Interview with Distinguished Scholar Award Winner


Arvind Karunakaran (AK), McGill University, Winner of the Louis Pondy Best Dissertation Award, interviewing Lynne Zucker (LZ), UCLA (University of California Los Angeles), Winner of the Distinguished Scholar Award (Abridged to Fit Interview Format)

 

AK: Congratulations on the OMT Distinguished Scholar Award.

LZ: Thank you.

AK: Perhaps we could start at the beginning of your career. We’ve read about the Organizational Theory renaissance at Stanford during the 70s, so it'd be great to know more about your experiences at Stanford in grad school at that time. What motivated you to go to grad school in sociology at Stanford?

 

LZ: I think the interest in theory was one of the major parts. It's not just institutions or institutional theory, but the Stanford tradition has been “formalized theory” actually, which institutional theory never really became, at least so far.

A lot of the work that stems off from Stanford was more of the formalized theory. There was a big interest in theory, and there was also a big interest in institutional theory. That was mainly driven by John Meyer, but earlier than that as well. I mean, I also worked with Dick Scott very closely, and my chair was (Morris) Buzz Zelditch, whom I worked most closely with. He was also interested in bringing in institutional interactions into the lab way before we even had the term “institutional theory.” He was bringing in different kinds of exterior interactions that you wouldn't think would be put into a laboratory.

The whole department really was oriented around, first of all, theory and secondly, abstract models. This is where John Meyer's work fits in. Of course, I worked most closely with him and with Buzz Zelditch.

 

The other part of Stanford, it was incredibly collegial. That is, everybody worked very well with each other. And we were really close friends, not just colleagues. It was a different kind of environment, and it was very nurturing for me. I could discuss the ideas I had that again were probably closer to John Meyer's, but also because of the experimental angle, closer to Buzz Zelditch. Most of the department was experimental – and were experimentalists.

AK: Very interesting. Was there a significant focus on organizations/organizational theory within the Stanford sociology department at that time?


LZ: I mean, there was a course I TA'd – a course on “Organization” taught by Dick Scott, but there wasn't much on organizations. And that wasn't a big focus of the department. That was more my focus. I was very interested in it as another setting in which institutional processes were front and center, very obvious, so easier to study. It also had to do with older traditions like Everett Hughes and others, but then it looked at regularities in organizations. Weber of course. But Weber had his prescribed set, and he wasn't as much of a purist. A number of the people that followed him were much more empirically-oriented. I think I was always very empirically oriented.

 

AK: Your 1977 ASR paper, which was part of your dissertation research, is a classic. It’s mandatory reading in every Org. theory doctoral seminar. How did the idea for that study come about?


LZ: I guess the idea came from the combination of working with Dick Scott and Buzz Zelditch. Buzz was an experimentalist, and I was really drawn to the experimental technique. My first experiment was actually done with Norman Alexander, who was just there briefly at Stanford but was there most of the time I was at Stanford.

He was an experimentalist as well. The first published experiment I had was a joint paper with him. I was already very comfortable with experimental methods. I'd taken a lot of coursework. I'd taken a lot of psychology too, and I had an undergraduate degree that was a joint sociology/psychology BA. So I went to Stanford sociology because it was the department to go to if you were interested in experimental work. It wasn't common in sociology.

I also took quite a few psychology classes, and studied with Albert Bandura, who did a lot of work on modeling using either quasi-experimental or completely experimental design. I was always more interdisciplinary, so it wasn't as big an issue for me that this was kind of a minor area in sociology. It wasn't very well developed. But I thought, well, I'm going to be across disciplinary lines anyway, it won't matter.

I just needed more help with getting the things that go along with experiments. Actually, I more or less did it on my own. Because the autokinetic effect was really easy to produce, you just need a flashlight or something, some source of light. And you beam it through a piece of cardboard with a very small hole, a pinhole.

 

I mean there are many different paradigms I could've picked, but the Sherif one had been used before in studies of conformity. That was the Sherif method that I used. I adopted various techniques from other people, and then in addition I developed my own post-experimental questionnaires. They were different in that they were really probing what people saw. I'm trying to find out if they really understood the legitimacy part of the structure. It was much more tuned into institutional themes.

AK: Fascinating. Did you present it internally at workshops within Stanford? What were some of the reactions?

