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.

Pew response and attempted clarification

First, a response from Pew, then a partial data clarification on generations. In response to my Washington Post Op-Ed on generations, Generation labels mean nothing. It’s time to retire them, Kim Parker, the director of social trends research at the Pew Research Center, published a letter that read:

Philip N. Cohen criticized the use of generation labels. Generations are one of many analytical lenses researchers use to understand societal change and differences across groups. While there are limitations to generational analysis, it can be a useful tool for understanding demographic trends and shifting public attitudes. For example, a generational look at public opinion on a wide range of social and political issues shows that cohort differences have widened over time on some issues, which could have important implications for the future of American politics.

In addition, looking at how a new generation of young adults experiences key milestones such as educational attainment, marriage or homeownership, compared with previous generations in their youth, can lend important insights into changes in American society.

To be sure, these labels can be misused and lead to stereotyping, and it’s important to stress and highlight diversity within generations. At Pew Research Center, we consistently endeavor to refine and improve our research methods. Therefore, we are having ongoing conversations around the best way to approach generational research. We look forward to engaging with Mr. Cohen and other scholars as we continue to explore this complex and important issue.

Kim Parker, Washington

I was happy to see this, and look forward to what they come up with. I am also glad to see that there has been no substantial defense of the current “generations” research regime. Some people on social media said they kind of like the categories, but no researcher has said they make sense, or pointed to any research justifying the current categories. With regard to her point that generations research is useful, that was in our open letter, and in my op-ed. Cohorts (and, if you want to call a bunch of a cohorts a generation, generations) matter a lot, and should be studied. They just shouldn’t be used with imposed fixed categories regardless of the data involved, and given names with stereotyped qualities that are presumed to extend across spheres of social life.

Several people have asked me for suggestions. My basic suggestion is to do like you learned in social science class, and use categories that make sense for a good reason. If you have no reason to use a set of categories, don’t use them. Instead, use an empty measure of time, like years or decades, as a first pass, and look at the data. As I argued here, there is not likely to be a set of birth years that cohere across time and social space into meaningful generational identities.

Data question

In the Op-Ed, I wrote this: “Generation labels, although widely adopted by the public, have no basis in social reality. In fact, in one of Pew’s own surveys, most people did not identify the correct generation for themselves — even when they were shown a list of options.” The link was to this 2015 report titled, “Most Millennials Resist the ‘Millennial’ Label” (which of course confirms a stereotype about this supposed generation). I was looking in particular at this graphic, which I have shown often:

It doesn’t exactly show what portion of people “correctly” identify their category, but I eyeballed it and decided that if only 18% of Silents and 40% of Millennials were right, there was no way Gen X and Boomers were bringing the average over 50%. Also, people could choose multiple labels, so those “correct” numbers was presumably inflated to some degree by double-clickers. Anyway, the figure doesn’t exactly answer the question.

The data for that figure come from Pew’s American Trends Panel Wave 10, from 2015. The cool thing is you can download the data here. So I figured I could do a little analysis of who “correctly” identifies their category. Unfortunately, the microdata file they share doesn’t include exact age, just age in four categories that don’t line up with the generations — so you can’t replicate their analysis.

However, they do provide a little more detail in the topline report, here, including reporting the percentage of people in each “generation” who identified with each category. Using those numbers, I figure that 57% selected the correct category, 26% selected an incorrect category, 9% selected “other” (unspecified in the report), and 8% are unaccounted for. So, keeping in mind that people can be in more than one of these groups, I can’t say how many were completely “correct,” but I can say that (according to the report, not the data, which I can’t analyze for this) 57% at least selected the category that matched their birth year, possibly in combination with other categories.

The survey also asked people “how well would you say they term [generation you chose] applies to you?” If you combine “very well” and “fairly well,” you learn, for example, that actual “Silents” are more likely to say “Greatest Generation” applies well to them (32%) than say “Silent” does (14%). Anyway, if I did this right, based on the total sample, 46% of people both “correctly” identified their generation title, and said the term describes them “well.” I honestly don’t know what to make of this, but thought I’d share it, since it could be read as me misstating the case in the Op-Ed.

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.

Why you’ll never establish the existence of distinct “generations” in American society

An update from Pew, today’s thoughts, and then another data exercise.

