Freakonomics Radio - 254. What Are Gender Barriers Made Of?

Episode Date: July 21, 2016

Overt discrimination in the labor markets may be on the wane, but women are still subtly penalized by all sorts of societal conventions. How can those penalties be removed without burning down the hou...se?

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Starting point is 00:00:00 Okay, hello, Professor Strober. Hello. Hey, Stephen Dubner, how are you? Fine, how are you? Myra Strober was born in Brooklyn, 1941. She was a good student. She went to college at Cornell. At the time, only one in four undergraduates at Cornell were women.
Starting point is 00:00:23 Strober was planning to become a schoolteacher, but then she was offered a graduate school fellowship. Her two areas of interest were economics and history. I thought historians had to know everything about everyone, anytime. And so I thought economics would be a little easier. She studied economics at Tufts and then at MIT. In the economics Ph.D. program at MIT, women were even scarcer than they'd been in undergrad. I was completely shocked at how male my program was. So male that when she walked into the first day of her labor econ class...
Starting point is 00:01:00 The professor said, I think you're in the wrong room, young woman. And I looked him square in the eye and said, I don't think so. I'm Myra Strober. Strober got her Ph.D. in economics from MIT and later became an assistant professor at the University of Maryland. She'd gotten married and her husband was offered a tenure track job a professor of medicine at Stanford in Palo Alto, California. So they moved to California. By now, they had two young children. Stroberg got a teaching job at Berkeley, about 40 miles north of Palo Alto. But she was hired as a lecturer, not an assistant professor, which is what she'd been at Maryland. The very first day I was at Berkeley, I saw that two of my classmates from MIT were assistant professors at Berkeley.
Starting point is 00:01:51 That is, two male classmates from MIT. And so I made an appointment with the chair of the economics department, George Brake, to find out why I was a lecturer and they were assistant professors. He told me that the reason was that I lived in Palo Alto. Meaning 40 miles away. And I was astonished. But I believed him, you know, that was the reason. So she left his office.
Starting point is 00:02:16 And got into my car to drive back to Palo Alto from Berkeley. The route took her over the Bay Bridge. And on that bridge, I realized that his answer was absolutely ridiculous. And that, in fact, there was only one other woman in the economics department at Berkeley. She'd been there for 20 years, and she was still a lecturer. And I always say I became a feminist on the Bay Bridge. It took a while, but Strober got a second meeting with her department chair. First he asked me if I would like him to be frank, and I said yes I would.
Starting point is 00:03:03 And so he told me that I had two young children, and they couldn't give me an assistant professor position because they didn't know, quote, what was going to happen to me. I don't know what he thought would happen to me, but I said, well, why don't you put me on the tenure track, and in six years we'll all see what happens to me. And he said I could never sell that to the department. Strober wound up leaving Berkeley. In 1972, she became the first female faculty member at Stanford's Graduate School of Business. And then the advisory board told the dean that they needed to hire women, and they couldn't find any because none had been trained. And they urged the business school to start admitting more women. There were only five female students in the business school out of a few hundred. So the business school recruited women for one year, and I helped with that. And that was the end of the recruiting because as soon
Starting point is 00:04:07 as women knew that the business school, and this was not just at Stanford, this was nationwide, as soon as they knew that business schools wanted to enroll women, they applied in droves. Think about that. As soon as women knew the business schools wanted to enroll women, they applied in droves. Is it really that easy? What if many of the gender barriers we're staring down lately are as flimsy as that? Today on Freakonomics Radio, how to tweak and nudge and occasionally subvert society to do away with some of our oldest, stalest traditions. We need to go into our organizations and redesign how we hire, how we promote, how we evaluate people.
Starting point is 00:04:54 By removing the penalties for wrong answers, these gender differences went away. I think very small changes could be made that would have huge effects. From WNYC Studios, this is Freakonomics Radio, the podcast that explores the hidden side of everything. Here's your host, Stephen Dubner. We've been talking with the economist Myra Strober. I am a professor emerita at Stanford University. I am still teaching a course there on work and family. The relationship between women and work has come up constantly for Strober in both her academic and personal life. This led her to ask a simple question.
