 (6): 1893–1915. https://doi.org/10.1007/s13524-015-0437-7.

Seltzer, Nathan. 2019. “Beyond the Great Recession: Labor Market Polarization and Ongoing Fertility Decline in the United States.” Demography 56 (4): 1463–93. https://doi.org/10.1007/s13524-019-00790-6.

Sobotka, Tomas, Aiva Jasilioniene, Ainhoa Alustiza Galarza, Kryštof Zeman, Laszlo Nemeth, and Dmitri Jdanov. 2021. “Baby Bust in the Wake of the COVID-19 Pandemic? First Results from the New STFF Data Series.” SocArXiv. https://doi.org/10.31235/osf.io/mvy62.

Tavernise, Sabrina, Claire Cain Miller, Quoctrung Bui, and Robert Gebeloff. 2021. “Why American Women Everywhere Are Delaying Motherhood.” The New York Times, June 16, 2021, sec. U.S. https://www.nytimes.com/2021/06/16/us/declining-birthrate-motherhood.html.

Draft: Open letter to the Pew Research Center on generation labels

This post has been updated with the final signing statement and a link to the form. Thanks for sharing!

I have objected to the use of “generation” divisions and names for years (here’s the tag). Then, the other day, I saw this introduction to an episode of Meet the Press Reports, which epitomized a lot of the gibberishy nature of generationspeak (sorry about the quality).

OK, it’s ridiculous political punditry — “So as their trust in institutions wanes, will they eventually coalesce behind a single party, or will they be the ones to simply transform our political system forever?” — but it’s also generations gobbledygook. And part of what struck me was this: “millennials are now the largest generation, they have officially overtaken the Baby Boom.” Well-educated people think these things are real things, official things. We have to get off this train.

If you know the generations discourse, you know a lot of it emanates from the Pew Research Center. They do a lot of excellent research — and make a lot of that research substantially worse by cramming into the “generations” framework that they more than anyone else have popularized — have made “official.”

After seeing that clip, I put this on Twitter, and was delighted by the positive response:

So I wrote a draft of an open letter to Pew, incorporating some of the comments from Twitter. But then I decided the letter was too long. To be more effective maybe it should be more concise and less ranty. So here’s the long version, which has more background information and examples, followed by a signing version, with a link to the form to sign it. Please feel to sign if you are a demographer or other social scientist, and share the link to the form (or this post) in your networks.

Maybe if we got a lot of signatories to this, or something like it, they would take heed.


Preamble by me

Pew’s generation labels — which are widely adopted by many other individuals and institutions — encourage unhelpful social science communication, driving people toward broad generalizations, stereotyping, click bait, sweeping character judgment, and echo chamber thinking. When people assign names to generations, they encourage anointing them a character, and then imposing qualities onto whole populations without basis, or on the basis of crude stereotyping. This fuels a constant stream of myth-making and myth-busting, with circular debates about whether one generation or another fits better or worse with various of its associated stereotypes. In the absence of research about whether the generation labels are useful either scientifically or in communicating science, we are left with a lot of headlines drawing a lot of clicks, to the detriment of public understanding.

Cohort analysis and the life course perspective are important tools for studying and communicating social science. We should study the shadow, or reflection, of life events across people’s lives at a cultural level, not just an individual level. In fact, the Pew Research Center’s surveys and publications make great contributions to that end. But the vast majority of popular survey research and reporting in the “generations” vein uses data analyzed by age, cross-sectionally, with generational labels applied after the fact — it’s not cohort research at all. We shouldn’t discourage cohort and life course thinking, rather we should improve it.

Pew’s own research provides a clear basis for scrapping the “generations.” “Most Millennials Resist the ‘Millennial’ Label” was the title of a report Pew published in 2015. This is when they should have stopped — based on their own science — but instead they plowed ahead as if the “generations” were social facts that the public merely failed to understand.

This figure shows that the majority of Americans cannot correctly identify the generational label Pew has applied to them.

The concept of “generations” as applied by Pew (and many others) defies the basic reality of generations as they relate to reproductive life cycles. Pew’s “generations” are so short (now 16 years) that they bear no resemblance to reproductive generations. In 2019 the median age of a woman giving birth in the U.S. was 29. As a result, many multigenerational families include no members of some generations on Pew’s chart. For example, it asks siblings (like the tennis-champion Williams sisters, born one year apart) to identify as members of separate generations.