Pew response

After sending it the folks in charge at the Pew Research Center, I received a very friendly email response to our open letter on generation labels. They thanked me and reported that they already had plans to begin an internal discussion about “generational research” and will be consulting with experts as they do, although the timeline was not given. I take this to mean we have a bona fide opportunity to change course on this issue, both with Pew (which has outsized influence) and more widely in the coming months. But the outcome is not assured. If you agree that the “generations” labels and surrounding discourse are causing more harm than good, for researchers and the public, I hope you will join with me and 140+ social scientists who have signed the letter so far, by signing and sharing the letter (especially to people who aren’t on Twitter). Thanks!

avocado toast

Why “generations” won’t work

Never say never, but I don’t see how it will be possible to identify coherent, identifiable, stable, collectively recognized and popularly understood “generation” categories, based on year of birth, that reliably map onto a diverse set of measurable social indicators. If I’m right about that, which is an empirical question, then whether Pew’s “generations” are correctly defined will never be resolved, because the goal is unattainable. Some other set of birth-year cutoffs might work better for one question or another, but we’re not going to find a set of fixed divisions that works across arenas — such as social attitudes, family behavior, and economic status. So we should instead work on weaning the clicking public from its dependence on the concept and get down to the business of researching social trends (including cohort patterns), and communicating about that research in ways that are intelligible and useful.

Here are some reasons why we don’t find a good set of “generation” boundaries.

1. Mass media and social media mean there are no unique collective experiences

When something “happens” to a particular cohort, lots of other people are affected, too. Adjacent people react, discuss, buy stuff, and define themselves in ways that are affected by these historical events. Gradations emerge. The lines between who is and is not affected can’t be sharply drawn by age.

2. Experiences may be unique, but they don’t map neatly onto attitudes or adjacent behaviors

Even if you can identify something that happened to a specific age group at a specific point in time, the effects of such an experience will be diffuse. To name a few prominent examples: some people grew up in the era of mass incarceration and faced higher risks of being imprisoned, some people entered the job market in 2009 and suffered long-term consequences for their career trajectories, and some people came of age with the Pill. But these experiences don’t mark those people for distinct attitudes or behaviors. Having been incarcerated, unemployed, or in control of your pregnancy may influence attitudes and behaviors, but it won’t set people categorically apart. People whose friends or parents were incarcerated are affected, too; grandparents with unemployed people sleeping on their couches are affected by recessions; people who work in daycare centers are affected by birth trends. And, of course, African Americans have a unique experience with mass incarceration, rich people can ride out recessions, and the Pill is for women. When it comes to indicators of the kind we can measure, effects of these experiences will usually be marginal, not discrete, and not universal. (Plus, as cool new research shows, most people don’t change their minds much after they reach adulthood, so any effects of life experience on attitudes are swimming upstream to be observable at scale.)

3. It’s global now, too

Local experiences don’t translate directly to local attitudes and behavior because we share culture instantly around the world. So, 9/11 happened in the US but everyone knew about it (and there was also March 11 in Spain, and 7/7 in London). There are unique things about them that some people experienced — like having schools closed if you were a kid living in New York — but also general things that affected large swaths of the world, like heightened airline security. The idea of a uniquely affected age group is implausible.

4. Reflexivity

Once word gets out (through research or other means) about a particular trait or practice associated with a “generation,” like avocado toast or student debt, it gets processed and reprocessed reflexively by people who don’t, or do, want to embody a stereotype or trend for their supposed group. This includes identifying with the group itself — some people avoid it and some people embrace it, and some people react to who does the other things in other ways — until the category falls irretrievably into a vortex of cultural pastiche. The discussion of the categories, in other words, probably undermines the categories as much as it reinforces them.

If all this is true, then insisting on using stable, labeled, “generations” just boxes people into useless fixed categories. As the open letter puts it:

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.

Mapping social change

OK, here’s today’s data exercise. There is some technical statistical content here not described in the most friendly way, I’m sorry to say. The Stata code for what follows is here, and the GSS 1972-2018 Cross-Sectional Cumulative Data file is free, here (Stata version); help yourself.