LZ: People were really interested in it because I had applied the different ideas that were out there, but I put them together in a different way and tested them in a very different way. Also, I then extended the ideas.

AK: One of the main findings of that particular study is that institutionalized standards of interpretation are less sensitive to the autokinetic stimulus, but these interpretations eventually converge to the baseline through repeated exposure to the stimulus.  Subsequent research that built upon your work took note of the first part of your finding, but what is your sense of how the second part of the finding (that the interpretations eventually converged to the baseline through repeated exposure) was received?

 

LZ: I don't think as many people paid attention to the later stages of the experiment especially. It was a question of whether this is really a learning process? Do you maintain the standards after you've been in a setting, giving particular sets of responses? Do you then maintain it after you're not in that setting? I don't think that really got enough attention. I think that was just less seen as an important part. For me that was the most important part because it wasn't going to be institutional unless it did persist.

AK: Your 1986 paper on the Production of Trust, describing the ascendancy of institutional trust-producing structures during the early periods of industrial formation in the US, is also a classic and highly influential. Given your previous work on institutionalization, how did this project come about, what was the broader motivation?


LZ: I wanted to use historical data. I had the idea that we were missing a lot of what was in front of our faces about how institutions actually work. I didn't have a theory in mind when I started the paper. I really developed it as a part of writing the paper.

I did it by puzzling out different examples in anthropology, economics, and sociology about how people actually produce trust. The choice really came from seeing examples and then generalizing from that. I'm kind of a detective. I'm like a sleuth. So when I get going on one of these ideas, I then just prove it out. It's like solving a murder mystery. To me, it's solving what are these structures? How do people actually really use them? What is this process like? How does this really take place?

I took a very empirical point of view, but I was just collecting other kinds of data than in the lab. This real change between Stanford and UCLA, which I joined after graduating, is that at Stanford we had our own  “small groups” lab because this was a place that did a lot of experiments. We actually controlled the lab. We had a lab. I could get it assigned to me easily. When I moved to UCLA, the only way I could get a lab room, and I had no joint appointment with psych, was to go to social psych. It was extremely difficult. It was expensive.

I couldn't get support to pay subjects and that kind of thing, which was easy at Stanford. Yeah. I mean, I had to move the work forward. If I'd been really wealthy, I probably would've just funded myself, but I couldn't.

 

So that’s how this article, which used historical data, emerged. I would say I'm very determined. I think that's one of the big things… is really just being determined. You'll have lots of obstacles in front of you, and you just, you manage the obstacles. You don't let the obstacles manage you.

AK: When I first read that paper, I was curious about how long it would have taken you to collect so much historical materials, analyze them, and write the manuscript. Could you talk a little bit about that process?


LZ: Yeah. I was already embarked on the research when I had the opportunity to pull this article together, and I was suggesting that I might pull something together. I saw where I was going. But yes, it took a long time. It took much more time than I expected.

It was very hard to get it done. Yes, now our publication schedules are not at all conducive to that because I mean you really either go with the article already done or you have to just put it together very quickly. There's not enough flexibility in publication time to allow for the kind of work I did on that article.

I'm working on a new one now, and I'm finding I'm doing the same kind of detective work I did on this article. But it's much easier though, yeah, because we have different tools now and have the web, right. It's become much easier. But still, it's not a simple thing because everyone brags about what they basically present. They have all this great historical data, and then you go in there and you find out for a whole book they have five tables. And only two of them cover the time period you're interested in. It's like the worst kind of false advertising.

AK: How do you see the institutional trust-producing structures work today, especially with the rise of online platforms and platform firms which have ambiguous rules about data sharing and ownership, and with unclear legal structures for addressing trust breaches?

 

LZ: Yeah. I think it's better to actually have a market model and have people pay for it. The reason to do that is because then you know who picked up the data. I mean, I know certainly a lot of data that's publicly available.

But I'd say that ethics has become very weak in the profession. Ethics, it would've prevented that, where you clearly always acknowledge other people. You never would not acknowledge somebody’s sources of data. I mean it's like a pride thing to say I accumulated all these great sources, and here they all are, right. Instead, it's like don’t acknowledge, hide my sources and it looks like I did this myself! And I can't tell you how much work it was to create those datasets.