Perhaps due to their ubiquitous use, and Pew’s reputation as a trustworthy arbiter of social knowledge, many people think these “generations” are official facts. Chuck Todd reported on NBC News just this month, “Millennials are now the largest generation, they have officially overtaken the Baby Boom.” (NPR had already declared Millennials the largest generation seven years earlier, using a more expansive definition.) Pew has perhaps inadvertently encouraged these ill-informed perspectives, as when, for example, Richard Fry wrote for Pew, “Millennials have surpassed Baby Boomers as the nation’s largest living adult generation, according to population estimates from the U.S. Census Bureau” — despite the fact that the Census Bureau report referenced by the article made no mention of generations. Note that Chuck Todd’s meaningless graphic, which doesn’t even include ages, is also falsely attributed to the U.S. Census Bureau.

Generations are a beguiling and appealing vehicle for explaining social change, but one that is more often misleading than informative. The U.S. Army Research Institute commissioned a consensus study report from the National Academies, titled, Are Generational Categories Meaningful Distinctions for Workforce Management? The group of prominent social scientists concluded: “while dividing the workforce into generations may have appeal, doing so is not strongly supported by science and is not useful for workforce management. …many of the stereotypes about generations result from imprecise use of the terminology in the popular literature and recent research, and thus cannot adequately inform workforce management decisions.”

As one of many potential examples of such appealing, but ultimately misleading, uses of the “Millennial” generation label, consider a 2016 article by Paul Taylor, a former executive vice president of the Pew Research Center. He promised he would go beyond “clichés” to offer “observations” about Millennials — before describing them as “liberal lions…who might not roar,” “downwardly mobile,” “unlaunched,” “unmarried,” “gender role benders,” “upbeat,” “pre-Copernican,” and as an “unaffiliated, anti-hierarchical, distrustful” generation who nevertheless “get along well with their parents, respect their elders, and work well with colleagues” while being “open to different lifestyles, tolerant of different races, and first adopters of new technologies.” And their “idealism… may save the planet.”

In 2018 Pew announced that it would henceforth draw a line between “Millennials” and “Generation Z” at the year 1996. And yet they offered no substantive reason, just that “it became clear to us that it was time to determine a cutoff point between Millennials and the next generation [in] order to keep the Millennial generation analytically meaningful, and to begin looking at what might be unique about the next cohort.” In asserting that “their boundaries are not arbitrary,” the Pew announcement noted that they were assigning the same length to the Millennial Generation as they did to Generation X — both 16 years, a length that bears no relationship to reproductive generations, nor to the Baby Boom cohort, which is generally considered to be 19 years (1946-1964).

The essay that followed this announcement attempted to draw distinctions between Millennials and Generation Z, but it could not delineate a clear division, because none can be drawn. For example, it mentioned that “most Millennials came of age and entered the workforce facing the height of an economic recession,” but in 2009, the trough year for that recession, Millennials by Pew’s definition ranged from age 13 to 29. The other events mentioned — the 9/11 terrorist attacks, the election of Barack Obama, the launch of the iPhone, and the advent of social media — similarly find Millennials at a range of ages too wide to be automatically unifying in terms of experience. Why is being between 12 and 28 at the time of Obama’s election more meaningful a cohort experience than being, say, 18 to 34? No answer to this is provided, because Pew has determined the cohort categories before the logical scientific questions can be asked.

Consider a few other hypothetical examples. In the future, we might hypothesize that those who were in K-12 school during the pandemic-inflicted 2020-2021 academic year constitute a meaningful cohort. That 13-year cohort was born between 2003 and 2015, which does not correspond to one of Pew’s predetermined “generations.” For some purposes, an even narrower range might be more appropriate, such as those who graduated high school in 2020-2021 alone. Under the Pew generational regime, too many researchers, marketers, journalists, and members of the general public will look at major events like these through a pre-formed prism that distorts their ability to pursue or understand the way cohort life course experiences affect social experience.