This is just me pushing at my assumptions and supplementing my reading with some tactile data machinations to help it sink in. Following on the previous exercise, here I’ll try out an empirical method for identifying meaningful birth year groupings using attitude questions from the General Social Survey, and then see if they tell us anything, relative to “empty” categories (single years or decades) and the Pew “generations” scheme (Silent, Baby Boom, Generation X, Millennials, Generation Z).

I start with five things that are different about the cohorts of nowadays versus those of the olden days in the United States. These are things that often figure in conversations about generational change. For each of these items I use one or more questions to create a single variable with a mean of 0 and a standard deviation of 1; in each case a higher score is the more liberal or newfangled view. As we’ll see, all of these moved from lower to higher scores as you look at more recent cohorts.

  • Liberal spending: Believing “we’re spending too little money on…” seven things: welfare, the environment, health, big cities, drug addiction, education, and improving the conditions of black people. (For this scale, the measure of reliability [alpha] is .66, which is pretty good.)
  • Gender attitudes: Four questions on whether women are “suited for politics,” working mothers are bad for children, and breadwinner-homemaker roles are good. High scores mean more feminist (alpha = .70).
  • Confidence in institutions: Seven questions on organized religion, the Supreme Court, the military, major companies, Congress, the scientific community, and medicine. High scores mean less confidence (alpha = .68).
  • General political views from extremely conservative to extremely liberal (one question)
  • Never-none: People who never attend religious services and have no religious affiliation (together now up to about 16% of people).

These variables span the survey years 1977 to 2018, with respondents born from 1910 to 1999 (I dropped a few born in 2000, who were just 18 years old in 2018, and those born before 1910). Because not all questions were asked of all the respondents in every year I lost a lot of people, and I had to make some hard choices about what to include. The sample that answered all these questions is about 5,500 people (down from almost 62,000 altogether — ouch!). Still, what I do next seems to work anyway.

Clustering generations

Once I have these five items, I combine them into a megascale (alpha = .45) which I use to represent social change. You can see in the figure that successive cohorts of respondents are moving up this scale, on average. Note that these cohorts are interviewed at different points in time; for example, a 40-year-old in 1992 is in the same cohort as a 50-year-old in 2002, while the 1977 interviews cover people born all the way back to 1910. That’s how I get so many cohorts out of interviews from just 1977 to 2018 (and why the confidence intervals get bigger for recent cohorts).

The question from this figure is whether the cohort attitude trend would be well served by some strategic cutpoints to denote cohorts (“generations” not in the reproductive sense but in the sense of people born around the same time). Treating each birth year as separate is unwieldy, and the samples are small. We could just use decades of birth, or Pew’s arbitrary “generations.” Or make up new ones, which is what I’m testing out.

So I hit on a simple way to identify cutpoints using an exploratory technique known as k means clustering. This is a simple (with computers) way to identify the most logical groups of people in a dataset. In this case I used two variables: the megascale and birth year. Stata’s k means clustering algorithm then tries to find a set of groups of cases such that the differences within them (how far each case is from the means of the two variables within the group) are as small as possible. (You tell it k, the number of groups you want.) Because cohort is a continuous variable, and megascale rises over time, the algorithm happily puts people in clusters that don’t have overlapping birth years, so I get nicely ordered cohorts. I guess for a U-shaped time pattern it would put young and old people in the same groups, which would mess this up, but that’s not the case with this pattern.

I tested 5, 6, and 7 groups, thinking more or fewer than that would not be worth it. It turns out 6 groups had the best explanatory power, so I used those. Then I did five linear regressions with the megascale as the dependent variable, a handful of control variables (age, sex, race, region, and education), and different cohort indicators. My basic check of fit is the adjusted R2, or the amount of variance explained adjusted for the number of variables. Here’s how the models did, in order from worst to best:

Cohort variable(s)Adjusted R2
Pew generations.1393
One linear cohort variable.1400
My cluster categories.1423
Decades of birth.1424
Each year individually.1486

Each year is good for explaining variance, but too cumbersome, and the Pew “generations” were the worst (not surprising, since they weren’t concocted to answer this question — or any other question). My cluster categories were better than just entering birth cohort as a single continuous variable, and almost as good as plain decades of birth. My scheme is only six categories, which is more convenient than nine decades, so I prefer it in this case. Note I am not naming them, just reporting the birth-year clusters: 1910-1924, 1925-1937, 1938-1949, 1950-1960, 1961-1974, and 1975-1999. These are temporary and exploratory — if you used different variables you’d get different cohorts.