Starting point is 00:06:04 How is it and why is it that men are the majority in certain occupations, the more lucrative ones, and women are the majority in others? Why is it that there's so much occupational segregation? Occupational segregation is a major driver of the gender pay gap. You've probably heard the famous statistic that women earn roughly 77 cents for every dollar that men earn for doing the same work. It's also a famously flawed statistic, as we discussed in an earlier episode that was called The True Story of the Gender Pay Gap. And it features research done by the Harvard economist Claudia Golden. Well, it is true that if you took individuals in the labor force and took those who are working full-time, full-year,
Starting point is 00:06:51 and took all women, took the median annual earnings of those women, and took the same thing for men, and divided the two, it would be.77, or around that. So does that mean that women are receiving lower pay for equal work? That is possibly the case in certain places, but by and large, it's not that. It's something else. One component of that something else is occupational sorting, or as Myra Strober calls it, occupational segregation.
Starting point is 00:07:26 It was her own experience as the rare female economist that got her thinking about this. And I came across this notion that men had monopolized the lucrative professions. So her big research question? in others? Why is it that there's so much occupational segregation? And after studying occupations that change their gender designation, like bank telling and elementary school teaching, I realized that although people talk about occupations becoming feminized, that is, women taking them over, really what's going on is that men are leaving occupations which are no longer relatively attractive in terms of salary, working conditions, and promotion opportunities. Why did men, historically at least, get first dibs on the best-paying jobs?
Starting point is 00:08:46 I think the answer is that society, and I think this is still true, thinks that men are the supporters of their families. And so it makes sense to give them the best jobs because they need to earn what used to be called a family wage. They need to earn what used to be called a family wage. They need to earn enough to support a family. Whereas a woman either needs to earn nothing because the man is supporting her, or she needs to simply support herself. I hear you when you say that, and it sounds perfectly sensible,
Starting point is 00:09:20 but I'm curious if it's really true. I mean, on the one hand, I think if I own a steel mill and I want to produce a certain amount of product and I want to do it as affordably as I can and I say, well, women earn less than men, I should hire them. And if some people don't like it because it goes against our traditional national or tribal or religious norms, yeah, you know what? So what? You're saying that nobody ever did that? Those norms were so strong that they were never violated? As far as I know, nobody was trying to put women into steel worker jobs,
Starting point is 00:09:56 into coal mining jobs, into construction jobs. No. And it's not just from the employer side. Women would have thought it unseemly for them to do that kind of work. And so once a job is designated as male or female, it's very hard to change that designation. Do you think there was willful either discrimination or exclusion in order to protect wages and privilege and so on that males had? Or was it more like it took way too long for the feminization of the workforce to happen, but not necessarily because of ill will? I think it was a combination of both. I think that, for example, in medicine,
Starting point is 00:10:47 medical schools had a quota and simply did not admit more than a few women in any year. I think that when an employer or an industry group is thinking about hiring women into jobs that have been previously all male. They have to be a little innovative. I think you could get more young women interested in engineering if you discuss the ways in which engineers help people in society. Women like to help people in society. Well, engineers, by and large, do that. But that's not the way that engineering is sold. And so I think very small changes could be made that would have huge effects.
Starting point is 00:11:39 Small changes having huge effects. That is a favorite theme of ours around here. It describes a lot of what behavioral economics tries to do. Okay, well thank you for having me. I'm Iris Bonet. Thanks for joining us. I'm a professor of public policy at the Harvard Kennedy School and I'm an economist by training. Anything else?
Starting point is 00:12:01 And I also direct the Women in Public Policy program. Anything else? And I also direct the Women in Public Policy program. Anything else? I co-chair the Behavioural Insights Group, and that's a group that focuses on better understanding behavioural insights, the mechanisms that help us make better decisions in organisations and in society more broadly. Anything else? I'm the author of What Works? Gender Equality by Design,
Starting point is 00:12:27 which brings these insights to bear on the question of gender equality. The focus of the book? The book focuses on what organizations can do, including schools, but then companies, agencies, governments, can do to close gender gaps using behavioral insights. Bonet, like many smart people, believes that you can't solve a problem until you understand its root causes. So when you consider gender gaps in the labor market, whether it's wages or occupational segregation or opportunity, what are some of the factors that drive these gaps?