Unlike the other “generations” in Pew’s map, the Baby Boom corresponds to a unique demographic event, painstakingly, empirically demonstrated to have begun in July 1946 and ended in mid-1964. And being part of that group has turned out to be a meaningful experience for many people — one that in fact helped give rise to the popular understanding of birth cohorts as a concept. But it does not follow that any arbitrarily grouped set of birth dates would produce a sense of identity, especially one that can be named and described on the basis of its birth years alone. It is an accident of history that the Baby Boom lasted 18 years — as far as we know having nothing to do with the length of a reproductive generation, but perhaps leading subsequent analysts to use the term “generation” to describe both Baby Boomers and subsequent cohorts.

The good researchers at Pew are in a tough spot (as are others who rely on their categories). The generations concept is tremendously appealing and hugely popular. But where does it end? Are we going to keep arbitrarily dividing the population into generations and giving them names — after “Z”? On what scientific basis would the practice continue? One might be tempted to address these problems by formalizing the process, with a conference and a dramatic launch, to make it even more “official.” But there is no scientific rationale for dividing the population arbitrarily into cohorts of any particular length for purposes of analyzing social trends, and to fix their membership a priori. Pew would do a lot more to enhance its reputation, and contribute to the public good, by publicly pulling the plug on this project.


Open letter to the Pew Research Center on generation labels

Sign the letter here.

We are demographers and other social scientists, writing to urge the Pew Research Center to stop using its generation labels (currently: Silent, Baby Boom, X, Millennial, Z). We appreciate Pew’s surveys and other research, and urge them to bring this work into better alignment with scientific principles of social research.

  1. Pew’s “generations” cause confusion.

The groups Pew calls Silent, Baby Boom, X, Millennial, and Z are birth cohorts determined by year of birth, which are not related to reproductive generations. There is further confusion because their arbitrary lengths (18, 19, 16, 16, and 16 years, respectively) have grown shorter as the age difference between parents and their children has lengthened.

  1. The division between “generations” is arbitrary and has no scientific basis.

With the exception of the Baby Boom, which was a discrete demographic event, the other “generations” have been declared and named on an ad hoc basis without empirical or theoretical justification. Pew’s own research conclusively shows that the majority of Americans cannot identify the “generations” to which Pew claims they belong. Cohorts should be delineated by “empty” periods (such as individual years, equal numbers of years, or decades) unless research on a particular topic suggests more meaningful breakdowns.

  1. Naming “generations” and fixing their birth dates promotes pseudoscience, undermines public understanding, and impedes social science research.

The “generation” names encourage assigning them a distinct character, and then imposing qualities on diverse populations without basis, resulting in the current widespread problem of crude stereotyping. This fuels a stream of circular debates about whether the various “generations” fit their associated stereotypes, which does not advance public understanding.

  1. The popular “generations” and their labels undermine important cohort and life course research

Cohort analysis and the life course perspective are important tools for studying and communicating social science. But the vast majority of popular survey research and reporting on the “generations” uses cross-sectional data, and is not cohort research at all. Predetermined cohort categories also impede scientific discovery by artificially imposing categories used in research rather than encouraging researchers to make well justified decisions for data analysis and description. We don’t want to discourage cohort and life course thinking, we want to improve it.

  1. The “generations” are widely misunderstood to be “official” categories and identities

Pew’s reputation as a trustworthy social research institution has helped fuel the false belief that the “generations” definitions and labels are social facts and official statistics. Many other individuals and organizations use Pew’s definitions in order to fit within the paradigm, compounding the problem and digging us deeper into this hole with each passing day.

  1. The “generations” scheme has become a parody and should end.

With the identification of “Generation Z,” Pew has apparently reached the end of the alphabet. Will this continue forever, with arbitrarily defined, stereotypically labeled, “generation” names sequentially added to the list? Demographic and social analysis is too important to be subjected to such a fate. No one likes to be wrong, and admitting it is difficult. We sympathize. But the sooner Pew stops digging this hole, the easier it will be to escape. A public course correction from Pew would send an important signal and help steer research and popular discourse around demographic and social issues toward greater understanding. It would also greatly enhance Pew’s reputation in the research community. We urge Pew to end this as gracefully as possible — now.

As consumers of Pew Research Center research, and experts who work in related fields ourselves, we urge the Pew Research Center to do the right thing and help put an end to the use of arbitrary and misleading “generation” labels and names.