Here’s what they look like with my social change indicators:

Shown this way, you can see the different pace and timing of change for the different indicators — for example, gender attitudes changed most dramatically for cohorts born before 1950, the falling confidence in institutions was over by the end of the 1950s cohort, and the most recent cohort shows the greatest spike in religious never-nones. Social change is fascinating, complex, and uneven!

You can also see that the cuts I’m using here look nothing like Pew’s, which, for example, pool the Baby Boomers from birth years 1946-1964, and Millennials from 1980 to 1996. And they don’t fit some stereotypes you hear. For example, the group with the least confidence in major institutions is those born in the 1950s (a slice of Baby Boomers), not Millennials. Try to square these results with the ridiculousness that Chuck Todd recently offered up:

So the promise of American progress is something Millennials have heard a lot about, but they haven’t always experienced it personally. … And in turn they have lost confidence in institutions. There have been plenty of scandals that have cost trust in religious institutions, the military law enforcement, political parties, the banking system, all of it, trust eroded.

You could delve into the causes of trust erosion (I wrote a paper on confidence in science alone), but attributing a global decline in trust to a group called “Millennials,” one whose boundaries were declared arbitrarily, without empirical foundation, for a completely unrelated purpose, is uninformative at best. Worse, it promotes uncritical, determinist thinking, and — if it gets popular enough — encourages researchers to use the same meaningless categories to try to get in line with the pop culture pronouncements. You get lots of people using unscrutinized categories, compounding their errors. Social scientists have to do better, by showing how cohorts and life course events really are an important way to view and comprehend social change, rather than a shallow exercise in stereotyping.

Conclusion

The categories I came up with here, for which there is some (albeit slim) empirical justification, may or may not be useful. But it’s also clear from looking at the figures here, and the regression results, that there is no singularly apparent way to break down birth cohorts to understand these trends. In fact, a simple linear variable for year of birth does pretty well. These are sweeping social changes moving through a vast, interconnected population over a long time. Each birth cohort is riven with major disparities, along the stratifying lines of race/ethnicity, gender, and social class, as well as many others. There may be times when breaking people down into birth cohorts helps understand and explain these patterns, but I’m pretty sure we’re never going to find a single scheme that works best for different situations and trends. The best practice is probably to look at the trend in as much detail as possible, to check for obvious discontinuities, and then, if no breaks are apparent, use an “empty” category set, such as decades of birth, at least to start.

It will take a collective act of will be researchers. teachers, journalists, and others, to break our social change trend industry of its “generations” habit. If you’re a social scientist, I hope you’ll help by signing the letter. (I’m also happy to support other efforts besides this experts letter.)


Note on causes

Although I am talking about cohorts, and using regression models where cohort indicators are independent variables, I’m not assessing cohort effects in the sense of causality, but rather common experiences that might appear as patterns in the data. We often experience events through a cohort lens even if they are caused by our aging, or historical factors that affect everyone. How to distinguish such age, period, or cohort effects in social change is an ongoing subject of tricky research (see this from Morgan and Lee for a recent take using the GSS) , but it’s not required to address the Pew “generations” question: are there meaningful cohorts that experience events in a discernibly collective way, making them useful groups for social analysis.

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.

Against the generations, with video

I had the opportunity to make a presentation at the National Academies to the “Committee on the Consideration of Generational Issues in Workforce Management and Employment Practices.” If you’ve followed my posts about the “generation” terms and their use in the public sphere you understand how happy this made me.

The committee is considering a wide array of issues related to the changing workforce — under a contract from the Army — and I used the time to address the uses and misuses of cohort concepts and analysis in analyzing social change.

In the introduction, I said generational labels, e.g., “Millennials”:

encourage what’s bad about social science. It drives people toward broad generalizations, stereotyping, click bait, character judgment, and echo chamber thinking. … When we give them names and characters we start imposing qualities onto populations with absolutely no basis, or worse, on the basis of stereotyping, and then it becomes just a snowball of clickbait confirmation bias. … And no one’s really assessing whether these categories are doing us any good, but everyone’s getting a lot of clicks.