I think that if they had more of a market-model, but not expensive, keeping it very low-priced... It's more for the visibility of these people who are actively using the data, and you're able to have a list out there. I'm thinking of putting on my website the people that have gotten the data from the website, so at least there's a list somewhere.

I never would have thought if it hadn't been for these people... Most people really cite it and they're fine, but then there are these few people that use it extensively and don't cite it at all. I just think having the list on the website front page would be a good idea. Getting some credit. Not only that, NSF, they expect me to be able to say something about the data. It's really important, but I'm really limited when there are people that are using it extensively and never citing it.

AK: Given your ongoing research on knowledge production in the biological sciences, how do the natural scientists deal with these issues about data sharing?

 

LZ: Well, if they do data sharing like that, instead of having the datasets just up on the web, I would have them and I would tell them, I would make it available to them but I would take co-authorship. That's what the natural sciences do. They're a co-author on the paper that used their dataset. The person isn't just acknowledging them. They're saying that this is so important and integral, and they really needed the data to be able to do it.  The co-author is just based on the research materials they're using. So it's a much better system, and it's one that's been in existence for a long time. It's not 100% perfect. I mean they do have people who steal things through the lab, but because there's monetary value attached to this, they actually prosecute those in the court. They stop people at airports that are leaving with the data. It's a whole different kind of system.

AK: Maybe this is a good transition to talk about your research on basic science and knowledge transmission. Given your previous work, I’m curious about what motivated you to pursue this topic. In this line of research, you’d collaborated with economists, you are also affiliated with the National Bureau of Economic Research [NBER] as a Research Associate.

 

LZ: I should also say that I have PhD students from econ, and I have TAs from econ... On the research, how did all of that happen? Well, it happened because I realized when I wanted to study new industries, which I was interested in because I thought they'd be like a black box, information wouldn't get out because they'd just be keeping it very closely held so no one else could use it. I discovered that it was much more of a system for basically, you could say, pricing information. How much is this going to cost you? It's going to cost you something and that also made the transfer, the sharing of information, more open and more possible.

Otherwise, without the way of documenting that transfer occurred and maybe paying for the transfer, it was too much like the wild west. Initially, there was a lot of that, and that got shut down pretty quickly when cases were prosecuted. It was run so differently, and I was really fascinated by that. I was also fascinated by how quickly this is done because of the money involved. Universities found ways to work around [limitations to technology transfer] anyway and created new structures around collaborations between scientists and industry. It was particularly poignant to me because at UCLA, we couldn't do that, and they actually made scientists who created the company leave.

That led UCLA not to get the huge endowments like Stanford and Caltech got because the scientists were so grateful later that they made huge gifts to the university. That only happened here in a few cases relatively recently, after UCLA changed its policy.

I also was fascinated by how much those policy differences, the lack of flexibility in some universities or the inability to find an institutional mechanism that they felt was sufficient to be able to allow them to broker these relationships, turned out to be so successful for the private universities.

The reason I got involved, I always got involved independently of any kind of funding – because I had no idea there was any funding for this, by the way – I didn't know until after the fact that I could get funding… I got my first funding from UCLA. The program was run in biology by a molecular biologist who had made some of the basic discoveries. Part of the patent royalties that came to the university had been committed to supporting the kind of research that was producing these patents. This was specifically in the genetic engineering area. That was such a natural fit for what I was doing. So I started doing it independently. I just happened to be there.

Then that was incredibly influential in being able to help me develop that whole line of research. It was very expensive to develop because at that time we didn't have electronic databases. So it meant going to the library. When you see anything about genetic sequences, that was all done by going to the library and pulling out the front page of papers of people who had many articles that were in this genetic database that I used as the basis for the sampling. It was actually developed by Los Alamos, but then it was commercialized by IntelliGenetics, which was a small company in the Bay Area. But it came from Los Alamos to begin with, this genetic database, and I used it.

It started out first being just the discovery of new genetic sequences. At the time it really was divorced from commerce completely. I was just looking at that part, and then I discovered by doing this, how much was going on between the university and commercial enterprises. I still should do, but I don't know if I will, I haven't gotten to it yet – the reverse flow of knowledge. It's huge, and it hasn't been documented well. And I really need to write about it. You could just say, oh, that's brain drain, but it's not brain drain. It's really a two-way street, and the question is, how much of a two-way street? But I don't know yet how it's going to work. It's another huge project.