Starting point is 00:13:03 Let's start with something that's hard to quantify, our perception of competence and how that perception may differ from women to men. So tell me about Heidi Roizen and her fictional twin brother, Howard. Heidi Roizen is a venture capitalist in Silicon Valley and an entrepreneur and a very successful businesswoman. And a few years ago, Kathleen McGinn and a team of collaborators wrote a case about Heidi. It's the kind of case that people who are in a graduate school would be confronted with when they study business, for example, or public policy. And the case talks about Heidi and, you know, what she did to create her network in Silicon Valley
Starting point is 00:13:51 and how she built her enterprises. And then a few years later, a few colleagues of ours, in fact, two men at Columbia Business School, replaced Heidi's name with Howard. They gave half of their students the case with the protagonist being called Heidi, and the other half with the protagonist being called Howard. And I'm assuming they're randomizing, and I'm assuming that the other half doesn't know what the other half is getting, correct? That's exactly right. What we typically find is that when we ask our students to evaluate Heidi and Howard after they have done the case. People, and I specifically say people, so this is not just men, but men and women, will say that Heidi and Howard both did a good job,
Starting point is 00:14:33 were competent, they perform well, but they don't like Heidi. And they don't like Heidi because Heidi defies the stereotypes that we have about what a typical venture capitalist looks like, but also what a typical woman does. But they only don't like it when they know or think that she is a woman. If they know or think that she's a man, then she's considered, what, a kind of maverick who, good for him slash her, he, she got where he, she wanted to get by breaking the rules. Is that the idea? They didn't quite break the rules, but by being assertive. So yes, so competence and assertiveness and success and leadership
Starting point is 00:15:11 go together for men, but they don't go together for women. Right. So why do you suspect this is the case, especially because it's the case not only for male students assessing him slash her, but female students as well. Seeing is believing. And there's tons of evidence suggesting that what we see or who we see more importantly is more important than who we are ourselves. Okay, that makes sense. Men may see men and women differently. Women may see men and women differently. Women may see women and men differently.
Starting point is 00:15:49 But how do women and men see themselves? And how does that feed the gender gap? I think economists have started to recognize that there are dimensions in which men and women on average behave differently. And sometimes that can interact with the way we've designed a system to produce sort of inefficient results. That's Catherine Kaufman. She's at Harvard Business School. So I was studying psychology and economics and thinking about ways in which individual decisions might be biased. One of these ways is through anchoring, right? So I give you a random number and you have to decide how tall is Mount Everest.
Starting point is 00:16:23 Is it taller or shorter than that number? So Kaufman designed a survey and asked this very question to men and women. I saw really consistently that men were willing to guess, even when they were really unsure about the answer, and give me a very precise estimate for the height of the mountain, where women were very likely on these surveys to write that they didn't know or they weren't sure. They really wish they could help me with their research, but they just didn't know the answer to the question. And so I started to think about how this sort of unwillingness to volunteer ideas you're unsure about might manifest itself in sort of really important contexts.
Starting point is 00:17:00 Important contexts like taking the SAT, one of the benchmark tests for American college admission, where you get one point for a correct answer, a quarter point penalty for a wrong answer, and zero points for skipping the question. So if you had a relatively high probability of answering correctly and actually just a positive probability of choosing something better than choosing at random, you would be leaving points on the table by skipping the question, at least in expectation. Historically, there's been a big gap between male and female performance on the math portion of the SAT. In 2015, the average male score was 527 out of 800 possible points. The average female score, just 496. Kaufman decided to run an experiment to see if any of that gap could be explained by the gender gap in willingness to guess at answers. So what I do is I bring participants into the lab and they do a test that looks like the SAT. They take the first part where they have
Starting point is 00:18:05 the option to skip questions with that similar structure of deducting penalties for wrong answers. But then I come back in that same session, 10 minutes later, and I show them those same questions, and I force them to provide an answer to every question. And by doing so, I can see sort of how they would have done on the test had everyone chosen to answer questions rather than skip. So what did Kaufman find? When there were penalties for wrong answers, women skipped on average about twice as many questions as the men. But then Kaufman ran the experiment again with a different set of participants.