The slides I used are here in PDF. The whole presentation was captured on video, including the Q&A.

From my answer to the last question:

Cohort analysis is really important. And the life course perspective, especially on demographic things, has been very important. And as we look at changes over time in the society and the culture, things like how many times you change jobs, did you have health insurance at a certain point in your life, how crowded were your schools, what was the racial composition of your neighborhood or school when you were younger — we want to think about the shadow of these events across people’s lives and at a cultural level, not just an individual level. So it absolutely is important. … That’s a powerful way of thinking and a good opportunity to apply social science and learn from it. So I don’t want to discourage cohort thinking at all. I just want to improve it… Nothing I said should be taken to be critical of the idea of using cohorts and life course analysis in general at all.

You know, this is not my most important work. We have bigger problems in society. But understanding demographic change, how it relates to inequality, and communicating that in ways that allow us to make smarter decisions about it is my most important work. That’s why I consider this to be part of it.

Breaking Millennial divorce drop news explained

[With updates as new stories come in.]


Millennials are fun to disparage.

Phones and selfies are all that they cherish.

And what’s par for the course, they have ruined divorce.

‘Cuz Millennials hang on to their ______.

Wait Wait Don’t Tell Me, 9/29/18

The divorce paper I posted two weeks ago, “The Coming Divorce Decline,” suddenly took off in the media the other day (blog post | paper | data and code). I’ve now written an op-ed about the findings for The Hill, including this:

I am ambivalent about these trends. Divorce is often painful and difficult, and most people want to avoid it. The vast majority of Americans aspire to a lifelong marriage (or equivalent relationship). So even if it’s a falling slice of the population, I’m not complaining that they’re happy. Still, in an increasingly unequal society and a winner-take-all economy, two-degree couples with lasting marriages may be a buffer for the select few, but they aren’t a solution to our wider problems.

Here’s my media scrapbook, with some comment about open science process at the end.

The story was first reported by Ben Steverman at Bloomberg, who took the time to read the paper, interview me at some length, send the paper to Susan Brown (a key expert on divorce trends) for comment, and produce figures from the data I provided. I was glad that his conclusion focused on the inequality angle from my interpretation:

“One of the reasons for the decline is that the married population is getting older and more highly educated,” Cohen said. Fewer people are getting married, and those who do are the sort of people who are least likely to get divorced, he said. “Marriage is more and more an achievement of status, rather than something that people do regardless of how they’re doing.”

Many poorer and less educated Americans are opting not to get married at all. They’re living together, and often raising kids together, but deciding not to tie the knot. And studies have shown these cohabiting relationships are less stable than they used to be.

Fewer divorces, therefore, aren’t only bad news for matrimonial lawyers but a sign of America’s widening chasm of inequality. Marriage is becoming a more durable, but far more exclusive, institution.

The Bloomberg headline was, “Millennials Are Causing the U.S. Divorce Rate to Plummet.” Which proved irresistible on social media. I didn’t use the terms “millennials” (which I oppose), or “plummet,” but they don’t fundamentally misrepresent the findings.

Naturally, though, the Bloomberg headline led to other people misrepresenting the paper, like Buzzfeed, which wrote, “Well, according to a new study, millennials are now also ‘killing’ divorce.” Neither I nor Bloomberg said anyone was “killing” divorce; that was just a Twitter joke someone made, but Buzzfeed was too metameta to pick up on that. On the other hand, never complain about a Buzzfeed link, and they did link to the paper itself (generating about 800 clicks in a few days).

Then Fox 5 in New York did a Skype interview with me, and hit the bar scene to talk over the results (additional footage courtesy of my daughter, because nowadays you provide your own b-roll):

The next day Today did the story, with additional information and reporting from Bowling Green’s National Center for Family and Marriage Research, and Pew.

The Maryland news office saw the buzz and did their own story, which helped push it out.