AK: Are there other research projects that you are currently working on and excited about?

LZ: The one I just told you on reverse flow. I'm likely to do some experimental work again. I don't know exactly when. I'm doing another piece of historical research, which is with one of my students. I'm just at the beginning of that, really.

 

I possibly have another one in which I'm going to be looking, and go back to look at some of the really early documentation on genetic engineering. I don't know what that's going to look like yet really, too soon to tell. My RAs always think I have a definite idea and I know exactly where I'm headed the whole time. But if I did, I'd be a different kind of researcher altogether. I don't know. I do all these explorations, get some ideas. Some ideas are there, but a lot of it is discovering. It's what I actually find by doing these investigations. It's not just hypothesis testing.

 

My dissertation, or when I think of doing an experiment, I'm much more likely to be in a different mode where I've really thought it through. I know what my different conditions are going to be. I may not have everything written up when I start my pre-test. I may not have written the first experimental questionnaire yet, but I do the pre-test first. Then I finish the rest of it. But a lot of it is in place. It's more front-loaded.

 

When you do these other studies such as the historical ones, you actually discover things yourself. I mean, I have to be open to surprise because if I'm not, I'm going to miss a lot of what is actually there. I never would've seen the importance of the way intellectual property is transferred in the biological sciences. I never would've understood those mechanisms. I can't go in with a lot of preconceptions, because then I miss some of the most important aspects of what I'm studying.

AK: Since you are affiliated with NBER as a Research Associate, I have a question on what organizational theorists and sociologists could learn from institutions such as NBER, especially with respect to knowledge dissemination?

 

LZ: It [NBER] is actually much more open than sociology because most sociologists are not posting their early papers. It's the whole question of what mechanisms do we need to promote trust? Is it really just trust, or is it just that our mechanisms are out of date? I think really our mechanisms are out of date.

The visibility of NBER papers is huge. If you look, you'll find that NBER papers are among the most highly cited papers as just NBER papers before they're even published in journals. Okay, some of the papers are never published, but they're still highly cited.

NBER has been around a long time, but so has something like the Center for Advanced Study in the Behavioral Sciences (CASBS) at Stanford. There's also the one at Princeton, the Institute for Advanced Studies. But we haven't used them in the same way [as the economists have used NBER]. NBER determines business cycles. Did you know that? Like when we're in a recession, NBER calls the recession.

 

Also, being seen as “the expert” in some area, that helps too... In sociology, we've had more ephemeral institutions that haven't lasted. Then again, I've pointed out a few that have and that actually have a pretty substantial impact... I mean for the social sciences, CASBS definitely. We need to think about what kinds of institutional structures we need that we don't have that would help support our work. It could be in sociology, or it could be interdisciplinary.

 

My bet for sociology would be it's better to go interdisciplinary because we have the population studies people, the demography people, that are really already working extensively with economists and have been not since the beginning of when I came to UCLA. But by the time I was probably about halfway through my career, they were beginning to work with economists.

It's a question of what we want to promote, what the Center would promote. It's like NSF went on this big kick of promoting interdisciplinary research, which it backed off of at a later point, I think. It's a mistake because I think interdisciplinary research is extremely important. That's a niche that NBER does not fill.

 

I'm the only sociologist at NBER who’s a Research Associate there.  That was because of Zvi Griliches. Do you know of his work?

AK: Yes, his famous study on hybrid corn and technological change…

LZ: Yeah, the hybrid corn one. He recommended me, and that was strong enough that I got invited. I gave a presentation. He invited Michael Darby and me to give a presentation on our work. Because of that, I was invited to join as a Research Associate at NBER.

As sociologists, we have to find something which we can really predict – something that the government is really interested in. Actually, I'll make a suggestion: discovering new mechanisms; I think we're best at that. And identifying them and saying what they do. We don't have any national indicators about this. So that's the thing about NBER, it does a national indicator. We need to think about what could we do that the whole country would be interested in and that would help understand how the new industries are developing like Google and Apple and so on. And why aren't there more competitors? It's kind of interesting. I mean early on there are often monopolies, and the monopolies get broken up. We're still early on, so it's not a big surprise. But with the amount of wealth that's being generated, it is a surprise there haven't been more competitors...

 

I think I could write something good about what we could do as sociologists. I'll try. When I get invited, that's something I can write.