Starting point is 00:18:41 And in this iteration, there was no penalty for a wrong answer. By removing the penalties for wrong answers, we saw that everyone now decided to answer every question. And so the gender gap in skipping questions and also these gender differences in score that were related to that went away. In other words, when she redesigned the test to not penalize female test takers for what seems to be a predominantly female behavior. They did about as well as the males. Yeah. So, you know, the SAT announced that they were going to remove penalties for wrong answers. I didn't work with them on that change, although it was a change that I was happy to hear about.
Starting point is 00:19:22 The College Board, that's the nonprofit that designs the SAT and other tests, they said the bigger reason they changed SAT scoring was to take some of the gamesmanship out of it. Whatever the case, it is the kind of change that Iris Bonet and Myra Strober and others are talking about, identifying potential gender biases or barriers that may be subtle, but may also be so obstinate because they're subtle. Coming up on Freakonomics Radio, what other clues have we been missing? It's a very strong effect, and girls are doing this more strongly than the boys. And we talk solutions. I can't tell my female students, let's wait for 100 years until we fix the system. This is Freakonomics Radio. I'm Stephen Dubner. I'm also male, which means that when I say something, regardless of what I say and how I say it, it will be received differently than if my non-existent female twin Stephanie Dubner were to say the very same thing.
Starting point is 00:20:42 Okay. I'm Megan Sumner. And she is? I'm an associate professor of linguistics at Stanford University. Which means what, exactly? I'm a phonetician, and my research focuses on how we understand spoken language. So what's uttered, and who has spoken something, and how we integrate that information. Different people, as we all know, often speak with different accents. When we're listening to speakers with different accents, we listen differently.
Starting point is 00:21:09 And when I said we listen differently, I don't mean it's a conscious choice and I choose to not listen to one talk or another. I mean, in the automatic processes that we're using to understand spoken languages, there are social biases present already. So as soon as I hear a speaker, how I view that speaker influences everything that happens next. In one experiment, Sumner had average American listeners listen to two speakers speaking the same words, one with a New York City accent.
Starting point is 00:21:37 Angel. Asthma. Bagel. The other with a Southern Standard British English voice. Asthma. Bagel. Between. Cabinet.
Starting point is 00:21:50 The difference in listeners' perceptions was astonishing. They did a much better job remembering exactly what the English speaker said, and they judged the English speaker to be smarter than the New York City speaker. This led me to thinking about variation in other domains, specifically gender. For instance, how do we perceive the same words spoken by a woman versus a man? Sumner and her colleague Ed King recorded a man's voice and a woman's voice saying the same word. For instance, Academy. Academy.
Starting point is 00:22:16 She then asked listeners of both genders to immediately say the next word that came to mind. When participants would hear a word spoken by a man, like academy, the first word that pops into their mind, and this held true for female and male listeners, would be school. But when they heard the same word spoken by a woman, academy, the first word that pops into their mind would be award. So when a man says the word academy, the top associate is school. But when a female says the word academy, the top associate is school. But when a female says the word academy, the top associate is a ward. The idea, Sumner argues, is that our unconscious stereotyping influences how we listen.
Starting point is 00:23:06 And both male and female listeners are apparently more likely to anticipate a woman talking about Hollywood than, say, a school. Now, if you broaden that out, it means that we are processing language differently based on whether a woman or man is doing the speaking. And it's not just adults. Sumner and her colleagues have found that gendered listening, as she calls it, starts by the age of four. And this effect, it's a very strong effect. And what's interesting is that the girls that are listeners are doing this more strongly than the boys.
Starting point is 00:23:32 And to us, that's interesting as well. So how does this play out among adults in, say, a work environment or education or politics? It's not hard to imagine two political candidates, one male, It's really nice, thank you. one female, Well, thank you, and thanks to everyone.
Starting point is 00:23:51 being perceived very differently, even if they were saying exactly the same words, as, through the magic of audio editing, we've arranged for them to do. The challenges we face in protecting our country. We honor the sacrifice. Megan Sumner and her colleagues did another experiment looking at our absolute and then our relative rankings
Starting point is 00:24:15 of male and female speakers. So a man's voice that's rated as not so reliable on its own is rated as more reliable in the context of a woman's voice so it gets a kind of boost and a woman's voice that's rated as reasonably reliable alone gets downgraded as less reliable in the context of a man's voice. And you can imagine how that would penalize women in just about any setting. I think this has huge implications just for how we interact and the types of information that we're using to make decisions on an everyday basis. Consider a job interview.