An article in Atlantic featured an interview with Andrew Cherlin putting the trends in historical context. Rachelle Hampton in Slate tied the divorce trend to a Brookings report showing marriage is increasingly tied to higher education. On KPCC, AirTalk hosted a discussion with Megan Sweeney and Steven Martin. On Wisconsin Public Radio, Stephanie Coontz widened the discussion to put changes in marriage and divorce in historical perspective.

Rush Limbaugh read from the Bloomberg article, and was just outraged: “Now, who but deranged people would look at it this way?”

How anybody thinks like this… You have to work to be this illogical. I don’t know where this kind of thing comes from, that a plummeting divorce rate is a bad sign for America in the left’s crazy world of inequality and social justice and their quest to make everybody the same. So that’s just an example of the… Folks, that is not… That kind of analysis — and this is a sociology professor at the University of Maryland. This is not stable. That kind of thinking is not… It’s just not normal. Yet there it is, and it’s out there, and it’s be widely reported by the Drive-By Media, probably applauded and supported by others. So where is this coming from? Where is all of this indecency coming from? Why? Why is it so taking over the American left?

The Limbaugh statement might have been behind this voicemail I received from someone who thinks I’m trying to “promote chaos” to “upend the social order”:

I had a much more reasonable discussion about marriage, divorce, and inequality in this interview with Lauren Gilger in KJZZ (Phoenix public radio).

The Chicago Tribune editorial board used the news to urge parents not to rush their children toward marriage:

This waiting trend may disturb older folks who followed a more traditional (rockier?) path and may be secretly, or not so secretly, wondering if there’s something wrong with their progeny. There isn’t. Remember: Unlike previous generations, many younger people have a ready supply of candidates at their fingertips in the era of Tinder and other dating apps. They can just keep swiping right. Our advice for parents impatient to marry off a son or daughter? Relax. The older they get, the less likely you’ll be stuck paying for the wedding.

The Catholic News Agency got an expert to chime in, “If only we could convince maybe more of them to enter into marriage, we’d be doing really well.”

I don’t know how TV or local news work, but somehow this is on a lot of TV stations. Here’s a selection.

Fox Business Network did a pretty thorough job.

Some local stations added their own reporting, like this one in Las Vegas:

And this one in Buffalo:

And this one in Boise, which brought in a therapist who says young people aren’t waiting as long to start couples therapy.

Jeff Waldorf on TYT Nation did an extended commentary, blaming capitalism:


Open science process

Two things about my process here might concern some people.

The first is promoting research that hasn’t been peer reviewed. USA Today was the only report I saw that specifically mentioned the study is not peer reviewed:

The study, which has not been published in a peer-reviewed journal, has been submitted for presentation at the 2019 Population Association of America meeting, an annual conference for demographers and sociologists to present research.

But, when Steverman interviewed me I emphasized to him that it was not peer-reviewed and urged him to consult other researchers before doing the story — he told me he had already sent it to Susan Brown. Having a good reporter consult a top expert who’s read the paper is as good a quality peer review as you often get. I don’t know everything Brown told him, but the quote he used apparently showed her endorsement of the main findings:

“The change among young people is particularly striking,” Susan Brown, a sociology professor at Bowling Green State University, said of Cohen’s results. “The characteristics of young married couples today signal a sustained decline [in divorce rates] in the coming years.”

For the story to be clear enough to become a news event, the research often has to be pretty simple. That’s the case here: what I’m doing is looking at an easily-identified trend and providing my interpretation of it. If this has to be peer-reviewed, then almost anything an academic says should be. Of course, I provided the publicly verifiable data and code, and there are a lot of people with the skills to check this if it concerned them.

On the other hand, there is a lot of research that is impossible to verify that gets reported. Prominent examples include the Alice Goffman ethnographic book and the Raj Chetty et al. analysis of confidential IRS data. These were big news events, but whether they were peer reviewed or not was irrelevant because the peer reviewers had no way to know if the studies were right. My conclusion is that sharing research is the right thing to do, and sharing it with as much supporting material as you can is the responsible way to do it.