AK: Your presentation at the OMT Distinguished Scholar breakfast was very interesting. You raised a lot of interesting points, especially the assumptions behind the macro and micro parts of institutional theory. For those who couldn't attend your presentation, what did you hope the OMT members took away from your talk?


LZ: I tried to emphasize the way knowledge moves. I emphasize how central knowledge is and how it moves from one place to another. I think trying to talk about mechanisms and processes is really important because of that, and that it's not just making a paper that can be sold, that you can get someplace to accept and you can have it published. I think it's about developing ideas that might take a long time to accept because they're very different, and not being afraid to take on such tasks as part of your career and certainly maybe after tenure – things that aren't as easy for people to see, but you can see their importance, but other people don't necessarily buy it. I would be using the market mechanisms to talk about how others changed, and it was very useful. But I think the market mechanisms and knowledge are tricky, because you market things you already understand. Markets are for things where knowledge is relatively high, but it's hard to have a well-defined market when the underlying products aren't very well-known.

It can be hard to get things accepted. You'd have no idea how much trouble Michael Darby and I had getting the first paper accepted, and Marilynn Brewer, who worked with us throughout the beginning of the project. She was on the first NSF grant. She was on, and she's from social psych, by the way. It's a social psychologist, an economist and a sociologist working together. Then she left UCLA. I don't think she would've stopped working with us. She moved to Ohio State... But that move meant that it was just too hard to collaborate. Yeah, that didn't stay, which was too bad because it was a great thing. Sometimes I mean it's partly serendipity, but it's also not backing off on something that's hard to solve. Because, it's hard to solve problems, the ones that a lot of people shy away from because they think it's going to take them too long might be so important. But leaving it out means the whole area never gets developed. So I'm saying take more risks.


On institutional theory, I think there are a couple of different theories floating around, and it needs to narrow down specific theories so that we can actually start to consolidate some of the ideas around a couple broader theories. To the extent that doesn't happen, this’ll be like population ecology – it'll be something that we study at one point and then it largely disappears from the literature. Population ecology at some point needed to expand what it was taking into account and didn't. This means institutional research is at that crucial place – being willing to take a risk. This is not work for timid people. You have to be willing to put your neck out there, say what you think, and then watch people say, "That can't possibly be true."

By the way, as a side note, a number of people have come up and apologized to me for having told me that what I found wasn't right, that Stars [star scientists and engineers] weren't going to be important, because “a few people” couldn't be that important. That was the thing that went against the ideology of the social sciences.

 

Also the whole institutional work, no one believed micro institutions were important. They thought these were broad structures that went across all different societies. But I thought no, that they are. They thought that they're not important. You really have to understand the microstructure to understand if they really are championing the same processes or something quite different.

 

A lot of these things that look on the surface the same underneath aren't the same at all.  Societies on the surface appear more similar than they are and if you go underneath would see many more differences. I'm sure anyone who migrates to the US from another country can see that in a minute. Because on the surface, you know, eating lunch means the same thing in one case. We're working on using this example actually. On the surface, in every culture people eat lunch, maybe at slightly different times. But eating lunch together has really different meanings in different cultures. If you just look at the process of eating lunch, no big difference. But if you start to look at the meaning of eating lunch together with others... my eating lunch with a member of the other gender for many years led to rumors… You just can't tell what's going to be made of it by others, right? That's part of the culture. That's part of what we call institutional structure – on the micro level.


If you ever follow Garfinkel's work, this was in Garfinkel's writing about surprises. The shock. The shock itself is an indicator of the importance, and also the lack of understanding or the lack of shared meaning. And also, how easy it is to generate anger if you disrupt meaning and then in which context can you do that? So if the micro level and macro level can't be tied together, then you have an incomplete explanation – because you want to understand how these permanent, much bigger structures actually get constructed, and you also want to understand not just how they're similar, but how they're different. What we've focused on is only finding out how they're similar.


AK: You’d examined different topics and methodological approaches in your research. Is there a common thread that connects them?

LZ: I think both of these things I've been talking about, I'm very interested in how these pieces fit together. It's not that I'm interested in one substantive area. I would say that not looking at stability is a really important part, and what's happened with the macro side is they were always looking at stability. You'll see in my work I'm almost always looking at change, and it's because I don't think you can understand institutional stability without understanding the change processes first. But the change process is what actually creates stability.