Starting point is 00:24:50 You're the person doing the hiring. Here's what Sumner's research suggests. Let's say you interview a man for the job and you think he's only so-so. Then you interview a woman for the job. Suddenly, the man seems, in retrospect, a better candidate than he seemed before you interviewed the woman. And that, says the economist Iris Bonet, is why... Interviews are probably the most overvalued instrument at our disposal. It's another of those societal constructs that may be putting women at a disadvantage. It turns out, quite literally hundreds of studies have shown that interviews do a very bad job predicting future performance.
Starting point is 00:25:29 So it's not that nothing useful happens in an interview, but it's almost impossible for our minds to sift through what we've just learned and tease apart the valuable information from the less valuable information. So what's the solution? Do we change the way women speak? That's not what Megan Sumner wants, even though her own research points out the problem. It's kind of made me grumpy, quite honestly, because our voice and the way we talk is something about ourselves. And we're conveying who we are along with what we say.
Starting point is 00:26:03 And so I kind of had this feeling of, gosh, now maybe people are going to try to change how they talk. And that would be sad. I think we have to change how we listen. Iris Bonet agrees. She also thinks that leaning in, the idea that women just need to an assertive female entrepreneur less likable than a fictional male version of the same person. It's very important that we talk about the evidence that it is harder for women to lean in than for men because they violate gender norms. Women are penalized for being assertive because assertiveness is not traditionally associated with women while it is with men. And in men, we applaud it and think that makes for a good leader.
Starting point is 00:26:53 And in women, we think it is trying to find a better word than the B word. I'm not going to say the B word here. But we know the word you're thinking. We know what I mean. Yeah. So we don't have warm thoughts about assertive women, but we might call it aggressiveness. Let's call it aggressiveness instead of assertiveness. And women need to know that that is a risk that is real.
Starting point is 00:27:15 Right. So rather than wait around for the two or 200 or maybe 2 million years for assertiveness, let's say, to be associated with women? Because it sounds from what you're saying that there's no guarantee that that construct will change at least anytime soon. Rather than wait around for that and acknowledging that people have biases that are hard to erase, what do you do? What are the answers? What are the solutions? So we need to go into our organizations and redesign how we hire, how we promote, how we evaluate people. I think there's a number of things we can do. Most immediately, we can move from an unstructured interview protocol to a structured interview protocol.
Starting point is 00:27:57 And that means we think about the questions beforehand. We write down the questions beforehand, we write down the questions beforehand, ideally, in the best of all worlds, we then measure which questions do a good job predicting future performance. But at the very least, we think hard about which questions we think would do a good job. And then we ask these five questions in the same order. And we ask the same questions whenever we interact with a candidate. So all my 10 finalists, for example, will be asked the same five questions in the same order. And then ideally, I mean, this is literally what I do now. I blind myself to the demographic characteristics of these people and just assign numbers.
Starting point is 00:28:42 In fact, I have an assistant assign numbers to the answer to the questions. And then I compare the questions across, not vertically, but horizontally. So I look at the answer to question one for all of my 10 candidates. Then I look at question two for all of my 10 candidates and I rate them. And then at the end, I aggregate them. And then I give them back to my assistant and she tells me, you know, who was it, John or Susie or Jamal or May, who I rated? Another solution? Bonet suggests that firms do away with employees' self-evaluations. Now, if people differ in the degree of their self-confidence, that will lead to different self-appraisals. And these different self-appraisals will then influence how my manager is going to
Starting point is 00:29:25 appraise me and my colleague. And so I don't know of any evidence suggesting that sharing self-appraisals beforehand does any good. But we have found evidence that these numbers, in fact, do bias the managers, and the managers will adjust a little bit, but will adjust incompletely. And there will remain this gap between men and women, but not just between men and women. We've also found that there are certain cultures which are more comfortable with, let's call this bragging, and other cultures which are less comfortable with doing so. So I think that's a practice that we should just do away with tomorrow. Another suggestion addresses the idea that women are sometimes not seen as wanting success as much as men. Many organizations evaluate people who are up for promotion based on past performance and future potential.