The second concern is over the fact that I posted it while it was being considered for inclusion in the Population Association of America meetings. This is similar to posting a paper that is under review at a journal. Conference papers are not reviewed blind, however, so it’s not a problem of disclosing my identity, but maybe generating public pressure on the conference organizers to accept the paper. This happens in many forms with all kinds of open science. I think we need to see hiding research as a very costly choice, one that needs to be carefully justified — rather than the reverse. Putting this in the open is the best way to approach accountability. Now the work of the conference organizers, whose names are listed in the call for papers, can be judged fairly. And my behavior toward the organizers if they reject it can also be scrutinized and criticized.

Although I would love to have the paper in the conference, in this case I don’t need this paper to be accepted by PAA, as it has already gotten way more attention than I ever expected. PAA organizers have a tough job and often have to reject a lot of papers for reasons of thematic fit as well as quality. I won’t complain or hold any grudges if it gets rejected. There’s a lot of really good demography out there, and this paper is pretty rudimentary.

2016 U.S. population pyramid, with Baby Boom

I’m finishing up revisions for the second edition of The Family, and that means it’s time to update the population pyramids.

Because it’s not so easy (for me) to find population by age and sex for single years of age for the current year, and because there is a little trick to making population pyramids in Excel, and because I’m happy to be nearing the end of the revision, I took a few minutes to make one to share.

The data for single year population estimates for July 1, 2016 are here, and more specifically in the file called NC-EST2016-AGESEX-RES.csv, here. To make the pyramid in Excel, you multiply one of the columns of data by -1 and then display the results as absolute values by setting the number to a custom format, like this: #,###;#,###. Then in the bar graph you set the two series to overlap 100%.*

In this figure I highlighted the Baby Boom so you can see the tsunami rolling into the 70s now. Unlike when I discuss cohorts previously, when I let it slide, here I actually adjusted this from what you would get applying the official Baby Boom years (1946-1964) with subtraction from 2016. That would give you ages 52 to 70, but the boom obviously starts ate age 69 and ends at age 51 here, so that’s what I highlighted. Maybe this has to do with the timing within years (nine months after the formal end of WWII would be May 2, 1946). Anyway, this is not the official Baby Boom, just the boom you see.

Click to enlarge:

2016 pop pyramid


* I put the data file, the Census Bureau description, and the Excel file on the Open Science Framework here: https://osf.io/qanre/.

Fertility trends and the myth of Millennials

The other day I showed trends in employment and marriage rates, and made the argument that the generational term “Millennial” and others are not useful: they are imposed before analyzing data and then trends are shoe-horned into the categories. When you look closely you see that the delineation of “generations” is arbitrary and usually wrong.

Here’s another example: fertility patterns. By the definition of “Millennial” used by Pew and others, the generation is supposed to have begun with those born after 1980. When you look at birth rates, however,  you see a dramatic disruption within that group, possibly triggered by the timing of the 2009 recession in their formative years.

I do this by using the American Community Survey, conducted annually from 2001 to 2015, which asks women if they have had a birth in the previous year. The samples are very large, with all the data points shown including at least 8,000 women and most including more than 60,000.

The figure below shows the birth rates by age for women across six five-year birth cohorts. The dots on each line mark the age at which the midpoint of each cohort reached 2009. The oldest three groups are supposed to be “Generation X.” The three youngest groups shown in yellow, blue, and green — those born 1980-84, 1985-89, and 1990-94 — are all Millennials according to the common myth. But look how their experience differs!

cohort birth rates ACS.xlsx

Most of the fertility effect on the recession was felt at young ages, as women postponed births. The oldest Millennial group was in their late twenties when the recession hit, and it appears their fertility was not dramatically affected. The 1985-89 group clearly took a big hit before rebounding. And the youngest group started their childbearing years under the burden of the economic crisis, and if that curve at 25 holds they will not recover. Within this arbitrarily-constructed “generation” is a great divergence of experience driven by the timing of the great recession within their early childbearing years.

You could collapse these these six arbitrary birth cohorts into two arbitrary “generations,” and you would see some of the difference I describe. I did that for you in the next figure, which is made from the same data. And you could make up some story about the character and personality of Millennials versus previous generations to fit that data, but you would be losing a lot of information to do that.

cohort birth rates ACS.xlsx

Of course, any categories reduce information — even single years of age — so that’s OK. The problem is when you treat the boundaries between categories as meaningful before you look at the data — in the absence of evidence that they are real with regard to the question at hand.