It's not that I start out knowing them and think, oh boy, I'm going to go this way because it's a goal of mine. It's that I can see there's something different there that I need to understand, and so I use that as a kind of motivating wedge. I'm going to actually get more information, and I'm going to understand this better.

 

At the early points, I don't see all the links to the other side because I don't know where they exist yet, but I see that there are intriguing things going on there. So how does that happen? That's what I'm looking for – I mean what really happens as you go in the biotech and science areas, you've built a whole set of loose structures to carry all of the new things, the new ways that sciences were interacting not only internally but also with industry so that the changes then affected and redefined the stable equilibrium that was existing before.

It's a big search for empirical things that we can use to really identify institutions in a clearer way than before on both the micro and macro level. How do we do something that's more than talking about diffusion at the macro level? I mean diffusion is not even a way to explain anything because diffusion doesn't tell you anything about mechanisms. They leave it out. Well, not quite. That's a little bit of an overstatement, okay. But I would say it's not very dynamic-focused.

AK:  Based on your experience in our field, what would you tell a junior OT colleague today?

 

LZ:  I teach my students this, including my graduates. Bureaucracy is not the way to go. We've built up bureaucracies, and bureaucracies are inflexible. They protect themselves in ways that harm individuals, and we should get rid of them. We need to find alternatives to bureaucracy and ways of running things.

AK: You mean within universities, or more generally?

LZ: More generally. Bureaucracies in general are really problematic. It's not any one place, but bureaucracies lead to a deflection of activity away from things that are at the heart of what you're really trying to accomplish. And they decrease rather than increase the use of merit-based standards. And that we need to move away from it. Does it mean organizational theory is dead? No, because organizational theory also deals with teams, right? And so what's right about teams? I mean they're much more based on trust, which I said in my talk.

The question is how can we influence teams or some other similar mechanism. I'm not going to say they're the best either because you'll also hear about leaders who can get all kinds of resources, for instance team leaders in science, but are terrible people. They're just like a despot, so I'm not claiming any one mechanism is going to cut it. I mean, maybe no mechanism we know yet but think of something that could be a substitute for bureaucracy. Maybe something different. But I'm encouraging people to think beyond bureaucracy.

Apart from that, I also get the difficulty of combining family life and work. I've always brought my kids to work. I'm really unusual. Nowadays people don't do it. I really had to. I had a child born with an enzyme deficiency after I was already at UCLA, and I had to bring her in to school because she had to be fed exclusively on breast milk because she couldn't digest regular food at all for a long time. It would've actually made her develop allergies. Yeah. I had to go to a pediatric allergist. That was a long, long time ago. But she lived in a playpen in my office, and I brought a babysitter to school. For my personal experience, a big part of my family roles and my teaching roles had to be integrated better. I see some of my colleagues do bring their kids in after school, and I think it actually humanizes the department and makes it a better place. Some people will say it interferes, but I don't think so.

I think that's one way bureaucracy sometimes is too inflexible to not allow combining, like we did in family businesses. They brought the whole family – maybe the kids were in the back room. It's a way to make bureaucracy a little more gentle. That's a way to survive if someone is pregnant or already has kids. I mean, whether a dad or a mom, these days the dads are doing as much.

Bureaucracy, it's not human-oriented, and that’s because we can't bring our families in… Bringing family to work – and it's not just one day a year, which a lot of the places have, one day a year you can bring in your family, but you should always be able to bring in your family. Maybe not for the whole day. You have to take the disruption factor into account, but later in the day or on some occasions you should be able to bring in your kids – some way of being flexible.

 

I don't know what it is because I don't know enough about the current demands on people's lives to know how this all works out, but their kids shouldn't be always in the care of someone else. Kids also should see what's involved in work. My kids were xeroxing for me at age three – learning xeroxing for me and then xerox procedures, because I wanted them to love the work. Actually, I paid them. I paid them to do it, but I had them working rather young. And that's like family business in life, right? I mean, there are different ways that we – and our organizations –  can become more human.

AK: Great. Thank you so much for your time, and for sharing these interesting thoughts. Congratulations again on the OMT Distinguished Scholar Award.

 

LZ: Well, it's been really good to talk to you, and I enjoyed it a lot. It was a lot of fun. Thank you.