Starting point is 00:30:18 And the bias tends to kick in in terms of potential for two reasons. A, it's much harder to measure than performance. And B, of course, potential goes back to the Heidi Howard problem where we can't imagine that women would like to want to climb up the career ladder, and therefore we think she has less potential. So try to break down potential into its subcomponents and be very honest with yourself on what you're actually trying to measure with potential. A lot of these changes seem, no offense, really easy. I mean, pretty simple to build.
Starting point is 00:30:53 If they are so easy, why do you think that many of them haven't been used more? So first of all, I don't take offense at all. In fact, one of the big arguments of the book is that these are low hanging fruit, often relatively cheap, and we should do them tomorrow. So a number, you know, here's a number of potential culprits. Now, I don't think I have evidence to tell us, you know, which one it is. But there's this interesting thing going on that we tend to rely on evidence and data in our finance departments and even in our marketing departments where we often even run experiments, real scientific methods to understand whether Diet Coke or Pepsi Max works for men and women respectively,
Starting point is 00:31:39 for example. And we haven't used those same methods in our HR departments. I don't know exactly where that comes from, why we haven't used the same kind of rigor and scrutiny when we think about people. In many ways, we should be even more careful when we make people decisions compared to product decisions. But there seems to be this last bastion in many ways in HR that, honestly, I think is going to change dramatically with the new data, big data, the new technologies, machine learning that we have available now in the next 10 years. We just haven't used the same tools that we have used in other parts of our organizations
Starting point is 00:32:16 so far. That may be true. We may be entering an era in which more firms use more data to understand how to get the most out of their employees and how to make their employees happier and more productive. But there's also this human nature being what it is, a bundle of cognitive biases and adherence to social norms. You can't solve every problem according to logic. Sometimes you need to design a solution that factors in all these biases and norms.
Starting point is 00:32:48 I think we have to take human psychology seriously and meet people where they're at and not ask for the impossible. Sometimes, rather than relying on people to constantly make good decisions, you have to design the system so that success is not dependent
Starting point is 00:33:03 on every decision being a good one. You need to design the system so that success is not dependent on every decision being a good one. You need to find a way to do good and important work without being crippled by everything that could go wrong. Myra Strober, the pioneering economist we heard from earlier, has written a book called Sharing the Work, what my family and career taught me about breaking Through and Holding the Door Open for Others. It's part memoir, part analysis of how the workplace has always been, probably always will be, a different kind of challenge for men and women. Consider the seemingly simple notion of workplace feedback. We all know it's really hard to get better at anything without feedback,
Starting point is 00:33:45 but Strober argues there's an almost universal fear of feedback. Well, not only do people fear asking for feedback, but employers fear giving it. I think employers fear giving men feedback because they're afraid. And I get this from the consulting that I've done. They fear that the men will be angry. In the worst case, they'll stomp, they'll scream, they'll throw erasers. I don't know what they'll do, but they'll be very angry. Women, on the other hand, they fear will cry. But very few women cry. And if they do, so they do. And some women fear getting feedback because they will cry. And, you know, I tell them, well, practice not crying,
Starting point is 00:34:35 and you must have feedback in order to improve your work. If you don't know what you're doing wrong or what you could be doing better, you're never going to improve, you're never going to improve. You're never going to get the promotion you want. If you've got feedback on this show or any other episode of Freakonomics Radio, let us hear it. We're on Twitter, we're on Facebook, we're at Freakonomics.com. You can write to us at radio at Freakonomics.com.
Starting point is 00:35:04 Coming up next week on Freakonomics.com. You can write to us at radio at Freakonomics.com. Coming up next week on Freakonomics Radio, do you love our electoral system? No, I didn't think so. So if there were one election idea that you could personally kill off, what would it be? The idea that we ought to abolish. The idea that I would like to die unmourned, buried as quickly as possible, no funeral. We need to change the way we currently vote. We hear from politicians and scholars, donkeys and elephants, and everyone in between on This Idea Must Die, Election Edition.
Starting point is 00:35:39 That's next time on Freakonomics Radio. Freakonomics Radio is produced by WNYC Studios and Dubner Productions. This episode was produced by Kim Gittleson. Our staff also includes Irva Gunja, Merritt Jacob, Christopher Wirth, Jay Cowett, Greg Rosalski, Caitlin Pierce, Alison Hockenberry, Emma Morgenstern, and Jolenta Greenberg.
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